Processes

49 pages, 13115 KB

Open AccessArticle

The Experimental and Numerical Studies on Optimizing Injection Strategies for Microspheres-Alternating-Nanoemulsion Flooding in Tight Reservoirs

by Jun Wang, Lijun Zheng, Changhao Yan, Baoqiang Lv, Pengzhen Zhao, Wensheng Wu, Xiukun Wang and Jun Yang

Processes 2025, 13(12), 4093; https://doi.org/10.3390/pr13124093 - 18 Dec 2025

Viewed by 273

Abstract

In recent years, the production of tight reservoirs with waterflooding in China has entered a progressively declining phase with unstable oil rate and higher water cut, rising challenges to any further enhancement of oil recovery. Targeting the high water cut and complex pore [...] Read more.

In recent years, the production of tight reservoirs with waterflooding in China has entered a progressively declining phase with unstable oil rate and higher water cut, rising challenges to any further enhancement of oil recovery. Targeting the high water cut and complex pore structure characteristics typical of these reservoirs, this work evaluates the reservoir compatibility of a microspheres-alternating-nanoemulsion flooding process and optimizes its injection strategy. Representative reservoir scenarios were first established; laser-particle-size analyzers and other laboratory instruments were then employed to quantify formulation-reservoir compatibility. A multiscale numerical study has been performed with CMG-STARS v.2022. The core-scale simulations systematically examined the influence of key factors on displacement efficiency improvement and water cut reduction, matched with the experimental results of core flooding tests. The combined experimental/numerical workflow furnishes a theoretical framework for optimizing the injection scheme. Beyond assessing formulation compatibility, the study delivers optimized injection parameters and strategies for microspheres-alternating-nanoemulsion flooding, providing both theoretical analysis and practical technology reference for improving oil recovery in tight reservoirs with higher water cut. Specifically, when the microsphere concentration increased from 0.1% to 0.3%, the minimum water cut was reduced by approximately 5%, while further concentration increases showed no significant additional impact on water content. Compared with water flooding, the relative permeability curve of the microspheres-alternating-nanoemulsion flooding system shifted entirely to the right. Numerical simulation of representative well groups revealed that a slug design with a microsphere-to-nanoemulsion ratio of 1:3 yielded the optimal enhanced oil recovery effect, and after ten years of production, the recovery factor increased by 0.46%. Full article

(This article belongs to the Special Issue Flow Mechanisms and Enhanced Oil Recovery)

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23 pages, 4191 KB

Open AccessArticle

Optimizing Structural Parameters of Load Distributive Compression Anchor for Enhanced Grout Performance in Deep Excavations

by Erchao Fu, Wei Yao, Xianqi Zhou, Lyuliang Lin and Jin Yu

Processes 2025, 13(12), 4092; https://doi.org/10.3390/pr13124092 - 18 Dec 2025

Viewed by 220

Abstract

Prestressed flexible support systems have become essential in deep excavation engineering, with the load distributive compression anchor (LDCA) widely adopted to enhance load-bearing performance through effective load dispersion among multiple anchoring units. Structural parameters of the anchor, particularly perforation ratio and height-to-diameter ratio, [...] Read more.

Prestressed flexible support systems have become essential in deep excavation engineering, with the load distributive compression anchor (LDCA) widely adopted to enhance load-bearing performance through effective load dispersion among multiple anchoring units. Structural parameters of the anchor, particularly perforation ratio and height-to-diameter ratio, play a critical role in determining the mechanical behavior of the surrounding grout. In this study, grout located 500 mm behind the anchor body was selected as the test specimen. Unconfined compression tests were conducted to evaluate the ultimate load-bearing capacity under varying anchor configurations. Based on experimental measurements, a numerical simulation model was established and calibrated to investigate the internal stress distribution of the grout under different perforation ratios and height-to-diameter ratios. Results indicate that the perforation ratio significantly influences both the magnitude and location of stress peaks within the grout, with higher perforation ratios shifting the x-directional stress peak toward the anchor orifice and gradually reducing ultimate load-bearing capacity. Reducing the height-to-diameter ratio leads to a more uniform stress distribution, mitigating stress concentration while maintaining near-constant load-bearing capacity, although it increases anchor deformation. Optimal perforation ratio ranges were determined as [11%, 23%], [31%, 37%], and [42%, 50%] for anchors 1, 2, and 3, respectively, and the recommended height-to-diameter ratio is [15%, 17%]. The integration of experimental testing and numerical simulation provides quantitative insights into the effects of anchor design on grout performance, offering practical guidance for optimizing LDCA structures in deep excavation projects. Full article

(This article belongs to the Section Petroleum and Low-Carbon Energy Process Engineering)

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39 pages, 7186 KB

Open AccessArticle

Process Simulation of Pseudo-Static Seismic Loading Effects on Buried Pipelines: Finite Element Insights Using RS2 and RS3

by Maryam Alrubaye, Mahmut Şengör and Ali Almusawi

Processes 2025, 13(12), 4091; https://doi.org/10.3390/pr13124091 - 18 Dec 2025

Viewed by 259

Abstract

Buried pipelines represent critical lifeline infrastructure whose seismic performance is governed by complex soil–structure interaction mechanisms. In this study, a process-based numerical framework is developed to evaluate the pseudo-static seismic response of buried steel pipelines installed within a trench. A comprehensive parametric analysis [...] Read more.

Buried pipelines represent critical lifeline infrastructure whose seismic performance is governed by complex soil–structure interaction mechanisms. In this study, a process-based numerical framework is developed to evaluate the pseudo-static seismic response of buried steel pipelines installed within a trench. A comprehensive parametric analysis is conducted using the finite-element software Rocscience RS2 (version 11.027) to examine the influence of burial depth, pipeline diameter, slope angle, groundwater level, soil type, and permanent ground deformation. The seismic loading was represented using a pseudo-static horizontal acceleration, which approximates permanent ground deformation rather than full dynamic wave propagation. Therefore, the results represent simplified lateral seismic demand and not the complete dynamic soil–structure interaction response. To verify the reliability of the 2D plane–strain formulation, a representative configuration is re-simulated using the fully three-dimensional platform Rocscience RS3. The comparison demonstrates excellent agreement in shear forces, horizontal displacements, and cross-sectional distortion patterns, confirming that RS2 accurately reproduces the dominant load-transfer and deformation mechanisms observed in three-dimensional (3D) models. Results show that deeper burial and stiffer soils increase shear demand, while higher groundwater levels and larger permanent ground deformation intensify lateral displacement and cross-sectional distortion. The combined 2D–3D evaluation establishes a validated computational process for predicting the behavior of buried pipelines under a pseudo-static lateral load and provides a robust basis for engineering design and hazard mitigation. The findings contribute to improving the seismic resilience of lifeline infrastructure and offer a validated framework for future numerical investigations of soil–pipeline interaction. Full article

(This article belongs to the Special Issue Design, Inspection and Repair of Oil and Gas Pipelines)

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17 pages, 1227 KB

Open AccessFeature PaperArticle

Enhancing the Biorefinery of Chestnut Burrs, Part II: Influence of Pretreatment with Choline Chloride–Urea-Diluted Deep Eutectic Solvent on Enzymatic Hydrolysis

by Iván Costa-Trigo, María Guadalupe Morán-Aguilar, Nelson Pérez Guerra, Ricardo Pinheiro de Souza Oliveira and José Manuel Domínguez

Processes 2025, 13(12), 4090; https://doi.org/10.3390/pr13124090 - 18 Dec 2025

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Abstract

Agro-industrial chestnut waste derived from chestnut processing is usually discharged without further use. However, these residues are attractive due to their high-value composition, rich in sugars and lignin. Among these residues, chestnut burrs (CB) represent a promising feedstock for biorefinery applications aimed at [...] Read more.

Agro-industrial chestnut waste derived from chestnut processing is usually discharged without further use. However, these residues are attractive due to their high-value composition, rich in sugars and lignin. Among these residues, chestnut burrs (CB) represent a promising feedstock for biorefinery applications aimed at maximizing the valorization of their main constituents. In this study, we propose an environmentally friendly approach based on deep eutectic solvents (DES) formed by choline chloride and urea (ChCl/U) (1:2, mol/mol) for the selective deconstruction of lignocellulosic architecture, followed by enzymatic hydrolysis to release second-generation (2G) fermentable sugars. Pretreatments were applied to raw CB, washed CB (W-CB), and the obtained solid fraction after prehydrolysis (PreH). Structural and morphological modifications, as well as crystallinity induced by DES pretreatment, were characterized using attenuated total reflectance Fourier-transform infrared spectroscopy (ATR-FTIR), field emission scanning electron microscopy (FE-SEM), and X-ray diffraction (XRD). Remarkable results in terms of effectiveness and environmental friendliness on saccharification yields were achieved for PreH subjected to DES treatment for 8 h, reaching approximately 60% glucan and 74% xylan conversion under the lower enzyme loading (23 FPU/g) and liquid-to-solid ratio (LSR) of 20:1 studied. This performance significantly reduces DES pretreatment time from 16 h to 8 h at mild conditions (100 °C), lowers the LSR for enzymatic hydrolysis from 30:1 to 20:1, and decreases enzyme loading from 63.5 FPU/g to 23 FPU/g, therefore improving process efficiency and sustainability. Full article

(This article belongs to the Special Issue Advances in Green Extraction and Separation Processes)

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20 pages, 5542 KB

Open AccessArticle

Experimental Study on the Creep Behavior and Permeability Evolution of Tuff Under Unloading Confining Pressure with Seepage–Stress Coupling Effects

by Wenlong Dong, Lijun Han, Zishuo Liu, Yijiang Zong, Jun Tang and Dalong Yang

Processes 2025, 13(12), 4089; https://doi.org/10.3390/pr13124089 - 18 Dec 2025

Viewed by 200

Abstract

The long-term stability of deep underground excavations near aquifer-bearing strata is primarily controlled by the time-dependent deformation and permeability changes in the surrounding rock mass under the combined effects of mechanical loading and groundwater seepage. This study experimentally investigates the creep behavior and [...] Read more.

The long-term stability of deep underground excavations near aquifer-bearing strata is primarily controlled by the time-dependent deformation and permeability changes in the surrounding rock mass under the combined effects of mechanical loading and groundwater seepage. This study experimentally investigates the creep behavior and permeability evolution of tuff specimens subjected to stepwise reductions in confining pressure under coupled seepage and stress conditions. Conventional triaxial compression tests were conducted to determine the peak strength at confining pressures of 10, 15, and 20 MPa. Subsequently, triaxial creep tests were performed, maintaining axial stress at 70% of the previously established peak strength, with a constant seepage pressure of 4 MPa, while progressively decreasing the confining pressure. The results clearly reveal a three-stage creep process—with instantaneous, steady-state, and accelerated phases—with the radial strain exceeding axial strain and ultimately dominating at failure. This indicates that failure is characterized by significant volumetric expansion. At the specified initial confining pressures of 10 MPa, 15 MPa, and 20 MPa, the tuff specimens exhibited volumetric strains of −1.332, −1.119, and −0.836 at failure, respectively. Permeability evolution depends on the creep stage, showing a pronounced increase during the accelerated creep phase that often surpasses the cumulative permeability changes observed earlier. The specimen’s permeability at failure increased by factors of 3.97, 3.21, and 3.61 compared to the initial stage of the experiment, respectively. Additionally, permeability evolution exhibits a strong functional relationship with volumetric strain, which can be effectively modeled using an exponential function. The experimental findings further indicate that, as the confining pressure is gradually reduced, the permeability evolves following a clear exponential trend. Additionally, a higher initial confining pressure slows the rate at which permeability increases. These findings clarify the three-stage creep behavior and the associated evolution of the permeability index in tuff under coupled seepage–stress conditions. Additionally, they present a quantitative model linking permeability to volumetric strain, offering both a theoretical foundation and a new approach for assessing the long-term stability risks of deep underground engineering projects. Full article

(This article belongs to the Special Issue Optimization of Complex Engineering Systems and Application of Advanced Digital and Intelligent Technologies)

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25 pages, 395 KB

Open AccessReview

Low-Cost Adsorbents for Water Treatment: A Sustainable Alternative for Pollutant Removal

by Leticia Nishi, Anna Carla Ribeiro, Carolina Moser Paraíso, Diana Aline Gomes Cusioli, Laiza Bergamasco Beltran, Luís Fernando Cusioli and Rosângela Bergamasco

Processes 2025, 13(12), 4088; https://doi.org/10.3390/pr13124088 - 18 Dec 2025

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Abstract

This review addresses the potential of low-cost adsorbents (LCAds) derived from agro-industrial and marine residues as sustainable alternatives for water purification. Although raw biomass offers economic advantages, its application is often limited by low surface area and reactivity. Consequently, this paper examined physicochemical [...] Read more.

This review addresses the potential of low-cost adsorbents (LCAds) derived from agro-industrial and marine residues as sustainable alternatives for water purification. Although raw biomass offers economic advantages, its application is often limited by low surface area and reactivity. Consequently, this paper examined physicochemical modifications—such as pyrolysis, acid/alkali activation, and surface grafting—that enhance adsorptive properties. The superior performance of these modified materials in removing heavy metals, dyes, pesticides, and pharmaceuticals is highlighted. Furthermore, the transition from laboratory scale to industrial application faces key hurdles, such as biomass variability, reactor engineering, and regulatory gaps. Finally, future perspectives are presented, focusing on the integration of LCAds into hybrid treatment systems and their pivotal role in the circular economy for decentralized water management. Full article

(This article belongs to the Special Issue Natural Low-Cost Adsorbents in Water Purification Processes)

17 pages, 2475 KB

Open AccessArticle

Antibacterial Potential and Cytotoxicity Assessment of Zinc-Based Ternary Deep Eutectic Solvents: Towards Innovative Applications in Dental Medicine

by Jelena Filipović Tričković, Nikola Zdolšek, Snežana Brković, Filip Veljković, Suzana Veličković, Bojan Janković, Ana Valenta Šobot, Milica Nemoda and Jelena Marinković

Processes 2025, 13(12), 4087; https://doi.org/10.3390/pr13124087 - 18 Dec 2025

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Abstract

Zn-based ternary deep eutectic solvents (TDESs) have attracted significant attention due to their good biodegradability, stability, and sustainability. In this work, TDESs composed of choline chloride:urea (ChCl:U) and zinc salts, ZnCl₂, Zn(CH₃COO)₂, and ZnSO₄ were synthesized [...] Read more.

Zn-based ternary deep eutectic solvents (TDESs) have attracted significant attention due to their good biodegradability, stability, and sustainability. In this work, TDESs composed of choline chloride:urea (ChCl:U) and zinc salts, ZnCl₂, Zn(CH₃COO)₂, and ZnSO₄ were synthesized and characterized by Fourier transform infrared (FTIR) spectroscopy and laser desorption ionization mass spectrometry (LDI MS). Their antibacterial activity against cariogenic Streptococcus species isolates was determined by microdilution assay, while their cytotoxic potential and effect on the intracellular reactive oxygen species (ROS) induction were analyzed on the MRC-5 fibroblast cell line by XTT, trypan blue, and DCF assays, respectively. FTIR confirmed that hydrogen bonds prevail in the molecular structure of ChCl:U:Zn salts, while LDI MS revealed the interactions between zinc salts and ChCl:U. The antibacterial TDES potential was high, especially against Streptococcus sanguinis, with ChCl:U:ZnCl₂ displaying the most promising effects (MICs 1.13–18.12 µg/mL). Cytotoxicity assessment showed that concentrations up to 100 µg/mL of all TDESs did not display significant cytotoxicity, while higher concentrations significantly reduced cell viability by increasing ROS production and cell membrane damage, outlining the safety window of up to 100 µg/mL. Strong antibacterial activity of low TDESs concentrations combined with their good biocompatibility highlights their potential as innovative candidates for biomedical application. Full article

(This article belongs to the Special Issue Green Processes Based on Ionic Liquids for Advanced Chemical Technologies)

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27 pages, 1475 KB

Open AccessArticle

Operationalizing the R4VR-Framework: Safe Human-in-the-Loop Machine Learning for Image Recognition

by Julius Wiggerthale and Christoph Reich

Processes 2025, 13(12), 4086; https://doi.org/10.3390/pr13124086 - 18 Dec 2025

Viewed by 351

Abstract

Visual inspection is a crucial quality assurance process across many manufacturing industries. While many companies now employ machine learning-based systems, they face a significant challenge, particularly in safety-critical domains. The outcomes of these systems are often complex and difficult to comprehend, making them [...] Read more.

Visual inspection is a crucial quality assurance process across many manufacturing industries. While many companies now employ machine learning-based systems, they face a significant challenge, particularly in safety-critical domains. The outcomes of these systems are often complex and difficult to comprehend, making them less reliable and trustworthy. To address this challenge, we build on our previously proposed R4VR-framework and provide practical, step-by-step guidelines that enable the safe and efficient implementation of machine learning in visual inspection tasks, even when starting from scratch. The framework leverages three complementary safety mechanisms—uncertainty detection, explainability, and model diversity—to enhance both accuracy and system safety while minimizing manual effort. Using the example of steel surface inspection, we demonstrate how a self-accelerating process of data collection where model performance improves while manual effort decreases progressively can arise. Based on that, we create a system with various safety mechanisms where less than 0.1% of images are classified wrongly and remain undetected. We provide concrete recommendations and an open-source code base to facilitate reproducibility and adaptation to diverse industrial contexts. Full article

(This article belongs to the Special Issue Advances in Computer Vision and Image Processing for Industrial Processes)

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19 pages, 3316 KB

Open AccessArticle

Enhancing Bio-Oil Quality Through Ethyl Esterification Catalyzed by Candida antarctica Lipase B

by Aline Gonçalves Gehrke, Leonardo Pellizzari Wielewski, Vinicyus Rodolfo Wiggers, Vanderleia Botton, David Alexander Mitchell and Nadia Krieger

Processes 2025, 13(12), 4085; https://doi.org/10.3390/pr13124085 - 18 Dec 2025

Viewed by 290

Abstract

Fast pyrolysis of vegetable oils and residues generates bio-oil (BO), a renewable hydrocarbon source with high acidity that limits its direct use in refineries. In this study, BOs were produced from refined soybean oil (RSO) and waste cooking oil (WCO) at 525 °C [...] Read more.

Fast pyrolysis of vegetable oils and residues generates bio-oil (BO), a renewable hydrocarbon source with high acidity that limits its direct use in refineries. In this study, BOs were produced from refined soybean oil (RSO) and waste cooking oil (WCO) at 525 °C in a continuous bench-scale pyrolysis at 525 °C, with a 390 ± 8 g h⁻¹ feed rate, under steady-state conditions. The resulting bio-oils exhibited high acidity (acid index of 145 and 127 mg KOH g⁻¹, respectively) and elevated olefinic and oxygen contents, making them corrosive and unsuitable for co-refining with petroleum. To reduce acidity, ethyl esterification was performed using lipase B from Candida antarctica (CALB), using a Box–Behnken 3³ factorial design. Variables included temperature (40–60 °C), bio-oil:ethanol mass ratio (1:1–1:5), and catalyst concentration (3–10% w/w). The acid index was reduced by up to 76%, with optimal conditions (62 °C, 1:1 mass ratio, 11% CALB) yielding a final value of 28 mg KOH g⁻¹. Similar reductions were obtained for waste cooking oil bio-oil, confirming robustness across feedstocks. CALB retained over 70% activity after three cycles, demonstrating stability. This enzymatic esterification process shows strong potential for lowering bio-oil acidity, enabling integration into petroleum refineries, diversifying feedstocks, and advancing renewable fuel production. Full article

(This article belongs to the Special Issue Enzymes, Biocatalysis and Metabolic Engineering for Enabling Sustainability)

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34 pages, 3017 KB

Open AccessReview

Practical Application of Condition-Based Monitoring (CBM) Technologies in the Modern Manufacturing Industry: A Review

by Andres Hurtado Carreon and Stephen C. Veldhuis

Processes 2025, 13(12), 4084; https://doi.org/10.3390/pr13124084 - 18 Dec 2025

Viewed by 422

Abstract

The competitive nature of the modern manufacturing industry, coupled with the constant demand from consumers for high-quality products, push manufacturers to use their production machines beyond their capable operational limits. Condition monitoring and maintenance are crucial necessities to maintain the nominal operation of [...] Read more.

The competitive nature of the modern manufacturing industry, coupled with the constant demand from consumers for high-quality products, push manufacturers to use their production machines beyond their capable operational limits. Condition monitoring and maintenance are crucial necessities to maintain the nominal operation of these machines and ensure the quality of their production processes. The introduction of condition-based monitoring (CBM) from the Industry 4.0 movement opens various opportunities that ensure a machine’s nominal and reliable operation. However, a major gap still exists between newly researched CBM technologies and how to practically apply them in the modern industry, without increasing cost and diminishing their value. Therefore, this paper provides a comprehensive review of the recent research works in CBM that aim to fill this gap. Additionally, this review provides guidance for both researchers and industry practitioners focusing on implementing CBM. Finally, the review concludes with a discussion on the challenges that arise in CBM technologies, future trends, and recommendations. Full article

(This article belongs to the Special Issue Fault Diagnosis and Condition Monitoring of Electrical Machines and Drives)

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17 pages, 1569 KB

Open AccessFeature PaperArticle

Techno-Economic Assessment of Hydrogen and CO₂ Recovery from Broccoli Waste via Dark Fermentation and Biorefinery Modeling

by Carlos Eduardo Molina-Guerrero, Idania Valdez-Vazquez, Arquímedes Cruz López, José de Jesús Ibarra-Sánchez and Luis Carlos Barrientos Álvarez

Processes 2025, 13(12), 4083; https://doi.org/10.3390/pr13124083 - 18 Dec 2025

Viewed by 280

Abstract

Broccoli waste (Brassica oleracea), comprising non-commercialized stems and leaves, represents a valuable substrate for bioenergy and commodity recovery within agro-industrial systems. This study evaluates the potential of dark fermentation (DF) to produce hydrogen (H₂) and carbon dioxide (CO₂ [...] Read more.

Broccoli waste (Brassica oleracea), comprising non-commercialized stems and leaves, represents a valuable substrate for bioenergy and commodity recovery within agro-industrial systems. This study evaluates the potential of dark fermentation (DF) to produce hydrogen (H₂) and carbon dioxide (CO₂) from unpretreated broccoli residues. Batch experiments (120 mL) yielded maximum gas production rates of up to 166 mL/L·d, with final compositions of 41.43 mol% and 58.56 mol% of H₂ and CO₂, respectively. Based on these results, two biorefinery models were simulated using COCO v3.10 and SuperPro Designer^® v12.0, incorporating absorption and cryogenic separation technologies in the purification stage. Two scenarios were considered: Option A (169.82 kmol/day; H₂: 0.5856 mol fraction, CO₂: 0.4143 mol fraction) and Option B (72.84 kmol/day; H₂: 0.6808 mol fraction, CO₂: 0.3092 mol fraction). In both configurations, the purities of the final streams were the same, being 99.8% and 99.8% for both H₂ and CO₂, respectively. However, energy consumption was 43.76% higher in the cryogenic H₂/CO₂ separation system than in the absorption system. Noteworthily, this difference does not depend on the stream’s composition. Furthermore, from a financial standpoint, the cryogenic system is more expensive than the absorption system. These findings confirm the feasibility of designing biorefineries for H₂ production with high CO₂ recovery from broccoli waste. However, the economic viability of the process depends on the valorization of the secondary effluent from the fermentation reactor, which may require subsequent anaerobic digestion stages to complete the degradation of residual organic matter and enhance overall resource recovery. Full article

(This article belongs to the Special Issue Advances in Biomass Conversion and Biorefinery Applications)

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21 pages, 4304 KB

Open AccessArticle

Multi-Condition Fault Diagnosis Method for Rolling Bearings Based on Enhanced Singular Spectrum Decomposition and Optimized MMPE + SVM

by Wenbin Zhang, Xianyun Zhang and Yingyin Chen

Processes 2025, 13(12), 4082; https://doi.org/10.3390/pr13124082 - 18 Dec 2025

Viewed by 217

Abstract

Aiming to improve the currently low accuracy of fault diagnosis due to the difficulty of extracting the non-stationary and nonlinear features of rolling bearing fault signals, a multi-condition fault diagnosis method for rolling bearings was proposed based on enhanced singular spectrum decomposition (ESSD), [...] Read more.

Aiming to improve the currently low accuracy of fault diagnosis due to the difficulty of extracting the non-stationary and nonlinear features of rolling bearing fault signals, a multi-condition fault diagnosis method for rolling bearings was proposed based on enhanced singular spectrum decomposition (ESSD), optimized multi-scale mean permutation entropy (MMPE), and support vector machine (SVM). Firstly, aiming to address the problem of singular spectrum decomposition (SSD) producing false components and signals with low energy proportions that cannot be accurately decomposed when the residual energy ratio is used as the final iteration termination condition, an enhanced singular spectral decomposition method is proposed. Secondly, the effect of the MMPE extraction of fault features depends on the selection of parameters, and after comprehensively considering the interaction between MMPE parameters, a method to optimize MMPE based on the particle swarm optimization (PSO) algorithm is proposed to maximize the performance of the extracted features. Finally, considering that the classification performance of SVM is affected by the penalty factor c and kernel function g, the fault characteristics proposed by ESSD + PSO - MMPE are identified by an SVM classifier model that is optimized by the particle swarm algorithm, so as to realize the effective diagnosis of multi-condition faults in rolling bearings. Using rolling bearing simulation signals, the Case Western Reserve University bearing dataset, and the online monitoring signal from the front bearings of a wind farm’s 1.5 MW wind turbine, the proposed method is compared with EMD + MMPE + SVM, SSD + MMPE + PSO - SVM, ESSD + MMPE + PSO - SVM, and other methods, and the results show that the proposed method can effectively identify multi-working faults in rolling bearings. Full article

(This article belongs to the Special Issue Fault Diagnosis and Condition Monitoring of Electrical Machines and Drives)

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13 pages, 1616 KB

Open AccessArticle

Real-Time Prediction of Bottom Hole Pressure via Graph Neural Network

by Zhaoyu Pang, Rui Zhang, Mengnan Ma, Haizhu Wang, Qihao Li and Chaochen Wang

Processes 2025, 13(12), 4081; https://doi.org/10.3390/pr13124081 - 18 Dec 2025

Viewed by 304

Abstract

Accurately and efficiently predicting bottomhole pressure (BHP) is of great importance for safe drilling in complex formations. Many researchers have conducted extensive investigations into intelligent BHP prediction techniques. However, the current intelligent models mostly focus on the data-driven relationship between logging parameters and [...] Read more.

Accurately and efficiently predicting bottomhole pressure (BHP) is of great importance for safe drilling in complex formations. Many researchers have conducted extensive investigations into intelligent BHP prediction techniques. However, the current intelligent models mostly focus on the data-driven relationship between logging parameters and BHP, and less on the influence of the correlation between the logging parameters on the BHP. This paper proposes a real-time prediction framework based on graph neural networks. Our model selects input features based on drilling mechanisms and statistical analyses, and utilizes adaptive learning of the graph based on multivariate time-series parameters to capture the relationship between multivariate logging parameters and BHP. Finally, the model performance is thoroughly analyzed based on field drilling datasets after optimizing model hyperparameters using the Bayesian optimization method. Results indicate that the proposed method performs better in terms of prediction accuracy, captures the inflection points of curve changes better, and is more robust under the new well section. The mean absolute percentage error of the method reaches 1.28% which is reduced by 25% compared with other traditional intelligent models. This study provides a solution for achieving accurate real-time predictions of bottom hole pressure, establishing a solid foundation for the realization of precise pressure control during drilling operations. Full article

(This article belongs to the Special Issue Modeling, Control, and Optimization of Drilling Techniques)

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21 pages, 7958 KB

Open AccessArticle

Multi-Scale Characterization and Modeling of Natural Fractures in Ultra-Deep Tight Sandstone Reservoirs: A Case Study of Bozi-1 Gas Reservoir in Kuqa Depression

by Li Dai, Xingnan Ren, Chengze Zhang, Yuanji Qu, Binghui Song, Xiaoyan Wang and Wei Tian

Processes 2025, 13(12), 4080; https://doi.org/10.3390/pr13124080 - 18 Dec 2025

Viewed by 266

Abstract

Natural fractures in tight sandstone reservoirs are the key factors controlling hydrocarbon flow and productivity. The Bozi-1 gas reservoir in the Kuqa Depression, as a typical ultra-deep tight sandstone gas reservoir, is characterized by low-porosity and ultra-low-permeability sandstones. This study addresses the limitations [...] Read more.

Natural fractures in tight sandstone reservoirs are the key factors controlling hydrocarbon flow and productivity. The Bozi-1 gas reservoir in the Kuqa Depression, as a typical ultra-deep tight sandstone gas reservoir, is characterized by low-porosity and ultra-low-permeability sandstones. This study addresses the limitations of previous fracture characterization, which primarily focused on macro-structural fractures while neglecting medium- and small-scale fractures. We integrate multi-source heterogeneous data, including core, well-logging imaging, seismic, and production observations, to systematically conduct multi-scale natural fracture characterization and modeling. First, the overall geology of the study area is briefly introduced, followed by a detailed description of the development characteristics of large-scale and medium–small-scale fractures, achieving a multi-scale representation of complex curved fracture networks. Finally, the three-dimensional multi-scale fracture model is validated using static indicators, including production characteristics, water invasion features, and well leakage data. The main findings are as follows: (1) Large-scale fractures in the Bozi-1 reservoir are mainly oriented near EW, NE–SW, and NW–SE, acting as the primary hydrocarbon migration pathways. Medium–small-scale fractures predominantly develop near SN, NE–SW, NW–SE, and near EW directions, exhibiting strong heterogeneity. (2) The complex curvature of large-scale fractures was captured by the “adaptive sampling + segmented splicing + equivalent distribution of fracture flow capacity” method, while the distribution of effective medium–small-scale fractures across the study area was represented using “single-well Stoneley wave inversion + seismic machine learning prediction”, achieving an 86% match with actual single-well measurements. (3) Model reliability was further verified through static comparisons, including production characteristics (unimpeded flow vs. effective fracture density, R² = 0.92), water invasion features (fracture-dominated water invasion matching fracture distribution), and well leakage characteristics (matching rate of high fracture density zones: 84.2%). The results provide key technical support for the precise characterization of fracture systems and establish a model ready for dynamic simulation in ultra-deep tight sandstone gas reservoirs. Full article

(This article belongs to the Special Issue Advances in Evaluation, Development, Simulation and Utilization of Geo-Energy Resources and Underground Space)

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6 pages, 2020 KB

Open AccessEditorial

Industrial Chemistry Reactions (3rd Edition): Kinetics, Mass and Heat Transfer in View of the Design of Industrial Reactors

by Vincenzo Russo and Riccardo Tesser

Processes 2025, 13(12), 4079; https://doi.org/10.3390/pr13124079 - 18 Dec 2025

Viewed by 195

Abstract

The first and second editions of the Special Issue entitled “Industrial Chemistry Reaction: Kinetics, Mass Transfer and Industrial Reactor Design” have both been successful. [...] Full article

(This article belongs to the Special Issue Industrial Chemistry Reactions (3rd Edition): Kinetics, Mass and Heat Transfer in View of the Industrial Reactors Design)

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21 pages, 4455 KB

Open AccessArticle

Field Chemical Characterization of Sulfate-Induced Deterioration: A Case Study of Two Auxiliary Shafts in China

by Yong Xue, Tao Han, Tingting Luo, Yansen Wang, Chenyi Zhang, Yingfeng Tan, Tingding Zhou and Weihao Yang

Processes 2025, 13(12), 4078; https://doi.org/10.3390/pr13124078 - 18 Dec 2025

Viewed by 243

Abstract

Vertical shafts are the lifelines of coal mines, serving as critical conduits for resources and personnel. However, the long-term exposure of shaft walls to groundwater erosion significantly reduces their service life and increases the risk of structural failures. This issue is particularly pressing [...] Read more.

Vertical shafts are the lifelines of coal mines, serving as critical conduits for resources and personnel. However, the long-term exposure of shaft walls to groundwater erosion significantly reduces their service life and increases the risk of structural failures. This issue is particularly pressing in Inner Mongolia and Henan Provinces, two of China’s major coal-producing regions, where the challenge of sulfate attack on shafts in deep stratigraphic environments has become a growing concern. This study focused on the corrosion damage observed in these two typical auxiliary shafts: the net diameters and depths of the auxiliary shafts in Shunhe Coal Mine and Mataihao Coal Mine are 6 m and 768.5 m and 9.2 m and 457 m, respectively. The rock section shaft walls in the study range from 5 to 10 m in thickness and are constructed using C40 to C60 grade concrete. To assess the extent of this damage, we conducted a comprehensive analysis of shaft wall samples using water analysis, XRD (X-ray diffraction) analysis, FT-IR (Fourier transform infrared) spectroscopy, and XRF (X-ray fluorescence) analysis. The findings reveal that the identified secondary sulfate reaction products within the shaft wall concrete include calcium sulfate, gypsum, ettringite, and thaumasite. The CaO loss rates in the auxiliary shaft walls of Shunhe Coal Mine and Mataihao Coal Mine are as high as 66% and 47%, respectively. Additionally, the concentrations of SO₃ and MgO in both mines exceed normal levels by up to 5 and 11 times, and 13 and 3 times, respectively. Despite this, severe corrosion is primarily confined to the inner surface of the auxiliary shaft walls, without significant penetration into the deeper shaft structure. The corrosion damage is predominantly concentrated in the shaft sections where the geological environment is characterized by bedrock. This study provides field evidence and laboratory analyses to inform the mitigation of sulfate attack in auxiliary shafts. Full article

(This article belongs to the Section Chemical Processes and Systems)

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17 pages, 2190 KB

Open AccessArticle

The Mechanism of Calcium Leaching from Steel Slag Based on the “Water-Acetic Acid” Two-Step Leaching Route

by Kai Zhang, Qiong Cang, Lijie Peng, Yitong Wang, Shan Zhang, Hongyang Li, Shan Yu, Baojia Hu, Xin Yao, Peipei Du and Yajun Wang

Processes 2025, 13(12), 4077; https://doi.org/10.3390/pr13124077 - 17 Dec 2025

Viewed by 315

Abstract

Converter steel slag (BOFS) contains abundant reactive Ca-bearing minerals and represents a promising feedstock for indirect CO₂ mineralization. However, conventional acid leaching suffers from excessive reagent consumption and low process sustainability. This study develops a “water–acetic acid” two-step leaching strategy aimed at [...] Read more.

Converter steel slag (BOFS) contains abundant reactive Ca-bearing minerals and represents a promising feedstock for indirect CO₂ mineralization. However, conventional acid leaching suffers from excessive reagent consumption and low process sustainability. This study develops a “water–acetic acid” two-step leaching strategy aimed at reducing acid/alkali usage while enhancing calcium recovery. Thermodynamic calculations were performed to elucidate the hydrolysis behaviors of primary phases (f-CaO, C₃S, and β-C₂S) and the stability of secondary minerals in BOFS. The kinetic behavior and dissolution mechanisms of water-leached residues in acetic acid were further analyzed. Parametric experiments were conducted to evaluate the effects of the liquid-to-solid ratio (L/S), temperature, stirring rate, and acid concentration. Results show that the L/S is the dominant factor controlling Ca dissolution in both steps, while temperature exerts opposite effects: lower temperatures favor water leaching due to the exothermic nature of silicate hydrolysis, whereas higher temperatures enhance acid leaching. The proposed two-step route achieves a Ca recovery of 75.9%, representing a 7.6% improvement over direct acid leaching, while lowering acid consumption by ∼90%. This work provides mechanistic insight and process evidence supporting the efficient and sustainable utilization of BOFS for indirect CO₂ mineralization. Full article

(This article belongs to the Special Issue Processes in 2025)

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26 pages, 8084 KB

Open AccessArticle

Multi-Scale Validation of CFD Simulations for Pollutant Dispersion Around Buildings

by Chao Wang, Wei Wang, Jue Qu, Qingli Wang, Xuan Wang and Xinwei Liu

Processes 2025, 13(12), 4076; https://doi.org/10.3390/pr13124076 - 17 Dec 2025

Viewed by 292

Abstract

This study establishes a multi-scale validation framework for Computational Fluid Dynamics (CFD) simulations of building-induced pollutant dispersion, integrating wind tunnel experiments, the CEDVAL benchmark dataset, and field measurements from a thermal power plant that serves as a proxy for nuclear facilities. The RNG [...] Read more.

This study establishes a multi-scale validation framework for Computational Fluid Dynamics (CFD) simulations of building-induced pollutant dispersion, integrating wind tunnel experiments, the CEDVAL benchmark dataset, and field measurements from a thermal power plant that serves as a proxy for nuclear facilities. The RNG k-ε and Large Eddy Simulation (LES) models were evaluated across these validation tiers. Results demonstrate that both models effectively capture key flow characteristics, with LES showing superior performance in predicting roof-level velocity and turbulence intensities. A systematic overestimation of rooftop and leeward concentrations was observed, though predictive accuracy improved with downwind distance (e.g., FAC2 > 0.5). The RNG k-ε model provided the best balance between accuracy and computational efficiency for engineering applications, while LES is recommended for high-fidelity near-field analysis. This work provides validated methodologies for environmental risk assessment in nuclear power planning and emission control strategy development. Full article

(This article belongs to the Section Process Control and Monitoring)

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19 pages, 6757 KB

Open AccessArticle

Visualization Real-Time Monitoring Platform for Ultra-Thin Strip Rolling Mills Based on Digital Twin Technology

by Yang Zhang, Linzhe Hu, Sijing Wang, Yijian Hu, Chaoyue Ji, Chenchen Zhi, Shangju Hu and Lifeng Ma

Processes 2025, 13(12), 4075; https://doi.org/10.3390/pr13124075 - 17 Dec 2025

Viewed by 260

Abstract

The stable operation of a rolling mill is crucial for the extremely thin strip rolling process. Moreover, the performance of the rolling mill directly dictates the quality of the extremely thin strip products. In view of the lack of research on the digital [...] Read more.

The stable operation of a rolling mill is crucial for the extremely thin strip rolling process. Moreover, the performance of the rolling mill directly dictates the quality of the extremely thin strip products. In view of the lack of research on the digital twin model and condition monitoring of twenty-high rolling mills, this paper takes the Sendzimir 280 mm twenty-high reversible rolling mill, an extremely thin strip rolling equipment, as the research object, and conducts digital twin modeling and visualization design for it. First and foremost, finite element analysis and vibration analysis were conducted on the rolling mill, based on which the finite element model and dynamics model of the twenty-high rolling mill were established. Secondly, through a comparison between the vibration data of the rolling mill obtained from simulation and those of the physical rolling mill, the accuracy of the simulation model was validated. Finally, a digital twin model of the rolling mill was constructed based on the finite element model and the dynamics model, and the digital twin model of the rolling mill was built using Unity (version 2022.3.57, Unity Technologies, San Francisco, CA, USA) software to complete the visualization design of the digital twin model. The results show that the digital twin platform of the rolling mill established in this paper achieves a high degree of similarity between the virtual rolling mill and the physical one, which proves the effectiveness of the platform and can meet the actual engineering requirements. Full article

(This article belongs to the Section Process Control and Monitoring)

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18 pages, 1872 KB

Open AccessArticle

Kinetics and Thermodynamics of Ultrasound-Assisted Extraction of Taxanes from Taxus chinensis by Natural Deep Eutectic Solvents

by Ying Guo, Wenna Song, Lingyu Hu, Runbo Liu, Izni Atikah Abd Hamid and Jiaxin Quan

Processes 2025, 13(12), 4074; https://doi.org/10.3390/pr13124074 - 17 Dec 2025

Viewed by 222

Abstract

This study aimed to enhance the extraction efficiency and elucidate the mechanism of ultrasound-assisted extraction (UAE) of taxanes from Taxus chinensis by natural deep eutectic solvents (NADES). The processes of kinetics and thermodynamics were systematically investigated. These extractions adhered to a pseudo-second-order kinetic [...] Read more.

This study aimed to enhance the extraction efficiency and elucidate the mechanism of ultrasound-assisted extraction (UAE) of taxanes from Taxus chinensis by natural deep eutectic solvents (NADES). The processes of kinetics and thermodynamics were systematically investigated. These extractions adhered to a pseudo-second-order kinetic model (R² > 0.972), with intraparticle diffusion identified as the dominant mechanism. Key parameters such as temperature, ultrasonic power, and solid/liquid ratio significantly improved the effective diffusion coefficient (D_e) and mass transfer coefficient (K_T), reaching values of 6.21 × 10⁻⁹ m²/s and 4.14 × 10⁻³ m/s, respectively. A high Biot number (B_i > 59.21) confirmed that internal diffusion is the rate-determining step. Thermodynamic analysis indicated that the process is endothermic (ΔH > 0), irreversible (ΔS > 0), and spontaneous (ΔG < 0). These results elucidate the underlying mechanisms of UAE and establish a foundational framework for its industrial-scale implementation. Full article

(This article belongs to the Special Issue Advances in Green Extraction and Separation Processes)

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18 pages, 16402 KB

Open AccessArticle

Pore-Scale Numerical Simulation of CO₂ Miscible Displacement Behavior in Low-Permeability Oil Reservoirs

by Tingting Li, Suling Wang, Jinbo Li, Daobing Wang, Zhiheng Tao and Yue Wu

Processes 2025, 13(12), 4073; https://doi.org/10.3390/pr13124073 - 17 Dec 2025

Viewed by 222

Abstract

CO₂ miscible flooding provides dual advantages in enhancing oil recovery and facilitating geological sequestration, and has become a key technical approach for developing low-permeability oil reservoirs and carbon emission reduction. The pore-scale flow mechanisms governing CO₂ behavior during miscible flooding are [...] Read more.

CO₂ miscible flooding provides dual advantages in enhancing oil recovery and facilitating geological sequestration, and has become a key technical approach for developing low-permeability oil reservoirs and carbon emission reduction. The pore-scale flow mechanisms governing CO₂ behavior during miscible flooding are crucial for achieving efficient oil recovery and secure geological storage of CO₂. In this study, pore-scale two-phase flow simulations of CO₂ miscible flooding in porous media are performed using a coupled laminar-flow and diluted-species-transport framework. The model captures the effects of diffusion, concentration distribution, and pore structure on the behavior of CO₂ miscible displacement. The results indicate that: (1) during miscible flooding, CO₂ preferentially displaces oil in larger pore throats and subsequently invades smaller throats, significantly improving the mobilization of oil trapped in small pores; (2) increasing the injection velocity accelerates the displacement front and improves oil utilization in dead-end and trailing regions, but a “velocity saturation effect” is observed—when the inject velocity exceeds 0.02 m/s, the displacement pattern stabilizes and further gains in ultimate recovery become limited; (3) higher injected CO₂ concentration accelerates CO₂ accumulation within the pores, enlarges the miscible sweep area, promotes a more uniform concentration field, leads to a smoother displacement front, and reduces high-gradient regions, thereby suppressing local instabilities, and improves displacement efficiency, although its effect on overall recovery remains modest; (4) CO₂ dynamic viscosity strongly influences flow stability: low-viscosity conditions promote viscous fingering and severe local bypassing, whereas higher viscosity stabilizes flow but increases injection pressure drop and energy consumption, indicating a necessary trade-off between flow stability and operational efficiency. Full article

(This article belongs to the Special Issue Hydrogen–Carbon Storage Technology and Optimization)

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16 pages, 1280 KB

Open AccessFeature PaperArticle

Solubility Prediction in N₂O + Ionic Liquid Systems Using Artificial Neural Networks Including Thermodynamically Consistent Data

by Elías N. Fierro, Ariana S. Muñoz, Patricio I. Cerda and Claudio A. Faúndez

Processes 2025, 13(12), 4072; https://doi.org/10.3390/pr13124072 - 17 Dec 2025

Viewed by 199

Abstract

The solubilities of 498 datasets of N₂O and ionic liquid systems were predicted using a multilayer perceptron. The data used to train the artificial neural network was subjected to the Gibbs–Duhem test to analyze their thermodynamic consistency. The Peng–Robinson cubic equation [...] Read more.

The solubilities of 498 datasets of N₂O and ionic liquid systems were predicted using a multilayer perceptron. The data used to train the artificial neural network was subjected to the Gibbs–Duhem test to analyze their thermodynamic consistency. The Peng–Robinson cubic equation of state, combined with the Kwak–Mansoori mixing rule, was used as the thermodynamic model to implement the test. The analysis indicated that 71.9% of the data were declared thermodynamically inconsistent. The ability of artificial neural networks (ANNs) to predict the solubility of these systems using experimental datasets that do not satisfy the thermodynamic consistency criteria based on the Gibbs–Duhem equation was studied. The multilayer perceptron model achieved an average absolute deviation of 1.81% and a maximum individual deviation of 7.56%. These results highlight the potential of ANNs as robust predictive tools even when the available data do not fully satisfy thermodynamic consistency criteria. Full article

(This article belongs to the Special Issue Applications of Artificial Intelligence Technologies in Energy, Manufacturing and Automatic Control Processes)

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29 pages, 1510 KB

Open AccessReview

State of the Art of Fracture Assessment Method on High-Strength Oil and Gas Pipeline Girth Weld

by Xiaoben Liu, Dong Zhang, Jiaqing Zhang, Qingshan Feng, Zhongjia An and Hong Zhang

Processes 2025, 13(12), 4071; https://doi.org/10.3390/pr13124071 - 17 Dec 2025

Viewed by 192

Abstract

High-strength oil and gas pipeline girth welds exhibit significant material and geometric discontinuities with high susceptibility to defects, making them a critical weak link in oil and gas pipelines. Researching the fracture assessment technology pipeline’s girth welds is essential for enhancing the pipeline’s [...] Read more.

High-strength oil and gas pipeline girth welds exhibit significant material and geometric discontinuities with high susceptibility to defects, making them a critical weak link in oil and gas pipelines. Researching the fracture assessment technology pipeline’s girth welds is essential for enhancing the pipeline’s inherent safety and protection levels. Key issues and research progress related to fracture assessment technology are systematically addressed from the perspectives of pipeline fracture behavior and fracture assessment methods in this paper. The core focus of fracture behavior research is determining the crack driving force at the girth weld and the material’s fracture toughness. Fracture assessment methods include failure assessment diagrams and limited tensile strain capacity models. The development of single-parameter and multi-parameter fracture mechanics theories in establishing the relationship between in-plane and out-of-plane constraints and material fracture toughness is reviewed. Four commonly used methods for calculating crack driving forces in pipelines are presented. Moreover, the usage scenarios of various failure assessment diagrams in pipeline fracture assessment are analyzed. A comparison of the parameter ranges and applicability of commonly used international tensile strain capacity models is also provided. The paper highlights existing issues in current research on the fracture assessment of high-strength pipelines and outlines directions for further study. Lastly, this paper aims to provide theoretical and technical support for improving the inherent safety level of high-strength pipeline girth welds. Full article

(This article belongs to the Special Issue Design, Inspection and Repair of Oil and Gas Pipeline)

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12 pages, 2737 KB

Open AccessFeature PaperArticle

Polymer Solar Cells Using Au-Incorporated V₂O_x as the Hole Transport Layer

by Yu-Shyan Lin and Shiun-Ming Shiu

Processes 2025, 13(12), 4070; https://doi.org/10.3390/pr13124070 - 17 Dec 2025

Viewed by 208

Abstract

This study investigates the feasibility of adding gold nanoparticles (Au-NPs) to vanadium oxide (V₂O_x) serving the hole transport layer (HTL) material oin polymer solar cells to enhance cell performance. The first part of this study used Poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) as [...] Read more.

This study investigates the feasibility of adding gold nanoparticles (Au-NPs) to vanadium oxide (V₂O_x) serving the hole transport layer (HTL) material oin polymer solar cells to enhance cell performance. The first part of this study used Poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) as a baseline and optimized the parameters of this HTL material. Then, the V₂O_x was substituted as the HTL material, and its parameters were optimized again. The second part involved incorporating an aqueous solution of gold nanoparticles (Au-NPs) with an average particle size of approximately 80 nm into V₂O_x. Due to the excitation of localized surface plasmon resonance (LSPR) by Au-NPs, the addition of Au-NPs to the V₂O_x layer can enhance the absorption efficiency of the P3HT:PCBM blended film. Therefore, compared with V₂O_x alone, the solar cells with Au-NPs incorporated into the V₂O₅ hole transport layer demonstrate improved power conversion efficiency (PCE). Full article

(This article belongs to the Special Issue Development and Characterization of Advanced Polymer Nanocomposites)

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22 pages, 3868 KB

Open AccessArticle

Research on the Optimization of Mining Structure Parameters Based on the Pressure Arch Theory

by Weile Geng, Libing Zhen, Tihua Zhang, Shengli Guo, Gun Huang and Yangtao Xiong

Processes 2025, 13(12), 4069; https://doi.org/10.3390/pr13124069 - 17 Dec 2025

Viewed by 205

Abstract

The arching effect of surrounding rock pressure is critical for ground pressure control in mining areas. Taking a stope in Malipo tungsten mine as the engineering background, this study optimizes stope structural parameters based on the arching pressure theory. Analysis of the stope [...] Read more.

The arching effect of surrounding rock pressure is critical for ground pressure control in mining areas. Taking a stope in Malipo tungsten mine as the engineering background, this study optimizes stope structural parameters based on the arching pressure theory. Analysis of the stope pressure arch shape equation shows that the pressure arch shape is mainly determined by the lateral pressure coefficient (λ) and stope span (L), while the actual load on pillars equals the weight of rock mass within the overlying pressure arch shell. Pillar loads differ at various stope locations. Combined with the pillar area bearing theory, the rock weight supported by pillars at different stope positions under the arching pressure theory was determined, and a load calculation formula for pillars at various locations was derived. A stope pillar size optimization method was also proposed, which overcomes the defect of excessively large pillar sizes caused by the pillar area bearing theory. It ensures pillar stability during mining while improving ore recovery rates. Taking an existing 830 m-deep stope in the tungsten mine as an example, the optimization method based on the arching pressure theory determined the actual required widths of pillars at different locations. This increased the ore recovery rate from the original 67.56% to 69.47% (an increase of 1.91%). This study provides a reference for the reasonable setting of pillar sizes. Full article

(This article belongs to the Section Energy Systems)

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19 pages, 4696 KB

Open AccessArticle

Research on the Prediction of Cement Precalciner Outlet Temperature Based on a TCN-BiLSTM Hybrid Neural Network

by Mengjie Deng and Hongtao Kao

Processes 2025, 13(12), 4068; https://doi.org/10.3390/pr13124068 - 16 Dec 2025

Viewed by 213

Abstract

As the global cement industry moves toward energy efficiency and intelligent manufacturing, refined control of key processes like precalciner outlet temperature is critical for improving energy use and product quality. The precalciner’s outlet temperature directly affects clinker calcination quality and heat consumption, so [...] Read more.

As the global cement industry moves toward energy efficiency and intelligent manufacturing, refined control of key processes like precalciner outlet temperature is critical for improving energy use and product quality. The precalciner’s outlet temperature directly affects clinker calcination quality and heat consumption, so developing a high-accuracy prediction model is essential to shift from empirical to intelligent control. This study proposes a TCN-BiLSTM hybrid neural network model for the accurate prediction and regulation of the outlet temperature of the decomposition furnace. Based on actual operational data from a cement plant in Guangxi, the Spearman correlation coefficient method is employed to select feature variables significantly correlated with the outlet temperature, including kiln rotation speed, high-temperature fan speed, temperature A at the middle-lower part of the decomposition furnace, temperature B of the discharge from the five-stage cyclone, exhaust fan speed, and tertiary air temperature of the decomposition furnace. This method effectively reduces feature dimensionality while enhancing the prediction accuracy of the model. All selected feature variables are normalized and used as input data for the model. Finally, comparative experiments with RNN, LSTM, BiLSTM, TCN, and TCN-LSTM models are performed. The experimental results indicate that the TCN-BiLSTM model achieves the best performance across major evaluation metrics, with a Mean Relative Error (MRE) as low as 0.91%, representing an average reduction of over 1.1% compared to other benchmark models, thereby demonstrating the highest prediction accuracy and robustness. This approach provides high-quality predictive inputs for constructing intelligent control systems, thereby facilitating the advancement of cement production toward intelligent, green, and high-efficiency development. Full article

(This article belongs to the Section Chemical Processes and Systems)

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18 pages, 11320 KB

Open AccessArticle

Grain Size-Controlled Mechanical Behavior and Failure Characteristics of Reservoir Sandstones

by Ronghui Yan, Sanjun Liu, Xiaogang Zhang, Gaoren Li, Xu Yang, Wancai Nie, Jibin Zhong and Gao Li

Processes 2025, 13(12), 4067; https://doi.org/10.3390/pr13124067 - 16 Dec 2025

Viewed by 189

Abstract

Understanding the deformation–failure process of sandstone is essential for energy extraction and stability assessment. Here, laboratory mechanical tests and discrete element simulations are combined to resolve how grain size controls deformation, cracking, and failure. Under uniaxial compression, fine-grained sandstone shows the highest strength [...] Read more.

Understanding the deformation–failure process of sandstone is essential for energy extraction and stability assessment. Here, laboratory mechanical tests and discrete element simulations are combined to resolve how grain size controls deformation, cracking, and failure. Under uniaxial compression, fine-grained sandstone shows the highest strength (60.85–65.37 MPa) yet undergoes an abrupt brittle transition to axial splitting at a small peak axial strain of 0.41–0.42%; coarse-grained sandstone exhibits lower strength (26.94–28.67 MPa) but fails at peak axial strains of 0.44–0.53%, on average about 17% higher than those of FGS, indicating enhanced ductility; medium-grained sandstone lies in between in both strength (41.15–43.79 MPa) and peak axial strain (0.42–0.45%). With confining pressure, fine- and medium-grained sandstones display pronounced process evolution toward ductility, whereas coarse-grained sandstone shows limited pressure sensitivity. DEM results link microcrack evolution with the macroscopic response: under uniaxial loading, fine-grained sandstone is dominated by intergranular tensile cracking, while coarse-grained sandstone includes more intragranular cracks. Increasing confinement controls the cracking process, shifting fine- and medium-grained rocks from intergranular tension to mixed intragranular tension–shear, thereby enhancing ductility; in contrast, coarse-grained sandstone at high confinement localizes shear bands and remains relatively brittle. Normalized microcrack aperture distributions and fragment identification capture a continuous damage accumulation process from micro to macro scales. These process-based insights clarify the controllability of failure modes via grain size and confinement and offer optimization-oriented guidance for design parameters that mitigate splitting and promote stable deformation in deep sandstone reservoirs and underground excavations. Full article

(This article belongs to the Special Issue Advances in Evaluation, Development, Simulation and Utilization of Geo-Energy Resources and Underground Space)

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27 pages, 9713 KB

Open AccessArticle

Hybrid Droop-Enhanced Virtual Impedance Control for Circulating Current Mitigation and Power Balancing in Parallel SiC Three-Phase Inverters

by Chaoyang Zhang, Zhengcong Du, Yipu Xu, Yi Shi and Fuyuan You

Processes 2025, 13(12), 4066; https://doi.org/10.3390/pr13124066 - 16 Dec 2025

Viewed by 235

Abstract

Silicon carbide (SiC) three-phase converters are widely adopted in parallel power distribution systems for their high efficiency, yet their performance is challenged by high switching frequency and communication constraints. For the parallel inverter system, problems such as uneven power distribution and circulating current [...] Read more.

Silicon carbide (SiC) three-phase converters are widely adopted in parallel power distribution systems for their high efficiency, yet their performance is challenged by high switching frequency and communication constraints. For the parallel inverter system, problems such as uneven power distribution and circulating current may occur. Therefore, the droop control method was proposed. The droop control method is limited in precise power sharing and circulating current mitigation. To address these issues in the communication-free parallel inverter system, a hybrid droop-enhanced virtual impedance method is proposed. The methodology integrates droop characteristics with frequency-selective virtual impedance compensation, enabling concurrent optimization of power sharing and circulating current suppression. Through simulation, the droop control method and the improved droop control method were compared and analyzed. Finally, the effectiveness of the improved droop control method was verified through experiments. Full article

(This article belongs to the Special Issue Design, Control, Modeling and Simulation of Energy Converters)

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16 pages, 2727 KB

Open AccessFeature PaperArticle

γ-Valerolactone Pulping as a Sustainable Route to Micro- and Nanofibrillated Cellulose from Sugarcane Bagasse

by Roxana Giselle González, Nanci Ehman, Fernando Esteban Felissia, María Evangelina Vallejos and María Cristina Area

Processes 2025, 13(12), 4065; https://doi.org/10.3390/pr13124065 - 16 Dec 2025

Viewed by 258

Abstract

The study explores γ-valerolactone (GVL) pulps as a sustainable approach to producing microfibrillated (MFC) and nanofibrillated (NFC) cellulose from sugarcane bagasse, a widely available agro-industrial by-product. Pulp was obtained by acid-catalyzed organosolv delignification with a GVL–water system. MFC was generated through a simple [...] Read more.

The study explores γ-valerolactone (GVL) pulps as a sustainable approach to producing microfibrillated (MFC) and nanofibrillated (NFC) cellulose from sugarcane bagasse, a widely available agro-industrial by-product. Pulp was obtained by acid-catalyzed organosolv delignification with a GVL–water system. MFC was generated through a simple disc refiner, while NFC was produced by TEMPO-mediated oxidation followed by mechanical treatment in a colloidal mill. NFC and MFC produced using the same methodology from a commercial sugarcane totally chlorine-free (TCF) soda–anthraquinone (soda–AQ) pulp served as a reference. Structural and physicochemical characterization involved optical transmittance, turbidity, conductimetry, X-ray diffraction, viscosity, FTIR, carboxyl content, cationic demand, degree of polymerization, and morphology by scanning electron microscopy (SEM). Results demonstrated that xylan and residual lignin contents influenced MFC formation, and the NFC showed properties comparable to those of the commercial pulp with fewer fibrillation passes. The study highlights GVL pulping as a greener, efficient alternative to conventional processes, opening new pathways for producing viscosity-controlled nanocellulose suspensions suitable for advanced applications. Full article

(This article belongs to the Special Issue Sustainable Nanocellulose Processes Toward New Products and Markets)

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33 pages, 22741 KB

Open AccessReview

Microscopic Deterioration Mechanism and Different Reinforcement Methods of Concrete Under Freeze–Thaw Environment: A Review

by Wenlong Niu, Tiesheng Dou, Meng Li and Shifa Xia

Processes 2025, 13(12), 4064; https://doi.org/10.3390/pr13124064 - 16 Dec 2025

Viewed by 245

Abstract

In cold regions, concrete is inevitably subjected to freeze–thaw (F–T) damage, where repeated water–ice phase transitions progressively erode its microstructure and shorten its service life. Compared with the abundant research focusing on macroscopic performance degradation, systematic summaries addressing the microstructural evolution of pores, [...] Read more.

In cold regions, concrete is inevitably subjected to freeze–thaw (F–T) damage, where repeated water–ice phase transitions progressively erode its microstructure and shorten its service life. Compared with the abundant research focusing on macroscopic performance degradation, systematic summaries addressing the microstructural evolution of pores, cracks, and the interfacial transition zone (ITZ), as well as corresponding prevention measures, remain limited. This paper reviews studies from 2013 to 2025, outlining key deterioration mechanisms under F–T action, including pore coarsening, ITZ weakening, and microcrack propagation. Four frost resistance enhancement strategies are compared: introducing stable microbubbles, refining the pore structure with pozzolanic or nano admixtures, bridging cracks with fibers, and applying hydrophobic treatments to block water ingress. The findings indicate that combining multiple measures yields superior frost resistance. By integrating microstructural observations with engineering improvement approaches, this review provides a holistic perspective for the design of durable concrete in cold regions and highlights the need for further research on multi-factor coupling mechanisms, optimization of composite admixture systems, and the functional mechanisms of novel nanomaterials. Full article

(This article belongs to the Section Materials Processes)

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