Processes doi: 10.3390/pr14162545

Authors: Dongmei Li Zhiwei Lu

In this study, a rapid analytical framework is developed for reconstructing transient formation-pressure distributions in sparsely connected fractured-vuggy carbonate reservoirs using well-test-derived fracture–cave geometry and source allocation. Pressure–flow relationships are established for caves, fractured bodies, and finite line-source fractures; unit-source solutions are combined via spatial superposition and Duhamel convolution for variable-rate production; and the framework is evaluated by comparing Well EX-1 against a PEBI-grid simulation. Cave response is derived from mass conservation and effective compressibility, while point- and line-source Green’s functions describe pressure diffusion. For the 30-day EX-1 case, analytical and PEBI pressures at four locations show close internal agreement, with a mean absolute error of 0.070 MPa, a root-mean-square error of 0.083 MPa, and a maximum absolute error of 0.13 MPa. This method is applicable mainly to single-phase, slightly compressible, linear-flow conditions with a constrained fracture–cave topology. It provides a rapid screening tool for deep carbonate reservoirs with sparse well control, while multiphase, strongly nonlinear, reactive, or geomechanically coupled cases require conventional numerical simulation.

Processes doi: 10.3390/pr14162544

Authors: Suling Feng Tao Liu Junwei Zhao Hongtao Yang Ziyu Wang Wenliang Chen Xingxing Wang

The mechanical performance of CFRP/2024 Al alloy hybrid laminates joined by transverse ultrasonic vibration-assisted riveting (TUVAR) was investigated. The experiments were conducted on a self-developed ultrasonic riveting system with a power of 3000 W and a vibration frequency of 19.8 kHz, covering ultrasonic amplitudes from 0 to 24 μm. Test specimens were fabricated from T300/CFRP laminates, 2024 Al alloy sheets, and 2A10 Al alloy rivets. The influences of ultrasonic amplitudes (12 μm, 16 μm, 20 μm, and 24 μm) on riveting load, driven head geometry, interference, static tensile strength, and cyclic loading behavior were systematically analyzed. The results showed that TUVAR reduced the riveting force and promoted rivet deformation. As the amplitude increased, the driven head diameter increased, and the driven head height decreased, with a maximum reduction of 6.62%. The mean interference generally increased up to 20 μm and then decreased slightly at 24 μm; the relative interference variance coefficient ranged from 0.070 to 0.155 under TUVAR. Static tensile tests showed that the joint strength first increased and then decreased with increasing amplitude, with the highest mean static tensile load obtained at 20 μm. Cyclic tensile tests indicated that load-bearing capacity was improved with increasing amplitude, while the maximum deviation was maintained within 3.5%. These findings demonstrate that TUVAR can enhance both the forming quality and the mechanical performance of CFRP/2024 Al alloy riveted joints, and provide a useful reference for the high-performance joining of composite-metal hybrid structures in aerospace applications.

Processes doi: 10.3390/pr14162543

Authors: Helen C. Sereti Panagiotis Tsarouhas George Besseris

This paper examines the reliability of a product in terms of its lifetime, based on the investigation of certain factors within the framework of maintaining the principles of the circular economy and the sustainable design of the experiment. The study aims to investigate the critical factors that could affect the product’s lifespan and long-term efficiency. Initially, a statistical analysis of interactions was achieved through an interaction diagram using the Minitab software and for trials scheduled using the Plackett–Burman planner. Subsequently, the most significant interactions were selected and further analysis was conducted using the screening model, a combination of Pareto chart and the Lenth method to filter out weaker performing controlling factors and their associated two-way interactions. This was followed by a life-data regression analysis, and the results identified statistically strong factors and interactions based on various commonly used reliability distributions. Such findings are important in improving the life extent of a product, which in the specific case was a manufactured industrial-level thermostat, while reducing the risk for early product failure. In conclusion, the study demonstrates the variability and multiplicity in prediction accuracy of the screened effects when considering different reliability distributions in research which employs statistical reliability tools. Such tools are regularly encountered in product design and improvement efforts, aiming to successfully prevent early failures while ameliorating the environmental footprint in production.

Processes doi: 10.3390/pr14162542

Authors: Jose A. Benavides Birol Dindoruk

Deep saline aquifers are among the most promising formations for large-scale carbon capture and storage (CCS); however, reservoir pressure buildup, limited CO2 dissolution, plume migration, and salt precipitation can reduce storage efficiency and injectivity. This study evaluates the technical and economic performance of engineered CO2 injection strategies, including intermittent CO2 injection (ICI), water-alternating-CO2 (WA–CO2), carbonated water injection (CWI), and carbonated water-alternating-CO2 (CWA–CO2), under low- (180 mD) and high-permeability (1000 mD) saline aquifers and injection rates ranging from 0.01 to 0.5 MTPA. Laboratory-derived relative permeability and CO2 diffusivity data were incorporated into three-dimensional compositional reservoir simulations, while the most promising strategy was validated using the Sleipner benchmark model. Techno-economic performance was assessed through Monte Carlo uncertainty and sensitivity analyses. The results show that injection strategy, rate, and reservoir permeability strongly influence trapping efficiency and pressure evolution. ICI increased dissolution trapping by up to 20%, enhanced residual trapping by approximately 40%, and reduced average reservoir pressure by up to 10%, although its extended operating period reduced its economic attractiveness. Among the evaluated alternatives, WA–CO2 provided the best balance between technical and economic performance by enhancing dissolution trapping, improving pressure management and plume control, and maintaining storage costs within 3.6–3.7% of the continuous injection base case. Field-scale validation using the Sleipner model demonstrated improved long-term trapping efficiency and reduced mobile CO2 and plume extent. Monte Carlo analysis (20,000 realizations) confirmed the economic robustness of the evaluated strategies under the assumed policy framework, identifying Section 45Q tax credit and discount rate as the dominant economic drivers. These findings demonstrate that properly designed WA–CO2 schemes can significantly improve the technical and economic performance of geological CO2 storage.

Processes doi: 10.3390/pr14162541

Authors: Hongke Wang Chengzhi Xia Wei Lu Zhao Lv Qianli Lu

Addressing the challenges in quantitative characterization of post-fracture fracture geometry in unconventional reservoirs such as tight gas and shale, for which existing prediction methods provide only limited accuracy, this study proposes an intelligent inversion method for fracture morphology by integrating G-function post-fracture diagnosis with a CNN-LSTM network. The number of branch fractures determined from G-function analysis of pressure decline curves is employed as a hard constraint. Latin hypercube sampling (LHS) is adopted to generate multi-dimensional fracture geometry samples, and a CNN-LSTM model is constructed to establish the nonlinear mapping from fracture morphology to production response, thereby forming a sample database that correlates production with fracture geometry. Leveraging this database, intelligent inversion of post-fracture fracture geometry can be efficiently realized. Field validation demonstrates that the inverted fracture half-length deviates by less than 3% from microseismic monitoring results, while the production prediction error remains below 6%, significantly outperforming the 10% tolerance threshold commonly accepted in field engineering. The proposed method requires only single-well pressure decline curves and production data to accomplish post-fracture fracture geometry evaluation, exhibiting broad application prospects.

Processes doi: 10.3390/pr14162539

Authors: Duc Quan Nguyen Thi Trang Do Nhung Thi Hong Lai Minh Thi Tuyet Phan Tu Thi Minh Hoa Thoa Kim Nguyen

Polyhydroxyalkanoates (PHAs) are biodegradable microbial polyesters that may reduce dependence on petroleum-derived plastics, but broader use remains constrained by production costs and tightly controlled cultivation. Thermophilic microorganisms have attracted increasing attention as promising PHA producers because they can be cultivated at elevated temperatures, reducing contamination risks and operational costs. In this study, a thermophilic Geobacillus sp. strain SL28 isolated from a Vietnamese hot spring was evaluated for its PHA-producing capability. Temperature, initial pH, carbon and nitrogen sources, C/N ratio, and cultivation time were examined. Intracellular inclusions were assessed by Sudan Black B and Nile Blue A staining and transmission electron microscopy, whereas the recovered polymer was characterized by FE-SEM, Fourier-transform infrared spectroscopy (FTIR), gas chromatography–mass spectrometry (GC–MS), 1H- and 13C-nuclear magnetic resonance (NMR) spectroscopy, capillary viscometry, differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), and tensile testing. Under the optimized cultivation conditions identified by one-factor experimentation (50 °C, pH 7.0, sucrose, peptone, C/N 25:1, and 72 h), SL28 reached a dry cell weight of 2.215 ± 0.16 g/L and a PHA concentration of 1.383 ± 0.04 g/L, equivalent to 62.57 ± 2.82% of DCW. Structural characterization confirmed that the recovered polymer was poly(3-hydroxybutyrate) (PHB). The purified PHB also exhibited favorable thermal stability, a relatively high molecular weight, and satisfactory mechanical properties. These results demonstrate the potential of thermophilic Geobacillus sp. SL28 as a promising candidate for PHB production.

Processes doi: 10.3390/pr14162540

Authors: Lorenzo Reyes-Bozo Eduardo Vyhmeister Héctor Valdés-González Gabriel G. Castane Juan Carlos Vidal J. Eduardo Martínez-Hernández Eduardo Villarroel-Utreras

Artificial intelligence (AI) is increasingly being investigated to support decision-making and process improvement in copper mineral processing and extractive metallurgy; however, the available evidence remains fragmented across operational units, methods, sustainability dimensions, and geographical contexts. This systematic mapping review, complemented by qualitative cross-study synthesis, analysed publications from 2014 to 2025 retrieved from IEEE Xplore, Scopus, and Google Scholar. Of the 410 records identified before screening, 71 studies were classified according to four predefined research questions addressing copper-processing operations, AI domains, sustainability contributions, and geographical distribution. The findings show an uneven distribution of research across the processing flowsheet. Comminution and froth flotation received the greatest attention, whereas lixiviation, solvent extraction, electrowinning, and electrorefining were less represented. Machine learning was the dominant AI domain, particularly supervised approaches based on historical operational data; however, no algorithm was universally superior, as reported performance depended on the dataset, target variable, operational context, and validation procedure. Most studies focused on prediction, monitoring, fault diagnosis, and operational optimisation, while reinforcement learning, hybrid mechanistic–data-driven models, adaptive control, and sustained industrial deployment remained comparatively limited. Sustainability assessments emphasised operational and economic outcomes more frequently than social, ethical, circular-economy, and broader environmental implications. Geographical results reflected the locations assigned to the reviewed studies and industrial cases rather than regional AI maturity. The review identifies data availability, heterogeneous validation practices, model transferability, and limited evidence of sustained industrial deployment as recurring challenges. It proposes a staged research agenda to develop more reliable, transferable, and human-supervised AI applications across copper-processing operations.

Processes doi: 10.3390/pr14162538

Authors: Xingyou Li Wei Yan Chang Xing

Accurate prediction of NO emissions is important for the development of low-emission gas turbine combustors. This study evaluates several NO formation models for a 78 MW F-class gas turbine using a decoupled post-processing framework. Steady RANS simulations were performed with a partially premixed flamelet/PDF combustion model. Thermal NO, prompt NO, the N2O intermediate pathway, and turbulence–chemistry interaction were assessed at 50% and 100% load. Thermal NO was the dominant pathway and showed strong load dependence. Using partial equilibrium for O radicals increased outlet NO by 16.46% at 50% load and 43.69% at 100% load. Including partial-equilibrium OH further increased NO by 8.67% at 50% load but had little effect at full load. Prompt NO remained on the order of 10−3 ppm. The N2O pathway and turbulence–chemistry interaction also affected the prediction, especially at full load. The selected model was further compared with field measurements during load ramping and pilot-ratio variation. Most load-ramping predictions agreed with measurements within 18%. The results demonstrate the applicability of the proposed framework for engineering NO emission prediction while also identifying limitations under transitional operating conditions.

Processes doi: 10.3390/pr14162537

Authors: Xiaobing Bian Jiaxing Zhou Liang Fu Aoran Jin Wei Zhang

Hydraulic fracturing is a critical technology for unconventional oil and gas development, but its performance is strongly affected by geological heterogeneity, complex fracture propagation, operational uncertainty, and nonlinear interactions among engineering parameters. Artificial intelligence (AI) provides tools for extracting relationships from geological, geophysical, operational, and production data. This structured narrative review synthesizes AI applications across four sequential stages of the hydraulic-fracturing workflow: sweet-spot identification, fracturing-parameter optimization, operational diagnosis and risk warning, and post-fracturing flowback prediction and control. Representative studies reported sweet-spot classification accuracy of 97.5% and R2 = 0.97 for production-performance prediction; a simulator-coupled optimization study reported a 13% economic improvement, and field-data models used cohorts of up to 295 wells. Operational studies reported point-event recognition above 97%, pressure forecasting 30 s ahead, and risk forecasts over three consecutive 60 s intervals. A post-fracturing model trained on 286 wells predicted responses over 30-, 90-, 180-, and 360-day horizons. These values are study-specific and are not directly comparable because the datasets, targets, partitions, and metrics differ. Collectively, the evidence indicates measurable but uneven progress; field readiness remains limited by data quality, multimodal alignment, physical consistency, uncertainty quantification, external validation, and weak coupling between model outputs and operational decisions. The review contributes a reproducible workflow-oriented coding framework and defines validation and deployment priorities for reliable, interpretable, and executable AI-assisted fracturing decision support.

Processes doi: 10.3390/pr14162535

Authors: Xuezhan Zhao Guangjin Chen Yi Hong Jingtian Qin Shujie Liu Lei Li Shuzhan Li Gengchen Li Jiale Yang Lingfang Tan Xiaolong Yang Kun Jiang

To improve the bending resistance and support the domestic development of deepwater subsea wellhead equipment, a three-dimensional finite element model (FEM) of the SXW-15 subsea wellhead system was established in ANSYS Workbench considering contact nonlinearity and rigid-locking mechanisms. Based on representative deepwater drilling and completion conditions, the effects of the friction coefficient, locking preload, blowout preventer (BOP)/lower marine riser package (LMRP) top load, casing hanger internal pressure, and tubing load on the ultimate bending capacity of the system were systematically investigated. The results show that the bending capacity increases with increasing friction coefficient and locking preload, whereas it decreases with increasing top load and tubing weight. The internal pressure of the casing hanger exhibits a pronounced nonlinear influence on the bending resistance, and the maximum bending capacity occurs at an internal pressure of approximately 4000 psi. Based on the mechanical analysis, several innovative designs were proposed, including a layered load-bearing structure, a gravity-set metal sealing assembly, a self-supporting rigid-locking mechanism, and an integrated multifunctional tool system, aiming to improve load-transfer efficiency, connection stiffness, and high-pressure sealing stability. Land-based testing and offshore field applications were subsequently conducted to verify the engineering applicability of the system. The subsea wellhead system with innovative designs maintained satisfactory structural integrity and sealing reliability under conditions of 15,000 psi internal pressure and 12.7 million lb axial load. Good agreement was obtained between finite element predictions and field test results. The present study provides theoretical support and guidance for the structural designs and engineering applications of deepwater subsea wellhead systems.

Processes doi: 10.3390/pr14162536

Authors: Bartolomeo Cosenza Riccardo Minardi Luca Usai Riccardo Allodi Alessandro Concas Daniele Sofia Giancarlo Cravotto Giovanni Denaro Antonio Messineo Maurizio Volpe Antonio Picone Robinson Soto-Ramirez Catalina Valencia Peroni Giovanni Antonio Lutzu

Microalgal bioprocesses increasingly rely on predictive modelling to support automated control and reduce the cost of laboratory experimentation. Yet, the scarcity of high-quality datasets and the nonlinear nature of microalgal growth severely limit the accuracy and robustness of conventional machine-learning approaches. This study introduces an ensemble-learning framework for forecasting biomass accumulation in Limnospira platensis cultures supplemented with Effective Microorganism (EM) consortia. The method combines temporally consistent, strictly causal feature engineering with tree-based ensemble learning under a prospective validation protocol designed to mirror real deployment. Growth measurements are transformed into temporal descriptors that encode phase transitions, short-term growth dynamics, and treatment effects, enabling tree-based ensemble algorithms to capture nonlinear patterns inaccessible to traditional models. When features are restricted to information available strictly before each prediction, and models are evaluated only on real held-out measurements, one-step nowcasting does not surpass a trivial persistence baseline. For genuine multi-horizon forecasting of a monitored culture, the regime with practical value, a horizon-aware gradient-boosting model trained jointly on two cultivation media (Jordan and Zarrouk), attains R2 ≈ 0.72 on the held-out Jordan observations (0.72 ± 0.02, mean ± SD over 30 seeds; RMSE ≈ 0.20 g L−1, Pearson r ≈ 0.85) and remains stable across forecast horizons of 1–28 days, outperforming persistence roughly fourfold in pooled R2 (0.72 vs. 0.16) at medium-to-long horizons where the naive baseline collapses. Permutation-based feature-importance analysis identifies current biomass and the EM dilution level as the leading predictors, whereas EM treatment identity contributes only modestly. Including an independent second-medium experiment (Zarrouk) in joint training did not materially change held-out Jordan performance, indicating that, under these data-limited conditions, neither additional model complexity nor a second training medium substantially improved forecasting once the causal, horizon-aware framework was in place. Among treatments, EM3 most strongly suppressed biomass accumulation. Overall, the study provides an honest, fully reproducible, two-medium benchmark for microalgal biomass forecasting under data-limited conditions, and identifies the forecast horizon as the regime in which ensemble learning adds genuine value over trivial baselines.

Processes doi: 10.3390/pr14162534

Authors: Sirong Zhu Ning Li Zhiwen Huang Kai Ye Fangpeng He Shiqian Xu Kuankuan Wu Wenxi Ren

Clay minerals are significant constituents of shale reservoirs, yet the confinement-induced phase behavior of hydrocarbons within clay nanopores has received comparatively less attention than in carbonaceous materials. In this study, Grand Canonical Monte Carlo (GCMC) simulations were performed to investigate the confinement-induced shifts in the critical properties of hydrocarbons within illite slit pores ranging from 2 to 20 nm. The simulation results indicate apparent reductions in both critical temperature (Tc) and critical pressure (Pc) under confined conditions. The relative shift in critical properties is more pronounced for n-pentane than for methane, which is attributed to the larger molecular size and complex chain-like structure of n-pentane compared to methane. The simulation results also show that the extent of these shifts varies among different pore geometries and materials due to the differences in fluid–solid interactions and specific surface areas. Illite exerts a weaker confinement effect than graphite, while cylindrical pores intensify the shift compared to slit pores. As the pore size increases from 2 to 20 nm, the nanoconfinement-induced shifts in the critical properties of alkanes in illite slit pores progressively diminish, and the critical properties approach their corresponding bulk values at a pore size of 20 nm. Finally, new correlations are proposed to quantify the critical property shifts in illite slit nanopores. Overall, this study provides a quantitative characterization of confinement-induced critical-property shifts for the investigated hydrocarbons in illite slit nanopores.

Processes doi: 10.3390/pr14162533

Authors: Lien Qiu Jiaqi Shen Hai Zhao Xianyan Guo Ailan Yan

The accumulation of sediment in rivers and lakes can elevate riverbeds, leading to a reduction in river channel flood-carrying capacity, impairment of water conservancy project benefits, and destruction of aquatic ecosystems. Systematic dredging projects are required in the routine maintenance of river channels to ensure flood control safety and ecological health. This study utilized a successfully constructed efficient composite engineering bacterial strain system to conduct field pilot-scale validation in a closed river environment with a water volume of 10,000 cubic meters. Various indicators such as sediment thickness, organic matter, COD (chemical oxygen demand), total nitrogen, and total phosphorus were measured, along with metagenomic analysis, to explore the application effectiveness and feasibility of microbial composite strain technology in river sediment remediation. The results demonstrated that the composite strain technology effectively reduced the thickness and pollutant content of river sediment. The average sediment thickness significantly decreased from 32 cm to 22 cm, with a 10 cm thick mineralized layer forming within two weeks. The reductions in organic matter content, COD content, total nitrogen, and total phosphorus content reached 60.03%, 47.73%, 37.36%, and 29.16%, respectively. Metagenomic analysis revealed that the biodiversity of the treated river channel was higher than that of parallel and control channels at both the phylum and genus levels. The experimental results are useful for optimizing river sediment remediation.

Processes doi: 10.3390/pr14162531

Authors: Haiming Zhang Ligang Chen Xiaoxiao Ma Tao Liang Ge Zhang Chenyang Liu Shuyi Xie

The detection of outer-wall defects in thick ferromagnetic structures by conventional pulsed eddy current testing is limited by the shallow penetration depth caused by the high magnetic permeability of ferromagnetic materials. In this study, a magnetic saturation pulsed eddy current testing method is proposed to improve the detectability of such defects. The analytical dependence of the eddy current skin depth on magnetic permeability was first clarified, and finite element simulations were carried out to visualize the effect of magnetic saturation on the magnetic field and eddy current distributions. Pulsed eddy current responses under different relative permeabilities were then numerically analyzed, followed by experimental validation using Q345B steel plates with different thicknesses and cubic Q345B specimens containing flat-bottom hole defects of different depths. The influence of the direction of the saturation magnetic field on testing performance was also investigated. The results demonstrate that magnetic saturation effectively increases eddy current penetration depth and significantly improves the sensitivity of pulsed eddy current testing to wall-thinning defects in thick ferromagnetic structures. Signal separation for different defect depths was markedly enhanced under saturated conditions. In addition, the optimal testing performance was achieved when the saturation magnetic field was parallel to the probe axis. These results, obtained on uncoated specimens under laboratory conditions, provide a validated physical basis and a preferred field-probe configuration for applying magnetic saturation pulsed eddy current testing to thick-walled ferromagnetic components.

Processes doi: 10.3390/pr14162532

Authors: Krešimir Mastanjević Martina Hederić Silvio Halt Kristina Habschied

Polycyclic aromatic hydrocarbons (PAHs) are hazardous contaminants formed during incomplete combustion and frequently detected in smoked, grilled, roasted, and fried meat products. Their formation is influenced by temperature, smoking duration, fuel type, fat content, and the distance from the heat source. Available studies indicate that traditionally smoked and charcoal-grilled products contain higher PAH concentrations than raw or less processed meat. Under Regulation (EU) 2023/915, the maximum permitted levels are 2 µg/kg for benzo[a]pyrene (BaP) and 12 µg/kg for the sum of four marker PAHs (PAH4) in standard smoked meat products, while derogation limits of 5 and 30 µg/kg, respectively, apply to certain traditionally smoked products. Chromatographic methods enable sensitive PAH determination, with limits of detection of 0.003–0.200 µg/kg reported for high-performance liquid chromatography with fluorescence detection (HPLC–FLD) of meat products. Literature data indicate that PAH formation can be reduced through indirect smoking, appropriate fuel selection, smoke purification, prevention of fat dripping, and antioxidant-rich marinades. Overall, effective PAH control requires optimized processing technologies, sensitive analytical monitoring, and compliance with regulatory standards while preserving product quality and traditional practices. Unlike reviews focusing on individual aspects, this review integrates current knowledge on PAH formation, occurrence, health risks, analytical determination, legislation, and mitigation within a single meat-focused framework.

Processes doi: 10.3390/pr14152530

Authors: Xinyan Pei

Developing green propulsion engines and effective environmental pollution control technologies has become an important pathway toward sustainable transportation, low-carbon aviation, and cleaner energy conversion [...]

Processes doi: 10.3390/pr14152529

Authors: Alma Rosa Méndez-Gordillo Sixtos A. Arreola-Villa Héctor Javier Vergara-Hernández Octavio Vázquez-Gómez Julio César González-Juárez José Sergio Pacheco-Cedeño

Comminution–classification circuits are difficult to optimize because hydraulic, granulometric, energy, and economic responses are nonlinearly coupled, while circuit simulation, equipment sizing, simulator benchmarking, and operating optimization are often treated separately. This study aimed to develop an open Python framework for steady-state simulation and five-objective optimization of a rod mill–hydrocyclone–ball mill circuit processing a gold ore. The framework integrates solid and water balances, Rosin–Rammler particle-size reconstruction, comminution and hydrocyclone models, preliminary equipment sizing, explicit feasibility constraints, and Multiobjective Particle Swarm Optimization (MOPSO). Its novelty lies in coupling complete-circuit simulation, simulator-to-simulator benchmarking against USIM PAC®, model-based sizing, convergence diagnostics, and Pareto optimization within one transparent workflow. The benchmark produced zero or below 10−3% errors in solid balances and sizing differences of 1.07%, 8.21%, and 0.00% for the rod mill, ball mill, and hydrocyclone, respectively. Relative to the base case, the joint minimum-water, minimum-energy, and minimum-cost solution reduced specific water consumption by 24.50%, specific grinding energy by 4.24%, specific operating cost by 10.19%, and mass recirculation by 8.80%, while useful recovery decreased slightly from 82.67% to 81.78%. The maximum-recovery solution increased useful recovery to 84.45%, with higher water, energy, and operating-cost requirements. The framework supports reproducible evaluation of resource–recovery trade-offs in grinding–classification circuits.

Processes doi: 10.3390/pr14152528

Authors: Qing Yan Xinlu Yan Suoliang Chang Lei Xu Taotao Hou

At the same structural position within the northern part of Block K, the coalbed methane (CBM) wells in the 3# and 15# coal seams exhibit marked productivity disparities. This study integrates a correlation analysis of engineering parameters with dynamic diagnosis of production indicator curves to examine two dimensions: static engineering compatibility and dynamic seepage interference. The results show that the degree of matching between engineering parameters and geological conditions is a key factor controlling the productivity variation. The 3# coal seam has favorable engineering performance, and boosting fracturing scale and drainage rate both help promote gas output. Compared with the 3# coal seam, the 15# coal seam has a notable deficiency in engineering compatibility: its effective horizontal section length and coal encounter rate decrease by 8.4% and 5%, respectively, while sidetracking frequency increases approximately fivefold; moreover, enlarging fracturing scale does not bring better gas results. Production indicator curves were established based on the relationship between cumulative water production per unit effective horizontal length and production pressure difference and were classified into upward-convex and downward-concave types. The resulting chart for exogenous water interference enables quantitative characterization of key metrics, including theoretical ultimate gas production, interference level, and gas production efficiency. The theoretical ultimate gas production of the 3# coal seam reaches 69.454 m3/(d·m), over ten times that of the 15# coal seam, but the critical interference threshold of the 3# seam is lower than that of the 15# seam. Most 3# wells are stably located in the non-interference zone, indicating high production capacity and strong sensitivity to exogenous water interference. For the 15# seam, the production indicator curves of most wells deviate toward the interference zone at an early production stage, reflecting strong exogenous water leakage recharge. Therefore, for this block, CBM development must shift from the traditional approach of blindly enlarging stimulation scale to geological compatibility and recognition of exogenous water interference.

Processes doi: 10.3390/pr14152527

Authors: Shuaishuai Sun Guowei Zhu Guozhen Liu Shuai Zhang Guiqi Sun Xiang Zhou Liangjie Mao

Annular trapped pressure is an important factor affecting wellbore integrity during the production of high-temperature and high-pressure oil and gas wells. In wells with multilayer casing structures, one or more enclosed annuli may form because of cement top, packer setting, wellbore structural constraints and wellhead sealing. When the temperature and pressure fields in the wellbore change during production, the annular fluid undergoes thermal expansion, compressive deformation and possible phase-state changes, causing trapped pressure to evolve continuously with time. Conventional annular pressure prediction methods are usually based on a single annulus, quasi-static assumptions or simplified fluid properties, and therefore cannot fully describe deformation transfer among annuli, thermal expansion of tubular strings and nonlinear gas–liquid compression. To address this problem, this study analyses the formation mechanism of annular trapped pressure from the perspective of thermal–fluid–solid coupling and develops a dynamic pressure evolution model that accounts for transient temperature variation, annular fluid thermal expansion and compression, elastic deformation of tubular strings and multi-annulus coupling. The analysis indicates that annular trapped pressure is essentially a pressure response produced by fluid thermal expansion under structural confinement. A multi-annulus system is not a set of independent annuli, but a pressure–deformation–volume feedback system coupled through shared casing walls. The proposed solution framework and pressure evolution analysis provide a theoretical basis for annular pressure prediction, casing safety assessment and wellbore-integrity management in high-temperature and high-pressure gas wells.

Processes doi: 10.3390/pr14152526

Authors: Yiyu Chen Huimin Chen

Spray pretreatment is a key step in short-process textile cleaning, and spray deposition uniformity on the target plane directly determines the quality consistency of subsequent dyeing and finishing, with nozzle layout exerting a direct influence on this uniformity. However, the existing non-submerged free jet model suffers from physical distortions in planar flow projection, namely multi-valued flow at the origin and non-convergent far-field flow. To address this, the proportionality coefficient of the Gaussian distribution is redefined to establish a corrected planar flow distribution function with a unique origin flow and natural far-field convergence. Treating continuous fabric motion as equivalent nozzle translation, a cumulative flow superposition model for moving planes is constructed, and a collaborative optimization model for nozzle spacing, mounting height, and attitude angle is established using the Particle Swarm Optimization (PSO) algorithm, with adjacent nozzle pairs as the periodic unit. Experimental calibration shows that relative errors between theoretical and measured flow rates remain within 10%. Nozzle rotation about the local z-axis is identified as the most effective attitude variable for uniformity tuning; a 0.1 m increase in nozzle spacing reduces peak overlap flow by about 30% and overlap width by about 40%. For a dual-nozzle system on a 0.66 m-wide target plane, numerical simulation results show that the calculated cumulative flow variance decreases from 5.9193 to 1.1588, corresponding to an 80.4% reduction in the numerical uniformity index. This numerical optimization framework provides a quantitative reference for nozzle layout design in textile spraying processes.

Processes doi: 10.3390/pr14152524

Authors: Thanapat Yiamram Santipont Ananwattanaporn Chaiyan Jettanasen

In this study, a double-sheet detection system for automated metal stamping is developed and modeled. This study aims to address the issue of die damage caused by overlapping workpieces (double sheeting), a significant contributor to production line stoppages. The proposed solution involves a control system utilizing a programmable logic controller (PLC), combined with inductive proximity sensors installed on the die, for real-time processing of workpiece status. The system is designed to immediately halt machine operation upon detecting any abnormalities. The experimental results demonstrate that the developed system successfully reduced double-sheet incidents from one occurrence to zero and eliminated production downtime (reducing it from 4 days to zero), resulting in a total of 32,972.26 USD saved in potential damage costs per incident. Furthermore, the system reduced the production cycle time from 11 s to 9.5 s per piece, increasing the production capacity by 1240 pieces per day. The economic assessment indicates that an initial equipment investment of only 483.2 USD yielded a return on investment (ROI) of 6723.73%, a payback period of 5.35 days, a net present value (NPV) of 89,333 USD, and an internal rate of return (IRR) of approximately 6830%. These figures demonstrate a very high level of economic feasibility. Therefore, this system is a cost-effective, reliable, and practical approach to enhance productivity and sustainably support the Smart Factory concept in the metal stamping industry, aligning with the automotive parts manufacturing industry.

Processes doi: 10.3390/pr14152525

Authors: Xiaoxiang Wang Zongrui Wu Xiao Qu Zhiwei Huang Desheng Zhou Peng Zheng Haiyang Wang

Deep coalbed methane (CBM) resources are abundant and represent a critical component of future energy supply and carbon reduction strategies. However, deep coal seams are characterized by well-developed cleat systems and high Poisson’s ratios, rendering the mechanisms of hydraulic fracture initiation, propagation, and complex fracture network development insufficiently understood. In this study, deep coal rock at a burial depth of 2700 m is investigated. A finite element–based hydraulic fracturing model incorporating complex face-cleat and end-cleat networks is established by explicitly representing cleat geometry, mechanical properties, fluid leak-off behavior, and hydraulic loading conditions. Using this model, the effects of cleat inclination angle, horizontal stress difference, and displacement on fracture evolution are systematically analyzed. The results indicate that when face cleats are orthogonal to the maximum horizontal principal stress, fractures preferentially penetrate cleats and propagate along the maximum stress direction. In contrast, when face cleats form acute angles with the maximum horizontal stress, pronounced branching fractures develop along both face and end cleats, with propagation increasingly dominated by face cleats as the angle decreases. Increasing horizontal stress difference suppresses fracture branching, leading to simpler fracture networks but greater total fracture length and maximum fracture width. Moreover, under identical injection pressures, the equal-pressure fracture length increases, indicating enhanced fracture propagation capacity. With increasing displacement, fracture networks evolve from simple to complex patterns, accompanied by accelerated propagation and enlarged fracture widths; however, excessive displacement intensifies fluid leak-off, ultimately reducing the equal-pressure fracture length.

Processes doi: 10.3390/pr14152523

Authors: Kai Zuo Binggang Wang Yunchi Zhang Chuangang Liu Jingchao Liu Mingxuan Zhang

Flow-path switching is a key operating condition that enables flow regulation, zonal conversion, and filling-path redirection in sand-control completions. The associated flow characteristics directly govern the operational stability and service reliability of intelligent filling tools. Most existing studies have addressed erosion only under simple geometries such as pipe contractions and expansions, leaving the dominant erosion-controlling factors and rapid erosion-rate prediction methods for sand-control filling tools under flow-path switching conditions insufficiently understood. This study developed a Fluent-based numerical model of solid–liquid two-phase erosion for intelligent filling tools and characterizes the wall-erosion distribution pattern during flow-path switching. Guided by field practice, multi-factor simulations were performed over the reduction angle, cutting particle size, inlet flow capacity, flow-switching direction, opening area, and structural form. On this basis, a maximum-erosion-rate prediction model was constructed using a logarithmic transformation combined with a stepwise quadratic response-surface method. This regression-based approach was deliberately chosen over machine-learning black-box models, whose limited interpretability and small-sample reliability make it difficult to reveal the underlying physical mechanisms; in contrast, the proposed model yields an explicit algebraic expression whose significant interaction and quadratic terms directly reflect the coupling between structural and operating parameters, while the logarithmic transformation accommodates erosion-rate fluctuations spanning several orders of magnitude. The results show that the factors rank in influence as follows: flow-switching direction > opening area > reduction angle > inlet flow capacity > cutting particle size > structural form. The established prediction model attained a coefficient of determination of about 0.951 and an adjusted coefficient of determination of about 0.901; combined with the significance test and a residual analysis, the model can effectively characterize the coupling influence of structural parameters and operating parameters on the erosion rate. These findings provide quantitative guidance for the erosion-resistant structural design, field operating-parameter selection, and preliminary service-life assessment of intelligent filling tools in offshore sand-control well-completion operations. The prediction model is further validated through jetting-erosion bench tests; the measured erosion rates agree closely with the model-predicted values, confirming the practical reliability of the model and its capability to serve as an engineering reference for the erosion-resistant design and service-life assessment of intelligent filling tools in sand-control well-completion operations.

Processes doi: 10.3390/pr14152522

Authors: Qian Ma Chunxiao Liu Kui Huang Qinglin Zou Zelong Lu Xianzhuo Liu Binbin Chen Jingjing Wang Zuyi Li

Under the strategic goals of “peak carbon emissions and carbon neutrality”, traditional methods for solving economic dispatch problems involving carbon emission trading costs, wind power, and energy storage devices lack real-time performance and are difficult to support in real-time decision-making. This paper proposes an accelerated solution framework that expands the projection gradient descent method into a Deep Projected Gradient Network (D-PGNet). The network consists of K structured layers, each layer strictly embedding differentiable projection operations corresponding to physical constraints such as power balance, unit ramp-up, and energy storage timing dynamics. This paper systematically derived the projection closed-form solutions of each constraint set to the basic subset, designed an efficient differentiable projection layer based on Dykstra alternating projection, and analyzed the differentiability and convergence properties of the network. Multiple scenario tests have shown that the optimal gap of D-PGNet results is less than 1.08%, the carbon emission deviation is less than 0.2%, the solving speed is improved by more than 64 times at most, and the maximum violation of all physical constraints is below 1.3 × 10−5 p.u.

Processes doi: 10.3390/pr14152521

Authors: Jieyun Tang Zuhua Dong Wei Fu Pengchao Guo Yugang Li Fuzhen Chen Hong Zhang Zengyuan Zhou

Accurately identifying organic-rich shale intervals remains a major challenge in lacustrine shale oil exploration, particularly in continental rift basins characterized by rapid environmental change and pronounced vertical heterogeneity. This study investigates the upper Jiufotang Formation in the Ludong Sag, Kailu Basin, NE China, using total organic carbon (TOC), vitrinite reflectance, multi-stage programmed rock pyrolysis, and major and trace element geochemistry to constrain the processes governing organic matter enrichment and hydrocarbon occurrence. The studied shales contain abundant organic matter, with TOC values ranging from 1.91% to 7.55% and averaging 4.22%. Type II2 kerogen and vitrinite reflectance values of 0.60–0.94% indicate oil-prone organic matter at low-mature to mature stages within the oil generation window. Multi-stage pyrolysis shows that the hydrocarbon assemblage is dominated by bound oil and residual kerogen-derived fractions, whereas the low-temperature movable oil fraction is limited. TOC is more strongly associated with the high-temperature pyrolysis fractions than with the light free-oil fraction, indicating that organic matter abundance primarily controls residual hydrocarbon generation potential but does not directly determine present-day movable oil content. Multiple elemental proxies are collectively consistent with deposition in a hydrologically restricted, variably brackish–saline lacustrine system with water-mass differentiation. Redox-sensitive indicators, including V/(V + Ni) and Mo, suggest persistent weakly reducing to reducing bottom-water conditions. After correction for carbonate- and phosphate-associated Ca, CIA values fall within a narrow range of approximately 67–70, indicating moderate and relatively stable source area chemical weathering. Organic matter enrichment was governed by the coupled effects of organic matter supply, preservation under stratified oxygen-deficient waters, and sedimentary dilution. We therefore propose a two-stage process framework in which depositional productivity–preservation coupling first promoted organic matter accumulation, whereas subsequent thermal maturation, hydrocarbon expulsion, retention, and adsorption reshaped the present hydrocarbon occurrence state. The results demonstrate that high organic matter abundance and residual generation potential do not necessarily translate into high movable oil content and provide a well-scale geochemical basis for source rock evaluation and future multi-well assessment in continental rift lake systems.

Processes doi: 10.3390/pr14152520

Authors: Nannan Lv Xiaoxia Chen Zhigang Wen Lei Wang Di An Lingyun Kong

Hydraulic-fracture transmission across lithologic interfaces governs fracture-height growth and reservoir connectivity in shale–sandstone interbedded reservoirs, yet the coupled effects of mechanical contrast, interface properties, layer geometry, and operational parameters remain insufficiently quantified. A two-dimensional plane-strain hydraulic-fracturing model was developed in ABAQUS by coupling Biot poroelasticity, cohesive-zone damage, and fracture-fluid flow. The model explicitly represents thin, alternating continental shale–sandstone layers, lithology-dependent in situ stress and stiffness, and cohesive interfaces; its implementation was assessed against the KGD solution and published layered-rock fracture morphologies. Under the simulated conditions, increasing the shale-to-sandstone elastic-modulus ratio from 0.4–0.5 to 0.6–0.8 reduced the number of penetrated layers from eight to six. Increasing tensile strength from 4 to 16 MPa reduced the number of penetrated layers from ten to six and the final fracture length from 32 to 21 m, while increasing the maximum aperture from 6.75 to 9.02 mm. A sandstone interlayer thickness of approximately 3 m marked a transition in the present parameter set rather than a universal threshold. Sandstone-centered perforation and higher injection rates promoted vertical connectivity, whereas very high fluid viscosity increased near-wellbore aperture but restricted long-distance fracture-height growth. These results provide a mechanics-based framework for optimizing perforation placement and stage-specific fluid design in continental interbedded shale reservoirs.

Processes doi: 10.3390/pr14152519

Authors: Yuanmeng Zhou Haoyi Tan Jiawei Li

When flexible job shop scheduling faces concurrent disturbances such as machine failures and rush orders, worker-centric constraints emphasized under Industry 5.0 must also be satisfied. Existing deep reinforcement learning methods for the Dynamic Flexible Job Shop Scheduling Problem (DFJSP) seldom treat worker workload balance as an explicit constraint, and most depend on static penalty coefficients that are difficult to tune across different scenarios. In this paper, we suggest ALP-PPO, an adaptive Lagrangian penalty-enhanced proximal policy optimization algorithm, for real-time rescheduling under concurrent machine breakdowns and rush orders. We formulate the scheduling environment as a constrained Markov decision process. Worker skill heterogeneity, fatigue accumulation and workload equity are modeled as coupled constraints alongside classical scheduling objectives. By decoupling operation sequencing, machine allocation and worker assignment into coordinated sub-decisions, a hierarchical action space is constructed. Dual Lagrangian multipliers for workload balance and fatigue are updated adaptively during training, so that manual penalty tuning is no longer required. An event-triggered mechanism selects between right-shift and full rescheduling on the basis of a disruption severity index. We employ weighted-sum scalarization of makespan, energy consumption and workload variance during training, and Pareto solution sets are obtained by systematically varying the weight vectors across independent training runs. On extended Brandimarte benchmarks augmented with worker and dynamic event parameters, ALP-PPO delivers superior scheduling performance across makespan, energy consumption and workload variance when compared with Double DQN, Dueling DQN, standard PPO, NSGA-II and MOEA/D, as measured by Hypervolume (HV) and Inverted Generational Distance (IGD) indicators. Ablation studies indicate that the adaptive Lagrangian mechanism reduces constraint violations by more than 40% relative to fixed-penalty alternatives while keeping the primary objectives competitive. An analysis of computational efficiency shows that ALP-PPO completes online inference in under 20 ms per decision step, making real-time rescheduling practically feasible. Generalization experiments on previously unseen instances further validate the transferability of the learned policy. These findings support human-centric intelligent scheduling in Industry 5.0 manufacturing.

Processes doi: 10.3390/pr14152518

Authors: Chaojiang Yan Jiuqun Zou Shouzhong Feng Guoning Tang Jianyong Pang

To investigate the mechanical response and energy-damage evolution of argillaceous sandstone under coupled hydro-softening and confining pressure effects, triaxial compression tests were conducted under different water contents (0%, 3.1%, 6.2%, and 9.3%) and confining pressures (0, 3, 6, 10, and 15 MPa). The stress–strain characteristics, failure modes, strength criteria, and energy evolution laws were systematically analyzed. The results show that argillaceous sandstone exhibits a pronounced hydro-softening effect. When the water content increased from 0% to 9.3%, the peak strength decreased by 28.5–50.3% under different confining pressures, with more significant deterioration at the low-water-content stage. Increasing the confining pressure from 0 to 15 MPa increased the peak strength by 180–240% and enhanced the plastic deformation capacity, partly offsetting the weakening induced by hydro-softening. Regression analyses indicate that the exponential strength criterion provides the best applicability for the triaxial strength of argillaceous sandstone. The proposed water-content-modified exponential strength criterion can characterize both hydro-softening and confining pressure effects, with an average relative error of 2.11% and a maximum relative error of 4.70%. Energy analysis shows that increasing water content reduced the elastic energy storage capacity; under uniaxial compression, the peak elastic strain energy at 9.3% water content was 64.4% lower than that in the dry state. The energy-based damage model can describe the pre-peak damage evolution and stress response of argillaceous sandstone. The results can provide a theoretical basis for the stability evaluation of surrounding rock in water-rich soft rock underground engineering.

Processes doi: 10.3390/pr14152517

Authors: Lihua Tong Yaohua Li Jie Li Yantong Liu Lei Shi Caiqin Bi Wenjie Xia Yinbo Xu Yuan Yuan Yue Tang

The Cretaceous shallow oil sands in the Dagang area, located on the western slope of the Songliao Basin, are characterized by a burial depth of ≤182 m, an average reservoir temperature of 11.8 °C, an extremely high crude oil viscosity of 1,750,000 mPa·s at 15 °C, and water-bearing layers in both the roof and floor. Conventional thermal recovery methods such as SAGD and CSS are geologically unsuitable for this deposit and suffer from high energy consumption and carbon emissions. As microbial oil recovery is a technically advanced enhanced oil recovery technology that leverages microbial growth, reproduction and metabolism in the reservoir to alter the properties of oil, rock, gas and water through interaction with these components, and petroleum biotechnology research confirms that microorganisms can degrade high-molecular-weight petroleum hydrocarbons to reduce crude oil viscosity and improve its fluidity, this study explores the technical feasibility of microbial cold recovery for in situ extraction of such low-temperature, high-viscosity oil sands. The study adopts a five-well pilot pattern (one injector and four producers) with an integrated approach combining reservoir unblocking, microbial viscosity reduction, and vibration-assisted production. Systematic screening identified Pseudomonas, Chryseobacterium, and Citrobacter as the most efficient indigenous microbial strains. Pseudomonas exhibited a crude oil degradation rate of 32.17%, reducing asphaltene content from 7.47% to 3.56%, and achieved large-scale proliferation (2.5 × 108 cfu/mL) at 15 °C. It also achieved a 40.8% reduction in crude oil viscosity and a desulfurization rate, alongside 56.6% denitrification. With the optimal activator No. 3, the viscosity reduction rate reached 45.18%, and the viable cell count exceeded 9.45 × 108 cfu/mL. The synergistic action of Pseudomonas and an A-type nano-microemulsion surfactant reduced the oil–water interfacial tension from 49.56 to 1.25 mN/m (a 97.48% reduction) and lowered the crude oil viscosity at 25 °C from 302,000 to 11,023 mPa·s (a 96.35% reduction). Core flooding tests demonstrated an incremental oil recovery of 7.38% compared with the water-flooded control, with interfacial tension dropping from 48.21 to 1.18 mN/m. In the field trial, composite perforation (32 shots/m, 1610 mm penetration) and two cycles of oil-based fermentation fluid huff-n-puff reduced injection pressure from 2.0 to 2.5 MPa to 1.0–1.8 MPa. A total of 1489 m3 of microbial agent was injected into five wells, followed by a 125-day shut-in period. Nano-microemulsion single-well huff-n-puff (579 m3 over 87 days) further decreased injection pressure to 0 MPa. A downhole harmonic vibration source (≤20 Hz) was also applied during the trial. During the production phase, Pseudomonas was found to dominate the produced fluid, with its peak relative abundance exceeding 70%. Cumulative fluid production reached 4114 m3, yielding 21 m3 of oil sand oil. Wells with vibration assistance showed significantly higher oil content and better emulsification performance than wells without vibration assistance.

Processes doi: 10.3390/pr14152516

Authors: Zhiqiang Li Lei Liu Ruokun Zheng Liang Wang Yu Peng Wei Wang

The long-term productivity of hydraulically fractured deep coalbed methane (CBM) wells is jointly governed by desorption-driven gas supply from the coal matrix, the effective-stress response and time-dependent creep of natural cleats, and the progressive degradation of hydraulic-fracture conductivity. To address the difficulty of conventional models in consistently describing the time-dependent transport capacities of natural cleats and hydraulic fractures, this study develops a productivity-prediction model for hydraulically fractured deep CBM wells that couples gas storage in the coal matrix, dynamic natural-cleat permeability, and dynamic hydraulic-fracture conductivity. Based on mass conservation, the model accounts for free- and adsorbed-gas storage, single-phase gas flow, matrix-fracture mass transfer, and wellbore production. The evolution of natural-cleat permeability incorporates effective-stress-induced closure, Langmuir desorption shrinkage, and fractional-order creep, whereas the evolution of hydraulic-fracture conductivity considers fracture compaction, elastic deformation and embedment of proppants, and creep-induced closure of the coal rock. The nonlinear coupled equations are solved using a fully implicit finite-difference scheme. The field dataset comprises daily production records from six deep CBM wells and is used only to constrain physically reasonable ranges of field parameters and provide reference production characteristics. The results indicate that effective stress primarily controls the rapid closure of flow pathways during the early production stage, while the relative contribution of coal creep increases with production time. Neglecting either coal creep or stress sensitivity leads to an overestimation of cumulative gas production over the medium and long term. The proposed model provides a physically constrained analytical framework for evaluating the long-term productivity of hydraulically fractured deep CBM wells and comparing alternative production strategies.

Processes doi: 10.3390/pr14152515

Authors: Chanwoo Lee Haeyong Min Seik Paik Sungin Bae Dae Sung Lee

Evaluating the sealing integrity of caprocks is critical for ensuring the long-term safety and containment efficiency of geological hydrocarbon reservoirs and CO2 storage systems. In this study, we evaluated the caprock sealing capacity of the South Sea continental shelf using drill cutting samples collected from six wells across four structural blocks. Representative caprock intervals, consisting primarily of fine-grained sedimentary rocks, were identified based on well data and lithofacies information. Mercury Injection Capillary Pressure (MICP) analyses were performed to characterize pore structure and capillary sealing behavior. Results indicate that nanopores (<1 μm) dominate the pore system; however, pore size distributions exhibit significant heterogeneity. While B well samples displayed unimodal nanopore distributions, other wells showed bimodal or broad multiscale structures. As a result, MICP-derived Hg-air breakthrough pressures (Pb) varied considerably, ranging from 75 to 283 MPa. Notably, samples G-1 and J5-4 exhibited sealing capacities capable of retaining CO2 column heights exceeding 5052 m, whereas sample J1-1 showed the lowest sealing performance. In the B well, a clear depth-dependent trend was observed: as depth increased from 2480 m to 3685 m, the critical pore diameter decreased from 13.66 nm to 7.57 nm, and breakthrough pressure increased from 95 MPa to 171 MPa. Subsequent quantitative XRD analysis, corrected for drilling-induced contamination, revealed that these deeper intervals are characterized by clay-rich (50.85–63.19%) and relatively ductile mineralogical compositions. These findings suggest that burial-related compaction within a consistently clay-rich, relatively ductile matrix may contribute to pore-throat refinement and enhanced relative capillary sealing capacity in the B well. Overall, the caprocks of the South Sea continental shelf show significant potential for geological hydrocarbon and CO2 storage, though the observed spatial and depth-dependent heterogeneity underscores the necessity of well-specific site characterization.

Processes doi: 10.3390/pr14152514

Authors: Mikhail Petrushin Efim Kherson Nikita Smirnov Evgeniy Yudin Shadfar Davoodi Viktoriia Gorbacheva

Unstable well operations, driven by reservoir depletion, high gas–oil ratios, unstable inflow, and surface network interactions, have become a major challenge in modern production — especially in Western Siberian fields — causing flow instabilities and production losses. While numerous studies have advanced transient modeling for field optimization, their practical application remains largely limited to recommendation systems running on hourly or daily cycles, making recommendations irrelevant by the time they are applied. At the opposite end, PLCs (programmable logic controllers) relying on PID (proportional–integral–derivative) control cannot solve the main problem: determining the structure of the intermittent cycle. This work proposes a reduced-order transient model of the coupled “reservoir–tubing–annulus” system that captures the essential behavior of transient multiphase flow while remaining compact enough for on-edge real-time model predictive control. Constrained optimization algorithms built on this model provide autonomous closed-loop well control, ensuring equipment and reservoir limits are respected and enabling safe, smooth mode transitions. The solution was validated against high-fidelity simulations and real operating data from Western Siberian fields, demonstrating reliable intermittent ESP (electrical submersible pump) well operation, robust response to rapid operational changes, and effective disturbance rejection.

Processes doi: 10.3390/pr14152513

Authors: Wenjun Hu Huiming Kang Zenghui Shang Kegang Li Zhiqiang Qiao Hao Chen

To investigate the rockburst failure characteristics and underlying mechanisms of deep straight-wall arch roadways containing structural planes, deep-mined limestone was selected as the rock material. True triaxial rockburst experiments were conducted on cubic limestone specimens containing a straight-wall arch roadway. A high-speed camera and an acoustic emission system were employed to monitor, in real-time, the initiation and evolution of the rockburst process. In addition, numerical simulations of straight-wall arch roadways containing structural planes with different spacings were carried out using the PFC software, and the failure patterns and rockburst evolution characteristics of surrounding rock with different structural-plane spacings were systematically analyzed. The results indicate that the presence of structural planes significantly alters the stress and energy transmission paths within the rock mass, leading to local stress concentration, enhanced rockburst impact intensity, and more complex microscopic morphologies of the ejected rock fragments. Compared with specimens without structural planes, specimens containing structural planes exhibited higher cumulative acoustic emission ring-down counts and cumulative absolute energy, accompanied by pronounced transient high-amplitude acoustic emission activity. Moreover, the proportion of shear failure in specimens containing structural planes was higher than that in intact specimens without structural planes. With increasing structural-plane spacing, the failure mode of the surrounding rock gradually changed, while the mutual constraint between the rock mass and the structural planes weakened. As the structural-plane spacing increased, the failure pattern of the surrounding rock changed, and the constraining effect of the rock mass on the structural planes gradually weakened. Consequently, crack propagation paths became increasingly oriented toward the free surface, resulting in a progressive decrease in the propagation angle of wing cracks. Based on the experimental data, a theoretical relationship was established between structural-plane spacing and the stress characteristic parameter of the straight-wall arch roadway, σi/σmax. These findings can provide a useful reference for disaster prevention and mitigation, as well as rockburst prediction, in underground openings containing structural planes under impact disturbance.

Processes doi: 10.3390/pr14152511

Authors: Adán Cabal-Prieto Emmanuel de Jesús Ramírez-Rivera Lorena Guadalupe Ramón-Canul Lucía Sánchez-Arellano Jesús Atenodoro-Alonso José Vian Jorge Armida-Lozano Humberto Marín-Vega Víctor Daniel Cuervo-Osorio Erasmo Herman-Lara

The objective of this study was to apply the Temporal Dominance of Sensations (TDS) technique to the analysis of adulterated honey and to validate it by comparing its results with those obtained using the static sensory techniques Check All That Apply (CATA) and Rate All That Apply (RATA). Honey samples adulterated with 20%, 40%, 60%, and 80% high-fructose corn syrup (HFCS) were evaluated and compared with the original honey sample by three consumer panels (n = 300) using TDS, CATA, and RATA. Discriminant analysis was performed to evaluate sample discrimination, classification accuracy, and correlations among sensory techniques. The TDS curves revealed that the dominant attributes were honey, sugar, syrup, and sweep. The original sample was characterized by the dominance of the honey flavor attribute, whereas the adulterated samples exhibited competition among the sugar, syrup, and sweet attributes as the level of adulteration increased. This finding was confirmed by the TDS parameters Vmax and Tmax, which showed that higher levels of adulteration facilitated consumer identification of these sensory attributes. According to the λ test, the TDS and CATA techniques showed significant differences in all attributes (100% discrimination effectiveness), whereas the RATA technique achieved only 62.5% discrimination. However, the confidence ellipses showed lower dispersion for the TDS data, indicating that all honey samples were differentiated, whereas the confidence ellipses generated using the CATA and RATA techniques indicated that at least one pair of samples was classified as similar. These results were confirmed by the percentages of correct classification, with the TDS technique achieving correct classification rates between 69.77% and 85.38%, whereas those obtained with CATA and RATA ranged from 39.18% to 69.09% and from 6.36% to 63.64%, respectively. The Rv coefficients indicated good agreement between TDS and the static sensory techniques (Rv TDS-CATA = 0.70 and Rv TDS-RATA = 0.82). The TDS technique, together with the Vmax and Tmax parameters, represents a viable approach for identifying adulterated honey and monitoring its dynamic sensory changes during real-time consumption.

Processes doi: 10.3390/pr14152512

Authors: Li Wang Chaofan Wang Dongyang Zhang Yongxu Xing Linlin Xie Kun Gao

As intelligent power grid construction accelerates, power metering warehouses increasingly require fully automatic handling of diverse and fragile devices, ranging from smart meters to current transformers. Conventional rigid clamping schemes apply fixed empirical thresholds and cannot adapt to objects with different sizes, masses, and surface properties, so positioning errors and unexpected collisions often cause component damage. This paper proposes a flexible grasping scheme with adaptive force regulation for power metering equipment. A multifunctional end-effector controller generates gripping force profiles and impedance parameters according to the estimated properties of each target object. An online optimization module based on deep reinforcement learning fuses feedback from a six-axis force sensor and adjusts the grasping trajectory and controller parameters during contact. A closed-loop framework coordinates visual perception before contact with force-controlled execution after contact. Experiments on a UR5e platform with four categories of metering equipment show that the proposed method achieves a grasp success rate of 91.8% and a damage rate of 2.8%, outperforming five comparison methods.

Processes doi: 10.3390/pr14152510

Authors: Jiuzhou Tian Akira Tanaka Di Gao

Particle-scale analysis of blast furnace burden surfaces lacks an operational criterion for separating long-scale shape from short-scale texture on complex digital elevation models. This study proposes a prior-informed framework in which the application cutoff ω*=argminJ minimizes the mismatch between high-pass texture RMS height and the tiled-surface prior of the same particle batch. On cold-state large-coke belts with identical particles but different long-scale morphology, numerical validation via RMS–frequency transition analysis shows coincident transition structures. At a transition-informed validation cutoff of ω=4.2, absolute texture errors of 1.56–3.22 mm are comparable in magnitude to the approximately 2 mm instrument depth resolution. Grid-search application yields ω*=5.8 and 4.4 with absolute errors of 0.03 and 0.35 mm and operationally distinct shape and texture components. The separated fields can supply bed-surface boundaries and local roughness inputs for gas–solid simulation and charging optimization.

Processes doi: 10.3390/pr14152509

Authors: Tong Zhang Xiaolong Song Jian Liu Jiuhui Cheng Liang Yuan

Large-scale physical model experiments play a critical role in understanding the coupled thermo–hydro-mechanical responses during hydrate dissociation. In this study, a specially designed large-scale physical simulation apparatus (effective volume: 1178 L) was employed to investigate the depressurization-induced dissociation behavior of CO2 hydrate, which was used as a model system to simulate the macroscopic response of hydrate-bearing sediments under controlled laboratory conditions. Key reservoir parameters—including temperature, pressure, electrical resistivity, gas production rate, and stratum displacement—were continuously monitored using an integrated array of temperature sensors, pressure transducers, electrical resistivity probes, and displacement meters. During depressurization, the system pressure decreased from 3 MPa to 1 MPa (matching the backpressure), while the internal temperature dropped from 3.5 °C to approximately 1 °C due to the endothermic dissociation of the hydrate. Gas production exhibited a three-stage evolution: an initial slow release, a rapid increase as the dissociation front propagated through the sediment, and a plateau upon completion of hydrate dissociation. Based on the measured gas production and CO2 consumption, the hydrate saturation was estimated to be approximately 0.248. The dissociation process led to measurable sediment settlement, with a maximum vertical displacement of 88.3 mm (approximately 5.88% of the model height). Analysis of the evolution of effective stress indicates that depressurization reduced pore pressure and increased vertical effective stress by approximately 0.55 MPa, while hydrate dissociation weakened the sediment skeleton, jointly causing settlement. This study demonstrates the feasibility of using a large-scale apparatus to capture the coupled processes during hydrate dissociation. It provides benchmark experimental data for validating numerical models of hydrate-bearing sediment behavior. Further validation is required before these results can be extrapolated to CH4 hydrate systems.

Processes doi: 10.3390/pr14152505

Authors: Begzat Akhmetov Assylbek Nurumgaliyev Alibek Baisanov Talgat Zhuniskaliyev Bibigul Dossanova Gulnar Altayeva Indira Tolessinova

The aim of this study was to develop a roasting–magnetic separation technology for ferruginous manganese fines generated during the processing of ores from the Tur deposit in order to reduce iron content and increase manganese concentration in products suitable for subsequent metallurgical applications. A process flowsheet involving magnetizing reduction roasting with a carbonaceous reductant (Shubarkol coal) followed by magnetic separation was proposed. The effects of key process parameters, including reductant dosage (20 and 30 wt.%), roasting duration (180 and 300 min), and particle size distribution, were systematically investigated. The separation efficiency of iron and manganese was found to depend strongly on the roasting conditions and the reduction degree of iron-bearing phases. The proposed technology demonstrated high efficiency, with the best results obtained at 30 wt.% coal and 300 min of roasting, achieving manganese recovery of up to 73.40% in the non-magnetic product while reducing iron content to 2.13%. Furthermore, the inclusion of a preliminary magnetic separation stage improved process selectivity, producing a manganese concentrate containing up to 31.9% Mn and 2.0% Fe. X-ray diffraction analysis confirmed the formation of (Fe,Mn)O, hausmannite, and braunite, while quartz remained the dominant gangue phase. The results demonstrate the potential for efficient utilization of ferruginous manganese fines and the expansion of the metallurgical raw material base in Kazakhstan.

Processes doi: 10.3390/pr14152508

Authors: Xiaochun Liu Shengchen Xie Jiuzheng Yu Jinfeng Yang Jianshan Li Shijun Huang

Tight oil reservoirs are characterized by poor petrophysical properties, ultra-low permeability, and limited pressure-transmission capacity. After hydraulic fracturing, retained fracturing fluid can accumulate near the fracture–matrix interface and form a water shield, which restricts carbon dioxide (CO2) seepage, CO2–oil contact, and crude-oil mobilization during CO2 huff-n-puff. To clarify the control mechanism of a fracture-adjacent water shield on pressure dynamics and pore-scale oil mobilization in tight reservoirs, three stepwise core experiments were designed: a non-fractured core without a water shield (#E1), a single-fracture core without a water shield (#E2), and a single-fracture core with a MnCl2-induced water shield (#E3). Pressure monitoring, cumulative nuclear magnetic resonance (NMR) T2 spectra, and NMR imaging were integrated to compare the matrix, fracture, and water-shield effects. The results show that the water shield does not act as a constant resistance during cyclic CO2 huff-n-puff. In Cycle 1, the water shield restricts CO2–oil contact, and the relative pressure-decline amplitude of #E3 is approximately 10% lower than that of #E2. In Cycle 2, the relative pressure-decline amplitude of #E3 increases to 18.4%, approximately 1.8 times that of #E2, indicating a local water-shield transition rather than uniform matrix sweeping. The T2-derived recovery degrees of #E3 are 7.24%, 15.34%, 7.96%, and 4.07% from Cycles 1 to 4, respectively, and its cumulative recovery after four cycles is 34.61%, which is 7.32 percentage points lower than that of #E2. NMR imaging further shows that the swept region in #E3 is mainly concentrated near the fracture after Cycle 2, while matrix regions away from the fracture retain strong oil signals. These results indicate that the water shield first acts as a fracture-adjacent water-phase barrier and then undergoes a local transition into a preferential pressure-dissipation pathway. The findings provide a basis for interpreting pressure decline together with NMR evidence and for optimizing CO2 huff-n-puff operations in tight reservoirs affected by retained fracturing fluid.

Processes doi: 10.3390/pr14152507

Authors: Guo-Feng Li Zi-Tao Zhao Xin-Ye Lan Ya-Ya Ma Xian-Yong Wei Xing Fan He Li Wei-Qiang Yang Hui-Qiang Zheng Cheng-Lin Chang Wen-Long Mo

Vacuum residue (VR) is one of the more difficult heavy fractions to process in petroleum refining, and the development of clean utilization technologies for vacuum residue has become a major research focus in the petrochemical industry. This paper discusses the compositional and structural characteristics of vacuum residue from Karamay (KVR) using methods such as ultimate analysis, FTIR, and TG-DTG. The thermal gravimetric kinetics analysis was conducted based on TG-DTG curves at different heating rates. Ultimate analysis revealed that KVR has a high H/C atomic ratio (1.84), and combined with the strong peaks at 2920 cm−1 and 2850 cm−1 in its infrared spectrum, it indicates that KVR is mainly composed of aliphatic compounds, with aromatic compounds being relatively few. High-temperature simulated distillation showed that KVR had a broad boiling-range distribution, with the temperature corresponding to a cumulative recovery of 86.4% exceeding 720 °C, indicating the presence of a certain proportion of ultra-high-boiling components in KVR. The Coats–Redfern kinetic model shows significant variations in activation energy (Ea) at different temperature ranges and reaction orders. Kinetic studies using non-model methods show smaller differences in Ea derived from four different non-model methods. Overall, KVR’s pyrolysis process is complex, with Ea ranging between 100 and 300 kJ/mol.

Processes doi: 10.3390/pr14152506

Authors: Ruihao Zhou Penghui Liu Wenxiang Li Jugen Zhou Zhengyang Li

Large-scale integration of high-proportion new energy sources and continuous expansion of network scale complicate the transient characteristics of distribution networks. Conventional fault diagnosis methods suffer from insufficient feature extraction and weak capture of topological correlation, which degrade diagnosis accuracy. To tackle this issue, this paper proposes a complex fault diagnosis strategy for distribution networks based on analysis of the dynamic variation law of zero-sequence current. First, multivariate variational mode decomposition (MVMD) is adopted to process zero-sequence current signals, which effectively fuses multi-dimensional zero-sequence current data and fully excavates fault features. Moreover, the zebra optimization algorithm is utilized to optimize the parameters of MVMD for further improving feature extraction performance. Subsequently, a graph convolutional neural network is employed to extract temporal features from the processed waveforms, enhancing the model’s recognition capability under high-resistance faults and typical disturbance conditions. Finally, multiple IEEE test systems are used for verification, which demonstrates the effectiveness and feasibility of the proposed method.

Processes doi: 10.3390/pr14152504

Authors: Symbat Dyussenova Sergey Gladyshev Erzhan Kuldeyev Leila Imangaliyeva Dametken Fischer Ahmad Mohammad Bahgat Mohammad Gemeal Asya Kasymzhanova Alfiyam Manapova

The present study addresses the first stage in the development of a processing technology for low-grade high-silica bauxites aimed at producing solutions suitable for carbonation. The proposed process includes Bayer leaching of bauxite to obtain sodium aluminate liquor and red mud, followed by sintering of the red mud with limestone and soda ash. The resulting sinter is then leached with a recycled soda-caustic solution to produce an alkaline aluminate liquor and a residue. The alkaline aluminate liquor obtained from sinter leaching is subjected to carbonation to precipitate aluminum hydroxide, which is subsequently used as seed material during the decomposition of Bayer sodium aluminate liquor. The proposed technology reduces the volume of aluminate liquor directed to the Bayer decomposition stage while maintaining aluminum hydroxide yield, thereby improving the efficiency of the decomposition process.

Processes doi: 10.3390/pr14152503

Authors: Raimundo Fernández Gassó Lorenzo Sevilla Hurtado Juan Miguel Cañero-Nieto

Vertical Roller Mills (VRMs) are extensively used in the cement industry for their high energy efficiency. Nonetheless, the start-up phase remains a critical operational challenge due to its pronounced sensitivity to changing process conditions. Such variations frequently induce excessive vibrations, which can trigger unplanned shutdowns, mechanical damage, and diminished throughput. The underlying cause lies in the intrinsic variability of raw materials, particularly in parameters such as moisture, particle size distribution, and hardness, which exert a direct influence on the mill’s dynamic response during the transition to steady-state operation. This study presents the real-world implementation of an Expert System designed to automate the start-up sequence. By applying logical reasoning to key process setpoints, the system enables a controlled and gradual ramp-up, minimizing transient instabilities. Seamlessly integrated into the plant’s control infrastructure, it facilitates remote unattended operation, enhancing process reliability and operational efficiency. The proposed architecture addresses a key challenge in cement production and enables advanced control and intelligent optimization.

Processes doi: 10.3390/pr14152502

Authors: Kequan Lin Xiaoli Yi Haodong Du Lei Zhuang Cong Lin Shiao Wang Jie Zhao

To address the dynamic communication topology switching, asynchronous perception information, and uncertainty caused by vehicle mobility in the cooperative control of a vehicle-charger pile-grid under industrial Internet environments, this paper proposes a cooperative optimal control method based on decentralized holistic sensing graph-based estimation. First of all, this method constructs a time-varying weighted directed graph by using decentralized holistic sensing data obtained from the industrial Internet to characterize the dynamic evolution of communication topologies in real time. Secondly, a distributed graph estimator relying solely on local perception information is designed, enabling each agent to predict online its neighbor set and link reliability over a short future horizon based on its own position, the motion trends of nearby objects, and historical link states. On this basis, the graph-based estimation results are embedded as a feedforward compensation term into the consensus control law, forming a predictive graph consensus control algorithm that enables the system to proactively adjust control inputs before topology switching occurs, achieving a paradigm shift from “passive response” to “active pre-compensation.” Meanwhile, an Age of Information (AoI)-aware event-triggered mechanism is introduced, where broadcasting is triggered when the state error exceeds a threshold or the AoI approaches its upper bound, significantly reducing communication load while ensuring control accuracy. Finally, simulations are conducted on a modified IEEE 33-bus distribution system comprising 61 agents (20 electric vehicles, eight charging stations, and 33 grid nodes). The results show that, compared to the event-triggered consensus method without prediction, the proposed method reduces the steady-state error by 40.1%, shortens the convergence time by 40.5%, and decreases the number of broadcasts by 36.5%. In a large-scale system with 169 agents, the proposed method still maintains the highest accuracy, the fastest convergence speed, and the lowest communication overhead, while meeting real-time computational requirements. This method can fully exploit the spatiotemporal redundancy of decentralized holistic sensing, offering a new solution for efficient, robust, and low-cost cooperative control of “vehicle–charger–grid” under industrial Internet environments.

Processes doi: 10.3390/pr14152501

Authors: Carolina Ramírez Florencia Curi Alice Elizabeth González Lucía Rivadavia

Medium-density fiberboard (MDF) and other resin-bonded wood panels pose significant end-of-life management challenges due to the presence of urea–formaldehyde (UF) resins, which hinder material recovery and circular valorization. This study evaluates hydrolysis-based methods for removing UF resins from waste MDF, melamine-faced MDF, oriented strand board (OSB), and plywood generated in a technological industrial park in Montevideo, Uruguay. The evaluated hydrolysis treatments comprised acid, alkaline, and water hydrolysis at 80 °C under agitation, and steam-assisted hydrolysis in an autoclave. Treatment performance was evaluated using total Kjeldahl nitrogen analysis, elemental analysis, mass loss determination, and semi-quantitative formaldehyde measurements using Quantofix® indicator strips. Among the evaluated treatments, solvent-assisted hydrolysis using 0.1 M oxalic acid achieved the highest resin removal efficiency, reaching nitrogen removal values of up to 95%, while steam-assisted hydrolysis achieved removals above 90% using only distilled water. Treatment efficiency was strongly influenced by the solid-to-liquid ratio (S/L ratio) and the processed mass, highlighting key operational variables for process optimization. Overall, the proposed hydrolysis routes constitute effective pretreatment strategies for producing wood fibers with substantially reduced urea–formaldehyde resin content, thereby supporting the circular valorization of resin-bonded wood waste.

Processes doi: 10.3390/pr14152500

Authors: Sholpan Tursunbayeva Auyelbek Iztayev Zhuldyz Nurgozhina Madina Yakiyayeva Bauyrzhan Iztayev Bayan Muldabekova Maxat Mamyrayev Diana Abdraimova Fatima Yermetaeva

Mechanically aerated yeast-free dough is particularly susceptible to freeze–thaw damage because its porous structure is formed before freezing and cannot be restored during thawing due to the absence of fermentation. This study investigated the combined effects of apple powder incorporation and technological processing conditions on the rheological, structural, physicochemical, nutritional, and sensory properties of whipped yeast-free frozen dough and the resulting bread. Apple powder was incorporated at three formulation levels (50, 100, and 150 g per batch), while whipping speed (450–900 rpm), whipping time (3–7 min), freezing temperature (−14 to −38 °C), and microwave thawing time (4–8 min) were optimized using response surface methodology based on a Draper–Lin composite design. Dough properties were evaluated using Mixolab analysis and structural–mechanical measurements, whereas bread quality was assessed by specific volume, porosity, physicochemical characteristics, biochemical composition, amino acid profile, microbiological safety, and sensory evaluation. The developed regression models adequately described the effects of technological variables on dough quality (R2 > 0.95). Deep freezing at −38 °C followed by 4 min of microwave thawing minimized structural deterioration and improved dough stability after freeze–thaw treatment. Apple powder increased the nutritional value of the bread by enhancing the dietary fiber (4.8–7.3%), potassium (125.6–156.7 mg/100 g), iron (2.45–3.20 mg/100 g), and vitamin C (0–2.2 mg/100 g) contents. Although the highest level of apple powder provided the greatest nutritional enrichment, it also reduced the dough rheological stability and produced a less homogeneous crumb structure. Overall, the formulation containing 100 g of apple powder per batch combined with a whipping speed of 900 rpm, whipping time of 7 min, freezing at −38 °C, and microwave thawing for 4 min provided the best balance between rheological stability, freeze–thaw resistance, bread quality, nutritional enhancement, microbiological stability, and sensory acceptability. These findings demonstrate that simultaneous optimization of formulation and processing conditions is an effective strategy for improving mechanically aerated yeast-free frozen bakery products and provides a scientific basis for the development of functional frozen bread technologies.

Processes doi: 10.3390/pr14152498

Authors: Xiao-Juan Li Yong-Hua Li Li-Jie Zeng Jin-Yun Wu Jun Meng Meng-Na Li Jia-Yi Huang Man-Sheng Wang Xing-Fen Yang Yan-Yan Huang Xin-An Zeng

As naturally occurring bioactive molecules derived from plants, polyphenols exhibit significant potential for the functional modification and structural regulation of metal–organic frameworks (MOFs) due to their unique ortho-phenolic hydroxyl groups, excellent metal-coordinating ability, and favorable biocompatibility. This review systematically summarizes the functional roles of polyphenols in MOF systems, including their use as organic ligands to directly participate in framework construction, as surface modifiers to optimize MOF interfacial properties, or as encapsulation hosts to enable controlled loading and release. Polyphenol–MOF composites constructed based on these strategies demonstrate broad application prospects in fields such as biomedicine, food science, environmental remediation, and catalysis. This paper further analyzes the key challenges currently facing the research community, including unclear mechanisms of interfacial interactions, insufficient stability assessments under complex conditions, and a lack of scalable green synthesis processes. Future research should delve deeper into the relationship between polyphenol structures and MOF topological configurations and drive the transition from functional composites to functional synergies. These efforts will be key to realizing the practical application of such materials in intelligent food manufacturing, precision medicine, and sustainable environmental management.

Processes doi: 10.3390/pr14152499

Authors: Xinchi Han Zebin Wang Huaijun Ji Wendi Wang Hao Wu

Pore shape has a significant impact on methane adsorption. In this paper, graphene was used to construct coal pore models with different pore shapes. The adsorption of methane was simulated to investigate the effect of pore shape on the adsorption characteristics of coal methane. The results show that methane adsorption varies significantly among different pore models, and the influence of pore openness depends on the adsorption metric considered. In terms of absolute adsorption capacity, the open cylindrical pore exhibits a higher methane adsorption capacity than the semi-closed cylindrical pore, whereas for maximum excess adsorption capacity, the semi-closed cylindrical pore is slightly higher than the open cylindrical pore. The maximum methane adsorption of wedge-shaped pores was 0.6767 mmol/g, while the adsorption effect of ink bottle pores was the worst, with a maximum of only 0.5686 mmol/g. The methane concentration distribution inside the pores shows higher values at the edges and lower values at the center. The adsorption of methane molecules with the four pore models was in the range of 2.75–6 Å. The two cylindrical pore models exhibit lower potential energy than the wedge-shaped and ink-bottle pore models, indicating higher structural stability and smaller adsorption-induced swelling under the present simulation conditions. However, lower swelling and lower energy do not necessarily correspond to higher methane adsorption capacity, as the wedge-shaped pore exhibits the highest adsorption among the four models. With the increase in pressure, the adsorption positions of methane molecules in cylindrical pores gradually changes from a high-energy adsorption site to a low-energy adsorption site.

Processes doi: 10.3390/pr14152497

Authors: Shuai Li Guangqing Zhang Yongqing Ye

Crack-parallel stress modifies the near-tip stress state and may influence the development of the fracture process zone (FPZ) in rock. However, the spatial and temporal evolution of the FPZ during hydraulic fracturing cannot be reconstructed from the final fracture morphology alone. In this study, visual hydraulic-fracturing experiments were conducted on seven tight-sandstone specimens, with crack-parallel stress varied from 0 to 10 MPa while the other experimental conditions were kept consistent. Time-resolved full-field digital image correlation (DIC), combined with displacement–strain cross-calibration, was used to continuously track the initiation, expansion, localization, and coalescence of the FPZ, as well as the evolution of the traction-free crack tip and crack opening displacement (COD) on the specimen surface. The observations showed that the macroscopic traction-free crack did not form instantaneously but developed through progressive localization and coalescence of distributed damage within the FPZ. At the specimen level, the tests under nonzero crack-parallel stress exhibited shorter maximum FPZ lengths (14.7–30.6 mm) and lower critical COD values (10.5–27.5 μm) than the single 0 MPa reference specimen (80.9 mm and 38.2 μm, respectively). Given the limited replication, these differences are treated as descriptive specimen-level observations. The critical COD also varied non-monotonically across the tested stress levels. Three specimen-level FPZ–crack initiation patterns were identified: localized, matrix-nucleation, and diffuse-to-localized patterns. Their occurrence indicates that crack-parallel stress modifies near-tip confinement and crack-opening conditions, while specimen-scale heterogeneity and local defect distribution influence damage localization and the crack initiation site. These time-resolved observations reveal the spatiotemporal transition from distributed FPZ damage to traction-free crack formation, providing process-level information that cannot be obtained from the final fracture state alone.

Processes doi: 10.3390/pr14152496

Authors: Lin Guan Qiong Wu Shan Miao

The influence of guide-vane leading-edge profiles on interstage flow, particle transport, and erosion in multistage deep-sea mining pumps remains unclear. This study compares Convex, Linear, and Concave profiles in a two-stage pump using an Euler–Lagrange framework coupled with the Finnie erosion model. Hydraulic performance, pressure recovery, mainstream-flow organization, and particle transport were analysed at the design flow rate, whereas erosion characteristics were further evaluated over flow rates of 0.68Q–1.33Q and particle volume concentrations of 6–10%. At the design flow rate, the total head and overall hydraulic efficiency of the two-stage pump with the Concave profile reached 87.10 m and 53.32%, respectively. The Concave profile produced smoother pressure recovery, lower turbulent kinetic energy, and mainstream-flow ratios of 63.3% and 69.0% downstream of the first- and second-stage guide vanes, respectively. In the first-stage leading-edge region, its average particle mass concentration was 6.42% and 33.84% lower than those of the Convex and Linear profiles, respectively, demonstrating that the Concave profile effectively reduced particle accumulation near the guide-vane leading edge. In contrast, the Convex profile exhibited interstage erosion amplification, whereas erosion for the Linear profile was concentrated mainly in the first stage. Erosion increased with both flow rate and particle concentration for all profiles. Overall, the Concave profile provided the best balance among hydraulic performance, reduced particle accumulation, and predicted erosion resistance.

Processes doi: 10.3390/pr14152495

Authors: Diego Jauregui-Ontiveros Brian Medina-Santoyo Ramón Jaramillo-Martínez Umanel A. Hernández-González Miguel F. Delgado-Pamanes Luis A. Reyes-Osorio Johana Gamez-Treviño Hans Christian Correa-Aguado

Food waste represents a significant environmental and economic challenge, partly due to inefficient portion management during preparation, storage, and consumption. One strategy to mitigate this issue is to use single-dose (monodose) packaging, which allows precise dosing and encourages complete consumption, thereby minimizing leftovers. This work presents the design, construction, and experimental validation of an automated machine engineered for single-dose packaging of low-viscosity sauces. The system is capable of filling, sealing, and cutting off a continuous plastic film to produce hermetically sealed 60 mL pouches. The system contains a deposit equipped with an ultrasonic level sensor, a pneumatic dispenser mechanism, a PI-based temperature controller for the sealing and cutting processes, and a Human–Machine Interface (HMI) for system configuration and process monitoring. The general controller was implemented using a Programmable Logic Controller (PLC) and coordinated the stages of pouch filling, sealing, cutting, and counting. Experimental tests demonstrated stable and repeatable volumetric dosing. Mean dosing errors remained below ±1 mL for water and tomato-based sauce, whereas tomatillo-based and Chilean sauce exhibited higher deviations of +2.10 mL and +3.25 mL, respectively, reflecting the influence of viscosity and product heterogeneity. In addition, the system achieved hermetic sealing in more than 95% of samples and stable operation during continuous cycles. Additionally, the system showed thermal stability under PI control and high precision in the deposit level.

Processes doi: 10.3390/pr14152494

Authors: Xianyi Li Heqian Zhao Kaifu Mi Qing Liu Chen Guo Chunhui Zhao Xiaojun Chen Qingchen Wang Zhengming Xu

During ultra-deep well drilling, the bottomhole circulating temperature (BHCT) can easily exceed 150 °C, causing a series of problems such as drilling-fluid degradation, downhole instrument failure, and intensified well-control risks. Conventional surface-cooling methods experience sharply diminishing effectiveness under deep well conditions, while an insulated drill-pipe (IDP) offers good engineering feasibility as a passive cooling technique. However, existing studies lack a transient wellbore-formation coupled model validated by field data, and the influence patterns and interaction mechanisms of key parameters of the insulation coating under varying well depths remain unclear. Therefore, this study integrates a thermal-resistance representation into a transient wellbore-formation heat-transfer framework to characterize the insulation effect via an overall heat-transfer coefficient. Based on this framework, the cooling mechanism is systematically investigated from two perspectives: heat-absorption rate and cumulative blocked heat. Based on this model, the cooling mechanism is systematically investigated from two perspectives: heat-absorption rate and cumulative blocked heat. The results show that a 2000 m IDP section reduces BHCT from 161.81 °C (with a conventional drill-pipe, CDP) to 144.15 °C after 50 h of circulation. This yields an additional cooling of 17.66 °C and a cumulative blocked heat of 180.03 GJ. Parameter analysis further shows that lower thermal conductivity, longer coating length, and placement 200–400 m above the bottomhole enhance cooling, whereas coating thickness exhibits a marginal benefit threshold of 1 mm. More importantly, Sobol’ global sensitivity analysis reveals a distinct evolution of the dominant parameter controls with increasing well depth: at 6000 m measured depth (MD), coating length is the absolute governing factor; at 8000 m, coating position and length become equally important; at 10,000 m, the coupling between thermal conductivity and length emerges as critical; and at 12,000 m, thermal conductivity, thickness, position, and length jointly determine the cooling performance. This evolutionary pattern provides a depth-dependent priority framework for IDP parameter design, offering clear guidance for engineering application across varying well depths.

Processes doi: 10.3390/pr14152493

Authors: Fei Peng Yafei Zhang Qingyuan Zhu Juan Zhai Keliu Wu

Forced imbibition of a wetting liquid into a gas-filled tight rock is often expected to advance as a compact front because the liquid-to-gas viscosity ratio is favorable. This expectation can fail when narrow throats, pore-body/throat mismatch, capillary-valve pinning, and wall-associated wetting pathways reorganize the defending gas before it is displaced as a connected phase. We use a three-dimensional regularized color-gradient lattice Boltzmann model to examine these processes in a single, initially gas-saturated reconstructed tight-sandstone pore space. The simulations sample three capillary numbers, two or three Ohnesorge numbers depending on the capillary number, and two water-phase contact angles while keeping the water-to-gas viscosity ratio fixed at 26.11. The contact angle is measured through the aqueous phase, with θ = 20° representing strongly water-wet conditions and θ = 60° representing weakly water-wet conditions. For θ = 60°, terminal displacement efficiency changes little between the low and intermediate sampled capillary numbers and increases from approximately 0.660 to 0.736 at the highest sampled value. For θ = 20°, strong water-wetness is beneficial only after the bulk meniscus gains enough driving force to compete with precursor corner or wall flow; at a low capillary number, the same wetting affinity is associated with snap-off and premature gas isolation. The sampled Oh dependence is weaker than the Ca dependence and is consistent with conditional modulation of capillary-inertial damping and local interface relaxation; it is not interpreted as a new static entry criterion. Size-resolved and morphology-resolved statistics show contrasting terminal signatures: θ = 20° is associated with more large-pore gas and snap-off-consistent fragmentation, whereas θ = 60° is associated with more persistent small-pore gas and bypassing-consistent retention. Event-resolved phase-field sequences at one low-Ca condition directly show wall-first precursor advance, abrupt pore-body filling, gas-neck closure, persistent component splitting, and bypass-induced local entrapment. These events establish occurrence, not their frequency or dominance across parameter space. Because the study uses one pore-space realization and a sparse, non-factorial parameter matrix, the reported comparisons are restricted to the sampled conditions and do not define a continuous Ca–Oh–θ response surface or quantify structure-to-structure uncertainty.

Processes doi: 10.3390/pr14152492

Authors: Nadia Cerone Luca Contuzzi Giuseppe Domenico Zito Umberto Calice Carmine Florio Francesco Zimbardi

The use of biochar derived from agricultural wood waste represents a promising long-term carbon storage strategy, contributing to mitigation of climate change effects while offering agronomic benefits. This residue is considered as an appropriate material since it does not compete directly with the food chain. Life Cycle Assessment (LCA) is a widely recognized methodology to evaluate the potential environmental impacts associated with all the stages of the life cycle of a product, process or service. In this study, the potential environmental impact of biochar production and its application on soil have been assessed employing a cradle-to-grave approach. The biochar was produced through the pyrogasification of residual lignocellulosic biomass in a pilot-scale plant. The LCA model has been generated employing the GaBi software (LCA for experts 10.7), in accordance with ISO LCA standards and ILCD Handbook, using the experimental results collected during the test carried out in the pilot plant. Two scenarios have been discussed: a basic scenario, involving the biochar production and application on the soil, and an improved scenario, in which by-products from biochar production are used to replace energy in thermal processes. The Global Warming Potential (GWP) of biochar production resulted in −5.52 kg CO2 eq./kg of biochar including the sequestered carbon during plant growth and 1.81 kg CO2 eq./kg of biochar stored in soil and the heat recovery resulted in approximately 20 MJ/kg of biochar of avoided consumption of fossil-based fuels. These findings provide additional support to evaluate biochar potential as an environmentally beneficial solution.

Processes doi: 10.3390/pr14152491

Authors: Ao Feng Yufa He Kexin Zhang Chuanliang Yan

To investigate wellbore stability evolution during directional drilling in deepwater shallow soft hydrate reservoirs, a coupled thermo–hydro–mechanical–chemical (THMC) model incorporating hydrate phase change was established. The effects of drilling time, drilling fluid temperature, density, and well inclination were analyzed. The results indicate that wellbore collapse alters heat transfer paths, thereby expanding hydrate dissociation and plastic zones. With increasing drilling time, accumulated plastic deformation significantly intensifies wellbore instability. Maintaining drilling fluid density within an optimal range is the most critical factor for stabilizing the wellbore, and lowering the drilling fluid temperature can effectively reduce the hydrate dissociation extent and the borehole enlargement rate. Notably, well inclination exhibits a strong nonlinear influence: as inclination increases from 0° to 75°, the maximum plastic strain increases from 0.0047 to 0.0262, and the borehole enlargement rate rises from 38.1% to 152.6%; stability deteriorates dramatically beyond 30°. Higher initial hydrate saturation and greater water depth are beneficial to wellbore stability, whereas increased overburden thickness intensifies stress concentration. These results provide a reference for the directional drilling design of hydrate formations in deepwater shallow soft reservoirs.

Processes doi: 10.3390/pr14152490

Authors: Gilberto Pérez Lechuga Ana Lidia Martínez Salazar Marco Antonio Coronel García

The integrity of cold chains is critical for preserving the quality, safety, and efficacy of temperature-sensitive products, including pharmaceuticals, vaccines, and perishable goods. However, real-world cold-chain operations are subject to environmental variability, operational disturbances, and transport-related uncertainties that are often inadequately captured by deterministic models. This study presents a stochastic modeling methodology that integrates a physics-based heat-transfer model with a machine-learning residual correction to predict temperature dynamics and product degradation under uncertainty. Temperature evolution is represented through a stochastic heat-transfer model incorporating random perturbations, while product degradation is quantified using Arrhenius-based kinetics that link thermal exposure to quality loss. A machine-learning-based residual correction is subsequently incorporated to improve predictive accuracy while preserving the physical structure of the governing model. The proposed methodology is evaluated through computational experiments using a representative pharmaceutical cold-chain transportation scenario. Numerical experiments based on the Euler–Maruyama method and Monte Carlo analysis are performed to assess the proposed methodology under representative operating conditions. Results indicate that stochastic variability can produce transient temperature excursions even when average operating conditions remain acceptable, leading to increased degradation and higher failure probabilities. The computational results demonstrate the feasibility of the proposed methodology for the probabilistic estimation of thermal risk and product quality deterioration by integrating physics-based modeling, uncertainty analysis, and data-driven residual correction within a unified computational methodology. The proposed methodology provides a computational basis for the future development of intelligent cold-chain monitoring and decision-support systems. Overall, it offers practical capabilities for uncertainty quantification, reliability assessment, and informed decision making in temperature-sensitive supply chains.

Processes doi: 10.3390/pr14152489

Authors: Yuanshu Liu Ben Mou

This study investigates the effects of the length-to-diameter (L/D) ratio on the indirect tensile strength of red sandstone using Brazilian splitting tests combined with acoustic emission (AE) and digital image correlation (DIC) technology. Brazilian splitting tests were conducted on red sandstone disk specimens with a constant diameter of 50 mm and L/D ratios of 1.0, 0.8, 0.6, and 0.5. The results show that the apparent splitting strength decreased from 5.05 MPa at L/D = 0.5 to 1.35 MPa at L/D = 1.0, a reduction of 73.3%. As the L/D ratio decreased, the AE ring counts and energy release became increasingly concentrated near the peak load and exhibited more pronounced burst-like characteristics. Shear-type AE events increased from 62.4% to 82.9%, and tensile-type events decreased from 37.6% to 17.1%. The decrease in the AE b-value prior to failure indicates a transition of damage evolution from distributed small-scale microcrack activity to localized large-scale crack initiation, propagation, and coalescence. DIC showed that primary cracks initiated near the specimen center, whereas lower L/D ratios produced stronger localization, more secondary inclined cracks, and more abrupt failure. The higher calculated strengths obtained under low L/D conditions should be interpreted as apparent Brazilian splitting strengths resulting from the combined effects of specimen geometry and boundary constraints, rather than being directly regarded as the intrinsic tensile strength of red sandstone.

Processes doi: 10.3390/pr14152488

Authors: Ahmed Emin Kılıç Mohammad Alobeid Hasan Özcan Selahattin Çelik Bahman Amini Horri

Proton exchange membrane fuel cells (PEMFCs) are critical parts of new-age green hydrogen energy systems where reactant distribution and water management determine performance and reliability. A three-dimensional, steady-state, and single-phase model of a self-humidified low-temperature PEMFC was developed in COMSOL Multiphysics to compare parallel, single-serpentine and double-serpentine bipolar plate flow fields under identical active area membrane electrode assembly, material properties and operating conditions, so that flow field geometry was the only variable. The model is verified via grid independence and validated in terms of published experimental polarization data with mean absolute deviation under 2%. At 0.1 relative humidity of the cathode inlet, the single-serpentine flow field provides 717 mA cm−2 current density at 0.6 V and 595.7 mW cm−2 peak power density in contrast to 582 mA cm−2 and 492.3 mW cm−2 for the double-serpentine and 577 mA cm−2 and 463.2 mW cm−2 for the parallel flow field. These two designs therefore behave almost identically in electrochemical terms but differ hydraulically; their peak channel pressure drops, being 3.8 and 0.8 kPa against 14 kPa for the single-serpentine design. Once pumping power is included, the single-serpentine design remains the best net power choice below an active area of approximately 54 cm2.

Processes doi: 10.3390/pr14152487

Authors: Bohang He Shuai Dang Peng Li

Underground hydrogen storage in depleted gas reservoirs has emerged as a key technology for large-scale hydrogen energy storage. However, the occurrence state of hydrogen is governed by residual methane and reservoir mineral surfaces. This study combines grand canonical Monte Carlo and molecular dynamics simulations to investigate the competitive adsorption and diffusion of hydrogen and methane in quartz, kaolinite, and calcite. The results show that at low methane contents (<0.2), the adsorption capacity of hydrogen is primarily governed by its interaction with the mineral surface, exhibiting the strongest adsorption in calcite and the weakest in quartz, whereas the diffusivity follows the opposite trend. As the methane content increases, the occurrence state of hydrogen becomes increasingly controlled by the distribution of methane. The preferential occupation of surface adsorption sites by methane substantially suppresses hydrogen adsorption in quartz and calcite, whereas the abundant methane remaining in the bulk region of kaolinite imposes the strongest restriction on hydrogen diffusion. Increasing temperature promotes methane desorption, releasing interfacial adsorption sites, restoring the near-wall hydrogen adsorption peak, and enhancing hydrogen diffusivity, whereas increasing pressure shifts hydrogen from interfacial adsorption at low pressures to bulk-phase filling at high pressures while reducing its diffusivity.

Processes doi: 10.3390/pr14152486

Authors: Qian Chen Jiyang Wu Qiang Li Guangqiang Peng Ze Gong Xi Zhang Yilong Huang Bo Yang

Large-scale UHVDC and flexible DC projects accumulate scattered multi-modal O&M data across independent platforms, fragmenting domain knowledge and reducing the efficiency of intelligent fault diagnosis and disposal. Unstructured data typically account for more than 70% of converter-station O&M data volume, which intensifies fragmentation across SCADA, inspection media, fault recordings and documents. Distinct from prior HVDC intelligent O&M surveys, this review critically synthesizes the closed-loop knowledge construction chain via multi-modal data fusion—covering data governance, cross-modal semantic mapping, DIKW modeling, hybrid storage and knowledge graph development—and compares three fusion paradigms regarding latency, scalability and industrial deployment. It also addresses renewable-integrated O&M uncertainty, practical feature extraction, and why deep learning black-box behavior limits field practicality. Key gaps remain small-sample generalization, control-and-protection logic formalization, explainability and cross-system integration; future directions include few-shot cross-modal learning, LLM-driven knowledge evolution and digital twin coupling.

Processes doi: 10.3390/pr14152485

Authors: Jianzheng Zhang Helin Wang Kun Wei

This paper addresses the high-precision trajectory tracking control problem for robotic manipulators operating in uncertain environments by proposing a novel fuzzy adaptive gain-tuning sliding-mode control (FAGT-SMC) algorithm. While conventional sliding-mode control offers strong robustness against matched uncertainties, its fixed-gain switching mechanism inevitably induces severe chattering phenomena, causing actuator wear and performance degradation in practical implementations. To overcome this fundamental limitation, this paper designs an intelligent gain adaptation framework that dynamically regulates the sliding-mode switching gain through a fuzzy inference system. The control system structure integrates a nominal equivalent control component derived from the robotic dynamics model with an adaptively tuned discontinuous switching term. Theoretical analysis establishes global stability through Lyapunov-based methods, proving uniform ultimate boundedness (practical stability) of tracking errors under bounded uncertainties and residual fuzzy approximation errors. The proposed FAGT-SMC algorithm effectively balances robustness and control smoothness; therefore, numerical simulations demonstrate effectiveness for advanced robotic applications requiring both precision and adaptability in dynamic operating conditions.

Processes doi: 10.3390/pr14152484

Authors: Angappan Palanisamy Duraiswamy Palanisamy Abhishek Agarwal Chellamuthu Prakash Sembian Manoharan Natarajan Manikandan

Incoloy 800H (Fe–Ni–Cr) is an iron-based superalloy that is difficult to machine because of its rapid work-hardening behaviour. Although Taguchi-based grey relational analysis has previously been applied to machining optimisation problems, studies employing an integrated grey-fuzzy framework for the dry turning of Incoloy 800H remain limited. Therefore, the present investigation aims to develop and validate a grey-fuzzy optimisation approach for determining the optimal dry turning parameters of Incoloy 800H by simultaneously minimising machining forces, surface roughness, and specific cutting pressure. Cutting speed (35, 45, and 55 m/min), feed rate (0.02, 0.04, and 0.06 mm/rev), and depth of cut (0.5, 0.75, and 1 mm) were selected as input factors, whereas feed force, thrust force, cutting force, surface roughness, and specific cutting pressure were considered output responses. Experiments were conducted using a Taguchi L27 orthogonal array (OA). The proposed methodology integrates grey relational analysis (GRA) with fuzzy logic (FL) to obtain a grey-fuzzy reasoning grade (GFRG) for multi-response optimisation. Analysis of variance (ANOVA) was employed to identify the most influential machining parameter. The results demonstrated that the grey-fuzzy approach provided a more discriminative optimisation index than conventional grey relational analysis by reducing uncertainty in multi-response decision-making. The confirmation experiments revealed an increase in GFRG from 0.550 to 0.900, corresponding to a relative improvement of 63.64% at the optimal parameter setting. The proposed methodology demonstrates that integrating grey relational analysis with fuzzy inference provides a reliable and statistically supported approach for multi-response optimisation of dry turning parameters for Incoloy 800H.

Processes doi: 10.3390/pr14152482

Authors: Yahui Wang Xu Sun Junyi Li Shuna Hong Anqi Xiang Shuqiang Shi Tingji Ding

A gas field in the eastern South China Sea has entered the middle-to-late stage of development and is strongly affected by medium-to-strong water drive and severe edge- and bottom-water encroachment. After water breakthrough, gas wells exhibit different productivity-decline patterns, and some wells suffer from insufficient liquid-carrying capacity, liquid loading, and production decline. Conventional classification methods based on individual indicators or empirical thresholds cannot adequately characterize the current production state, stable-production behavior, and future deterioration risk. Therefore, an ELF-index-based HGC-ELF Pro framework was developed for dynamic gas-well classification and deliquification-process screening. PCA and CRITIC retained 14 indicators from 22 candidates, and the first five principal components explained 90.089% of the total variance. K-means divided 25 wells into three classes; K = 3 produced the highest reported average silhouette coefficient of 0.617 among K = 2–6. Class I contained 12 wells (48%), Class II contained 6 wells (24%), and Class III contained 7 wells (28%). The recommended primary processes included foam-assisted deliquification for 13 wells (52%), gas lift/ESP screening for 6 wells (24%), gas lift for 4 wells (16%), and velocity strings for 2 wells (8%). Because independent field class labels are unavailable, supervised classification accuracy is not reported. The framework integrates multi-timescale production information, interpretable E/L/F state representation, cluster-validity assessment, and differentiated process screening. The results provide a quantitative basis for hierarchical well management, although the small sample and field-specific calibration requirements limit direct generalization.

Processes doi: 10.3390/pr14152483

Authors: Alibek Muratbayev Sandugash Toleubekova Aitbek Kakimov Aigerim Bepeyeva Gulmira Zhumadilova Madina Jumazhanova Zhadyra Imangaliyeva Nazerke Muratzhankyzy Marzhan Tashybayeva Aslan Sovetkanov

This study evaluated the effects of alginate–pullulan-encapsulated herbal bioactives on the processing characteristics, quality, and refrigerated storage stability of cottage cheese spread. Capsules containing rosehip, echinacea, and levzeya extracts were incorporated at levels of 0–5%, and the resulting samples were assessed for physicochemical properties, bioactive composition, antioxidant activity, rheological behavior, capsule integrity, sensory acceptability, and safety. The formulation containing 3% capsules was selected as the formulation providing the best balance between enrichment and product quality. It contained 0.94 mg/100 g vitamin C, 6.75 mg/100 g polyphenols, and 4.50 mg/100 g flavonoids, with DPPH antioxidant activity of 6.0% and a mean sensory score of 4.69/5. Capsule levels of 4–5% further increased bioactive content but reduced sensory scores to 4.11 and 3.71 because of more visible inclusions and lower taste and consistency ratings. During 7 days of refrigerated storage, moisture content and water activity remained statistically stable, and lactic acid bacteria remained close to 7 log10 CFU/g. Meanwhile, pH decreased, whereas titratable acidity and syneresis increased, with sensory deterioration becoming more evident after day 3. By day 7, vitamin C, polyphenols, and antioxidant activity retained 92.6%, 95.6%, and 94.0% of their initial values, respectively. Pathogenic microorganisms were not detected, and the tested safety indicators remained within permissible limits. These results demonstrate that 3% capsule incorporation provides a suitable balance between bioactive enrichment, processability, sensory acceptability, and refrigerated quality retention.

Processes doi: 10.3390/pr14152481

Authors: Tomoki Kono Chun-Ping Lu Yi-Chung Lai Bang-Yuan Chen Meng-I Kuo

Drying is a critical post-fermentation process because it influences product stability and the retention of bioactive compounds. The present study evaluated the effects of different drying techniques on the physicochemical characteristics, functional properties, bioactive compounds, and antioxidant activities of SCOBY-fermented pomelo peel substrate powders. Pomelo peel substrates fermented with 6% (w/w) SCOBY inoculum for 25 days were subjected to freeze drying (FD), hot-air drying (HAD; 50, 70, and 90 °C), and radio-frequency drying (RFD; electrode distances of 14, 15, and 16 cm). Drying kinetics, effective moisture diffusivity (Deff), water activity, color, particle size distribution, functional properties, total phenolic content (TPC), total flavonoid content (TFC), and antioxidant activities were determined. RFD showed comparable or slightly higher moisture diffusivity (1.19–2.06 × 10−9 m2/s) compared with HAD (1.03–1.95 × 10−9 m2/s) under suitable drying conditions, suggesting that radio-frequency heating effectively promoted internal moisture migration through volumetric dielectric heating. FD retained the highest antioxidant activity, with DPPH radical scavenging activity of 74.25% and TEAC of 24.85 μmol TE/g. However, moderate thermal treatments enhanced phenolic extractability, and HAD at 50 °C showed the highest TPC (161.65 mg gallic acid equivalents (GAE)/g DW). Among the RFD treatments, RFD at 15 cm exhibited the highest TFC (27.18 mg rutin equivalents (RE)/g DW) and maintained relatively high antioxidant capacity. FD powders showed superior water solubility and swelling capacity, whereas RFD produced finer particle distributions and improved drying efficiency. These findings demonstrate that drying techniques significantly influence the quality attributes of SCOBY-fermented pomelo substrate powders, and RFD represents a promising alternative drying technology for balancing drying efficiency and bioactive compound retention.

Processes doi: 10.3390/pr14152480

Authors: Fatema Tuz Zohra Hribhu Chowdhury Bahram Asiabanpour

This study investigates the laser powder bed fusion (LPBF) fabrication of 17-4 PH stainless steel triply periodic minimal surface (TPMS) structures and the wettability response of corresponding flat plates subjected to selected post-processing treatments. Five TPMS geometries were fabricated and visually examined to document their overall condition and manufacturing irregularities. Thermal aging, steel shot blasting, commercial hydrophobic coating, and selected treatment combinations were evaluated on flat plates manufactured using the same material and LPBF process. Wettability was assessed using time-dependent static contact angle (CA) measurements and a preliminary comparison of three steel shot grades. The fabricated TPMS structures retained their overall geometries but exhibited localized burnt edges, distortion of thin boundary features, and differences in surface appearance. The untreated LPBF-fabricated surface was hydrophilic and exhibited time-dependent wetting, with the CA decreasing from approximately 81° to as low as 48° within 4 min and complete wetting occurring within approximately 8–10 min. Among the evaluated blasting media, S-330 produced the highest CA values; however, blasted surfaces remained hydrophilic, and the response depended on whether the plate was untreated or aged. The coating produced CA of approximately 153–170° across all coated regions, both with and without prior blasting. These findings identify manufacturing considerations for LPBF-fabricated TPMS structures and demonstrate the effects of the investigated treatments on the wettability of corresponding flat surfaces, thereby providing insights for future studies of TPMS-based condensation surfaces in atmospheric water generation applications.

Processes doi: 10.3390/pr14152479

Authors: Manuel J. Heredia-Rios Luis Hernandez-Matinez Mónico Linares-Aranda Javier Flores Méndez Ana C. Piñón Reyes

Accurate extraction of single-diode model (SDM) parameters is essential for photovoltaic performance analysis, especially when only datasheet values or graphical I-V characteristics are available. This study presents a graphical–deterministic parameter extraction framework that combines calibrated curve digitization, local differential analysis, uncertainty-aware slope estimation, and analytical SDM closure. Unlike conventional datasheet-based analytical methods that operate directly from tabulated characteristic points, the proposed approach explicitly incorporates the graphical-to-numerical conversion stage and evaluates its impact on the estimation of the resistive parameters. The shunt and series resistances are obtained as effective local slope estimates near short-circuit and open-circuit conditions, respectively, while the photocurrent, saturation current, and ideality factor are determined from characteristic operating point equations. The ideality factor is solved through a deterministic scalar root procedure within the physically admissible interval 1≤n≤2. The method was evaluated using four photovoltaic devices, including laboratory-scale cells and commercial modules. Normalized reconstruction errors of 0.82% and 0.88% were obtained for the RTC-France cell and the KC200GT module, respectively. The INAOE laboratory cell and the SP450M half-cut module showed higher sensitivity to graphical slope extraction and energetic closure. For the SP450M module, the use of an equivalent series cell number NS,eq = 72 improved agreement with the digitized graphical I–V curve, although the reconstructed maximum power remained below the nominal datasheet value, revealing a graphical/datasheet consistency issue. These results show that the proposed framework is a transparent and reproducible alternative for SDM identification from graphical sources, while also defining its sensitivity limits when applied to low-resolution curves or half-cut high-power modules with complex equivalent electrical configurations.

Processes doi: 10.3390/pr14152478

Authors: Jian Chen Qiang Xu Xiao Guo

During the production of high-sulfur-content gas–water wells, elemental sulfur saturated in natural gas gradually precipitates as solid particles with decreasing wellbore temperature and pressure. When these sulfur particles cannot be continuously carried upward in the gas–liquid–solid three-phase flow formed with natural gas and formation water, they tend to deposit in the wellbore, potentially blocking the production string and even severely restricting the gas well’s deliverability. Current research on predictive models for the critical gas flow velocity required to carry sulfur particles remain inadequate. Therefore, accurately predicting this critical velocity and adjusting production to prevent deposition are crucial for managing high-sulfur gas wells. The primary innovation of this study lies in the development of a predictive model for the critical gas flow velocity required for sulfur particle entrainment. Grounded in the “gas–liquid coalescence–liquid film entrainment” coupling mechanism revealed by preliminary experiments, this model is established through a mechanical analysis of sulfur particles within liquid films in vertical and inclined pipes. Recognizing liquid film thickness and velocity as pivotal parameters for model solving, auxiliary models for predicting these two parameters in inclined pipe annular flow were developed based on experimental results and the momentum balance principle. The proposed model comprehensively incorporates factors such as well inclination angle, pipe diameter, liquid flow rate, and sulfur particle size, rendering it applicable to diverse well configurations including vertical, horizontal, and deviated wells. Evaluation against 48 sets of experimental data yielded a Mean Absolute Percentage Error (MAPE) of 2.28%, demonstrating high predictive accuracy. Furthermore, an engineering calculation program for the critical gas flow velocity was developed. A case study involving a well in the Puguang Gas Field was conducted to predict and diagnose sulfur deposition conditions, thereby verifying the model’s practical utility. This research provides a scientific basis for the safe and efficient development of high-sulfur gas fields.

Processes doi: 10.3390/pr14152477

Authors: Hongli Wang Yujun Ma

To address the challenges in risk assessment of complex emergency systems, such as difficulties in closed-loop structure modeling, insufficient quantification of dynamic evolution, and poor adaptability to multiple scenarios, this study proposes a dynamic risk assessment method that integrates the System-Theoretic Accident Model and Processes (STAMP) and the Cascading Failure Propagation Model (CFPM). The novelty of this coupling lies in a bidirectional “qualitative diagnosis → quantitative prediction” logic: STAMP’s identification of Unsafe Control Actions (UCAs) provides a theory-grounded blueprint for configuring the CFPM network topology and propagation parameters, while CFPM’s dynamic simulation translates these qualitative control flaws into computable risk evolution trajectories. The proposed framework adopts a two-layer structure of “qualitative modeling–quantitative analysis”. STAMP is used to construct a hierarchical control structure, identify Unsafe Control Actions (UCAs), and analyze the nonlinear interaction mechanisms among “human–organization–technology” factors. For typical scenarios of “fault not processed” and “online fault processing”, CFPM is employed to abstract the system into a node network, quantify the time-step propagation process of node failure probability, calculate the system residual performance index, and generate real-time risk evolution curves. A case study of the Tianjin Port ‘8·12’ explosion accident demonstrates that this method effectively captures the closed-loop interaction characteristics and dynamic risk evolution patterns of emergency systems. Quantitative results reveal a distinct contrast between the two handling scenarios: in the absence of maintenance intervention, system residual performance deteriorates exponentially and rapidly approaches a critical threshold; in contrast, effective online maintenance significantly retards risk accumulation and facilitates gradual system recovery, thereby preventing further escalation of consequences. Compared to traditional methods like Bayesian Networks, it shows stronger applicability by explicitly modeling closed-loop feedback structures and enabling discrete time-step quantification of risk accumulation, and can accurately identify control flaws and quantify risk accumulation effects, thereby providing support for optimizing emergency strategies. Future research should focus on enhancing the method’s adaptability to data uncertainty and cybersecurity threats.

Processes doi: 10.3390/pr14152476

Authors: Dongmei Gao Majid Hussain Yunyan Li Muhammad Azam Muhammad Faizan Ali Faseha Jameel Tian Zeng Ifra Iqrar Yanglei Yi Fan Zhao

Fenugreek seed oil contains bioactive constituents of interest for functional-food applications, but its susceptibility to environmental degradation may limit processing and storage. This study developed an alginate–chitosan encapsulation system and examined how chitosan molecular weight affected the physicochemical properties and in vitro bioactivity of the resulting formulations. Fenugreek seed oil was obtained by mechanical pressing and Soxhlet extraction, yielding 2.81% and 5.50% (v/w), respectively. The oil was incorporated into calcium-alginate beads (T1), which were left uncoated or coated with high-molecular-weight chitosan (HMC; T2) or low-molecular-weight chitosan (LMC; T3). The formulations were characterized by color measurement, microscopy, scanning electron microscopy, Fourier-transform infrared spectroscopy, thermogravimetric analysis, and particle-size analysis of oil droplets released from the polymer matrix. Free and encapsulated oil samples were also exposed to UV-C irradiation and evaluated using antioxidant assays, an albumin-denaturation inhibition assay, and an α-amylase inhibition assay. Dry-product recovery ranged from 76.72% for T2 to 94.79% for T1, with T3 showing a higher recovery than T2. SEM showed that T2 had the smoothest and most uniform dried morphology. FTIR spectra were consistent with interactions between alginate and chitosan while retaining characteristic bands associated with the oil. The chitosan-coated formulations also showed altered thermal-degradation profiles compared with alginate alone. After irradiation, T3-UV showed DPPH radical-scavenging activity of 63.03% and albumin-denaturation inhibition of 94.95%, whereas T2-UV showed the highest α-amylase inhibition. These findings indicate that chitosan molecular weight influences formulation recovery, morphology, thermal behavior, and measured in vitro activity. Further work using matched non-irradiated controls, standardized oil-equivalent concentrations, release testing, and gastrointestinal models is required before functional-food delivery claims can be established.

Processes doi: 10.3390/pr14152475

Authors: Jianchao Shi Jiwei Wang Xiaoke Li Yongjian Feng Qiang Liu Wenyan Yang Shuai Duan Xinyu Li

Natural fractures strongly influence fluid flow, hydraulic-fracturing performance, and production heterogeneity in tight oil reservoirs. Their identification from conventional logs remains challenging because image-log and core coverage is limited, fracture-related logging responses are non-unique, and discrete fracture interpretations are difficult to align with regularly sampled logging sequences. This study used conventional logging data and electrical image-log interpretations from 17 wells in the Xifeng Oilfield, Ordos Basin, together with core observations from selected intervals, to develop a fracture response mapping and triangular topology-optimized bidirectional long short-term memory model (FRM-BiLSTM-TTAO). After sliding-window construction and density-based undersampling, 1713 samples were retained and partitioned at the well level into 14 training wells and three independent test wells, yielding an approximate training-to-test sample ratio of 75:25. FRM extracts lithologic-background, local-abrupt-change, multiscale-fluctuation, and integrated fracture response features; BiLSTM captures bidirectional depth dependencies; and TTAO selects fracture response features and optimizes the network architecture and training parameters. On the test set, the model achieved a ROC-AUC of 0.9079, a recall of 0.8671, and an F1-score of 0.8464, outperforming CNN, MLP, ResNet1D, XGBoost, and the corresponding ablation models. The predicted high-probability intervals were generally consistent with image-log interpretations and core observations, indicating the feasibility of the proposed method for identifying fracture-prone intervals within the study area.

Processes doi: 10.3390/pr14152474

Authors: Gaofeng Zou Liang Xue Haiyang Chen Ruyue Wang Yubin Dong Di Tian Minghao Wang

Accurate water saturation estimation in deep shale reservoirs is complicated by clay-related additional conductivity and coupled pore, organic-matter, and structural effects. This study develops a feature-level physics-guided machine-learning framework, termed PhysML-Hybrid. Five mechanism-derived descriptor groups representing clay–water interfacial behavior, low-resistivity correction, pore connectivity, organic-pore development, and structural stress were integrated with conventional reservoir variables in a validation-weighted ensemble of random forest, XGBoost, and Bayesian neural network models. The framework was evaluated using 153 depth-matched samples from five wells in the Dingshan area of the Sichuan Basin. The data were divided into 107 training, 16 validation, and 30 independent test samples, and target-stratified five-fold cross-validation was conducted exclusively within the training set. Mean cross-validation R2, MAE, and RMSE were 0.907±0.009, 1.69%±0.10%, and 2.25%±0.14%, respectively. On the independent test set, the corresponding values were 0.902, 1.77%, and 2.34%. PhysML-Hybrid outperformed Archie, SVM, ML-only, and Phy-XGB. SHAP and statistical analyses identified clay content, the curvature–clay interaction, TOC, pore connectivity, and structural descriptors as influential variables; candidate transitions were interpreted as dataset-specific rather than universal thresholds or causal relationships. Three blind-well cases provided supplementary evidence of cross-well applicability, although larger independent multi-basin datasets are required to assess transferability.

Processes doi: 10.3390/pr14152473

Authors: Jesús Alberto Rodríguez-Flores Alexander Sánchez-Rodríguez Diego Hernando Arroyo-Almeida Andrés Fernando Morocho-Caiza Daniel Andrés Revelo-Cáceres Alexis Cordovés-García

This study presents an experimental framework for hybrid grey-box–ARX identification and constrained model predictive control (MPC) in a 250 L jacketed batch milk pasteurizer. The plant was represented as a closed, stirred, energy-accumulating system rather than as a continuous high-temperature short-time process. The workflow combined manufacturer specifications, field measurements, a batch–jacket grey-box model, local autoregressive with exogenous input (ARX) identification in the approach and holding region, and controller evaluation under common sampling, reference, actuator, and exclusion conditions. In five paired experimental blocks, the nominal MPC–ARX reduced RMSE by 1.959 °C, IAE by 7801 °C s, specific energy consumption by 0.0081 kWh/kg, overshoot by 3.573 °C, actuator saturation by 44.46 percentage points, and thermal overexposure by 4717 °C s relative to a fixed-parameter PI controller with anti-windup. The optimization remained feasible at all evaluated instants, with a mean computation time of 6.4 ms for a 5 s control period. Supervised adaptive strategies provided diagnostic value but did not outperform the nominal MPC. The conclusions are restricted to batches near the nominal fill condition and the 65 °C/30 min milk recipe.

Processes doi: 10.3390/pr14152472

Authors: Zhengzheng Cao Yi Xiong Yufeng Xue Desheng Zhu Guosheng Li Youlin Xu Teng Teng Yi Xue

To solve the whole cutting-off and large-area weighting of thick-hard roof led by the high-intensity mining in working face, the mechanical mechanism of the impact pressure of thick-hard top working face in the Shendong mining area is studied. The thick-hard roof in the Shendong mining area is characterized by large thickness, high strength, and difficulty in caving, which frequently triggers strong mine pressure, coal wall spalling, rock bursts, and mining-induced seismicity. Traditional thin-plate theory ignores transverse shear deformation and cannot satisfy the calculation accuracy requirements of thick-hard strata with a large thickness–width ratio, so it is necessary to establish a more accurate medium-thick plate mechanical model. By analyzing the boundary conditions of the thick-hard-roof working face in the Shendong mining area, the mechanical model of the medium-thick plate under four typical boundary conditions is established. Then, the finite integration method is used to solve the deflection, bending moment, and shear force of the thick-hard roof under the four boundary conditions. Through the programming operation, the influence laws of the deflection, bending moment, and shear force of the thick-hard roof are analyzed. The results show that under tensile failure, the cracks expand along the long side. Then, the cracks occur on the short side of the thick roof. Along the short side, the cracks occur in the middle and expand on the short side of the two sides with the increase in plate thickness, and the bending moment and shear values gradually decrease. For the medium plate of the same thickness, as the width-to-length ratio increases, the deflection value gradually increases, and the bending moment and shear value gradually decrease. The research results reveal the deformation and breaking rules of thick-hard roofs based on the mechanical model of thick plates, which lays a theoretical foundation for the study of the coal-wall plate impact-pressure mechanism induced by the instability of thick-hard roofs.

Processes doi: 10.3390/pr14152471

Authors: Chunyu Du Xingrui Jia Xuanwei Pang Shijie Zhu

Developing complex fault-block low-permeability reservoirs faces great challenges in constructing efficient injection-production flow pathways, which often leads to unsatisfactory waterflooding development performance. To improve the recovery efficiency of this type of reservoir, this study first carried out laboratory extraction experiments and then conducted CO2 extraction numerical simulations on low-permeability porous media via ANSYS to validate the experimental results. Based on investigations targeting the target reservoir, the key findings are summarized as follows: Supercritical CO2 preferentially extracts light hydrocarbon components lighter than C10, which accounts for more than 60% of the total extracted components; when the pressure exceeds 20 MPa, a small amount of heavy components C15+ can also be extracted. Under the experimental conditions adopted in this study, the optimal CO2 reinjection pressure range is determined as 12–20 MPa. Within this range, the extraction efficiency increases by 2.0–2.5% per 1 MPa increment of pressure, and this pressure condition can effectively dissolve medium hydrocarbon components and promote the formation of uniform plug flow. However, when the reinjection pressure continues to rise beyond 20 MPa, the CO2 extraction efficiency will gradually decrease. The numerically simulated CO2 extraction efficiency of crude oil shows high consistency with the experimental measurements. This study confirms that CO2 huff-n-puff can be effectively applied for crude oil extraction in the peripheral areas of tight reservoirs and fault-block reservoir units. Nevertheless, in field application, it is imperative to optimize the reinjection pressure design: accurately customizing injection pressure parameters according to different reservoir types and their specific development requirements is a core measure to improve CO2 extraction efficiency.

Processes doi: 10.3390/pr14152470

Authors: Hao Zha Qifei Zhang Zelin Cao Dazhang Yang

To advance the goals of carbon peaking and carbon neutrality alongside the global energy transition, energy conservation and carbon reduction in refrigeration and air-conditioning systems have garnered widespread attention. Dew-point evaporative cooling (DPEC) represents a promising energy-efficient cooling technology, whose performance is strongly governed by the water supply strategy. This study presents a systematic comparison of falling-film and atomization water supply modes on a counter-flow DPEC test bench featuring 3D-printed palm fiber filament walls. Experiments were conducted over inlet air temperatures of 32–50 °C, velocities of 1.3–4.0 m/s, and a range of water supply temperatures. The results demonstrate that the falling-film mode yields 15–25% higher dew-point efficiency than the atomization mode under baseline operating conditions. Water supply temperature (15–30 °C) exerts a negligible influence on falling-film cooling performance. The hybrid falling-film–atomization mode achieves the highest cooling capacity in the medium-to-low air velocity range, with a maximum wet-bulb efficiency of 1.15, while the falling-film mode yields the highest COP of up to 2.2. These findings offer experimental guidance for optimizing water supply strategies in fiber-wall DPEC systems.

Processes doi: 10.3390/pr14152469

Authors: Xiuyu Wu Honghua Xu Zijian Hu Ye Ji

This study proposes dynamic resource allocation and coordinated dispatch based on a source–load association graph for an electric–gas–heat system with wind, photovoltaics, fixed and mobile storage, power-to-gas (P2G), combined heat and power (CHP), and soft open points (SOPs). At each operating update, storage states, mobile-storage location and availability, and forecast profiles determine five typed relations and the subgraph classifications. Capacity-weighted centering then maps the state scores to time-varying device bounds without changing installed capacities or locations. The coordinated dispatch is formulated as a mixed-integer second-order cone program with SOC DistFlow constraints and an SOS2 gas-flow approximation. For the normal operating day, graph-guided dispatch yields an operating cost of 51,996.84 CNY, compared with 52,294.33 CNY for static equal-budget allocation and 52,829.05 CNY for topology-only allocation. The corresponding reductions are 0.5689% and 1.5753%, respectively, while all three policies serve 100% of demand and use 100% of available renewable energy within numerical tolerance. The graph-guided solution reaches a 0.0340% optimality gap, supporting its operating-cost advantage for the tested day.

Processes doi: 10.3390/pr14152468

Authors: Shuolin Zhang Yue Yu Ye Tao Lin Xue

To address the insufficient feature representation of conventional data-driven transient stability assessment (TSA) models and their limited adaptability to changes in power-system operating conditions, which result in inadequate assessment accuracy, this paper proposes a TSA method based on high-level sample feature extraction and model updating. First, a self-supervised contrastive random feature perturbation model for transient stability assessment, called TSA-SCRF, is developed. By introducing random perturbations into steady-state power flow features and employing contrastive learning, the proposed model extracts robust deep feature representations while preserving fault-type information. Second, a boundary-aware ensemble support vector machine (BAESVM) is constructed, which exploits multiple kernel functions to learn complementary discriminative information and dynamically assigns classifier weights according to both classifier performance and the samples’ decision distances. Finally, high-value newly acquired samples are selected based on sample uncertainty and, together with the support vectors of the original model, are utilized for model updating. Case studies conducted on a provincial power grid in China demonstrate that the proposed method improves the accuracy of data-driven transient stability assessment and enhances the model’s adaptability to changes in power-system operating conditions.

Processes doi: 10.3390/pr14152467

Authors: Yujie Hou Yibin Gong Xueqi Wang Zhiyong Li Xingqing Yan

High-pressure ethylene relief is a key safety issue in low-density polyethylene production, where ethylene is typically handled under dense real-fluid conditions. Conventional ideal-gas relief equations may lead to significant errors because thermodynamic properties vary strongly with pressure and temperature. In this study, a real-fluid isentropic relief model was developed using thermodynamic properties obtained from the Reference Fluid Thermodynamic and Transport Properties Database (REFPROP). The critical mass flux was determined by searching for the maximum value along the isentropic expansion path, and the equivalence between the maximum-mass-flux condition and the sonic condition was examined. Four industrial relief cases were compared with proprietary design-calculation outputs. The real-fluid model predicted mass flow rates with deviations of −9.9%, −9.1%, −2.3%, and −1.0%, whereas the ideal-gas model produced larger underpredictions, particularly under ultra-high-pressure conditions. The effects of upstream pressure and temperature on critical mass flux, depressurization paths, speed of sound, and critical pressure ratio were analyzed. A response-surface correlation based on 95 calculated states was developed for preliminary estimation, with all deviations within ±10% over the fitted domain. These results demonstrate the importance of accounting for real-fluid thermodynamics when evaluating high-pressure ethylene relief capacity.

Processes doi: 10.3390/pr14152466

Authors: De Fang Jie Yuan Xiaocai He Huixian Shi Yina Li Shengnan Lin Renqiang Liu Chuyuan Jin

The printing adaptability and sintering compactness of photovoltaic back silver paste are highly dependent on the physical properties of the silver powder, such as tap density and particle size distribution, which in turn are directly influenced by the purity of the precursor silver nitrate. When using 4N silver ingots as the raw material, trace impurities such as Nb, Fe, Cu, and Pb remaining in the crude solution can seriously interfere with the uniform nucleation and growth of silver crystallites, leading to decreased tap density and broadened particle size distribution. This paper presents a combined impurity removal–crystallization process integrating an adsorbent with controlled evaporative crystallization. Under optimized conditions, the concentrations of Nb, Fe, Cu, and Pb impurities decreased from 44, 21, 16, and 12 ppm to below 4 ppm, respectively. Meanwhile, the controlled crystallization step further enhanced the purity of the silver nitrate crystals through the redistribution of impurities between the solid and liquid phases. When the high-purity silver nitrate prepared by this process was used to produce photovoltaic back silver powder, the tap density of the resulting silver powder increased from 2.5 g cm−3 to 3.4 g cm−3, accompanied by a smooth surface morphology. Thermogravimetric (TG) analysis further confirmed a lower residual organic content on the particle surface. These comprehensive improvements in powder properties demonstrate the effectiveness of the proposed process in producing high-quality silver powder for photovoltaic back silver applications.

Processes doi: 10.3390/pr14152465

Authors: Meika Syahbana Rusli Dwi Setyaningsih Obie Farobie Hari Setiapraja Veni Anggita Sari

The nationwide implementation of B35 biodiesel in Indonesia is constrained by elevated water and particulate contents, which accelerate fuel degradation and promote filter clogging. Mitigating these issues is essential to ensure fuel quality, safe distribution, and stable engine operation. This study proposes a renewable essential-oil-derived bioadditive as an alternative to petroleum-based additives, with novelty arising from a fractionation-guided multi-essential-oil formulation and its comprehensive validation, encompassing molecular characterization, fuel-quality compliance, engine performance, and exhaust emissions. The objective of this study was to develop and validate an essential-oil bioadditive capable of (i) reducing water and particulate contents in B35 biodiesel in compliance with Indonesian fuel standards and (ii) evaluating its effects on engine performance and emissions. Turpentine, clove terpene, citronella, and rhodinol oils were characterized by GC–MS and fractionated to obtain α-pinene-, caryophyllene-, and rhodinol-rich fractions. Eight formulations were prepared by varying oil ratios and blended into B35 at 0.1% v/v. Water content was monitored over 7 days of storage, followed by flash point screening. The optimal formulation was further evaluated for particulate content, physicochemical properties, engine performance using a dynotest, and exhaust emissions on a Kubota D722 diesel engine. Among all formulations, D1 (turpentine:clove terpene:citronella = 1:8:1) exhibited the most balanced performance. D1 reduced water content to 320 mg/kg, meeting the ≤400 mg/kg limit, and increased the flash point to 75 °C (minimum requirement: 52 °C). Particulate levels across 4, 6, and 14 μm fractions were substantially reduced. The B35 + D1 blend satisfied key fuel specifications, including a cetane number of 54.7, viscosity of 3.171 mm2/s, and oxidation stability exceeding 35 h. Engine testing showed more stable torque and power at high speeds with D1 at 1% v/v compared with 0.1% v/v. Smoke emissions decreased markedly, while NOx emissions increased, indicating a combustion trade-off typical of oxygenated additives.

Processes doi: 10.3390/pr14152464

Authors: Baijun Yue Yu Wang Xianghong Zeng Yunpeng Hu Wenqiang Han Yukai Wu

Cement-based grouting materials may suffer strength loss and impermeability degradation when exposed to oil- and gas-bearing corrosive environments. In this study, 7.0% waterborne epoxy resin was used as a polymer admixture to improve the durability of cement-based grout under coupled corrosive exposure. Actual corrosive fluid from an engineering site and accelerated dry–wet cycling were used to simulate the service environment. The evolution of mechanical properties, impermeability, and dominant microstructural damage was then examined. The results show that the unmodified grout deteriorated markedly during cyclic exposure. After 120 cycles, its compressive strength decreased from 37.4 MPa to 26.2 MPa, the elastic modulus decreased by 44.1%, and the impermeability pressure dropped from 0.9 MPa to 0.3 MPa. By contrast, the grout containing 7.0% waterborne epoxy resin showed better durability. The strength and modulus losses were limited to 17.4% and 21.0%, respectively, and the impermeability pressure remained at 0.6 MPa, about twice that of the unmodified grout. Microscopic results indicate that dry–wet alternation promoted aggressive ingress and crack growth. The epoxy phase formed a relatively continuous film in the matrix, reduced penetration pathways, and slowed internal damage development. Based on the observed damage evolution, a mechanical prediction model and a new impermeability grading method were established. These findings show the potential of polymer admixture modification for improving the long-term performance of cement-based grouting materials in aggressive environments.

Processes doi: 10.3390/pr14152463

Authors: Qi Miao Zhengdong Jiang Xianfeng Jiao Conghua Ran Jinsheng Zou Jinxiang Li Hongzhao Fan Xianxiang Bai Yunfeng Ma

Municipal solid waste (MSW) incineration power generation has become the dominant waste treatment technology in China. However, acid flue gas dominated by HCl and SO2 induces severe boiler corrosion, a surge in hazardous fly ash, and uncontrolled operational costs, significantly hindering the industry’s low-carbon transition. While conventional dry, semi-dry, and wet deacidification processes meet emission standards, they face an irreconcilable trilemma, failing to concurrently optimize removal efficiency, economic viability, and solid waste reduction. This review clarifies that high-temperature in-furnace deacidification represents a future development direction yet identifies two critical limitations: above 700 °C, external mass transfer remains the rate-controlling step, and the combined effects of CaSO3 decomposition and sorbent sintering lead to inefficient desulfurization. Meanwhile, in the 130–400 °C range, HCl preferentially occupies active sites, inhibiting SO2 adsorption. To address these challenges, this study proposes an innovative staged temperature–gradient synergistic deacidification pathway driven by catalytic oxidation. This strategy utilizes transition metals at high temperatures to oxidize SO2 into SO3, which is subsequently converted into thermally stable CaSO4, while decoupling SO2 pre-removal from the targeted capture of HCl in their respective optimal windows. Finally, four executable development directions are systematically proposed: industrial waste-based bifunctional sorbents, multi-field coupled gas–solid mass transfer intensification, staged deacidification processes, and full-process AI closed-loop control. These findings provide systematic theoretical support and actionable technical references for upgrading MSWI technology under China’s “Dual Carbon” and “Waste-Free City” initiatives.

Processes doi: 10.3390/pr14152462

Authors: Feras Alrowaie

Industrial process safety systems are predominantly reactive: alarms activate after limits are crossed, faults are diagnosed after deviations develop, and HAZOP knowledge remains offline during operation. This paper proposes Predictive Operational Safety Engineering (POSE) as an emerging research paradigm in which operational safety is treated as a continuously forecastable state rather than a post-event classification, shifting the operational question from what has gone wrong? to how much safe operating time remains, and which intervention is most urgent? Four integrated predictive safety metrics anchor the framework: Remaining Safety Margin (RSM), quantifying the normalized distance between the predicted process trajectory and the nearest safety boundary; Remaining Safe Operating Time (RSOT), estimating when that boundary will be crossed under the current trajectory; the Operational Vulnerability Index (OVI), combining margin depletion rate, safeguard availability, and consequence severity into a single intervention-urgency signal; and Predictive Safety Confidence (PSC), the probability that a specific named operator intervention can be executed to completion before the predicted safety boundary is crossed, coupling prediction uncertainty with action execution time. The Predictive Operational Safety Twin (POST) is proposed as a three-layer reference architecture implementing POSE through predictive process intelligence, predictive safety intelligence, and human safety intelligence. The paper synthesizes six research streams, positions POSE against seven adjacent disciplines, states ten guiding principles, and formulates a research agenda. As a conceptual narrative review, the paper does not claim empirical validation of POSE. Instead, it establishes the foundational vocabulary, reference architecture, and research agenda required to advance predictive operational safety from an emerging concept toward benchmarked and industrially validated practice. This article constitutes the conceptual and evidence-synthesis phase of a staged research program; subsequent work must test the proposed constructs through benchmark simulation, uncertainty calibration, baseline comparison, operator studies, and industrial case studies.

Processes doi: 10.3390/pr14152461

Authors: Yang Tang Zhouyueyang Cheng Qilun Jin Xiaojun Yang Chuan Guan Miao Deng Binbin Tang Huan Gao Wenjie Jiang Yang Xian Ping Jiang Peiyuan Peng Zhenhua Feng

The concurrent disposal of industrial lithium slag (LS) and the remediation of heavy-metal-contaminated water remain critical environmental imperatives. Herein, industrial lithium slag was successfully upcycled into a high-capacity geopolymer via alkali activation to systematically evaluate its Pb(II) removal mechanisms. Synthesized under optimal conditions (11 mol/L alkali concentration, 0.616 solid-to-liquid ratio), the geopolymer showed exceptional Pb(II) capture, achieving ~99% removal efficiency within 120 min for a 100 mg/L Pb(II) solution at pH 6.0. The adsorption kinetics obeyed the pseudo-first-order model, yielding a remarkable theoretical equilibrium capacity of 284 mg/g. Thermodynamic results reveal a spontaneous (ΔG < 0), endothermic (ΔH = 17.66 kJ/mol) process with increased interfacial randomness (ΔS > 0). Integrating macroscopic performance with characterizations and density functional theory (DFT) computations elucidated a site-specific chemisorption mechanism and the precipitation of PbSO4 caused by Pb(II) and SO42− in LS. Ultimately, this work provides a sustainable paradigm for the value-added upcycling of industrial solid waste.

Processes doi: 10.3390/pr14152460

Authors: Federico Delle Fave Diego Cisternino Francesco Giorgi Pier Gianni Medaglia

Polydimethylsiloxane (PDMS) is a promising material for the fabrication of 3D scaffolds, thanks to its versatility and the possibility of producing sponge-like architectures through sugar-templating methods. The incorporation of functional additives further expands their potential, extending the applicability of PDMS-based systems toward advanced functional systems in areas such as environmental remediation, sensing, and biomedicine. Among these additives, metal-based nanomaterials such as layered double hydroxides (LDH) are particularly attractive due to their tuneable composition and multifunctional properties. LDHs have gained increasing attention in a range of fields, including biomedical and environmental research, thanks to their biocompatibility, controlled intercalated species release, catalysis, and sensing potential. Previous studies have incorporated LDHs into PDMS sponges via post-synthesis impregnation of pre-formed LDH crystallites, typically synthesized by co-precipitation. While widely used, co-precipitation may limit control over LDH crystallinity, morphology, and structure, affecting performance. In contrast, in situ growth strategies enable more controlled nucleation and development of the LDH structure, leading to improved structural definition and physicochemical properties. In this study, we propose a simple and cost-effective approach based on the incorporation of LDH synthesized under controlled in situ conditions into a porous PDMS sponge matrix with various architectures developed through the use of different sugar templates, enabling tuneable pore sizes while maintaining a scalable and accessible fabrication process.

Processes doi: 10.3390/pr14152459

Authors: Jun Lin Jiyong Li

With the increasing integration of photovoltaic (PV) and energy storage systems into power grids, stability issues caused by converter dynamics, grid impedance interactions, and AC/DC coupling have become increasingly significant. Conventional uniform frequency-scanning methods often fail to provide sufficient resolution in stability-critical frequency regions, limiting the accurate characterization of resonance phenomena. This paper proposes an adaptive two-port admittance modeling and stability assessment method for grid-connected PV-storage systems considering AC/DC coupling characteristics. A two-port frequency-domain model incorporating AC-side admittance, DC-side admittance, and transfer admittance is first established to describe dynamic interactions between the AC and DC subsystems. An adaptive frequency-domain modeling framework with physical constraints is then developed to improve modeling accuracy in critical frequency bands. Furthermore, an improved generalized impedance-ratio criterion considering AC/DC transfer effects and DC-side participation factors is proposed for resonance risk assessment and source identification. Simulation studies and hardware-in-the-loop experiments based on MATLAB 2024b and RT-LAB 2024.1.1 are conducted to validate the proposed method. Results demonstrate that the proposed approach effectively enhances frequency-domain resolution, improves the characterization of AC/DC-coupled resonance behavior, and accurately identifies dominant resonance sources under different operating conditions.

Processes doi: 10.3390/pr14152458

Authors: Ikrama Tariq Muhammad Wasim Muhammad Umer Sohail

This study develops a gain-scheduled Linear Quadratic Regulator (LQR) for the final landing burn of a reusable booster. Using thrust vector control (TVC) and thrust modulation as the primary braking and adjustment force, the vehicle booster is made to land with minimal velocity at the correct coordinates. The Falcon-9-inspired descent trajectory is used as a reference point for the landing. The nonlinear six-degree-of-freedom system is linearized at selected operating points along the reference trajectory, which includes different initial velocity, vehicle wet mass, and starting altitude. At each point, a controllable ten-state reduced model is used to compute a local LQR gain, and altitude interpolation is used to allow the controller to adjust the gain, reference state, and feedforward command. The controller is tested in eight nonlinear cases, including nominal descent, initial lateral and altitude offsets, a sustained thrust command disturbance, gimbal bias disturbance, and combined actuator–thrust and actuator–thrust–lateral disturbances. The vehicle makes soft landings for all the cases with vertical velocities between −0.713 m/s and −0.844 m/s, and a maximum final lateral error of 1.257 m, a maximum tilt of 5.22 deg, and gimbal demand within the imposed ±8 deg limit. In the lateral offset case, an initial 22.36 m horizontal error is reduced to about 0.005 m. A 2000-case Monte Carlo study of initial-state and mass dispersions gave a 100% pass rate, with touchdown velocities from −0.783 m/s to −0.654 m/s and a maximum final lateral error of 0.250 m. Within the assumptions of the present simulation model, the results show that LQR can be deployed as a practical baseline controller for reusable-booster landing burn studies.

Processes doi: 10.3390/pr14152457

Authors: Martina Bertino Serena Allesina Annachiara De Prisco Marco Pane Roberto Pisano

Scientific interest in probiotics continues to grow as accumulating evidence links microbiome modulation to improvements in host health. Probiotics are usually described as live microorganisms that, when administered in adequate amounts, confer a health benefit to the host. However, products are exposed to multiple stresses during manufacturing, storage, and gastrointestinal transit. Among these, drying, often employed to stabilize powders and extend shelf life, can impose high viability loss. This review synthesizes recent advances in drying process engineering, formulation design, and viability assessment aimed at improving survival during drying. Freeze drying remains the most widely used technology, while alternative approaches, including conventional spray drying, vacuum drying, spray freeze drying, and electrostatic spray drying, are increasingly evaluated. Protective strategies are discussed, encompassing sublethal conditioning (stress adaptation), optimization of operating parameters, incorporation of excipients, and encapsulation. Lastly, methods for viability assessment are also compared, contrasting culture-dependent assays (e.g., plate enumeration) with culture-independent techniques such as flow cytometry and PCR-based approaches. However, across studies, performance is highly strain-specific, and optimization often entails trade-offs among immediate survival, cycle time, powder stability, and downstream functionality.

Processes doi: 10.3390/pr14152456

Authors: Yuting Hou Jianhong Guo Jinyu Zhou Die Liu Changsheng Wang Lili Tian Kun Meng

With the gradual decline in conventional oil and gas production growth, unconventional natural gas has become a strategic alternative for hydrocarbon supply. Coal-rock gas (CRG) represents a deep unconventional gas resource with huge potential. Major exploration breakthroughs of CRG have been achieved in China, while systematic research targeting CRG as an independent gas reservoir is still lacking internationally. After effective commercial development, CRG serves as an important supplementary energy source for the domestic natural gas supply. Existing logging evaluation methods exhibit notable deficiencies, as porosity is typically estimated by fitting well logging data or proximate analysis data, resulting in limited accuracy. To address the lack of a dedicated logging volumetric model, ambiguous coal-matrix framework parameters, and substantial porosity calculation errors in deep CRG reservoirs, this study investigates the medium–high rank No. 8 coal seam of the Benxi Formation in the central-eastern Ordos Basin. From an oil and gas reservoir logging evaluation perspective, multi-scale experiments were conducted to systematically characterize the material composition and microscopic characteristics of the coal rock. From the perspective of oil and gas reservoir logging evaluation, a three-component logging volumetric model, consisting of a coal matrix, inorganic minerals, and pore fluids, was constructed, and the corresponding coal-matrix framework parameters were calibrated. The results demonstrate that coal rock is an organic–inorganic composite system, with organic macerals dominated by vitrinite (averaging 59.1%) and inertinite (27.1%). The sum of fixed carbon and volatiles exhibits strong correlations with total organic carbon (TOC) and micro-CT-derived coal-matrix content, yielding determination coefficients of 0.99 and 0.95, respectively, which validates the reliability of the multi-scale quantitative composition characterization. The coal-matrix framework parameters are non-constant: density ranges from 1.08 to 1.56 g·cm−3, acoustic slowness from 281 to 425 μs·m−1, and compensated neutron from 39% to 79%. Borehole enlargement severely affects compensated density and neutron logs but has negligible interference with acoustic slowness. Notably, inertinite content shows a significant negative correlation with the acoustic-slowness framework response (R2 = 0.80), indicating that structurally dense inertinite is a key intrinsic factor controlling the elastic response of the coal matrix. For porosity evaluation, a dual-variable framework model is proposed. The core novelty of this method is that it simultaneously incorporates variations in inorganic mineral content and differences in inertinite proportion within organic components as dynamic framework constraints, breaking through the limitation of the conventional constant-matrix assumption. The acoustic-slowness-based model achieves an average relative error of merely 7.1%, effectively resolving the large errors inherent in conventional fitting methods. The dedicated coal-rock logging evaluation system established in this study overcomes the limitations of fixed framework models, offers a scientific basis for fine-scale interpretation and resource assessment of deep CRG reservoirs, and provides a valuable reference for evaluating analogous reservoirs.

Processes doi: 10.3390/pr14152455

Authors: Guangming Ren Haotian Zhang Ming Zhu Yuwei Feng Tianyu Liu Yi Liu

Heavy oil reservoirs typically suffer from low recovery efficiency and high development costs during thermal production. This study investigates the A66 heavy oil reservoir and proposes an integrated hot-water flooding and hot-to-cold injection strategy. Laboratory experiments, numerical simulations, and techno-economic analysis are combined to optimize injection temperature, conversion timing, and injection parameters. Results show that injection temperature strongly affects oil recovery. Increasing temperature from 40 °C to 60 °C significantly improves recovery by reducing oil viscosity and enhancing mobility. However, further increases to 80 °C and 100 °C provide only marginal additional improvement, indicating a clear diminishing return effect. Considering both recovery performance and energy consumption, 60 °C is identified as the optimal injection temperature. Simulation results indicate that the timing of hot-to-cold conversion has a limited impact on final recovery, while significantly affecting development cost. A conversion window at a water cut of 10–20% achieves a balanced performance between displacement efficiency and thermal cost reduction. In addition, unstable injection improves sweep efficiency by dynamically adjusting flow paths and enhancing both areal and vertical displacement. A coupled hot-to-cold injection strategy is therefore proposed. It integrates temperature optimization, injection mode design, and conversion timing to improve both recovery and economic performance. Compared with conventional constant-temperature flooding, the proposed strategy better accounts for the time-dependent evolution of reservoir thermal conditions and fluid properties. Techno-economic evaluation confirms that the optimized scheme achieves higher economic efficiency while maintaining stable recovery improvement, demonstrating strong potential for field application in similar heavy oil reservoirs.

Processes doi: 10.3390/pr14152453

Authors: Gang Wang Yong Qin Liqiang Du Yijia Yang Yan Li

To elucidate the geochemical features of produced water in coalbed methane (CBM) wells of the Gujiao Block and their indicative significance for production, systematic testing of ion composition and total dissolved solids (TDS) of produced water from ten CBM wells was conducted through five discrete sampling campaigns over an 18-month period. Combined with production performance data, the spatiotemporal evolution patterns, controlling factors, and the response relationship with productivity were analyzed. The results show that the water chemistry type of produced water in the study area is mainly identified as the Na-HCO3 type. The TDS averages 1716.62 mg/L. The hydrochemical characteristics are primarily controlled by water/rock interactions, with Na+ and K+ mainly derived from silicate mineral weathering and dissolution, coupled with cation exchange processes. The Na/Cl ratio suggests that halite dissolution contributes to both Na+ and Cl−, whereas the excess Na+ relative to Cl− likely reflects cation exchange or dissolution of Na-bearing silicate minerals. As drainage proceeded, Na+ and K+ concentrations increased, Ca2+ decreased, Cl− increased, and SO42− first increased and then decreased. Spatially, TDS increases from north to south, with the central-southern region representing a stagnant groundwater zone. Productivity response analysis reveals that Na+, HCO3−, and TDS all show a trend of initially slow increase followed by rapid increase with increasing gas production. A negative trend is observed between gas production and the concentrations of Cl−, Ca2+, Mg2+, and SO42−. The productivity response index for the Gujiao Block ranges from 3.75 to 42.43, with an average of 17.78. As the productivity response index increases, gas production initially decreases and then increases. The findings clarify the geochemical evolution mechanisms of produced water in the Gujiao Block, providing a scientific basis for productivity evaluation of CBM wells.

Processes doi: 10.3390/pr14152454

Authors: Konstantinos Atsonios Panagiotis Tatoulis Sanna Tuomi Minna Kurkela Panagiotis Grammelis

This study provides the main performance estimates for new concepts, using flexible gasification operation modes, adaptable to prevailing market conditions, for the production of bio-synthetic natural gas (bio-SNG) and biochar from biogenic residues and waste, such as bark, straw, and Solid Recovered Fuel (SRF). Dedicated integrated process models were developed in Aspen Plus based on and validated against data from experimental campaigns in a gasification and gas cleaning pilot plant. Simulation runs show that the proposed concepts convert biomass to bio-SNG 10% more efficiently than the reference case, mainly due to the considerably reduced oxygen demand at the Autothermal Reformer (ATR) enabled by the improved catalyst. The co-production mode schemes showed promising results in terms of overall plant efficiency, at 76.5–78.2%, and total carbon utilisation, at 41–55.3%. The hybrid cases require an electrolyser with a power capacity almost 70% of the biomass thermal input to the gasifier, resulting in a total electricity consumption of up to 0.769 kWhe/kWh of biofuel. In return, they achieve over 50% utilisation of the carbon contained in the feedstock for biofuel production and a 70.1–76.5% total plant energy efficiency. Efficient biofuel and biochar production unlock negative emission potential, further strengthening the value of these flexible concepts.

Processes doi: 10.3390/pr14152452

Authors: Syed Haseeb Haider Zaidi Alex Shenfield Hongwei Zhang Augustine Ikpehai

Reliable bearing fault detection is essential for predictive maintenance in industrial systems; however, obtaining labelled fault data is often expensive, time-consuming, and impractical in real-world deployments. To address this challenge, this study proposes a healthy-only self-supervised anomaly detection framework for bearing health monitoring using vibration measurements. The proposed approach combines convolutional neural networks and Transformer-based temporal modelling to learn informative representations from healthy vibration signals without requiring fault labels during representation learning. Three self-supervised learning strategies—reconstruction-based, contrastive, and a unified contrastive–reconstruction objective—are investigated to evaluate the effectiveness of different representation learning approaches. The learned latent representations are subsequently analysed using Isolation Forest and Mahalanobis-distance anomaly scoring methods. To provide a realistic assessment of generalisation, a strict grouped cross-validation protocol is employed, where data are partitioned at the sample level to prevent information leakage between training and testing sets. Furthermore, prevalence-aware experiments are conducted under 5% and 10% fault prevalence scenarios to assess deployment robustness. Experimental results on the Paderborn bearing dataset demonstrate that the proposed CNN + Transformer model trained with combined contrastive and reconstruction objectives and evaluated using Isolation Forest achieves the best overall performance, obtaining a ROC-AUC of 0.878±0.015, a PR-AUC of 0.958±0.005, and an F1-score of 0.590±0.040. The results consistently outperform classical feature-based approaches, One-Class SVM, and autoencoder baselines. Ablation analysis further shows that combining contrastive and reconstruction objectives produces more informative representations than either objective alone. The findings demonstrate that the proposed healthy-only self-supervised framework provides an effective and label-efficient approach for rolling bearing anomaly detection and shows promise for predictive maintenance applications where labelled fault data are limited or unavailable.

Processes doi: 10.3390/pr14152451

Authors: Xijuan He Feifan Hong Jianbin Chen Liyang Fang Zhendong Huang Wei Liang Weitao Shi Yi Fan

For single-motor Formula Student Electric China (FSEC) race cars, current powertrain design methodologies commonly suffer from the disconnection among parameter matching, dynamic simulation, and structural optimization: gear ratio selection is mostly based on static theoretical calculations, lightweight design does not incorporate full-vehicle dynamic load spectra constraints, and the simulation toolchain (CarSim 2024, OptimumLap version 5, ANSYS 2022) lacks a standardized data closed-loop, leading to prolonged iteration cycles and unquantifiable reliability. To address these issues, this paper takes the Nanning University electric formula race car E66 as the research object and proposes a three-phase integrated design framework of “requirement-driven, multi-simulation co-validation, and lightweight iteration.” The study includes three core contributions: (1) establishing a powertrain parameter matching method based on power boundary calculations and multi-dimensional selection criteria, achieving the integrated selection of the Emrax 228 motor (power density 9.2 kW/kg, Emrax d.o.o., Kamnik, Slovenia) and the Unitek-D3 controller through comparative analysis with the JJE motor (5.7 kW/kg, Jing-Jin Electric Technologies Co., Ltd., Beijing, China); (2) constructing a co-simulation mechanism combining OptimumLap version 5 and CarSim 2024, completing the closed-loop optimization of the gear ratio from the range of 1.6–4.3 to the optimal value of 3.9 under the Hefei NIO track operating conditions, with a 75 m acceleration simulation result of 4.4 s and an endurance lap time of 86 s; (3) introducing ANSYS 2022 topology optimization technology to perform two-iteration lightweight design on the 7075 aluminum alloy main sprocket, achieving 35% mass reduction and 40% volume reduction while maintaining the maximum principal stress at 73.16 MPa (below yield strength). The expected outcome is a replicable development paradigm for single-motor powertrain systems, transforming drivetrain matching from experience-driven to simulation-driven, providing reliable data boundaries for physical vehicle commissioning, and effectively reducing trial-and-error costs.

Processes doi: 10.3390/pr14152450

Authors: Jinzhao Zhang Libao Jia Zhixin Ma Zongbin Wang

As mineral resource development moves deeper into the earth, mine dynamic disasters, represented by rockbursts, occur frequently. Due to the combined effects of in situ rock stress state and geostress conditions, it is difficult to obtain reliable prediction results using traditional empirical criteria or single-index prediction methods. To address these issues, this paper constructs a rockburst sample database based on the existing literature, including maximum tangential stress, uniaxial compressive strength, uniaxial tensile strength, elastic energy index, stress coefficient, and brittleness coefficient. Secondly, six typical machine learning algorithms are selected for rockburst level classification research. Then, to address the problem of imbalanced sample distribution, the SMOTE oversampling method is introduced to balance the data, and Bayesian optimization and cross-validation are combined to optimize the model hyperparameters. The results show that optimized XGBoost models exhibit high accuracy and stability in rockburst level discrimination, and accuracy reached 0.7664, recall was 0.7664, macro-P was 0.7664, and macro-F1 was 0.7662. Furthermore, taking the BO-XGBoost model as an example, the SHAP method is introduced to analyze the interpretability of the model’s prediction results. The results show that the elastic energy index and stress-related indices are the main controlling factors affecting the intensity of rockburst; they accounted for 25.75% and 22.68%, respectively. Based on the above research results, this paper further explores the ideas for rockburst safety management and prevention from the aspects of energy control, stress regulation, and optimization of rock mass structural characteristics, providing theoretical basis and technical support for the scientific formulation of rockburst risk identification, level prediction, and safety prevention and control measures in deep underground engineering.

Processes doi: 10.3390/pr14152449

Authors: Nasser Alkhaldi

Accurate solar radiation forecasting is essential for photovoltaic energy generation, smart grid stability, and renewable energy management. This study proposes a lightweight hybrid deep learning framework that combines a transformer encoder and Gated Rrecurrent Uunit (GRU) network for short-term solar radiation forecasting in Makkah and Madinah, Saudi Arabia. Hourly meteorological data from the NASA POWER dataset (2020–2025) were utilized, including solar radiation intensity, temperature, humidity, wind speed, cloud amount, rainfall, surface pressure, and dew point temperature. A preprocessing pipeline consisting of missing value treatment, outlier removal, normalization, timestamp alignment, and data cleaning was applied to improve data quality. Feature engineering techniques were incorporated to capture temporal dependency, meteorological interactions, weather dynamics, and solar variability patterns. The transformer encoder was used to learn long-range temporal dependencies through multi-head self-attention, while the GRU layer modeled sequential temporal dynamics efficiently. Hyperparameter optimization was performed using Bayesian optimization with Optuna. The experimental results demonstrate that the proposed transformer GRU framework achieved a Mean Absolute Error (MAE) of 0.014, Root Mean Square Error (RMSE) of 0.0219, and a coefficient of determination (R2) of 0.98. The proposed model outperformed ARIMA, LSTM, GRU, and XGBoost models while maintaining stable performance across varying weather conditions and forecasting horizons.

Processes doi: 10.3390/pr14152448

Authors: Mi Yang Zhan Zhang Xudong Zhu Jiguang Li

Effective task allocation is fundamental to the success of heterogeneous multi-robot cooperative missions in smart manufacturing workshops, yet real-world operational uncertainties pose severe challenges to solution feasibility and mission robustness. Addressing these challenges, this paper focuses on the inspection and maintenance task allocation problem for heterogeneous mobile robot teams operating under fluctuating equipment maintenance time windows, variable task execution durations, and uncertain robot travel speeds caused by workshop congestion and payload variations. First, the aforementioned uncertain parameters are characterized using triangular fuzzy numbers, upon which a fuzzy chance-constrained programming model is constructed with the objective of minimizing total operational cost while ensuring constraint satisfaction under uncertainty. The proposed model simultaneously handles two types of critical constraints: the service time window constraint, which requires each task to be completed before its latest allowable service deadline, and the time sequence constraint, which enforces that each equipment inspection task must be completed prior to the corresponding maintenance task. Then, to tackle the inherent NP-hardness of this problem, a multi-strategy hybrid Harris Hawks Optimization algorithm incorporating differential evolution, termed MSHHODE, is proposed. In detail, three targeted enhancement mechanisms are introduced: a hunting enthusiasm factor that governs the dynamic balance between global exploration and local exploitation throughout the search process; an elite-assisted guidance strategy that stabilizes convergence by leveraging high-quality solutions to direct population evolution; and an adaptive differential evolution mechanism that reinforces global search diversity and mitigates premature convergence to local optima. Finally, simulation experiments conducted across multiple workshop-scale scenarios demonstrate that MSHHODE consistently outperforms benchmark algorithms across different key performance metrics under varied uncertain conditions, which validates the effectiveness and robustness of the proposed approach in solving complex, constrained allocation problems, offering a practical and reliable framework for real-world heterogeneous multi-robot task planning in smart manufacturing environments.

Processes doi: 10.3390/pr14152447

Authors: Ruijie Dou Ran Chen Yi Hu Sheng Gong Man Jiang Zhiwen Wu Chuanxiang Ouyang Zhen Li Li Cheng

Metal centralizers suffer high frictional resistance, high self-weight, and severe pore shrinkage after perforation in deep, highly deviated, and horizontal wells. Targeting the performance demands of adhesive casing centralizers, this study uses epoxy resin as the matrix, introduces amino modification, and regulates inorganic filler composites to prepare an amino-modified epoxy resin composite centralizer material, followed by systematic property tests. The optimal formula of modified epoxy resin:curing agent:UR300 accelerator:amino-modified silica:silicon carbide:alumina is 100:10:1:1:35:20 and delivers superior comprehensive performance. Its compressive strength reaches 136.61 MPa with a Shore hardness of 92.32 HD, low linear expansion, and favorable thermal compatibility with steel casings. Hardness remains stable after 168 h of aging at 150 °C, and the material maintains low friction at ambient and elevated temperatures. After 30-day immersion in acidic, alkaline, and high-salinity fluids, its compressive strength retention exceeds 86% with a slight variation in volume and mass, while adhesion strength reaches 2.667 MPa at a pipe-wall roughness of 12.12 μm. Combining high strength, heat resistance, corrosion resistance, and strong adhesion, the material suits complex downhole conditions and supports the field application of resin composite centralizers.

Processes doi: 10.3390/pr14152445

Authors: Faraz Ali Uzma Amin Zifan Lin Yanyan Yin

The intensive development of electric vehicle (EV) technology, renewable energy systems, and stationary energy storage solutions has amplified the demand for advanced Battery Management Systems (BMS). The imbalance in cells within lithium-ion battery packs, due to manufacturing tolerances, varying aging, and thermal gradients, reduces available capacity, cycle life, and can cause thermal runaway. Active charge equalization with DC–DC converters has become a recent research focus among various balancing techniques because it has a better capability of redistributing energy. This paper gives a detailed study of converter-based cell-balancing topologies with a specific focus on the bidirectional flyback converter and the interleaved two-phase variant. Non-isolated topologies (buck–boost, Cuk converter topology, interleaved buck–boost) and isolated topologies (flyback, push–pull, dual-active bridge, LLC resonant) are compared concerning functional efficiency, component reduction, galvanic isolation, scalability, and bidirectional capability. The concept of soft-switching, including zero-voltage switching (ZVS) and zero-current switching (ZCS), and their circuit realizations are discussed. Advanced control models and artificial intelligence (AI) for the estimation of state-of-charge (SoC) and real-time optimization are mentioned. Thermal issues, scalability, reliability, and wide-bandgap semiconductor devices (SiC/GaN) are discussed.