Processes

29 pages, 7232 KB

Open AccessFeature PaperArticle

Exposing Vulnerabilities: Physical Adversarial Attacks on AI-Based Fault Diagnosis Models in Industrial Air-Cooling Systems

by Stavros Bezyrgiannidis, Ioannis Polymeropoulos, Eleni Vrochidou and George A. Papakostas

Processes 2025, 13(9), 2920; https://doi.org/10.3390/pr13092920 (registering DOI) - 12 Sep 2025

Abstract

Although neural network-based methods have significantly advanced the field of machine fault diagnosis, they remain vulnerable to physical adversarial attacks. This work investigates such attacks in the physical context of a real production line. Attacks simulate failures or irregularities arising from the maintenance [...] Read more.

Although neural network-based methods have significantly advanced the field of machine fault diagnosis, they remain vulnerable to physical adversarial attacks. This work investigates such attacks in the physical context of a real production line. Attacks simulate failures or irregularities arising from the maintenance or production department during the production process, a scenario commonly encountered in industrial environments. The experiments are conducted using data from vibration signals and operational parameters of a motor installed in an industrial air-cooling system used for staple fiber production. In this context, we propose the Mean Confusion Impact Index (MCII), a novel and simple robustness metric that measures the average misclassification confidence of models under adversarial physical attacks. By performing a series of hardware-level interventions, this work aims to demonstrate that even minor physical disturbances can lead to a significant reduction in the model’s diagnostic accuracy. Additionally, a hybrid defense approach is proposed, which leverages deep feature representations extracted from the original classification model and integrates them with lightweight classifiers retrained on adversarial labeled data. Research findings underscore an important limitation in existing industrial artificial intelligence (AI)-based monitoring systems and introduce a practical, scalable framework for improving the physical resilience of machine fault diagnosis in real-world environments. Full article

(This article belongs to the Special Issue Application of Artificial Intelligence in Industrial Process Modelling and Optimization (2nd Edition))

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27 pages, 5655 KB

Open AccessFeature PaperArticle

Process Route for Electric Arc Furnace Dust (EAFD) Rinse Wastewater Desalination

by Hedviga Horváthová, Eduardo Henrique Rotta, Tatiane Benvenuti, Andréa Moura Bernardes, Andrea Miskufova and Zita Takáčová

Processes 2025, 13(9), 2919; https://doi.org/10.3390/pr13092919 - 12 Sep 2025

Abstract

This study introduces a two-step treatment method for synthetic and real electric arc furnace dust (EAFD) wastewater, integrating sorption with Mg–Al layered double hydroxides (LDHs) and electrodialysis (ED). The hydrotalcite (LDH), mainly Mg₆Al₂(CO₃)OH₁₆·4H₂O [...] Read more.

This study introduces a two-step treatment method for synthetic and real electric arc furnace dust (EAFD) wastewater, integrating sorption with Mg–Al layered double hydroxides (LDHs) and electrodialysis (ED). The hydrotalcite (LDH), mainly Mg₆Al₂(CO₃)OH₁₆·4H₂O (hydrotalcite-2H), was characterized by XRD, FTIR, SEM, and EDX, confirming its layered structure and ion-exchange capacity. Calcination at 550 °C was identified as optimal, enhancing sorption efficiency while retaining rehydration potential. Sorption tests demonstrated high effectiveness in removing multivalent ions, achieving over 99% elimination of Ca²⁺, SO₄²⁻, and Pb²⁺ ions and Cr from both synthetic and real wastewater. In contrast, monovalent ions such as Na⁺ and K⁺ were not effectively removed, except for partial removal of Cl⁻. To overcome this limitation, electrodialysis was applied in the second step, successfully targeting the remaining monovalent ions and achieving more than 95% conductivity reduction. A key challenge of ED, salt precipitation caused by calcium and sulphate in the concentrate, was effectively mitigated by the prior LDH treatment. The combined process minimized scaling risks, improved overall ion removal (above 97% for Na⁺ and K⁺), and produced low-salinity effluents (0.84 mS cm⁻¹), suitable for reuse in hydrometallurgical operations. These findings demonstrate that coupling LDH sorption with electrodialysis provides a sustainable and efficient strategy for treating high-salinity industrial wastewaters, particularly those originating from EAFD processes. Full article

(This article belongs to the Topic Advanced Processes and Technologies for Wastewater: Collection, Treatment, and Resource)

21 pages, 817 KB

Open AccessArticle

The Supercritical Adsorption Potential Equation for Shale Gas and Its Application: A Case Study of Methane Adsorption in Danish Bornholm Shale

by Pei Xue, Quansheng Liang, Chao Gao, Jintao Yin, Cheng Huang and Yushan Ma

Processes 2025, 13(9), 2918; https://doi.org/10.3390/pr13092918 - 12 Sep 2025

Abstract

Since shale gas adsorption belongs to supercritical gas adsorption, the ideal gas adsorption potential equation is not suitable for calculating the adsorption potential of shale gas. In this study, the supercritical gas adsorption potential equation is proposed based on the assumption that the [...] Read more.

Since shale gas adsorption belongs to supercritical gas adsorption, the ideal gas adsorption potential equation is not suitable for calculating the adsorption potential of shale gas. In this study, the supercritical gas adsorption potential equation is proposed based on the assumption that the adsorbed phase is a real gas. The adsorbed phase pressure, as the parameter in the adsorption potential equation, was calculated using the Amankwah equation. For the unknown parameter K in the Amankwah equation, a method for determining the optimal value of K based on the consistency of the adsorption characteristic curve and the accuracy of the predicted isothermal adsorption curve is proposed, thus obtaining the adsorbed phase pressure. Simultaneously, based on a comparison of the ideal gas and supercritical gas adsorption potential, a simplified equation for the supercritical gas adsorption potential is proposed. In this paper, the isothermal adsorption curve of CH₄ adsorbed by Holm shale is used to carry out practical calculations. This study revealed that the optimal value of K for the CH₄ adsorption system in Holm shale is 2.9, with the adsorbed phase pressure ranging from 17.11 to 32.19 MPa within the temperature range of 300–373 K. The supercritical gas adsorption characteristic curves exhibited excellent consistency, and the average relative error of the predicted ascending segment of the excess adsorption isotherm at 373 K was merely 1.77%, thereby substantiating the rationality of the supercritical gas adsorption potential equation. The simplified equation for supercritical gas adsorption potential is straightforward in form, facilitating its widespread application and promotion. Full article

(This article belongs to the Special Issue Advances in Theory and Technology of Unconventional Oil and Gas Reservoirs)

19 pages, 3973 KB

Open AccessArticle

Comparison of Statistical Process Control Models for Monitoring the Biological Burden of a Buffer Solution Used as Input to Produce an Attenuated Viral Vaccine

by Josiane Machado Vieira Mattoso, Greice Maria Silva da Conceição, Ana Paula Roque da Silva, Paulo Vinicius Pereira Miranda, Letícia de Alencar Pereira Rodrigues, Marcelo Luiz Lima Brandão and Jeancarlo Pereira dos Anjos

Processes 2025, 13(9), 2917; https://doi.org/10.3390/pr13092917 - 12 Sep 2025

Abstract

The pharmaceutical industry faces various production challenges. Bioburden control is essential, and appropriate strategies and procedures must be implemented at all stages of production to prevent microbial contamination and comply with regulatory standards. Quality tools can provide important information for data management in [...] Read more.

The pharmaceutical industry faces various production challenges. Bioburden control is essential, and appropriate strategies and procedures must be implemented at all stages of production to prevent microbial contamination and comply with regulatory standards. Quality tools can provide important information for data management in production processes. The objective of this study was to compare two types of statistical process control charts (Laney’s U-chart and Bell distribution) in monitoring the bioburden of a buffer solution used as an input to produce an attenuated viral vaccine. Bioburden data for the buffer solution were obtained over a two-year period. The results showed that the analyzed products met the regulatory specifications, as 99% of them presented ≤10 colony-forming units (CFU)/100 mL after filtration. Various microorganisms were identified in the buffer solution, including species from the genus Bacillus spp., Micrococcus spp., Kocuria spp., Staphylococcus spp., and Acinetobacter spp. The Bell distribution proved to be statistically more suitable for application in the management of bioburden data for the buffer solution since the limits were closer to the specified value and could more effectively assist in the investigation of process deviations in the production of an attenuated viral vaccine. Full article

(This article belongs to the Special Issue Microbiological Environmental Monitoring in the Pharmaceutical Industry)

33 pages, 2763 KB

Open AccessReview

Electrocoagulation for the Removal of Antibiotics and Resistant Bacteria: Advances and Synergistic Technologies

by Laura Sol Pérez-Flores and Eduardo Torres

Processes 2025, 13(9), 2916; https://doi.org/10.3390/pr13092916 - 12 Sep 2025

Abstract

The persistence of antibiotics and antibiotic-resistant bacteria (ARB) in aquatic environments poses a significant risk to both the environment and public health. Conventional wastewater treatment systems are often inefficient in completely removing these emerging contaminants, highlighting the need for advanced and integrative treatment [...] Read more.

The persistence of antibiotics and antibiotic-resistant bacteria (ARB) in aquatic environments poses a significant risk to both the environment and public health. Conventional wastewater treatment systems are often inefficient in completely removing these emerging contaminants, highlighting the need for advanced and integrative treatment approaches. Electrocoagulation (EC) has emerged as a promising electrochemical method due to its operational simplicity, low chemical demand, and versatility in treating a wide range of wastewater types. This review critically analyzes the efficiency of EC, both as a standalone process and in combination with complementary technologies such as electrooxidation, membrane filtration, advanced oxidation processes (AOPs), and biological treatments. Emphasis is placed on the removal mechanisms, influencing parameters (pH, current density, electrode material), and the synergistic effects that enhance the degradation of antibiotics and the inactivation of ARB. Additionally, the review discusses the limitations of EC, including electrode passivation and energy consumption. The integration of EC with other technologies demonstrates improved pollutant removal and process robustness, offering a viable alternative for treating complex wastewater streams. This work provides a perspective on the current state and future potential of EC-based hybrid systems in mitigating the environmental impact of antibiotic pollutants and antimicrobial resistance. Full article

(This article belongs to the Special Issue Advanced Oxidation Processes for Waste Treatment)

24 pages, 4547 KB

Open AccessArticle

Removal of Cu and Pb in Contaminated Loess by Electrokinetic Remediation Using Novel Hydrogel Electrodes Coupled with Focusing Position Adjustment and Exchange Electrode

by Chengbo Liu, Wenle Hu, Xiang Zhu, Shixu Zhang and Weijing Wang

Processes 2025, 13(9), 2915; https://doi.org/10.3390/pr13092915 - 12 Sep 2025

Abstract

Electrokinetic (EK) remediation is a promising approach for the removal of heavy metals from fine-grained soils; however, its efficiency is often hindered by electrode polarization, pH imbalance, and ion accumulation. In this study, we developed a novel hydrogel-based electrode (NH electrode), composed of [...] Read more.

Electrokinetic (EK) remediation is a promising approach for the removal of heavy metals from fine-grained soils; however, its efficiency is often hindered by electrode polarization, pH imbalance, and ion accumulation. In this study, we developed a novel hydrogel-based electrode (NH electrode), composed of sodium alginate and multilayer graphene oxide (GO), to enhance the electrokinetic removal of Cu²⁺ and Pb²⁺ from loess. The electrode was systematically characterized by atomic force microscopy (AFM), cyclic voltammetry (CV), and electrochemical impedance spectroscopy (EIS), confirming its structural integrity, electrochemical activity, and interfacial conductivity. The NH electrode exhibited a smooth layered graphene structure with abundant oxygen-containing functional groups (AFM), negligible electrochemical polarization (CV), and low internal resistance with high conductivity (EIS), enabling efficient ion transport and adsorption. Electrokinetic tests revealed that the NH electrode outperformed conventional graphene (Gr) and electrokinetic graphite (EKG) electrodes. Single regulation strategies, including focusing position adjustment and electrode exchange, improved local removal efficiency by mitigating ion accumulation in targeted regions. The combined regulation strategy, integrating both measures, achieved the most uniform Cu²⁺ and Pb²⁺ removal, significantly suppressing hydroxide precipitation in cathodic zones and enhancing ion migration in the mid-section. Compared with literature-reported systems under similar or even more favorable conditions, the NH electrode and combined regulation approach achieved superior performance, with Cu²⁺ and Pb²⁺ removal efficiencies reaching 47.25% and 16.93%, respectively. These findings demonstrate that coupling electrode material innovation with spatial–temporal pH/flow field regulation can overcome key bottlenecks in EK remediation of heavy-metal-contaminated loess. Full article

(This article belongs to the Special Issue Advances in Heavy Metal Contaminated Soil and Water Remediation)

18 pages, 1127 KB

Open AccessArticle

Multi-Stage Microwave-Assisted Extraction of Phenolic Compounds from Tunisian Walnut (Juglans regia L.) Bark

by Nesrine Boukettaya, Houcine Mhemdi and Nabil Kechaou

Processes 2025, 13(9), 2914; https://doi.org/10.3390/pr13092914 - 12 Sep 2025

Abstract

This study aimed to optimize the extraction of total phenolic compounds (TPC) from Tunisian walnut bark using microwave treatment. Initially, a preliminary investigation was conducted to establish optimal levels for ethanol concentration, liquid–solid ratio, temperature, and time, which were then applied in subsequent [...] Read more.

This study aimed to optimize the extraction of total phenolic compounds (TPC) from Tunisian walnut bark using microwave treatment. Initially, a preliminary investigation was conducted to establish optimal levels for ethanol concentration, liquid–solid ratio, temperature, and time, which were then applied in subsequent conventional solvent extraction (CSE) experiments. To enhance the extraction yield, multi-stage microwave-assisted extraction (MS MAE) was evaluated using three microwave power settings: 100, 200, and 300 W. The results showed a statistically significant (p < 0.05) effect of microwave irradiation combined with multiple solvent extraction stages. The optimized MS MAE protocol, employing 300 W power, six stages of 10 min each, and a liquid–solid ratio of 10 mL/g, achieved an 86% recovery of TPC. In contrast, extraction involving 10 stages of 30 min each without microwave irradiation recovered only 79% of TPC. UHPLC–MS analysis revealed that the phenolic profile of the extracts was dominated by gallic acid, vanillic acid, and quercetin, and that microwave treatment did not significantly alter the qualitative or quantitative composition of these major phenolic compounds compared to conventional extraction. These findings demonstrate that MS MAE is a time-saving, energy-saving, solvent-reducing, and highly efficient extraction technology for producing bioactive extracts from walnut bark. Full article

(This article belongs to the Special Issue Process Intensification and Application for Bioprocesses and Green Chemical Engineering)

13 pages, 3632 KB

Open AccessArticle

Design and Analysis of Torque Ripple Reduction in Low-Pole Axial Flux Motor

by Si-Woo Song and Won-Ho Kim

Processes 2025, 13(9), 2913; https://doi.org/10.3390/pr13092913 - 12 Sep 2025

Abstract

With the growing demand for high-efficiency and high-performance electric motors in applications such as electric vehicles, drones, and industrial drive systems, Axial Flux Motors (AFMs) have gained significant attention due to their high torque density and compact structure. However, low-pole AFMs are prone [...] Read more.

With the growing demand for high-efficiency and high-performance electric motors in applications such as electric vehicles, drones, and industrial drive systems, Axial Flux Motors (AFMs) have gained significant attention due to their high torque density and compact structure. However, low-pole AFMs are prone to performance degradation and noise issues caused by magnetic saturation in the rotor back yoke and increased torque ripple. In this study, a conventional 6-pole, 9-slot Radial Flux Motor (RFM) was redesigned as an AFM within the same external volume. To minimize losses, the stator inner diameter and slot thickness were co-optimized. In addition, tapering techniques were applied to both the stator and magnets to reduce torque ripple, and a parametric analysis of magnet tapering was conducted to identify optimal design conditions. A rolling core fabrication method was adopted to ensure both electromagnetic performance and manufacturability. The final AFM design demonstrated a 1.4 percentage point improvement in efficiency. Additionally, torque ripple was reduced by 69.44%, thereby validating the effectiveness of the AFM redesign and ripple reduction strategy. Full article

(This article belongs to the Topic Energy Management and Efficiency in Electric Motors, Drives, Power Converters and Related Systems, 2nd Edition)

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17 pages, 2834 KB

Open AccessArticle

Design and Parameter Optimization of Winding Device of Chain Network Residual Film Recycling Machine Based on High-Speed Camera Analysis

by Yan Zhao, Xinliang Tian, Xuegeng Chen, Xuehu Liu, Yuanchao Li and Guangliang Huang

Processes 2025, 13(9), 2912; https://doi.org/10.3390/pr13092912 - 12 Sep 2025

Abstract

Aiming at the problems of low operating efficiency and the unclear mechanisms in the bundling process of existing residual film recycling machines, this paper designs a chain network-type residual film bundling device and analyzes the motion characteristics of the film bundling process using [...] Read more.

Aiming at the problems of low operating efficiency and the unclear mechanisms in the bundling process of existing residual film recycling machines, this paper designs a chain network-type residual film bundling device and analyzes the motion characteristics of the film bundling process using high-speed camera technology. A mechanical analysis of the bundling process was conducted, and a test rig for the chain network residual film bundling device was built. The bundling process was studied via a high-speed camera. Field tests were carried out with the density of the film bale as the evaluation indicator and the forward speed of the machine, the rotational speed of the active film-removing roller, and the rotational speed of the film-rolling support roller as influencing factors. A Box–Behnken experimental design was used to optimize the working parameters of the device. The results show that when the machine’s forward speed is 5.8 km/h, the active stripping roller rotates at 170 rpm, the roll support roller operates at 210 rpm, and the film bale density reaches 124.44 kg/m³, with a relative error of only 1.34 kg/m³ compared to the predicted value. This verifies the effectiveness of the device and demonstrates that it can meet the requirements of mechanized residual film recycling. Full article

(This article belongs to the Section Materials Processes)

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23 pages, 5246 KB

Open AccessArticle

Numerical Simulation of Sedimentation Behavior of Densely Arranged Particles in a Vertical Pipe Using Coupled SPH-DEM

by Peng Ji, Zhiyuan Wang, Weigang Du, Zhenli Pang, Liyong Guan, Yong Liu and Xiangwei Dong

Processes 2025, 13(9), 2911; https://doi.org/10.3390/pr13092911 - 12 Sep 2025

Abstract

This study develops a coupled Smoothed Particle Hydrodynamics (SPH) and the Discrete Element Method (DEM) framework to explore the sedimentation behavior of densely arranged particles in vertical pipes. An unresolved SPH-DEM model is proposed, which integrates porosity-dependent fluid governing equations through local averaging [...] Read more.

This study develops a coupled Smoothed Particle Hydrodynamics (SPH) and the Discrete Element Method (DEM) framework to explore the sedimentation behavior of densely arranged particles in vertical pipes. An unresolved SPH-DEM model is proposed, which integrates porosity-dependent fluid governing equations through local averaging techniques to connect pore-scale interactions with macroscopic flow characteristics. Validated against single-particle settling experiments, the model accurately captures transient acceleration, drag equilibrium, and rebound dynamics. Systematic simulations reveal that particle number, arrangement patterns, and fluid domain geometry play critical roles in regulating collective settling: Increasing particle count induces nonlinear terminal velocity reduction. Systems of 16 particles show 50% lower velocity than single-particle cases due to enhanced shielding and energy dissipation. Particle configuration (compact layouts 4 × 8 vs. elongated arrangements 8 × 4) dictates hydrodynamic resistance, compact layouts facilitate faster settling by reducing cross-sectional blockage, while elongated arrangements amplify lateral resistance. The width of the fluid domain exerts threshold effects: narrow boundaries (0.03 m) intensify wall-induced drag and suppress vortices, whereas wider domains promote symmetric vortices that enhance stability. Additionally, critical transitions in multi-row/column systems are identified, where stress-chain redistribution and fluid-permeation thresholds govern particle detachment and velocity stratification. These findings deepen the understanding of granular–fluid interactions in confined spaces and provide a predictive tool for optimizing particle management in industrial processes such as wellbore cleaning and hydraulic fracturing. Full article

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

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22 pages, 1053 KB

Open AccessReview

Edible Pouch Packaging for Food Applications—A Review

by Azin Omid Jeivan and Sabina Galus

Processes 2025, 13(9), 2910; https://doi.org/10.3390/pr13092910 - 12 Sep 2025

Abstract

Current food packaging, primarily made of non-biodegradable plastics, significantly contributes to environmental pollution. New packaging systems for food applications from biopolymers and/or with multifunctional properties are being developed as substitutes for synthetic polymers. The increasing concern over the environmental effects of packaging waste [...] Read more.

Current food packaging, primarily made of non-biodegradable plastics, significantly contributes to environmental pollution. New packaging systems for food applications from biopolymers and/or with multifunctional properties are being developed as substitutes for synthetic polymers. The increasing concern over the environmental effects of packaging waste is driving a transition toward renewable packaging materials. Edible films and coatings play a vital role in maintaining food quality by preventing the loss of aroma, flavour, and important components, while also extending shelf life. Biopolymers, including polysaccharides, proteins, and lipids, are gaining attention as the future of packaging due to the environmental issues linked to petrochemical-based plastics. Modern packaging should not only protect products but also be biodegradable, recyclable, and have a minimal ecological impact. This review comprehensively summarises edible packaging in the form of single-use, fast-dissolving pouches for food applications as a circular approach and a sustainable solution in food technology. Innovations have resulted in the development of a unique packaging solution made from renewable sources. This packaging utilises plant and animal by-products to create edible films and pouches that are easy to seal. Edible packaging is emerging as a sustainable alternative, designed to simplify food packaging while minimising waste. Fast-dissolving scalable packaging, particularly edible films that dissolve in water, is used for individual servings of dry foods and instant beverages. This includes items like breakfast cereals, instant coffee or tea, and various powdered products. Additionally, there is an innovative approach to single-use packaging for oils and powders, leveraging the convenience and efficiency of these fast-dissolving films. Edible pouch packaging, made from safe and edible materials, provides a biodegradable option that decomposes naturally, thereby reducing pollution and the need for disposal. Full article

(This article belongs to the Special Issue Feature Reviews in Food Processing Technologies: Present Innovations and Future Opportunities (2nd Edition))

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23 pages, 3086 KB

Open AccessFeature PaperArticle

Decarbonizing Rural Off-Grid Areas Through Hybrid Renewable Hydrogen Systems: A Case Study from Turkey

by Aysenur Oymak and Mehmet Rida Tur

Processes 2025, 13(9), 2909; https://doi.org/10.3390/pr13092909 - 12 Sep 2025

Abstract

Access to renewable energy is vital for rural development and climate change mitigation. The intermittency of renewable sources necessitates efficient energy storage, especially in off-grid applications. This study evaluates the technical, economic, and environmental performance of an off-grid hybrid system for the rural [...] Read more.

Access to renewable energy is vital for rural development and climate change mitigation. The intermittency of renewable sources necessitates efficient energy storage, especially in off-grid applications. This study evaluates the technical, economic, and environmental performance of an off-grid hybrid system for the rural settlement of Soma, Turkey. Using HOMER Pro 3.14.2 software, a system consisting of solar, wind, battery, and hydrogen components was modeled under four scenarios with Cyclic Charging (CC) and Load Following (LF) control strategies for optimization. Life cycle assessment (LCA) and hydrogen leakage impacts were calculated separately through MATLAB R2019b analysis in accordance with ISO 14040 and ISO 14044 standards. Scenario 1 (PV + wind + battery + H₂) offered the most balanced solution with a net present cost (NPC) of USD 297,419, with a cost of electricity (COE) of USD 0.340/kWh. Scenario 2 without batteries increased hydrogen consumption despite a similar COE. Scenario 3 with wind only achieved the lowest hydrogen consumption and the highest efficiency. In Scenario 4, hydrogen consumption decreased with battery reintegration, but COE increased. Specific CO₂ emissions ranged between 36–45 gCO₂-eq/kWh across scenarios. Results indicate that the control strategy and component selection strongly influence performance and that hydrogen-based hybrid systems offer a sustainable solution in rural areas. Full article

(This article belongs to the Special Issue Green Hydrogen Production: Advances and Prospects)

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28 pages, 6775 KB

Open AccessArticle

Reliability Study of Metal Bellows in Low-Temperature High-Pressure Liquid Carbon Dioxide Transportation Systems: Failure Mechanism Analysis

by Chao Liu, Yunlong Gu, Hua Wen, Shangwen Zhu and Peng Jiang

Processes 2025, 13(9), 2908; https://doi.org/10.3390/pr13092908 - 11 Sep 2025

Abstract

In order to meet the harsh working environment and complex and changeable stress conditions, the low-temperature and high-pressure liquid carbon dioxide conveying system used in oil extraction will choose metal bellows for transportation. In this paper, the bellows in an accident section are [...] Read more.

In order to meet the harsh working environment and complex and changeable stress conditions, the low-temperature and high-pressure liquid carbon dioxide conveying system used in oil extraction will choose metal bellows for transportation. In this paper, the bellows in an accident section are investigated and observed by the working environment and characterization methods such as macroscopic analysis, metallographic analysis, EDS component analysis, fracture scanning electron microscopy analysis, and related mechanical performance test methods. The failure mechanism of the accident is preliminarily judged, and the unidirectional fluid–structure coupling model and the standard k-ω turbulence model are used as the calculation models for subsequent simulation. Combined with Fluent finite element simulation analysis, it is verified that the failure is caused by a welding defect, the maximum stress of the metal bellows under normal conditions is less than its own yield strength, and the material can work normally. When the welding crack is greater than 2 mm, the strength of the workpiece weld will be reduced, and the stress concentration has exceeded the yield strength that the workpiece can bear, causing failure fracture at the welding defect part. Combined with ANSYS simulation of accident defects, compared with bellows without defects, the stress at the crack will increase with the increase in the inlet flow velocity and decrease with the increase in temperature, and the flow rate will have a greater influence on it. Therefore, in actual working conditions, the stiffness and fatigue life of the conveying system can be improved by appropriately reducing the liquid flow rate and increasing the temperature. It provides a reference for the future application research of bellows and the research on bellows fracture failure. Full article

(This article belongs to the Section Materials Processes)

20 pages, 3632 KB

Open AccessArticle

Use of Cedrela odorata L. as a Biomaterial for Dye Adsorption in Wastewater: Simulation and Machine Learning Approaches for Scale-Up Analysis

by Candelaria Tejada-Tovar, Ángel Villabona-Ortíz, Oscar E. Coronado-Hernández, Modesto Pérez-Sánchez and María Hueto-Polo

Processes 2025, 13(9), 2907; https://doi.org/10.3390/pr13092907 - 11 Sep 2025

Abstract

Methylene blue and safranin are dyes that may have harmful effects on both aquatic ecosystems and human health. This research aims to simulate an industrial-scale operational adsorption column for competitively removing these dyes from wastewater, employing Cedrela odorata L. as a bioadsorbent material. [...] Read more.

Methylene blue and safranin are dyes that may have harmful effects on both aquatic ecosystems and human health. This research aims to simulate an industrial-scale operational adsorption column for competitively removing these dyes from wastewater, employing Cedrela odorata L. as a bioadsorbent material. Aspen Adsorption (v.1) software simulated an industrial-scale packed-bed adsorption column under various configurations. Moreover, machine learning algorithms were applied to predict the results generated by Aspen, representing an advancement in the development of new strategies in this field. The kinetic model employed was the Linear Driving Force (LDF) model. Adsorption efficiencies of 96.1% were achieved for both methylene blue and safranin using the Langmuir–LDF model. The Freundlich–LDF model showed efficiencies of 94.8% for methylene blue and 96% for safranin. Meanwhile, the Langmuir–Freundlich–LDF model achieved up to 96.1% for methylene blue and 94.8% for safranin. This study demonstrated the feasibility of simulating the competitive adsorption of dyes in solution at an industrial scale using Cedrela odorata L. as a bioadsorbent. The application of LDF kinetic models and adsorption isotherms (Langmuir, Freundlich, and Langmuir–Freundlich) resulted in high adsorption efficiencies, highlighting the potential of this approach for the remediation of dye-contaminated effluents as a viable method for predicting the performance of full-scale packed columns. Machine learning algorithms were implemented in this research, obtaining R² higher than 0.996 for validation and testing stages for the responses of the model. Full article

(This article belongs to the Special Issue Modeling and Optimization for Multi-scale Integration)

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15 pages, 1181 KB

Open AccessFeature PaperArticle

Modeling of the Mutual Placement of Thermoanemometer Sensors on a Flat Surface of an Air Flow

by Taras Dmytriv, Vasyl Dmytriv and Michał Bembenek

Processes 2025, 13(9), 2906; https://doi.org/10.3390/pr13092906 - 11 Sep 2025

Abstract

A functional model of a thermoanemometer measuring the air flow velocity on a flat wall surface of the flow has been developed. From the heat balance equation of the sensing elements in the thermoanemometer, a dependence has been derived for determining the heating [...] Read more.

A functional model of a thermoanemometer measuring the air flow velocity on a flat wall surface of the flow has been developed. From the heat balance equation of the sensing elements in the thermoanemometer, a dependence has been derived for determining the heating temperature of the sensing elements. The distribution of the temperature field in the boundary layer was modeled by analogy with the velocity distribution, following a cubic dependence. The distribution of the temperature field on a flat wall surface of the flow from the heating of the sensing elements was obtained analytically by solving the heat conduction equation in the direction of the coordinate of the air flow velocity vector for the boundary conditions of the II as well as II and III kinds. The developed mathematical dependencies enable both the modeling of the distribution of temperature fields in the sensing elements and justifying the distance between them. The reliability of measurements of the air flow velocity on the wall surface of the flow depends on the impossibility of influencing the temperature of one sensing element of the sensor on the temperature of the other. The task of justifying the distance between the sensing elements of the sensor, which are located in the direction of the air flow velocity vector, aims to prevent the interaction of the temperature fields of the elements with each other. The boundary condition is that at the boundary of separation between the temperature fields of the sensing elements, there is a temperature that is 5 to 10% lower than the temperature of the colder sensing element. The ratio of the resistances of the sensing elements is 4/1. The power released by the first sensing element of the sensor, aligned along the air flow velocity vector, is 4 times lower than the heating power of the second sensing element of the sensor. The modeling was carried out at an air flow velocity within 30 and 330 m·s⁻¹. The values of the distances between the sensing elements of the thermal anemometer vary with the supply voltage. The material of the sensing elements is nickel. The contact area of the surface of the sensing elements was 214.337 mm². Full article

(This article belongs to the Special Issue Fluid Dynamics and Thermodynamic Studies in Gas Turbine)

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17 pages, 1832 KB

Open AccessFeature PaperArticle

Comparison of Active and Passive Grid Coupling in Distribution Grids Using Particle Swarm Optimization

by Frederik Gielnik, Sebastian Hormel, Michael Suriyah and Thomas Leibfried

Processes 2025, 13(9), 2905; https://doi.org/10.3390/pr13092905 - 11 Sep 2025

Abstract

Distribution networks are facing increasing challenges due to the growing share of renewable energy sources (RESs), particularly because of the volatile nature of the available power. In addition to targeted grid expansion measures, the concept of a dynamic grid topology offers an additional [...] Read more.

Distribution networks are facing increasing challenges due to the growing share of renewable energy sources (RESs), particularly because of the volatile nature of the available power. In addition to targeted grid expansion measures, the concept of a dynamic grid topology offers an additional layer of flexibility in the power system. Furthermore, there are concepts to use active coupling methods in distribution grids, such as medium-voltage direct current (MVDC) systems, which enable horizontal power flows between distribution grids and thus active control. This paper investigates the potential of combining dynamic passive and active coupling between two distribution grids. Particle swarm optimization (PSO) is used to determine both an optimized operating point of two MVDC interconnections as well as the most efficient switch configuration within both networks. The goal of the optimization is to reduce both network losses and power exchange between the different voltage levels. To evaluate its potential, various use cases are simulated using a representative feed-in of photovoltaics while considering grid constraints. Individual and combined impacts of dynamic AC switching and DC coupling are compared using a modified IEEE-123 test feeder. The results show a significant optimization potential, especially with an increase in RES penetration within the grid. In the best scenarios, the power losses can be decreased by 33.73% and the power transfer can be reduced by 8.75%. Full article

(This article belongs to the Special Issue AI-Based Modelling and Control of Power Systems)

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16 pages, 12051 KB

Open AccessArticle

Leaching Kinetics and Reactive Regulation of Boiling Furnace Pyrite Cinder (BPC) in an Oxalic Acid-Sulfuric Acid System

by Xiaojiao Li, Zhenlin Peng and Yang Yang

Processes 2025, 13(9), 2904; https://doi.org/10.3390/pr13092904 - 11 Sep 2025

Abstract

To address the challenge of low iron extraction efficiency from boiling furnace pyrite cinder (BPC), a significant secondary iron resource posing environmental risks due to massive stockpiling in China, this study investigated the kinetics and reactivity regulation of an oxalic acid-sulfuric acid hybrid [...] Read more.

To address the challenge of low iron extraction efficiency from boiling furnace pyrite cinder (BPC), a significant secondary iron resource posing environmental risks due to massive stockpiling in China, this study investigated the kinetics and reactivity regulation of an oxalic acid-sulfuric acid hybrid leaching system to overcome the inertness and diffusion barriers of hematite. Single-factor experiments and Response Surface Methodology (RSM) optimization were employed to determine optimal leaching parameters (time, temperature, liquid–solid ratio, H₂SO₄ concentration) under constant stirring (400 r/min) and BPC–oxalic acid ratio (50:1). Shrinking core kinetic modeling, complemented by SEM-EDS/XRD residue characterization, elucidated the dissolution mechanism. Results showed a maximum iron leaching rate of 94.7% at 90 °C, 40 wt% H₂SO₄, an L/S ratio of 5 mL/g, and a time of 7 h. Kinetics transitioned from liquid-film diffusion control (Ea = 76.9 kJ/mol) below 70 °C to mixed interfacial reaction/internal diffusion control (Ea = 32.4 kJ/mol) above 80 °C. Highly concentrated acid conditions (50% H₂SO₄) reduced efficiency by >20% due to oxalate protonation, CaSO₄ pore occlusion, and increased viscosity. RSM confirmed temperature-dominated kinetics and acid concentration-governed thermodynamics, with no synergy under combined high-temperature/high-acidity conditions. This optimized process enables efficient iron recovery from refractory BPC using minimal reagent consumption. Full article

(This article belongs to the Special Issue Advanced Methods of Metal Recycling)

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18 pages, 3556 KB

Open AccessArticle

Development of Double Crosslinked Nano Microspheres and Study on CO₂ Drive Blocking Mechanism

by Ping Guo, Yong Li, Yanbao Liu and Yunlong Zou

Processes 2025, 13(9), 2903; https://doi.org/10.3390/pr13092903 - 11 Sep 2025

Abstract

In this study, a new type of double crosslinked nanospheres (DCNPM-A) was developed to solve the problem of gas channeling caused by fracture development in the process of CO₂ oil displacement, and the microsphere system with delayed swelling was successfully synthesized by [...] Read more.

In this study, a new type of double crosslinked nanospheres (DCNPM-A) was developed to solve the problem of gas channeling caused by fracture development in the process of CO₂ oil displacement, and the microsphere system with delayed swelling was successfully synthesized by inverse micro lotion polymerization. The microsphere adopts a dual crosslinking structure of stable crosslinking agent (MBA) and unstable crosslinking agent (UCA), achieving intelligent sealing function of shallow low expansion and deep high temperature triggered secondary expansion. The successful preparation of microspheres was verified by characterization methods such as Zeta potential and SEM, and the effects of reaction temperature, time, initiator and crosslinking agent dosage on microsphere properties were systematically studied. The experimental results show that DCNPM-A microspheres exhibit excellent expansion performance, thermal stability, and acid resistance in acidic, high-temperature, and high mineralization environments. Their expansion ratio can reach 13.5 times, and they can maintain stability for more than 60 days in supercritical CO₂ environments. Core displacement experiments have confirmed that the microspheres have the best sealing performance in matrices with a permeability of 10 × 10⁻³ μm² and fractures with a width of 0.03 mm. The combination of 0.8 PV injection volume, 0.5 mL·min⁻¹ injection rate, and continuous injection method significantly improved the plugging rate and recovery rate of CO₂ flooding. This study provides new technical support for the efficient development of low-permeability fractured reservoirs. Full article

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

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18 pages, 18416 KB

Open AccessArticle

Radiation-Induced Degradation Mechanisms in Silicon MEMS Under Coupled Thermal and Mechanical Fields

by Xian Guo, Deshou Yang, Jibiao Qiao, Hui Zhang, Tong Ye and Ning Wei

Processes 2025, 13(9), 2902; https://doi.org/10.3390/pr13092902 - 11 Sep 2025

Abstract

Silicon-based MEMS devices are essential in extreme radiation environments but suffer progressive reliability degradation from irradiation-induced defects. Here, the generation, aggregation, and clustering of defects in single-crystal silicon were systematically investigated through molecular dynamics (MD) simulations via employing a hybrid Tersoff–ZBL potential that [...] Read more.

Silicon-based MEMS devices are essential in extreme radiation environments but suffer progressive reliability degradation from irradiation-induced defects. Here, the generation, aggregation, and clustering of defects in single-crystal silicon were systematically investigated through molecular dynamics (MD) simulations via employing a hybrid Tersoff–ZBL potential that was validated by nanoindentation and transmission electron microscopy. The influences of the primary knock-on atom energy, temperature, and pre-strain state on defect evolution were quantified in detail. Frenkel defects were found to cause a linear reduction in the Young’s modulus and a nonlinear decline in thermal conductivity via enhanced phonon scattering. To link atomic-scale damage with device-level performance, MD-predicted modulus degradation was incorporated into finite element (FE) models of a sensing diaphragm. The FE analysis revealed that modulus reductions result in nonlinear increases in deflection and stress concentration, potentially impairing sensing accuracy. This integrated MD–FE framework establishes a robust, physics-based approach for predicting and mitigating irradiation damage in silicon-based MEMS operating in extreme environments. Full article

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

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15 pages, 1698 KB

Open AccessArticle

Fluorescence Spectroscopy Applied to Thermal Conversion of Bitumen

by Raj Divyajeetsinh, Lina M. Yañez Jaramillo, Priscila T. H. Nascimento and Arno de Klerk

Processes 2025, 13(9), 2901; https://doi.org/10.3390/pr13092901 - 11 Sep 2025

Abstract

Phase instability that develops during thermal conversion of heavy oils and bitumen limits the extent of conversion in processes such as visbreaking. It was postulated that aromatic species with conjugated unsaturated systems extending beyond the aromatic rings likely contributed to reactions leading to [...] Read more.

Phase instability that develops during thermal conversion of heavy oils and bitumen limits the extent of conversion in processes such as visbreaking. It was postulated that aromatic species with conjugated unsaturated systems extending beyond the aromatic rings likely contributed to reactions leading to phase instability, fouling, and coking. Many fluorophores have such conjugated π-electron systems. Three case studies were presented where products from thermal conversion were analyzed by fluorescence spectroscopy: (i) Cold Lake bitumen converted at 150–300 °C; (ii) asphaltenes depleted and enriched Athabasca bitumen converted at 380 °C; and (iii) Athabasca bitumen converted at 400 °C and 0.5–4.0 MPa. It was found that the fluorescence intensity of bitumen increased on thermal conversion. Fluorescence intensity increased in relation to reaction time for conversion at 150–300 °C, but it had a weak relationship with temperature. At 380 and 400 °C, this monotonic relationship was no longer apparent. There was no relationship with refractive index. Despite some overlap in fluorescence intensity values, 400 °C converted products obtained at 2.5–4.0 MPa had lower fluorescence intensity than products obtained at 0.5–2.0 MPa. Tentative explanations were offered for these observations. The change in fluorescence intensity with operating conditions and nature of the feed was consistent with the expected free radical concentration associated with the operating conditions and extent of hydrogen transfer. Although the study did not provide proof for the relationship between the fluorescence intensity and the concentration of aromatic species with conjugated unsaturated systems, the experimental observations were congruent with it. Full article

(This article belongs to the Special Issue Petroleum Characterization and Bioprocesses: Numerical and Experimental Investigation (2nd Edition))

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14 pages, 4090 KB

Open AccessArticle

Experimental Study on Water-Hammer-Effect Fracturing Based on High-Frequency Pressure Monitoring

by Yanchao Li, Hu Sun, Longqing Zou, Liang Yang, Hao Jiang, Zhiming Zhao, Ruchao Sun and Yushi Zou

Processes 2025, 13(9), 2900; https://doi.org/10.3390/pr13092900 - 11 Sep 2025

Abstract

Horizontal well multi-stage fracturing is the primary technology for deep shale gas development, but dense multi-cluster fractures are prone to non-uniform initiation and propagation, requiring real-time monitoring and interpretation techniques to adjust fracturing parameters. Although high-frequency water hammer pressure-monitoring technology shows diagnostic potential, [...] Read more.

Horizontal well multi-stage fracturing is the primary technology for deep shale gas development, but dense multi-cluster fractures are prone to non-uniform initiation and propagation, requiring real-time monitoring and interpretation techniques to adjust fracturing parameters. Although high-frequency water hammer pressure-monitoring technology shows diagnostic potential, the correlation mechanism between pressure response characteristics and multi-cluster fracture morphology remains unclear. This study utilized outcrop rock samples from the Longmaxi Formation shale to construct a long-injection-tube pipeline system and a 1 kHz high-frequency pressure acquisition system. Through a true triaxial fracturing simulation test system, it systematically investigated the effects of flow rate (50–180 mL/min) and fracturing fluid viscosity (3–15 mPa·s) on water hammer signal characteristics and fracture morphology. The results reveal that when the flow rate rose from 50 mL/min to 180 mL/min, the initiation efficiency of transverse fractures significantly improved, artificial fractures more easily broke through bedding plane limitations, and fracture height propagation became more complete. When the fracturing fluid viscosity increased from 3–5 mPa·s to 12–15 mPa·s, fracture height propagation and initiation efficiency significantly improved, but fewer bedding plane fractures were activated. The geometric complexity of fractures positively correlated with the water hammer decay rate. This research demonstrates a link between water hammer signal features and downhole fracture morphology, giving a theoretical basis for field fracturing diagnostics. Full article

(This article belongs to the Section Energy Systems)

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22 pages, 1888 KB

Open AccessArticle

An Intelligent Design Method for Product Remanufacturing Based on Remanufacturing Information Reuse

by Chao Ke, Yichen Deng, Shijie Liu and Hongwei Cui

Processes 2025, 13(9), 2899; https://doi.org/10.3390/pr13092899 - 10 Sep 2025

Abstract

Design for remanufacturing (DfRem) is a green design mode that ensures good remanufacturability at the end-of-life (EOL) of the product. However, the diversity of service environments and operating modes makes it difficult to generate accurate DfRem solutions for the smooth implementation of remanufacturing. [...] Read more.

Design for remanufacturing (DfRem) is a green design mode that ensures good remanufacturability at the end-of-life (EOL) of the product. However, the diversity of service environments and operating modes makes it difficult to generate accurate DfRem solutions for the smooth implementation of remanufacturing. Moreover, the historical remanufacturing process contains a great deal of information conducive to DfRem. It will greatly enhance the efficiency and accuracy of remanufacturing design by feeding effective remanufacturing information back into the product design process. Unfortunately, there is a lack of direct correlation between them, which prevents remanufacturing information from effectively guiding DfRem. To improve the accuracy of DfRem solutions and the utilization rate of remanufacturing information, an intelligent design method for product remanufacturing based on remanufacturing information reuse is proposed. Firstly, rough set theory (RST) is used to identify key remanufacturability demand, and the quality function development (QFD) is used to establish a relationship between remanufacturability demand and engineering characteristics, which can accurately obtain the design objectives. Then, the correlation between remanufacturability demand, remanufacturing information, and DfRem parameters is analyzed, and the ontology technology is applied to construct the DfRem knowledge by ingratiating remanufacturing information. In addition, case-based reasoning (CBR) is applied to search for design cases from DfRem knowledge that best match the design objectives, and gray relational analysis (GRA) is used to calculate the similarity between design knowledge. Finally, the feasibility of the method is verified by taking an ordinary lathe as an example. This method has been implemented as a DfRem interface application using Visual Studio 2022 and Microsoft SQL Server 2022, and the research results indicate that this design method can accurately generate a reasonable DfRem scheme. Full article

(This article belongs to the Special Issue Artificial Intelligence Technologies and Methods for Green Manufacturing)

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20 pages, 2967 KB

Open AccessArticle

Physicochemical and Techno-Functional Properties of Extruded Corn Starch Snacks Enriched with Huitlacoche (Ustilago maydis): Effects of Extrusion Parameters and Process Optimization

by Betsabé Hernández-Santos, Jesús Rodríguez-Miranda, José M. Juárez-Barrientos, Juan G. Torruco-Uco, Emmanuel J. Ramírez-Rivera, Erasmo Herman-Lara, Carlos A. Gómez-Aldapa and Ariana González-García

Processes 2025, 13(9), 2898; https://doi.org/10.3390/pr13092898 - 10 Sep 2025

Abstract

The main objective of this research was to evaluate the effect of extrusion temperature (ET), feed moisture content (FMC), and the proportion of huitlacoche relative to corn starch (HCP/Starch) on the physicochemical, techno-functional, and color properties of an extruded snack, using response surface [...] Read more.

The main objective of this research was to evaluate the effect of extrusion temperature (ET), feed moisture content (FMC), and the proportion of huitlacoche relative to corn starch (HCP/Starch) on the physicochemical, techno-functional, and color properties of an extruded snack, using response surface methodology to optimize processing conditions and product quality. A Box–Behnken design and response surface methodology were used to model and optimize the process. The responses analyzed included residence time (RT), specific mechanical energy (SME), expansion index (EI), bulk density (BD), texture (Tex), water absorption index (WAI), water solubility index (WSI), pH, and color parameters (L*, a*, b*, C*, h°, and ΔE). Results showed that the huitlacoche proportion significantly affected BD, Tex, WSI, and color, while ET and FMC mainly influenced EI, SME, and other techno-functional traits. Multi-response optimization indicated that 150.4 °C, 15.8 g/100 g FMC, and 10–20 g/100 g HCP/Starch maximized EI (2.27) and minimized BD (0.40 g/cm³), Tex (17.5 N), and SME (347.6 J/g). The overall performance was summarized by global desirability (0.83–0.88), a metric that combines all responses into a single scale (0 = poor; 1 = is the most desired goal). The optimized conditions produced snacks with acceptable hydration capacity, pH, and color, supporting huitlacoche as a viable functional ingredient. These findings demonstrate the potential of this traditional resource for developing sustainable, value-added, and health-oriented extruded foods. Full article

(This article belongs to the Special Issue Advances in Process Detection and Control Technologies for Optimizing Food Processing)

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17 pages, 5466 KB

Open AccessArticle

Research on Photovoltaic Power Stations and Energy Storage Capacity Planning for a Multi-Energy Complementary System Considering a Combined Cycle of Gas Turbine Unit for Seasonal Load Demand

by Yongneng Ding, Yuxuan Lu, Weitao Yi, Yan Huang and Xi Zhu

Processes 2025, 13(9), 2897; https://doi.org/10.3390/pr13092897 - 10 Sep 2025

Abstract

Multi-energy systems could utilize the complementary characteristics of heterogeneous energy to improve operational flexibility and energy efficiency. However, seasonal fluctuations and uncertainty of load would have a great influence on the effectiveness of the system planning scheme. Regarding this issue, this paper proposes [...] Read more.

Multi-energy systems could utilize the complementary characteristics of heterogeneous energy to improve operational flexibility and energy efficiency. However, seasonal fluctuations and uncertainty of load would have a great influence on the effectiveness of the system planning scheme. Regarding this issue, this paper proposes a photovoltaic power (PV) station and thermal energy storage (TES) capacity planning model with considering the electrical load uncertainty based on a stochastic optimization method. And four-season load demand scenarios are built by Generative Adversarial Networks (GANs). At last, the proposed capacity configuration model is tested in a case study, and the results show the influence of seasonal fluctuations in load, scenario number, and TES capacity. Full article

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

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20 pages, 3569 KB

Open AccessArticle

Effect of Acid Treatment on the Structure of Natural Zeolite from the Shankhanai Deposit

by Sandugash Tanirbergenova, Dildara Tugelbayeva, Nurzhamal Zhylybayeva, Aizat Aitugan, Kairat Tazhu, Gulya Moldazhanova and Zulkhair Mansurov

Processes 2025, 13(9), 2896; https://doi.org/10.3390/pr13092896 - 10 Sep 2025

Abstract

Natural clinoptilolite from the Shankhanai deposit (Kazakhstan) was modified via acid and thermal treatments to improve its physicochemical and catalytic properties. The zeolite was activated using 10% nitric acid alone, nitric acid followed by thermal treatment (600 °C), and a mixed acid solution [...] Read more.

Natural clinoptilolite from the Shankhanai deposit (Kazakhstan) was modified via acid and thermal treatments to improve its physicochemical and catalytic properties. The zeolite was activated using 10% nitric acid alone, nitric acid followed by thermal treatment (600 °C), and a mixed acid solution (10% HNO₃ + 5% CH₃COOH) followed by mild thermal treatment (280 °C). Structural, textural, and thermal changes were characterized by XRD, FTIR, BET, TGA, SEM, and EDX. Nitric acid treatment increased the BET surface area from 4.95 to 59.9 m²/g but reduced crystallinity, whereas the dual-acid approach enhanced porosity and acidity while preserving framework integrity. Preliminary catalytic testing in thiophene hydrodesulfurization (HDS) revealed improved conversion (up to 20.7%) in the absence of active metals, confirming the potential of modified clinoptilolite as a catalyst support. The dual-acid method presents a promising, eco-friendly pathway for producing thermally stable and catalytically active zeolitic materials, suitable for selective hydrodesulfurization of thiophene. Full article

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

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17 pages, 2525 KB

Open AccessArticle

A Non-Destructive Deep Learning–Based Method for Shrimp Freshness Assessment in Food Processing

by Dongyu Hao, Cunxi Zhang, Rui Wang, Qian Qiao, Linsong Gao, Jin Liu and Rongsheng Lin

Processes 2025, 13(9), 2895; https://doi.org/10.3390/pr13092895 - 10 Sep 2025

Abstract

Maintaining the freshness of shrimp is a critical issue in quality and safety control within the food processing industry. Traditional methods often rely on destructive techniques, which are difficult to apply in online real-time monitoring. To address this challenge, this study aims to [...] Read more.

Maintaining the freshness of shrimp is a critical issue in quality and safety control within the food processing industry. Traditional methods often rely on destructive techniques, which are difficult to apply in online real-time monitoring. To address this challenge, this study aims to propose a non-destructive approach for shrimp freshness assessment based on imaging and deep learning, enabling efficient and reliable freshness classification. The core innovation of the method lies in constructing an improved GoogLeNet architecture. By incorporating the ELU activation function, L2 regularization, and the RMSProp optimizer, combined with a transfer learning strategy, the model effectively enhances generalization capability and stability under limited sample conditions. Evaluated on a shrimp image dataset rigorously annotated based on TVB-N reference values, the proposed model achieved an accuracy of 93% with a test loss of only 0.2. Ablation studies further confirmed the contribution of architectural and training strategy modifications to performance improvement. The results demonstrate that the method enables rapid, non-contact freshness discrimination, making it suitable for real-time sorting and quality monitoring in shrimp processing lines, and providing a feasible pathway for deployment on edge computing devices. This study offers a practical solution for intelligent non-destructive detection in aquatic products, with strong potential for engineering applications. Full article

(This article belongs to the Section Food Process Engineering)

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21 pages, 3665 KB

Open AccessArticle

Dynamic Fitting Method for Wellbore Multiphase Flow with Exponentially Weighted Parameter Updating

by Yuchen Ji, Xinrui Zhang, Mingchun Wang, Yupei Liu, Tianhao Wang, Zixiao Xing, Guoqing Han and Xiaolong Xiang

Processes 2025, 13(9), 2894; https://doi.org/10.3390/pr13092894 - 10 Sep 2025

Abstract

Accurate dynamic characterization of wellbore multiphase flow is fundamental for production optimization and real-time control in oil and gas wells. Addressing technical constraints of existing dynamic fitting methods, this study proposes a novel dynamic fitting methodology integrating physical mechanisms with exponentially weighted parameter [...] Read more.

Accurate dynamic characterization of wellbore multiphase flow is fundamental for production optimization and real-time control in oil and gas wells. Addressing technical constraints of existing dynamic fitting methods, this study proposes a novel dynamic fitting methodology integrating physical mechanisms with exponentially weighted parameter updating. The approach leverages multiphase flow theory to target the liquid holdup factor and friction factor as correction parameters for dynamic fitting. It incorporates Particle Swarm Optimization to achieve rapid and accurate fitting and introduces an Exponentially Weighted Moving Average mechanism to dynamically update parameters. By fusing historical data with real-time data, the Exponentially Weighted Moving Average method balances instantaneous responsiveness with long-term stability. Empirical validation using a dataset from Block XX of a Southern China oilfield demonstrates the superior accuracy of the fitting method under low-to-medium frequency data conditions. During data interruptions or anomalous disturbances, the method maintains high accuracy while exhibiting a low mean relative change percentage; it effectively suppressed the non-physical jumps of the fitting coefficients and maintained stable and accurate fitting. Full article

(This article belongs to the Section Energy Systems)

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22 pages, 2749 KB

Open AccessArticle

Pathway Evolution Modeling of Provincial Power Systems Under Multi-Scenario Carbon Constraints: An Empirical Analysis of Guangdong, China

by Guoxian Gong, Weijie Wu, Shuxin Luo, Yixin Li, Shucan Zhou, Haotian Yang, Jianlin Gu and Peng Wang

Processes 2025, 13(9), 2893; https://doi.org/10.3390/pr13092893 - 10 Sep 2025

Abstract

China’s energy system is transitioning from a state of coal-dependent, low-electrification to a low-carbon, high-electrification paradigm. Carbon emissions have become a central constraint that directly influences generation expansion and transmission investment decisions. This study develops a bottom-up optimization framework integrating dynamic carbon trajectories [...] Read more.

China’s energy system is transitioning from a state of coal-dependent, low-electrification to a low-carbon, high-electrification paradigm. Carbon emissions have become a central constraint that directly influences generation expansion and transmission investment decisions. This study develops a bottom-up optimization framework integrating dynamic carbon trajectories into a coupled generation–transmission–storage expansion model. Distinct carbon emission trajectories are established on the basis of Guangdong’s allocated carbon budget, and the analysis evaluates the resulting power system structures and transition pathways under each scenario. Results show that Guangdong’s clean energy transition relies on external power imports, nuclear power, and variable renewable energy (VRE), collectively accounting for 87% of generation by 2060. Flexibility requirements expand substantially, with storage capacity rising from 10% of installed VRE in 2030 to 26% in 2060. Critically, under identical cumulative carbon budgets, an accelerated decarbonization pathway achieving earlier peak emissions demonstrates a pivotal economic trade-off: it imposes modestly higher near-term operation costs but delivers significant long-term savings by avoiding prohibitively expensive end-of-period abatement measures. Specifically, advancing the emissions peak from 2030 to 2025 reduces cumulative system costs over the planning horizon by CNY 53.7 billion and lowers the 2060 levelized cost of electricity by 5.2%. Full article

(This article belongs to the Special Issue Modeling, Operation and Control in Renewable Energy Systems)

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20 pages, 2125 KB

Open AccessArticle

A Discriminative Model of Mine Inrush Water Source Based on Automatic Construction of Deep Belief Rule Base

by Zhupeng Jin, Hongcai Li and Yanwei Tian

Processes 2025, 13(9), 2892; https://doi.org/10.3390/pr13092892 - 10 Sep 2025

Abstract

Mine water inrush is a significant environmental catastrophe during the coal mining process, and the timely discrimination of the source of water inrush is the key to ensuring safe production in coal mines. This work suggests a mine water inrush—belief rule base (MWI-BRB) [...] Read more.

Mine water inrush is a significant environmental catastrophe during the coal mining process, and the timely discrimination of the source of water inrush is the key to ensuring safe production in coal mines. This work suggests a mine water inrush—belief rule base (MWI-BRB) source discrimination model to overcome the interpretability and performance issues with conventional models. MWI-BRB firstly automatically constructs the reference values of prerequisite attributes using the Sum of Squared Errors—K-means++ algorithm, which effectively combines expert knowledge and data-driven methods, and solves the limitation of the traditional belief rule base model relying on specialist knowledge. Secondly, the hierarchical incremental structure solves the rule explosion problem caused by complex features while using XGBoost to select features. Finally, in the inference process, the model adopts an evidential reasoning algorithm to realize transparent causal inference, guaranteeing the model’s interpretability and transparency. The Penalized Covariance Matrix Adaptation Evolution Strategy algorithm optimizes the model parameters to increase the discriminative accuracy of the model even more. Experimental results on a real coal mine dataset (a total of 67 samples from Hebei, China, covering four water inrush sources) demonstrate that the proposed MWI-BRB achieves 95.23% accuracy, 95.23% recall, and 95.36% F1-score under a 7:3 training–testing split with parameter tuning performed via leave-one-out cross-validation. The near-identical values across accuracy, recall, and F1-score reflect the balanced nature of the dataset and the robustness of the model across different evaluation metrics. Compared with baseline models, MWI-BRB’s accuracy and recall are 4.78% higher than BPNN and 9.52% higher than KNN, RF, and XGBoost; its F1-score is 4.85% higher than BPNN, 10.64% higher than KNN, 10.19% higher than RF, and 9.65% higher than XGBoost. Moreover, the model maintains high interpretability. In conclusion, the MWI-BRB model can realize efficient and accurate water inrush source discrimination in complex environments, which provides a feasible technical solution for the prevention and control of mine water damage. Full article

(This article belongs to the Section Energy Systems)

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25 pages, 2287 KB

Open AccessArticle

Processing High-Solid Sludge Through Hydrothermal Liquefaction to Boost Anaerobic Fermentation and Bioresource Yield

by Chun-Ming Yen, Chang-Lung Han and Jiunn-Jyi Lay

Processes 2025, 13(9), 2891; https://doi.org/10.3390/pr13092891 - 10 Sep 2025

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Abstract

The increasing need for effective sludge management has positioned hydrothermal liquefaction (HTL) as a viable solution, harnessing its capability to transform organic materials into renewable resources under elevated temperature and pressure conditions. This research seeks to assess the performance of HTL in processing [...] Read more.

The increasing need for effective sludge management has positioned hydrothermal liquefaction (HTL) as a viable solution, harnessing its capability to transform organic materials into renewable resources under elevated temperature and pressure conditions. This research seeks to assess the performance of HTL in processing high-solid organic sludge by examining the removal efficiencies of chemical oxygen demand (COD), total solids (TS), and suspended solids (SS), together with improvements in biogas potential (BGP) and hydrogen yield. Experimental procedures were carried out within a temperature range of 100–210 °C and pressure levels of 20–80 kg/cm², using a hydrogen-producing microbiome (HMb) and anaerobically digested sludge as inoculants for anaerobic fermentation. Multivariate analysis was applied to investigate the influence of temperature and pressure on COD, TS, and SS removal rates as well as BGP, while a series of batch tests further confirmed the effects of these parameters on fermentation outcomes. Findings revealed that COD, SS, and TS removal efficiencies reached 90.6%, 91.5%, and 87.4%, respectively, under conditions of 100 °C and 60 kg/cm². The maximum biogas potential (BGP) of approximately 500 mL was attained at 180 °C, whereas hydrogen production demonstrated substantial enhancement within the HTL pressure range of 40–60 kg/cm², decreasing beyond this range. Additionally, total dissolved solids (TDS) reached a peak concentration of 389 g/L under conditions of 180 °C and 40 kg/cm², emphasizing HTL’s positive impact on enhancing methane fermentation efficiency. These findings demonstrate that HTL pretreatment, when operated under optimized temperature and pressure conditions, offers a promising approach for enhancing both waste reduction and bioenergy recovery from high-solid organic sludge. Full article

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

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