Processes

29 pages, 15319 KB

Open AccessArticle

Analysis and Optimization Research on the Failure Mechanism of the Sealing Structure of the High-Pressure Casing Hanger

by Yaoming Zhang, Xuliang Zhang, Fudong Liu, Pengcheng Wang, Jianfei Wang, Fei Zhan, Rui Ma and Yang Liu

Processes 2026, 14(6), 1028; https://doi.org/10.3390/pr14061028 - 23 Mar 2026

Viewed by 484

Abstract

In order to design a new type of long-life and reliable casing hanger, this paper studied the failure mechanisms of the rubber sealing structures of the slip hanger and the mandrel hanger. Through tensile and compressive tests, the tests and analyses of different [...] Read more.

In order to design a new type of long-life and reliable casing hanger, this paper studied the failure mechanisms of the rubber sealing structures of the slip hanger and the mandrel hanger. Through tensile and compressive tests, the tests and analyses of different rubber structures were completed, data fitting was carried out, and the constitutive relationship of the rubber material was obtained. A superior constitutive model was applied to the sealing materials of the hanger. Numerical calculations were used to obtain the strength and sealing performance variation laws of the rubber sealing components with different structures, and the reasons for the failure of the conventional hanger were found. The results show that the rubber components and the ball-shaped metal sealing components will lose their elastic deformation under high-pressure and large-load conditions, and the reliability will decrease. Finally, a new type of metal sealing structure was designed. Compared with the previous metal sealing structures, this paper conducts a more in-depth and detailed study, and further presents the superiority of metal sealing in terms of structural dimensions and working principles. Experiments were conducted, and the results showed that this sealing structure can meet the usage requirements of the casing hanger with large loads and high pressure. The research results provide theoretical and application guidance for the design of long-life and reliable performance hanger sealing structures. Full article

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

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31 pages, 1355 KB

Open AccessArticle

A Closed-Loop PX–ISO Framework for Staged Day-Ahead Energy and Ancillary Clearing in Power Markets

by Lei Yu, Lingling An, Xiaomei Lin, Kai-Hung Lu and Hongqing Zheng

Processes 2026, 14(6), 1027; https://doi.org/10.3390/pr14061027 - 23 Mar 2026

Viewed by 421

Abstract

As modern power markets integrate more renewable generation, day-ahead energy clearing remains the central procurement step, while flexibility products are procured to ensure that the cleared energy schedule can be operated securely. This paper proposes a closed-loop framework linking the Power Exchange (PX) [...] Read more.

As modern power markets integrate more renewable generation, day-ahead energy clearing remains the central procurement step, while flexibility products are procured to ensure that the cleared energy schedule can be operated securely. This paper proposes a closed-loop framework linking the Power Exchange (PX) and the Independent System Operator (ISO) to bridge energy-market settlement and network-feasible operation. The PX performs staged day-ahead clearing with energy settled first, followed by aAutomatic generation control (AGC) and spinning reserve (SR) procured from the residual headroom of committed (energy-awarded) units. The ISO then validates the cleared schedule using an equivalent current injection (ECI)-based screening. This paper uses a single-period (single-hour) IEEE 30-bus case setting; multi-period scheduling and intertemporal constraints are not modeled. When congestion is detected, power-flow tracing identifies the main contributors and guides a minimal-change redispatch. The ISO-feasible dispatch is then sent back to the PX for re-clearing, aligning prices and welfare with an executable operating point. The resulting nonconvex clearing problems with valve-point effects and prohibited operating zones are solved by Artificial Protozoa Optimizer with Social Learning (APO–SL) and evaluated against representative metaheuristic baselines. IEEE 30-bus studies show that off-peak and average-load cases pass ISO screening directly, whereas the peak case tightens reserve headroom (SR capped at 39.08 MW) and triggers congestion. After ISO feedback and energy re-clearing, line loadings return within limits. The ISO-feasible dispatch changes the marginal accepted offer and lifts the MCP (3.73 → 4.38 $/MWh). The welfare value reported here follows the paper’s settlement-based definition (purchase total minus accepted offer cost), and it increases accordingly (113.77 → 190.17 $/h). Full article

(This article belongs to the Section Energy Systems)

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15 pages, 2907 KB

Open AccessArticle

Mechanistic Analysis of In Situ Hydrogen Production During Heavy Oil Gasification Based on Numerical Simulations

by Weidong Meng, Haijuan Wang, Chunsheng Yu, Yuhang Liu and Wenqing Wang

Processes 2026, 14(6), 1026; https://doi.org/10.3390/pr14061026 - 23 Mar 2026

Cited by 1 | Viewed by 380

Abstract

In situ hydrogen generation can extend in situ combustion (ISC) by converting part of the heavy oil in place into H₂-containing gas while allowing part of the carbonaceous products to remain in the reservoir. To clarify how operating conditions affect hydrogen [...] Read more.

In situ hydrogen generation can extend in situ combustion (ISC) by converting part of the heavy oil in place into H₂-containing gas while allowing part of the carbonaceous products to remain in the reservoir. To clarify how operating conditions affect hydrogen behavior, this study recalibrated key Arrhenius parameters in a pseudo-component kinetic network through least-squares-guided manual history matching against high-temperature/high-pressure (HTHP) reactor data obtained under three gas atmospheres (air, N₂, and CO₂). Model performance was evaluated through a direct comparison between raw simulator predictions and measured gas compositions using parity plots with a 1:1 reference line and residual-based statistics calculated from the simulated values rather than from regression-fitted values. The calibrated model was then used to compare hydrogen responses over 150–425 °C, 4–8 MPa, and 0.25–10 days. Within the tested range, three temperature regimes were identified: initiation (150–250 °C), pyrolysis-controlled (250–325 °C), and high-yield (325–425 °C). Oxygen and CO₂ generally reduced net hydrogen accumulation through competing pathways, whereas an inert N₂ background produced the highest H₂ fraction, reaching 28.6 vol% at 425 °C and 6 MPa after 10 days. These results provide a reactor-scale basis for selecting favorable operating windows and for subsequent reservoir-scale evaluation of in situ hydrogen generation under ISC conditions. Full article

(This article belongs to the Topic Enhanced Oil Recovery Technologies, 4th Edition)

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21 pages, 8574 KB

Open AccessArticle

Predicting Non-Darcy Inertial Resistance from Darcy Regime Characterization and Pore-Scale Structural Descriptors

by Quanyu Pan, Linsong Cheng, Pin Jia, Renyi Cao and Peiyu Li

Processes 2026, 14(6), 1025; https://doi.org/10.3390/pr14061025 - 23 Mar 2026

Viewed by 397

Abstract

High-velocity fluid flow in porous media frequently exhibits non-Darcy behavior, where inertial losses lead to nonlinear pressure gradient velocity behavior. Predicting the Forchheimer coefficient β remains challenging because β varies sensitively with pore geometry and is often not constrained by porosity and permeability [...] Read more.

High-velocity fluid flow in porous media frequently exhibits non-Darcy behavior, where inertial losses lead to nonlinear pressure gradient velocity behavior. Predicting the Forchheimer coefficient β remains challenging because β varies sensitively with pore geometry and is often not constrained by porosity and permeability alone. This study develops a structure-based method to estimate β using intrinsic descriptors obtained from the Darcy regime flow characterization and image-based geometry analysis. A set of two-dimensional granular porous media was generated with controlled variations in porosity, particle size distribution, and grain size variability. Single phase simulations are simulated with a body-force multiple-relaxation-time lattice Boltzmann method. The transition from Darcy flow to non-Darcy flow is identified from the velocity and pressure gradient response, and β is determined by fitting the inertial flow regime. Two tortuosity responses were observed. In uniform media, hydraulic tortuosity remained nearly constant in the Darcy regime and then gradually decreased. In disordered media, hydraulic tortuosity first increased with the onset of recirculation and then decreased as dominant flow paths became stable. Based on these results, a dimensionless inertial factor was correlated with porosity, intrinsic hydraulic tortuosity, and a pore structure index derived from specific surface area and hydraulic pore size. The resulting model predicts β from permeability and structural descriptors. The resulting correlation provides β estimates from Darcy permeability and geometry descriptors. Validation with quasi-two-dimensional microfluidic pillar array data showed that the model captured both the magnitude and relative ordering of β for the tested geometries. The proposed framework should be regarded as a proof of concept for idealized granular porous media and quasi-two-dimensional structured systems. Full article

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

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21 pages, 446 KB

Open AccessArticle

Resilience-Constrained Low-Carbon Dispatch of Industrial Parks with Storage and Quantum Acceleration

by Wenfang Li, Chen Li, Xuemei Zhang, Shuai Xu, Yaqing Yue and Haijing Zhang

Processes 2026, 14(6), 1024; https://doi.org/10.3390/pr14061024 - 23 Mar 2026

Viewed by 301

Abstract

Carbon-neutral industrial parks require large consumers, such as data centers, to balance low-carbon operation and service reliability. This paper proposes a resilience-constrained stochastic dispatch framework for a data-center virtual power plant (VPP) with renewable generation, short-duration batteries, and long-duration storage units. The dispatch [...] Read more.

Carbon-neutral industrial parks require large consumers, such as data centers, to balance low-carbon operation and service reliability. This paper proposes a resilience-constrained stochastic dispatch framework for a data-center virtual power plant (VPP) with renewable generation, short-duration batteries, and long-duration storage units. The dispatch is formulated as a two-stage stochastic program with normal and outage scenarios. To solve the resulting large mixed-integer problem, we develop a hybrid quantum–classical L-shaped method: the integer master is solved heuristically by quantum annealing, while scenario subproblems are solved exactly by classical optimization. In a case study based on real-world industrial-park data, the proposed storage strategy eliminates critical load shedding for the tested 6 h outage scenarios with a 3.7% increase in expected daily cost. The QA-driven method reaches the same best-known objective as the classical baseline with an empirical 1.36× runtime speedup. Full article

(This article belongs to the Special Issue Evaluation, Decision-Making and Market Simulation of a New Type of Power System, 2nd Edition)

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19 pages, 2510 KB

Open AccessArticle

Comparison of Granular and Pellet Olive Stone-Based Activated Carbon in Adsorption-Based Post-Combustion CO₂ Capture

by Meriem Moussa, Covadonga Pevida, Nausika Querejeta and Abdelmottaleb Ouederni

Processes 2026, 14(6), 1023; https://doi.org/10.3390/pr14061023 - 23 Mar 2026

Viewed by 447

Abstract

In the present study, we evaluate the CO₂ uptake capacities of four activated carbons (ACs) obtained from olive stones. Two of the samples were generated using a chemical process utilizing phosphoric acid, thereafter undergoing carbonization in a nitrogen steam, yielding both granular [...] Read more.

In the present study, we evaluate the CO₂ uptake capacities of four activated carbons (ACs) obtained from olive stones. Two of the samples were generated using a chemical process utilizing phosphoric acid, thereafter undergoing carbonization in a nitrogen steam, yielding both granular and pellet forms, designated CH-ACG-410 and CH-ACP-410, respectively. The third sample, labeled CO-ACG-390, was produced by carbonization under a steam-nitrogen flow, while the fourth sample, designated PH-ACG-850, was prepared by a physical process involving water vapor at 850 °C. The carbon materials obtained in granular and pellet form were subjected to textural characterization using N₂ and CO₂ adsorption isotherms at 77 K and 273 K, respectively. Additionally, surface chemistry was analyzed using FTIR, Boehm titration, and TPD-MS. The materials were also assessed for CO₂ adsorption in a binary mixture consisting of 10% CO₂ and 90% N₂ at two temperatures, 25 and 50 °C. The results demonstrated that all prepared adsorbents exhibited competitive CO₂ capture performance, with the CH-ACP-410 sample (pellet form), showing the highest adsorption capacities, achieving approximately 4.6 wt. % at 25 °C and 2.2 wt. % at 50 °C. This superior behavior can be attributed to the conditioning methods applied to this material, which significantly influenced its textural properties and, consequently, its CO₂ adsorption capability. Full article

(This article belongs to the Special Issue Innovations in CO₂ and Hydrogen Storage: Emerging Technologies and Applications)

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15 pages, 1195 KB

Open AccessArticle

Emerging Spectrophotonic Technologies to Predict the Maturation Time of Swiss-Type Cheese: Dielectric Spectroscopy vs. Portable NIR

by Tony Chuquizuta, Yuleysi Cieza, Joe González, Matthews Juarez, Marta Castro-Giraldez, Pedro J. Fito and Wilson Castro

Processes 2026, 14(6), 1022; https://doi.org/10.3390/pr14061022 - 23 Mar 2026

Viewed by 450

Abstract

The cheese maturation process involves complex physicochemical and structural changes that directly influence its final quality and consumer acceptance. The development of non-destructive and rapid analytical techniques is therefore essential for monitoring these changes and optimizing quality control strategies. This study evaluated the [...] Read more.

The cheese maturation process involves complex physicochemical and structural changes that directly influence its final quality and consumer acceptance. The development of non-destructive and rapid analytical techniques is therefore essential for monitoring these changes and optimizing quality control strategies. This study evaluated the potential of dielectric spectroscopy and near-infrared (NIR) spectroscopy as tools to predict properties associated with the quality of Swiss-type cheese during the maturation process. The cheese samples were matured for 60 days, and NIR profiles (900–1700 nm), dielectric profiles (40¹–10⁶ Hz) and physical characteristics (color and texture) were obtained every 15 days. Based on these data, models were developed to predict the maturation time (days) and physical properties using partial least squares regression (PLSR). The performance of the model was evaluated using the determination coefficient (

R^{2}

) and the root mean square error (RMSE). The results showed that dielectric spectroscopy provided a better fit for all the parameters evaluated (

R_{day}^{2} = 0.999

,

R_{L^{*}}^{2} = 0.912

,

R_{a^{*}}^{2} = 0.983

,

R_{b^{*}}^{2} = 0.982

, and

R_{firmness}^{2} = 0.625

), with prediction errors of

{RMSE}_{day} = 0.219

,

{RMSE}_{L^{*}} = 1.184

,

{RMSE}_{a^{*}} = 0.163

,

{RMSE}_{b^{*}} = 0.308

, and

{RMSE}_{firmness} = 91.094

. In conclusion, dielectric spectroscopy combined with PLSR showed slightly superior performance to predict maturation time and physical changes in Swiss-type cheese. Full article

(This article belongs to the Special Issue Innovative Food Processing and Quality Control)

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26 pages, 8282 KB

Open AccessArticle

Numerical Analysis of Composite Wind Turbine Blade Dynamics Under Shutdown Fault Scenarios

by Tianyi Wang, Zhihong Chen and Jiangfan Zhang

Processes 2026, 14(6), 1021; https://doi.org/10.3390/pr14061021 - 23 Mar 2026

Viewed by 445

Abstract

To ensure the safety and structural integrity of composite flexible blades under strong winds, this study investigates the extreme aeroelastic responses of the IEA 15 MW wind turbine blade during an emergency shutdown with pitch system faults. Existing studies often rely on simplified [...] Read more.

To ensure the safety and structural integrity of composite flexible blades under strong winds, this study investigates the extreme aeroelastic responses of the IEA 15 MW wind turbine blade during an emergency shutdown with pitch system faults. Existing studies often rely on simplified models or one-way coupling; we adopt a bidirectional computational fluid dynamics–finite element method (CFD–FEM) fluid–structure interaction (FSI) framework to examine how wind speed and pitch system faults affect aerodynamic loads, displacement responses, and structural stresses when the blade is shut down in a parked-upwind condition. The results reveal that, under the no-pitch condition, the blade experiences extreme loading, with thrust being approximately 15 times higher and the peak stress being 8.6 times that of the pitch condition. Furthermore, a high frequency of 1.969 Hz emerges, significantly increasing the risk of aeroelastic instability as the wind speed increases or under the no-pitch condition. A stress analysis identified that high stress is mainly located in the main spar region, with the peak stress location shifting closer to the blade root under the no-pitch condition. This study highlights the potential risks of composite flexible blades during shutdowns and provides a reference for structural safety design and targeted monitoring. Full article

(This article belongs to the Special Issue Fiber-Reinforced Composites: Latest Advances and Interesting Research)

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21 pages, 31208 KB

Open AccessArticle

Simulation and Performance Analysis of a Plateau-Adapted Five-Bed Portable Vacuum Pressure Swing Adsorption Oxygen Production System

by Ping Wu and Jianjun Li

Processes 2026, 14(6), 1020; https://doi.org/10.3390/pr14061020 - 22 Mar 2026

Viewed by 438

Abstract

To address the decline in oxygen production capacity and the increase in specific energy consumption of portable vacuum pressure swing adsorption (VPSA) oxygen systems under high-altitude low-pressure conditions, a rotary-valve integrated VPSA numerical model based on a five-bed, ten-step cycle was established in [...] Read more.

To address the decline in oxygen production capacity and the increase in specific energy consumption of portable vacuum pressure swing adsorption (VPSA) oxygen systems under high-altitude low-pressure conditions, a rotary-valve integrated VPSA numerical model based on a five-bed, ten-step cycle was established in this study and analyzed on the Aspen Adsorption platform. The results show that, under a trade-off between oxygen purity and recovery, an oxygen purity of 93.1% and an oxygen recovery of 27.8% can be achieved when the purge-valve flow coefficient is

6.67 \times 10^{- 5} kmol / (h \cdot bar)

. When the product-valve flow coefficient is

0.028 mol \cdot s^{- 1} \cdot {MPa}^{- 1}

and the altitude increases from 3000 m to 4500 m, the oxygen production rate decreases by about 22%, while the specific energy consumption increases by about 32.4%. This indicates that the reduction in oxygen partial pressure has a significant effect on the separation driving force. As the product-valve flow coefficient increases from

0.010

to

0.037 mol \cdot s^{- 1} \cdot {MPa}^{- 1}

, the oxygen production rate continuously increases and the specific energy consumption decreases at all altitude conditions. At an altitude of 3000 m, for example, the oxygen production rate increases from

0.12 m^{3} \cdot h^{- 1}

to

0.176 m^{3} \cdot h^{- 1}

, while the specific energy consumption decreases from

3.58 MJ \cdot m^{- 3}

to

2.93 MJ \cdot m^{- 3}

. The effect of feed flow rate on specific energy consumption shows a trend of first decreasing and then increasing. The minimum energy consumption is obtained in the range of 18–

20 L / \min

. These results provide a theoretical basis for parameter matching and energy-efficiency optimization of multi-bed rotary-valve VPSA systems under high-altitude conditions. Full article

(This article belongs to the Section Separation Processes)

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30 pages, 2519 KB

Open AccessArticle

Super-Twisting-Based Online Learning in High-Order Neural Networks for Robust Backstepping Control of DC Motors Under Uncertainty

by Ivan R. Urbina Leos, Jesus A. Medrano Hermosillo, Abraham E. Rodriguez Mata, Francisco R. Lopez-Estrada, Oscar J. Suarez and Alma Alejandra Luna-Gómez

Processes 2026, 14(6), 1019; https://doi.org/10.3390/pr14061019 - 22 Mar 2026

Viewed by 483

Abstract

This paper addresses the speed control problem of a DC motor in the presence of nonlinearities, disturbances, and unmodeled dynamics by proposing a neural backstepping control scheme based on a Recurrent High-Order Neural Network (RHONN). The proposed RHONN serves as an online approximator [...] Read more.

This paper addresses the speed control problem of a DC motor in the presence of nonlinearities, disturbances, and unmodeled dynamics by proposing a neural backstepping control scheme based on a Recurrent High-Order Neural Network (RHONN). The proposed RHONN serves as an online approximator to compensate for uncertain nonlinear dynamics in a PD-based backstepping controller, enabling the system to handle disturbances, modeling errors, and unmodeled dynamics. Instead of relying on the traditional Extended Kalman Filter (EKF) for RHONN weight adaptation, the neural parameters are updated online using a Super-Twisting Algorithm (STA). As a result, the proposed STA-based learning law provides a simpler and robust covariance-free adaptation mechanism with practical finite-time convergence properties, making it suitable for real-time embedded implementations. The proposed method was evaluated through numerical simulations and implemented on an embedded microcontroller to assess its real-time performance. Simulation results show reductions between 0.04% and 2.04% in steady-state and integral error metrics compared with a tuned PD controller, and improvements up to 25.66% and 23.82% over LQR and MPC in the IMSE index. Experimental results demonstrate good tracking performance, robustness under varying load conditions, and low computational requirements, confirming the practical feasibility. Full article

(This article belongs to the Special Issue Advances in Electrical Drive Control Methodologies)

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20 pages, 266 KB

Open AccessFeature PaperEditor’s ChoiceArticle

The Influence of Traditional and Industrial Smoking Technologies on the Physicochemical Properties, Color, and Texture of Traditional Meat Products

by Krešimir Mastanjević, Leona Puljić, Silvio Halt, Brankica Kartalović, Dragan Kovačević and Kristina Habschied

Processes 2026, 14(6), 1018; https://doi.org/10.3390/pr14061018 - 22 Mar 2026

Viewed by 567

Abstract

The aim of this study is to evaluate the influence of traditional and industrial smoking technologies on the physicochemical properties, color, texture, and mass loss of selected cured pork products. Four products (dry-cured pork neck, dry-cured pork loin, pancetta, and fermented sausages in [...] Read more.

The aim of this study is to evaluate the influence of traditional and industrial smoking technologies on the physicochemical properties, color, texture, and mass loss of selected cured pork products. Four products (dry-cured pork neck, dry-cured pork loin, pancetta, and fermented sausages in natural and collagen casings) were produced using two smoking regimes (traditional and industrial). The samples were analyzed at two processing stages, after smoking and at the end of the production process. Physicochemical composition, pH, water activity (a_w), color parameters (CIE L*a*b*), texture profile parameters, and mass loss were determined using standard analytical methods. Statistical differences between treatments were evaluated using the analysis of variance (ANOVA) followed by Fisher’s least significant difference (LSD) test (p < 0.05). Traditional smoking resulted in greater dehydration, with moisture content reduced by approximately 8–15% and water activity lower by about 0.04–0.09 compared with industrial smoking. Traditionally smoked products also showed higher mass loss (up to 10–12%) and lower L* values, indicating darker color. Texture profile analysis indicated higher hardness values in several traditionally smoked products, particularly in sausages and pancetta. In contrast, industrial smoking resulted in higher moisture retention and more uniform physicochemical characteristics. The differences between smoking regimes were less pronounced in dry-cured pork neck. These results demonstrate that smoking technology significantly influences dehydration dynamics and several technological quality parameters of cured meat products, providing useful information for optimizing smoking regimes in traditional and industrial meat processing. Full article

(This article belongs to the Section Food Process Engineering)

12 pages, 2051 KB

Open AccessArticle

Emulsion Prepared with Auricularia polytricha (Mont.) Sacc. As a Direct Emulsifier for β-Carotene Encapsulation: Stability and Digestibility

by Jianxin Fu, Jing Wei, Tingxia Yan, Xing Zhu, Yuhang Chen and Zhenghong Hao

Processes 2026, 14(6), 1017; https://doi.org/10.3390/pr14061017 - 22 Mar 2026

Viewed by 333

Abstract

β-Carotene is widely utilized in food systems due to its biological activities, but exhibits poor chemical stability and low bioavailability. This study utilized whole Auricularia polytricha (Mont.) Sacc. powder as a direct emulsifier to establish a natural emulsion-based delivery system designed to [...] Read more.

β-Carotene is widely utilized in food systems due to its biological activities, but exhibits poor chemical stability and low bioavailability. This study utilized whole Auricularia polytricha (Mont.) Sacc. powder as a direct emulsifier to establish a natural emulsion-based delivery system designed to enhance the stability of β-carotene. Under optimal conditions, using 7% Auricularia polytricha (Mont.) Sacc. powder (120 μm) and 1% oil phase fraction, microscopic analysis revealed that emulsion droplets were small and uniformly distributed, resulting in excellent long-term stability. After UV irradiation, the degradation rate of β-carotene in the emulsion was significantly lower than that of β-carotene directly dispersed in the oil phase. In vitro simulated digestion indicated that β-carotene retention in the intestinal phase reached 9.2% in the emulsion system, 1.2 ± 0.23% higher than in the conventional oil-dissolved system. This strategy offers a practical approach for the high-value utilization of this fungal resource, streamlining industrial processes and reducing production costs. Full article

(This article belongs to the Topic Sustainable Food Processing: 2nd Edition)

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25 pages, 2056 KB

Open AccessArticle

Game Theory and Optimal Planning Strategy for Electricity Heat Multiple Heterogeneous Energy Systems Based on Deep Temporal Clustering Method

by Zhipeng Lu, Yuejiao Wang, Pu Zhao, Song Yang, Yu Zhang, Nan Yang and Lei Zhang

Processes 2026, 14(6), 1016; https://doi.org/10.3390/pr14061016 - 22 Mar 2026

Viewed by 340

Abstract

With the continuous increase in the penetration rate of renewable energy sources, the uncertainty of new energy output has brought significant risks and challenges to the planning strategy of integrated energy systems. Meanwhile, power grid operators and heat network operators, belonging to different [...] Read more.

With the continuous increase in the penetration rate of renewable energy sources, the uncertainty of new energy output has brought significant risks and challenges to the planning strategy of integrated energy systems. Meanwhile, power grid operators and heat network operators, belonging to different stakeholder entities, exhibit complex cooperative-competitive game relationships, making it difficult to balance the interests of all parties. To address this issue, this paper proposes a game theory and optimal planning strategy for electricity-heat multiple heterogeneous energy systems based on a deep temporal clustering method from the perspective of different stakeholders. Firstly, typical scenarios of renewable energy output are generated through the deep temporal clustering method. Simultaneously, the charging and discharging behaviors of energy storage devices are utilized to assist the distribution system in new energy consumption. This paper incorporates battery life degradation costs into the objective function on the power grid side to achieve accurate accounting of energy storage device dispatch expenses. Additionally, an optimal dispatch model is established on the heat network side, upon which a game framework for multiple heterogeneous energy systems is constructed. The construction capacity and installation location of each flexible device can be determined through planning decisions in typical multi-scenario situations. Considering the non-convex and nonlinear characteristics of the model, this paper employs an improved firefly algorithm to achieve optimal solution search and rapid convergence. Finally, the effectiveness and feasibility of the proposed method are demonstrated through a case study of an electricity-heat energy system. Full article

(This article belongs to the Section Energy Systems)

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18 pages, 12230 KB

Open AccessArticle

Configuration Optimization of Lazy-Wave Dynamic Umbilicals Using Random Forest Surrogates and NSGA-II

by Jing Hou, Yi Liu, Fucheng Li and Depeng Liu

Processes 2026, 14(6), 1015; https://doi.org/10.3390/pr14061015 - 21 Mar 2026

Viewed by 429

Abstract

Dynamic umbilicals, as critical components connecting offshore platforms to subsea production systems, can effectively decouple platform motions through a lazy-wave configuration, thereby reducing top tension and fatigue damage. To address the engineering challenges of numerous configuration design variables and time-consuming dynamic analyses for [...] Read more.

Dynamic umbilicals, as critical components connecting offshore platforms to subsea production systems, can effectively decouple platform motions through a lazy-wave configuration, thereby reducing top tension and fatigue damage. To address the engineering challenges of numerous configuration design variables and time-consuming dynamic analyses for dynamic umbilicals, an efficient design optimization framework based on surrogate modeling and multi-objective optimization is proposed. An integrated finite-element model of a lazy-wave dynamic umbilical–offshore platform system is developed in OrcaFlex, incorporating environmental loads, material properties, and geometric parameters. The arrangement parameters of clump weights and buoyancy modules are selected as design variables, and the dynamic responses and parameter sensitivities of multiple configurations are investigated. Using simulation data, surrogate models for predicting tension and curvature are constructed via random forest regression, achieving coefficients of determination (R²) of 0.9948 and 0.9121 on the test set, respectively. Based on the surrogate predictors, the Non-dominated Sorting Genetic Algorithm II (NSGA-II) is employed to solve a multi-objective optimization problem that minimizes the maximum tension and curvature, yielding a set of Pareto-optimal solutions. The proposed approach effectively improves the stability and reliability of the dynamic umbilical system under complex sea states. 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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14 pages, 4096 KB

Open AccessArticle

Biochar-Enhanced Inorganic Gel for Water Plugging in High-Temperature and High-Salinity Fracture-Vuggy Reservoirs

by Shiwei He and Tengfei Wang

Processes 2026, 14(6), 1014; https://doi.org/10.3390/pr14061014 - 21 Mar 2026

Viewed by 440

Abstract

With the expansion of global oil and gas resource exploration and development into deep and ultra deep layers, the efficient development of deep carbonate rock fracture cave reservoirs has become the key to ensuring energy security. However, this type of reservoir commonly faces [...] Read more.

With the expansion of global oil and gas resource exploration and development into deep and ultra deep layers, the efficient development of deep carbonate rock fracture cave reservoirs has become the key to ensuring energy security. However, this type of reservoir commonly faces high temperatures, high salinity, and extremely strong heterogeneity, leading to increasingly severe water content spikes caused by dominant water flow channels. Although the existing traditional inorganic plugging agent has good temperature resistance, it has the defects of great brittleness and easy cracking, while the organic polymer gel is prone to degradation failure under high temperature and high salt environments. In order to solve the above problems, a new biochar-enhanced inorganic composite gel system was constructed by using biochar prepared from agricultural and forestry waste pyrolysis as a functional enhancement component. Through rheological testing, high-temperature and high-pressure mechanical experiments, long-term thermal stability evaluation, and dynamic sealing experiments of fractured rock cores, the reinforcement and toughening laws and rheological control mechanisms of biochar on inorganic matrices were systematically studied. Research has found that a biochar content of 0.5 wt% can significantly improve the micro pore structure of the matrix. By utilizing its micro aggregate filling effect and interfacial chemical bonding, the compressive strength of the solidified body can be increased to over 2 MPa, and there is no significant decline in strength after aging at 130 °C for 30 days. More importantly, the unique “adsorption slow-release” mechanism of biochar effectively stabilizes the hydration reaction kinetics at high temperatures, extending the solidification time of the system to 15 h and solving the problem of flash condensation in deep well pumping. This system exhibits excellent shear thinning characteristics and crack sealing ability, and presents a unique “yield reconstruction” toughness sealing feature. This study elucidates the multidimensional strengthening mechanism of biochar in inorganic cementitious materials, providing technical reference for stable oil and water control in deep fractured reservoirs. Full article

(This article belongs to the Special Issue New Advances in Low-Energy Processes for Geo-Energy Development: 2nd Edition)

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19 pages, 1711 KB

Open AccessArticle

Joint Planning Method for Soft Open Points and Energy Storage in Hybrid Distribution Networks Based on Improved DC Power Flow

by Wei Luo, Chenwei Zhang, Xionghui Han, Fang Chen, Zhenyu Lv and Yuntao Zhang

Processes 2026, 14(6), 1013; https://doi.org/10.3390/pr14061013 - 21 Mar 2026

Viewed by 402

Abstract

Intelligent soft open points (SOPs) and energy storage systems (ESSs) are effective ways to absorb distributed new energy in the spatial and temporal dimensions, and play an important role in improving the new-energy-carrying capacity of distribution networks. Existing planning models for SOPs and [...] Read more.

Intelligent soft open points (SOPs) and energy storage systems (ESSs) are effective ways to absorb distributed new energy in the spatial and temporal dimensions, and play an important role in improving the new-energy-carrying capacity of distribution networks. Existing planning models for SOPs and ESSs in distribution networks are often nonlinear and non-convex, and are usually transformed into a mixed-integer second-order cone optimization (MISOCP) model. However, this transformation often needs stringent relaxation conditions, and the solution speed and convergence performance of the model are poor. These disadvantages make traditional MISOCP models unsuitable for optimal planning for complex hybrid networks. To overcome these limitations, a joint planning method for AC/DC hybrid networks based on an improved DC power flow (IDCPF) algorithm is proposed in this paper. The proposed method transforms the original nonlinear model into an approximate linear model, improving the solution speed and accuracy of the model. The effectiveness of the proposed method is validated through case studies on an improved AC/DC 43-node network, which demonstrates the accuracy and numerical stability of the planning model. Full article

(This article belongs to the Special Issue Advances in Optimal Operation of Modern Power Systems for Flexibility Enhancement)

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18 pages, 2273 KB

Open AccessArticle

Physicochemical Characterization of Biochar Sorbents Produced at Different Temperatures from Malt Spent Rootlets

by Andreas Tzachristas, Panagiota D. Natsi, Panagiota E. Politi, Nikolaos Mourgkogiannis, Ioannis D. Manariotis and Hrissi K. Karapanagioti

Processes 2026, 14(6), 1012; https://doi.org/10.3390/pr14061012 - 21 Mar 2026

Viewed by 513

Abstract

Biochars are currently proposed as soil amendments or sorbent materials. There is an extensive scientific literature that deals with biochars originating from different raw materials. However, a holistic physicochemical characterization with simple analytical techniques is needed to provide insights on the characteristics of [...] Read more.

Biochars are currently proposed as soil amendments or sorbent materials. There is an extensive scientific literature that deals with biochars originating from different raw materials. However, a holistic physicochemical characterization with simple analytical techniques is needed to provide insights on the characteristics of the biochars produced from malt spent rootlets (MSRs) and how they vary using different pyrolysis temperatures. This way, their properties can be fully understood, and they can be used for commercial purposes more effectively. Initially, the texture of the biochars were visualized by SEM and was quantified by the adsorption/desorption of nitrogen and the Brunauer, Emmett, and Teller (BET) equation. Additionally, the moisture content, the ash content and the pH of each sample were measured. Furthermore, the electrical conductivity of each sample was measured. Different techniques were used to determine the properties of carbon and of the surface functional groups (Total Carbon, XRD, ATR-FTIR) and leachable organic matter. Also, sorption of the methylene blue dye solution has been studied, which is an indication of mesopores for each biochar. Molasses number was also determined, as this is an indicator of macropores. Finally, the chlorine removal rate was determined for each type of biochar. The experiments marked that the change in mass of biochars has stopped after three hours at 50 °C in the drying oven. The measured moisture content ranged from 6 to 11%. The specific surface area of our materials, calculated through the BET equation, for low temperature biochars (e.g., 28 m²/g, at 350 °C), is much lower than that of high temperature pyrolyzed biochar (e.g., 286 m²/g, at 850 °C). The pH value ranged from 7 to 10. The electrical conductivity values of samples ranged from 800 μS/cm to 2.55 mS/cm, and these decreased during the measurement after the second wash with deionized water. Crystallinity increased with increasing pyrolysis temperature whereas the number of functional groups decreased. MSR biochars produced at temperatures equal or higher than 750 °C demonstrate different characteristics to the ones produced at lower temperatures. Full article

(This article belongs to the Special Issue Biomass Pyrolysis Characterization and Energy Utilization)

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23 pages, 6469 KB

Open AccessFeature PaperEditor’s ChoiceArticle

Integrated CFD Modeling of Combustion, Heat Transfer, and Oxide Scale Growth in Steel Slab Reheating

by Mario Ulises Calderón Rojas, Constantin Alberto Hernández Bocanegra, José Ángel Ramos Banderas, Nancy Margarita López Granados, Nicolás David Herrera Sandoval and Juan Carlos Hernández Bocanegra

Processes 2026, 14(6), 1011; https://doi.org/10.3390/pr14061011 - 21 Mar 2026

Viewed by 483

Abstract

In this study, a three-dimensional simulation of a walking-beam reheating furnace was developed to improve the steel slab reheating process and reduce surface oxidation kinetics using computational fluid dynamics (CFD). Combustion, heat transfer, fluid dynamics, and chemical reaction models were integrated into the [...] Read more.

In this study, a three-dimensional simulation of a walking-beam reheating furnace was developed to improve the steel slab reheating process and reduce surface oxidation kinetics using computational fluid dynamics (CFD). Combustion, heat transfer, fluid dynamics, and chemical reaction models were integrated into the numerical framework of this study. In addition, dynamic mesh remeshing was coupled through user-defined functions (UDFs), enabling the simultaneous simulation of slab movement and evolution of the involved transport phenomena. Turbulence was modeled with the realizable k-ε formulation, combustion with the Eddy Dissipation model, and radiation with the P-1 model coupled with WSGGM to include CO₂ and H₂O gas radiation. Scale formation was modeled using customized functions based on Arrhenius-type kinetics and Wagner’s oxidation model, evaluating its growth as a function of time, temperature, and furnace atmosphere. The predicted thermal evolution inside the furnace was validated using industrial data, yielding an average deviation of 5%. Furthermore, the proposed operating conditions led to an average slab temperature of 1289.77 °C at the exit of the homogenization zone, which was 16 °C higher than that under the current operation but still within the target range (1250 ± 50 °C). The reduction in combustion air decreased energy losses and improved product quality, lowering the molar oxygen content in the furnace atmosphere from 4.9 × 10² mol to 6.7 × 10¹ mol. Additionally, annual savings of 4,793,472 kg of natural gas and 13,884 tons of steel were estimated owing to reduced oxidation losses. The proposed air–fuel adjustment led to estimated annual energy savings (equivalent to 4,793,472 kg of natural gas) and a reduction in material loss due to oxidation from 4.5% to 3.75% (an absolute reduction of 0.75 percentage points; relative reduction ≈ 16.7%), which has a significant industrial impact on metal conservation and descaling cost reduction. Although there are CFD studies on plate overheating and scale growth separately, this work presents three main contributions: (1) the integration, within a single numerical framework, of combustion, radiation, species transport, oxidation kinetics, and actual plate movement using a dynamic mesh; (2) validation against continuous industrial records (16 thermocouples) and quantification of operational benefits such as fuel savings and reduced material loss; and (3) a comparative analysis between actual and optimized conditions, which standardize the air–methane ratio. Full article

(This article belongs to the Special Issue Numerical Simulation and Heat Transfer in Material Processing and Casting Engineering)

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14 pages, 5220 KB

Open AccessArticle

Investigation on Flowback Efficiency and Permeability Damage Characteristics in Coal Reservoirs: A Case Study of the Midong Block, Xinjiang

by Xin Xie, Xuesong Xin, Zhengrong Chen, Dian Wang, Guiyang You, Zhaoyu Shen and Jun Li

Processes 2026, 14(6), 1010; https://doi.org/10.3390/pr14061010 - 21 Mar 2026

Viewed by 343

Abstract

The Midong Block is currently a primary target for coalbed methane (CBM) exploration and development in Xinjiang. However, fracturing operations in this region generally exhibit low flowback rates, which escalate the risk of reservoir damage and ultimately suppress daily gas production. To elucidate [...] Read more.

The Midong Block is currently a primary target for coalbed methane (CBM) exploration and development in Xinjiang. However, fracturing operations in this region generally exhibit low flowback rates, which escalate the risk of reservoir damage and ultimately suppress daily gas production. To elucidate the impact of various geological and engineering factors on flowback efficiency and permeability damage, as well as their underlying mechanisms, this study conducted fracturing fluid flowback simulation experiments. The pulse-decay permeability measurement and weighing methods were employed to quantify the variations in flowback rates and permeability damage intensities under different conditions. Experimental results indicated that the permeability damage rate in the Xishanyao Formation coal samples ranged from 3.12% to 92.86% after flowback, with 92% of the samples exhibiting a flowback rate of less than 10%. This significant impairment was primarily attributed to the synergistic effects of stress-induced fracture closure, clay mineral hydration swelling, and coal fines migration. Specifically, elevated confining pressures and prolonged soaking times exacerbated reservoir damage. A low flowback pressure differential intensified the water locking effect, hindering fluid recovery. Notably, the flowback velocity displayed a U-shaped velocity sensitivity profile. In the low-temperature regime, damage characteristics fluctuated, controlled by competitive thermal–hydro–mechanical (THM) coupling mechanisms. Full article

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

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21 pages, 2670 KB

Open AccessArticle

Caffeine and Paracetamol Adsorption and Antibacterial Activity Using Granular Activated Carbon Modified with Silver and Copper Compounds

by Luiza Carla Augusto Molina, Jayana Freitas Resende, Jumara Silva de Sousa, Luis Fernando Cusioli, Letícia Nishi, Sandro Rogerio Lautenschlager and Rosangela Bergamasco

Processes 2026, 14(6), 1009; https://doi.org/10.3390/pr14061009 - 21 Mar 2026

Viewed by 506

Abstract

Adsorption is a promising solution to the presence of contaminants in water resources that involves the use of adsorbent materials, such as granular activated carbon (GAC) and nanoparticles like silver (Ag) and copper (Cu). However, the practical challenge of using pure GAC lies [...] Read more.

Adsorption is a promising solution to the presence of contaminants in water resources that involves the use of adsorbent materials, such as granular activated carbon (GAC) and nanoparticles like silver (Ag) and copper (Cu). However, the practical challenge of using pure GAC lies in its susceptibility to biofouling. This study aimed to develop a multifunctional GAC/AgCu nanocomposite to address the dual challenge of pharmaceutical contamination and bacterial activity of Escherichia coli. Characterization by SEM, XRF, XRD and FTIR confirmed the successful impregnation of nanoparticles. Kinetic studies showed that the pseudo-first-order model was more suitable for both caffeine and paracetamol contaminants. The Langmuir model provided the best fit for isotherms, achieving maximum adsorption capacities of 138.35

m g g^{- 1}

for caffeine and 92.21

m g g^{- 1}

for paracetamol. In antibacterial tests, GAC/AgCu achieved a bacterial reduction of over 97%, whereas pure GAC showed no inhibitory effect, confirming that the antimicrobial properties are derived from the Ag and Cu nanoparticles. These results highlight GAC/AgCu as a promising multifunctional material for the simultaneous removal of emerging pharmaceutical pollutants and biological contaminants, offering a solution to mitigate biofouling and enhance water treatment efficiency. Full article

(This article belongs to the Section Environmental and Green Processes)

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19 pages, 3170 KB

Open AccessArticle

From Synergistic Preservation to Shelf-Life Prediction: Optimizing Storage Conditions for Kyoho Grapes with Subzero Temperature and Modified Atmosphere

by Anqi Ji, Shaoyu Tao, Zhaoyang Ding and Jing Xie

Processes 2026, 14(6), 1008; https://doi.org/10.3390/pr14061008 - 21 Mar 2026

Viewed by 430

Abstract

Kyoho grape, a leading table grape variety in China, is prone to rapid postharvest deterioration due to its soft texture and high respiration rate. Despite the use of low-temperature storage and modified atmosphere packaging (MAP), systematic studies defining the optimal combination of subzero [...] Read more.

Kyoho grape, a leading table grape variety in China, is prone to rapid postharvest deterioration due to its soft texture and high respiration rate. Despite the use of low-temperature storage and modified atmosphere packaging (MAP), systematic studies defining the optimal combination of subzero temperature and gas composition for Kyoho grapes remain lacking. This study aimed to fill this gap by evaluating the synergistic effects of subzero temperature and MAP on quality preservation. Results demonstrated that storage at −1 °C most effectively maintained fruit firmness, stem freshness, and key biochemical components. Based on this temperature, a gas composition of 3% O₂, 15% CO₂, and 82% N₂ was identified as the most effective, extending postharvest shelf life to 54 days. Additionally, a kinetic shelf-life prediction model based on firmness changes was developed with relative errors below 10%, demonstrating high accuracy. This study establishes an integrated preservation strategy combining subzero temperature (−1 °C) and optimized MAP (3% O₂, 15% CO₂, 82% N₂) that significantly extends the shelf life of Kyoho grapes, providing a practical solution for enhancing postharvest quality. Full article

(This article belongs to the Special Issue Development of Innovative Processes in Food Engineering)

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22 pages, 7274 KB

Open AccessArticle

An Intelligent Evaluation Method for Sweet Spots in Deep-Marine Shale Reservoirs Based on Lithofacies Control and Multi-Parameter Driving

by Yi Liu, Jin Wu, Boning Zhang, Chengyong Li, Dongxu Zhang, Tong Wang, Chen Yang, Yi Luo, Ye Gu, Li Zhang, Jing Yang and Kai Tong

Processes 2026, 14(6), 1007; https://doi.org/10.3390/pr14061007 - 21 Mar 2026

Viewed by 419

Abstract

Deep marine shale reservoirs are controlled by multi-factor coupling effects, and the genetic mechanism of “sweet spots” exhibits strong complexity, leading to prominent difficulties in quantitative prediction and precise evaluation of sweet spots. Aiming at the problems of an unclear lithofacies-controlled sweet spot [...] Read more.

Deep marine shale reservoirs are controlled by multi-factor coupling effects, and the genetic mechanism of “sweet spots” exhibits strong complexity, leading to prominent difficulties in quantitative prediction and precise evaluation of sweet spots. Aiming at the problems of an unclear lithofacies-controlled sweet spot evolution law and insufficient accuracy of multi-parameter quantitative evaluation in traditional evaluation methods, this paper takes the Wufeng Formation and Long1 member of the Longmaxi Formation in the LZ block, Southern Sichuan, as the research object. Innovatively integrating machine learning (ML), grey correlation analysis (GRA), and three-dimensiona (3D) geological modeling technologies, a refined prediction model for reservoir sweet spot evaluation indicators under lithofacies constraint conditions is established, and a multi-parameter fusion quantitative evaluation method for deep marine shale gas sweet spots with high prediction accuracy is proposed. The results demonstrate that the LightGBM-based prediction model for sweet spot evaluation indicators achieved excellent performance. Based on a total of 380 preprocessed samples divided into training and test sets in a 7:3 ratio, the coefficient of determination (R²) of the model exceeded 0.9 in both the test and validation datasets. The “sweetness index”, a comprehensive evaluation index of reservoir sweet spots constructed via GRA-based multi-factor fusion, shows a correlation coefficient of 0.91 with respect to actual gas well production, presenting a high fitting degree. The 3D sweet spot geological model reveals that Class I sweet spots are mainly developed in the 1st to 3rd sub-layers of the Long1 member, while Class II sweet spots are distributed in the 5th and 6th sub-layers, which is highly consistent with the actual development law of the gas field. This study breaks through the limitations of single evaluation methods and weak lithofacies control consideration in traditional sweet spot evaluation and forms a set of innovative technical process integrating “precision prediction—multi-factor fusion—3D characterization”. It provides a new technical approach for efficient and accurate evaluation of deep marine shale reservoir sweet spots and has important guiding significance for the efficient development of shale gas. Full article

(This article belongs to the Special Issue Recent Advances in Extraction of Oil from Heavy Oil, Medium-Low Maturity Shale, and Oil Shale)

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32 pages, 5214 KB

Open AccessArticle

Synergistic Design and Optimization of a Zero-Residue Self-Cleaning System for Wheat Breeding Trial-Plot Combine Harvesters

by Zenghui Gao, Cheng Yang, Nan Xu, Chao Xia, Dongwei Wang, Changjie Han and Shuqi Shang

Processes 2026, 14(6), 1006; https://doi.org/10.3390/pr14061006 - 21 Mar 2026

Viewed by 436

Abstract

Field breeding trial-plot harvesting is one of the key processes in crop breeding, as any mixing between varieties during harvest directly leads to the invalidation of breeding data. Therefore, achieving zero-residue self-cleaning inside the machine during harvesting is essential. Existing studies have largely [...] Read more.

Field breeding trial-plot harvesting is one of the key processes in crop breeding, as any mixing between varieties during harvest directly leads to the invalidation of breeding data. Therefore, achieving zero-residue self-cleaning inside the machine during harvesting is essential. Existing studies have largely relied on simulations to optimize cleaning parameters. However, research specifically targeting the synergistic design of the mechanical and pneumatic components of the cleaning device to achieve efficient and thorough self-cleaning in complex real-world conditions remains lacking. To address this issue, this paper presents a novel cleaning system specifically designed for efficient self-cleaning and optimizes its key parameters. Key structural parameters of the straw walker, vibrating sieve, and cleaning fan were analyzed, establishing preliminary ranges for crank speed, sieve-airflow angle, and fan speed. A test bench was developed, and single-factor experiments were conducted to investigate the effects of these parameters on core self-cleaning indicators, including the self-cleaning rate and self-cleaning time. The optimal parameter combination was obtained using the Box–Behnken design (BBD) response surface methodology: a crank speed of 390.80 r/min, a sieve-airflow angle of 29.88°, and a fan speed of 1995 r/min. Bench tests validated that the system achieved excellent cleaning performance while ensuring a self-cleaning rate of 100% and a reduced self-cleaning time of 20 s. The system’s effectiveness was further validated through field experiments using a 4LX1 prototype harvester on three wheat varieties. Results demonstrated zero grain mixing between plots, with self-cleaning times of 9–12 s. Both bench and field test results exceeded the relevant standards, effectively resolving the long-standing issue of grain residue in trial plot harvesting. Through dual validation, this study provides a referential solution for addressing grain residue and establishes a theoretical foundation for the synergistic design of efficient and precision breeding harvest technologies. Full article

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

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25 pages, 687 KB

Open AccessReview

The Continuous Oscillatory Baffled Reactor: A Review of Progress, Challenges, and Future Prospects (2014–2025)

by Jonildo dos Santos Silva, Príamo Albuquerque Melo and José Carlos Costa da Silva Pinto

Processes 2026, 14(6), 1005; https://doi.org/10.3390/pr14061005 - 21 Mar 2026

Viewed by 821

Abstract

This work presents a comprehensive literature review on Continuous Oscillatory Baffled Reactors (COBRs), surveying advancements from 2014 to 2025. Although widespread industrial adoption of COBRs remains a future goal, the analysis reveals the significant maturation of COBR technology, marked by a growing exploration [...] Read more.

This work presents a comprehensive literature review on Continuous Oscillatory Baffled Reactors (COBRs), surveying advancements from 2014 to 2025. Although widespread industrial adoption of COBRs remains a future goal, the analysis reveals the significant maturation of COBR technology, marked by a growing exploration of novel applications—particularly in enabling the transition from batch to continuous manufacturing. The review synthesizes both theoretical and experimental studies, categorizing them into key thematic areas to provide a clear and accessible overview of the field. The study concludes by identifying critical research gaps and offering a perspective on future directions, thereby aiming to guide and inspire subsequent research endeavors in overcoming the barriers to commercialization. Full article

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

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23 pages, 2927 KB

Open AccessArticle

Real-Time Edge Deployment of ANFIS for IoT Energy Optimization

by Daniel Teso-Fz-Betoño, Iñigo Aramendia, Jose Antonio Ramos-Hernanz, Koldo Portal-Porras, Daniel Caballero-Martin and Jose Manuel Lopez-Guede

Processes 2026, 14(6), 1004; https://doi.org/10.3390/pr14061004 - 21 Mar 2026

Viewed by 499

Abstract

This work presents the real-world deployment of an Adaptive Neuro-Fuzzy Inference System (ANFIS) for intelligent energy control in resource-constrained IoT devices. The proposed system employs a first-order Takagi–Sugeno fuzzy model with three Gaussian membership functions per input: ambient temperature, light intensity, and battery [...] Read more.

This work presents the real-world deployment of an Adaptive Neuro-Fuzzy Inference System (ANFIS) for intelligent energy control in resource-constrained IoT devices. The proposed system employs a first-order Takagi–Sugeno fuzzy model with three Gaussian membership functions per input: ambient temperature, light intensity, and battery voltage. The model was trained offline using augmented environmental datasets and subsequently translated into optimized embedded C code for execution on an ESP32 microcontroller. The controller dynamically adjusts the node’s deep sleep duration according to environmental conditions, enabling adaptive behavior based solely on local environmental conditions without requiring external connectivity. A 10-day field deployment compared the ANFIS controller with conventional fixed and rule-based strategies. Results show that the ANFIS-based strategy reduced energy consumption by 31.1% relative to the fixed approach while maintaining accurate adaptation to environmental conditions (RMSE = 9.6 s). The inference process required less than 2.5 ms and used under 30 KB of RAM, confirming the feasibility of real-time fuzzy inference on resource-constrained embedded platforms. Full article

(This article belongs to the Section Energy Systems)

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17 pages, 2469 KB

Open AccessArticle

CFD Investigation of CO₂ Capture Process with K₂CO₃ Sorbents in a Bubbling Fluidized Bed

by Yida Ge, Abdul Mateen, Asim Aamir, Xintao Pang, Yan Gao, Zhenya Duan and Xiaoxing Liu

Processes 2026, 14(6), 1003; https://doi.org/10.3390/pr14061003 - 21 Mar 2026

Viewed by 394

Abstract

This study employs a Computational Fluid Dynamics (CFD) approach based on the Two-Fluid Model (TFM) to investigate the CO₂ capture characteristics in a bubbling fluidized bed reactor using potassium carbonate (K₂CO₃) as the sorbent. The simulations are conducted [...] Read more.

This study employs a Computational Fluid Dynamics (CFD) approach based on the Two-Fluid Model (TFM) to investigate the CO₂ capture characteristics in a bubbling fluidized bed reactor using potassium carbonate (K₂CO₃) as the sorbent. The simulations are conducted at five superficial gas velocities ranging from 1.5 to 3.5 times the minimum bubbling velocity (u_mb = 0.26 m/s), with a particle diameter of 0.4 mm, particle density of 2300 kg/m³, and an initial solid volume fraction of 0.55. The gas mixture consists of CO₂, H₂O, and N₂ at a molar ratio of 0.1:0.1:0.8 and a temperature of 343 K. First, the numerical simulation was validated against experimental data reported in the literature, confirming its accuracy in quantitatively describing the adsorption process. Subsequently, the distributions of CO₂ concentration and adsorption reaction rate in both the bubble phase and the emulsion phase were analyzed under different superficial gas velocities. The simulation results indicate that CO₂ concentration and adsorption reaction rate in both phases decrease along the bed height. Compared to the emulsion phase, the bubble phase exhibits higher CO₂ concentration and gas temperature but a lower adsorption reaction rate. As the gas velocity increases, CO₂ concentration rises in both the bubble and emulsion phases, accompanied by an increase in the proportion of the bubble phase, and a higher CO₂ concentration at the reactor outlet. Further comparison of CO₂ concentrations in the bubble and emulsion phases at the upper part of the bed with the outlet concentration reveals that the outlet CO₂ primarily originates from the unadsorbed portion within the bubble phase, while the contribution from unadsorbed CO₂ in the emulsion phase is almost negligible. Full article

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

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15 pages, 3184 KB

Open AccessArticle

Wellbore Stability Analysis of Shale Formation Considering Sealing Effect of Mud Cake on Drilling Fluid Seepage

by Qiang Gao, Yun Bai, Shuaizhi Ji, Junying Zhang, Shitian Wan, Hongxia He, Feng Huang, Junling Lou and Qiang Li

Processes 2026, 14(6), 1002; https://doi.org/10.3390/pr14061002 - 21 Mar 2026

Viewed by 389

Abstract

Wellbore stability is one of the major challenges during drilling operations in shale gas formations. Drilling fluid seepage can significantly alter the pore pressure around the wellbore, thereby inducing wellbore instability. In this study, the Darcy pore fluid flow model was applied to [...] Read more.

Wellbore stability is one of the major challenges during drilling operations in shale gas formations. Drilling fluid seepage can significantly alter the pore pressure around the wellbore, thereby inducing wellbore instability. In this study, the Darcy pore fluid flow model was applied to both the mud cake and wellbore to predict pore pressure, which helps improve the accuracy of calculating collapse pressure and fracture pressure. Shale samples were collected from the Puguang Gas Reservoir, and their composition and physicochemical properties were systematically analyzed. The results indicate that the clay content in the formation can reach up to 35.5%, with distinct hydrophilic characteristics, and the maximum hydration expansion rate of the shale is 5.79%. The permeabilities of shale and mud cake were measured via the pore pressure transmission test. Specifically, shale samples from Sub-layer 1 exhibit the highest permeabilities for both rock and mud cake, which are 8.27 × 10⁻¹⁸ m² and 2.07 × 10⁻²⁰ m², respectively. In contrast, samples from Sub-layer 3 show the lowest permeability values, being 2.76 × 10⁻²⁰ m² and 1.66 × 10⁻²² m². The borehole tensile breakdown pressure and compressive collapse pressure were calculated using a poro-mechanical coupling model. The Sub-layer with the lowest cohesion strength after drilling fluid immersion presents the narrowest mud density window of 0.04 g/cm³, making it the most susceptible to wellbore stability failures; furthermore, the maintenance of wellbore stability requires strict control of the drilling mud density within the range. This study can provide guidance for accurate prediction of mud density window during drilling operations in shale formations. Full article

(This article belongs to the Special Issue Oil and Gas Well Engineering: Experimental and Numerical Investigation, 2nd Edition)

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23 pages, 3561 KB

Open AccessArticle

Design and Fabrication of 3D-Printed Gyroid Biocarriers for Biological Wastewater Treatment: Experimental and Pilot-Scale Evaluation

by Letícia Nishi, Lucas Gabriel de Souza Bairros, Gabriel Perina Gongora, Marcela Fernandes Silva, Rosângela Bergamasco, Celso Vataru Nakamura, Sueli de Oliveira Silva Lautenschlager and Sandro Rogerio Lautenschlager

Processes 2026, 14(6), 1001; https://doi.org/10.3390/pr14061001 - 21 Mar 2026

Cited by 1 | Viewed by 549

Abstract

Inadequate domestic wastewater treatment remains a major environmental challenge due to the discharge of nitrogen compounds that originate primarily from human excreta, food residues, and household products, and are commonly present as ammonium and organic nitrogen. During biological processes, these compounds are converted [...] Read more.

Inadequate domestic wastewater treatment remains a major environmental challenge due to the discharge of nitrogen compounds that originate primarily from human excreta, food residues, and household products, and are commonly present as ammonium and organic nitrogen. During biological processes, these compounds are converted to nitrite and nitrate, which are highly soluble and can easily migrate through soils, contaminating groundwater and posing risks to public health. Although Moving Bed Biofilm Reactors (MBBRs) are widely used for nitrogen removal, developing biocarriers with controllable geometry and optimized surface area for enhanced biofilm growth remains a challenge. This study aimed to design and fabricate gyroid-structured biocarriers using additive manufacturing (3D printing) from polylactic acid (PLA), acrylonitrile–butadiene–styrene (ABS), and polypropylene (PP), and to evaluate their performance in wastewater treatment for nitrogen removal. Bench-scale experiments showed significant chemical oxygen demand (COD) removal for all materials, with ABS and PP promoting the most stable biofilm formation. Pilot-scale tests with PP gyroid biocarriers achieved removal efficiencies of up to 87% for biochemical oxygen demand (BOD), 87% for ammonia, and 97% for nitrate. These results demonstrate that 3D-printed gyroid biocarriers provide a tunable geometry that enhances surface area and improves biological nitrogen removal in domestic wastewater treatment. Full article

(This article belongs to the Special Issue Sediment Contamination and Metal Removal from Wastewater)

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17 pages, 4538 KB

Open AccessArticle

Adaptability Evaluation of Water Injection at Structural Lows and Oil Production at Structural Highs in Dipping Reservoirs

by Xiutian Yao, Haoyu Shi, Shuoliang Wang and Zhiping Li

Processes 2026, 14(6), 1000; https://doi.org/10.3390/pr14061000 - 21 Mar 2026

Viewed by 255

Abstract

In the field of oil reservoir engineering, the development of large-dip-angle reservoirs poses significant challenges due to their strong heterogeneity, pronounced gravity effects, and inefficient water flooding sweep, all contributing to suboptimal oil recovery rates. This study aims to address these challenges by [...] Read more.

In the field of oil reservoir engineering, the development of large-dip-angle reservoirs poses significant challenges due to their strong heterogeneity, pronounced gravity effects, and inefficient water flooding sweep, all contributing to suboptimal oil recovery rates. This study aims to address these challenges by focusing on the core issue of optimizing water injection development strategies for such reservoirs. A numerical simulation mechanism model is constructed based on actual large-dip-angle reservoir A, and the impact of key parameters—including reservoir dip angle, permeability, injection–production well spacing, water injection intensity, and crude oil viscosity—on oil recovery is systematically analyzed under the “water injection at structural lows and oil production at structural highs” high-pressure water injection development mode. The simulation results reveal that the oil recovery rate increases with higher dip angles, permeability, injection–production well spacing, and water injection intensity; however, excessive water injection intensity or crude oil viscosity can lead to premature water breakthrough, reducing efficiency. Using the analytic hierarchy process, the primary controlling factors are ranked as permeability > crude oil viscosity > reservoir dip angle > water injection intensity > injection–production well spacing. Furthermore, development theory charts are established to guide the selection of appropriate water injection intensities for different injection–production well distances and permeabilities. This study offers valuable theoretical insights for optimizing water injection development in large-dip-angle reservoirs, thereby enhancing oil recovery and economic benefits and laying a foundation for future research and practical applications in similar reservoir settings. Full article

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

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12 pages, 1958 KB

Open AccessArticle

Temporal Wettability Dynamics in Sustainable Olive Pomace Biochar Composites: A Signal-Driven and Bat Algorithm Framework

by Mehmet Ali Biberci

Processes 2026, 14(6), 999; https://doi.org/10.3390/pr14060999 - 20 Mar 2026

Viewed by 316

Abstract

Olive pomace biochar, obtained through the pyrolysis of lignocellulosic biomass, has emerged as a sustainable and multifunctional additive for polymer composites. Its physicochemical properties, including porosity, surface area, and electrical conductivity, can be tailored by controlling feedstock type and pyrolysis conditions. Although mechanical [...] Read more.

Olive pomace biochar, obtained through the pyrolysis of lignocellulosic biomass, has emerged as a sustainable and multifunctional additive for polymer composites. Its physicochemical properties, including porosity, surface area, and electrical conductivity, can be tailored by controlling feedstock type and pyrolysis conditions. Although mechanical reinforcement and thermal stability improvements are well documented, the influence of biochar on surface-related properties such as wettability and contact angle remains insufficiently explored for environmentally relevant composite systems. In this study, epoxy-based composites containing biochar synthesized at 750 °C were evaluated in terms of their water interaction behavior by monitoring the evaporation dynamics of ultra-pure water droplets (10 μL, 0.055 mS/cm conductivity) at eight time intervals between 20 and 580 s using high-resolution digital microscopy. Image enhancement and segmentation were performed prior to Discrete Cosine Transform (DCT) analysis to describe droplet geometry in the frequency domain. Time-dependent variations in the standard deviations of DCT coefficients were optimized using the Bat Algorithm, resulting in mathematical models capable of accurately representing droplet evolution and surface–fluid interactions. The primary novelty of this study lies in the development of a hybrid experimental–computational framework that integrates droplet-based wettability measurements with signal-domain analysis and metaheuristic optimization. Unlike conventional studies focusing solely on material characterization, this approach establishes quantitative relationships between surface behavior and numerical descriptors derived from DCT and the Bat Algorithm. The proposed methodology provides a data-driven tool for predicting wettability trends in biochar-reinforced composites and supports the development of moisture-resistant materials for coatings, packaging, and thermal insulation applications within the context of sustainable composite design. Full article

(This article belongs to the Section Materials Processes)

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