Processes

23 pages, 3384 KB

Open AccessArticle

An Enhanced Workflow for Quantitative Evaluation of Fluid and Proppant Distribution in Multistage Fracture Treatment with Distributed Acoustic Sensing

by Wenqiang Liu, Bobo Li, Zhengguang Zhao, Rou Wen, Yu Bai, Haoran Guo, Jizhou Tang and Chunlei Wang

Processes 2025, 13(11), 3738; https://doi.org/10.3390/pr13113738 (registering DOI) - 19 Nov 2025

Abstract

Distributed Acoustic Sensing (DAS) technology has emerged as a valuable tool for monitoring fluid and proppant injection during hydraulic fracturing. One of its applications involves estimating cluster-level fluid and proppant allocations in real time. However, significant uncertainties remain in the quantitative calculation of [...] Read more.

Distributed Acoustic Sensing (DAS) technology has emerged as a valuable tool for monitoring fluid and proppant injection during hydraulic fracturing. One of its applications involves estimating cluster-level fluid and proppant allocations in real time. However, significant uncertainties remain in the quantitative calculation of injected volumes due to limitations in frequency band energy (FBE) data extraction, cluster depth determination, and volume estimation algorithms. This study presents an enhanced workflow for quantitatively estimating fluid and proppant allocations from DAS-derived FBE data while minimizing uncertainties. The workflow integrates multi-band and summed-energy analyses with the optimized selection of calculation algorithms to reduce interpretation uncertainties. The results show that FBE [50–200 Hz] exhibits the highest sensitivity to injection activities, local minima on summed FBE can accurately pinpoint top and bottom depths of each cluster, and a power-law model linking acoustic energy to flow rate allows for quantitative calculation. Field applications demonstrate consistent improvements in fluid and proppant volume estimation accuracy. Validation against post-frac numerical simulations shows that estimated fluid and proppant allocations agree within a 6% error, confirming the method’s quantitative reliability. By addressing key sources of uncertainty, this approach enhances DAS-based fracture diagnostics and provides actionable guidance for real-time decision making in unconventional completions. Full article

(This article belongs to the Special Issue Geological and Engineering Problems in the Development of Unconventional Oil and Gas Reservoirs (2nd Edition))

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19 pages, 778 KB

Open AccessFeature PaperArticle

Optimization of Green Extraction of Antioxidant Compounds from Blackthorn Pomace (Prunus spinosa L.) Using Natural Deep Eutectic Solvents (NADES)

by Sara Hourani, Jelena Vukosavljević, Nemanja Teslić, Ružica Ždero Pavlović, Boris M. Popović and Branimir Pavlić

Processes 2025, 13(11), 3737; https://doi.org/10.3390/pr13113737 (registering DOI) - 19 Nov 2025

Abstract

Blackthorn (Prunus spinosa L.) is a wild, understudied plant rich in bioactive compounds such as polyphenols with designated antioxidant potential. The main objective of this research was to optimize ultrasound-assisted extraction of blackthorn pomace using natural deep eutectic solvents (NADES). To obtain [...] Read more.

Blackthorn (Prunus spinosa L.) is a wild, understudied plant rich in bioactive compounds such as polyphenols with designated antioxidant potential. The main objective of this research was to optimize ultrasound-assisted extraction of blackthorn pomace using natural deep eutectic solvents (NADES). To obtain the highest yield of polyphenols and improved in vitro antioxidant activity, response surface methodology (RSM) and central composite experimental design were used. The screening step of the study included ten different NADESs using a one-factor-at-a-time approach. Two NADES mixtures (N12, containing proline and lactic acid in a molar ratio of 1:2, and N14, containing choline chloride and glycerol in a molar ratio of 1:1) were chosen for the second step of the study, which aimed to select the most influential process parameters. A fractional factorial 2⁵⁻¹ design was used, varying five different parameters at two levels: extraction time (30 and 60 min), extraction temperature (40 and 50 °C), and liquid-to-solid ratio (10 and 20 mL/g), water content in NADES (15 and 20%), and NADES type (N12 and N14). After the second step, N12 containing 20% water was chosen as the most potent solvent for the optimization study. For the final step, the other three parameters were varied on three levels, and thus optimal conditions were obtained (extraction time 90 min, extraction temperature 65 °C, and liquid-to-solid ratio 22.65 mL/g). Blackthorn juice was also tested in the first step, as well as under optimal conditions established for pomace, in order to evaluate whether these conditions are suitable for juice and to determine the percentage of improvement in extraction efficiency. Full article

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

18 pages, 3174 KB

Open AccessArticle

Hydration Properties and Modeling of Ternary Systems of Mechanically Modified Municipal Solid Waste Incineration Fly Ash–Blast Furnace Slag–Cement

by Zedong Qiu, Ziling Peng, Zhen Hu, Sha Wan, Gang Li, Xintong Xiao, Kun Liu, Zhicheng Xiang and Xian Zhou

Processes 2025, 13(11), 3736; https://doi.org/10.3390/pr13113736 (registering DOI) - 19 Nov 2025

Abstract

Municipal solid waste incineration fly ash (MSWIFA) can be reused as an admixture in cementitious materials, but its low activity limits its utilization as a resource. In this study, we systematically investigated the mineral and grinding characteristics of MSWIFA and then studied its [...] Read more.

Municipal solid waste incineration fly ash (MSWIFA) can be reused as an admixture in cementitious materials, but its low activity limits its utilization as a resource. In this study, we systematically investigated the mineral and grinding characteristics of MSWIFA and then studied its pretreatment and activation via mechanical force–surface modification. The results indicate that the fineness and angle of repose of MSWIFA during grinding are inversely proportional to grinding time, while specific surface area and powder fluidity increase. Agglomeration occurs in the later stage, and particle size fluctuates. Gray correlation analysis shows that MSWIFA powder with a particle size of 16–45 μm contributes most to compressive strength improvement. The composite surface modifier TEA-STPP benefits grinding, shortens ball-milling time, and increases active particle size content, thereby promoting hydration activity. The best process regarding the modifier was determined. MSWIFA and blast furnace slag (BFS) accelerate early hydration of ordinary Portland cement (OPC) and increase its reaction participation, promoting the generation of calcium chloroaluminate (Friedel’s salt) and monosulfate-aluminate phases (SO₄-AFm) and significantly enhancing the hydration of tricalcium aluminate (C₃A) in OPC. Full article

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

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20 pages, 1624 KB

Open AccessArticle

Experimental Study on Gas Particle Flow Characteristics of a Novel Stable Combustion Burner Under Different Primary Air Velocities

by Xiangjun Long, Leikai Deng, Nan Zhang, Weiyu Wang, Defu Xin, Zhen Chen and Zhengqi Li

Processes 2025, 13(11), 3735; https://doi.org/10.3390/pr13113735 (registering DOI) - 19 Nov 2025

Abstract

Existing faulty coal-fired units generally achieve oil-free stable combustion only at loads over 30%, failing to meet low load regulation demands. To address the insufficient flexibility of boilers, a novel flame-stabilization theory was developed for retrofitting a 350 MW faulty coal-fired unit boiler. [...] Read more.

Existing faulty coal-fired units generally achieve oil-free stable combustion only at loads over 30%, failing to meet low load regulation demands. To address the insufficient flexibility of boilers, a novel flame-stabilization theory was developed for retrofitting a 350 MW faulty coal-fired unit boiler. Based on the actual burner dimensions of the 350 MW unit boiler, a geometric scaling ratio of 1:7 between model and actual burners was established. Phase Doppler Anemometry (PDA) was employed to conduct gas particle flow experiments on the model burner, revealing the impact of different primary air velocities on the gas particle flow characteristics of the novel stabilized flow burner. The analysis of experimental results suggests that, When the primary air velocity is 9 m/s, a central recirculation zone forms at the burner outlet. At a primary air velocity of 10 m/s, an annular recirculation zone develops with a relatively large coverage area. When the primary air velocity increases to 11 m/s, the extent of the annular recirculation zone diminishes. At a primary air velocity of 10 m/s, an extensive annular recirculation zone forms at the burner outlet, which appears to provide sufficient energy for the ignition of pulverized coal. Elevated pulverized coal concentration near the burner centerline facilitates the formation of a high-temperature oxygen-lean reducing atmosphere, suppressing fuel-based NO_x generation. Therefore, it is recommended to set the actual operating parameters of the novel stabilized flow burner based on the 10 m/s primary air velocity condition in the gas particle flow experiments. Full article

(This article belongs to the Section Energy Systems)

25 pages, 15404 KB

Open AccessArticle

Voltage Balancing of a Bipolar DC Microgrid with Unbalanced Unipolar Loads and Sources

by Mateus Pinheiro Dias, Debora P. Damasceno, Eliabe Duarte Queiroz, Kristian P. dos Santos, Jose C. U. Penã and José A. Pomilio

Processes 2025, 13(11), 3734; https://doi.org/10.3390/pr13113734 (registering DOI) - 19 Nov 2025

Abstract

This paper presents the validation of a voltage balancing converter for a bipolar DC microgrid designed to ensure reliable operation in both grid-connected and islanded modes. This microgrid includes unipolar constant power loads (CPL), a unipolar Battery Energy Storage System (BESS), and local [...] Read more.

This paper presents the validation of a voltage balancing converter for a bipolar DC microgrid designed to ensure reliable operation in both grid-connected and islanded modes. This microgrid includes unipolar constant power loads (CPL), a unipolar Battery Energy Storage System (BESS), and local PV generation. The BESS converter employs a V–I droop strategy using only inductor current feedback, reducing sensing requirements while maintaining plug-and-play capability and ensuring smooth transitions between connected and islanded modes. In such a microgrid, the voltage balancing converter regulates the differential voltages under severe unbalanced load conditions and during transients caused by changes in unipolar loads and sources. The experimental results validate the voltage balancing strategy across various scenarios in a small-scale prototype. The results show tight voltage regulation under unbalanced conditions, and smooth transitions during load transients and unintentional islanding, even if there is no dc voltage source in one of the poles of the bipolar dc bus. For both conditions, the imbalance between the unipolar voltages is less than 0.5% of the total bipolar voltage. Full article

(This article belongs to the Special Issue Advances in Power Converters in Energy and Microgrid Systems)

18 pages, 1094 KB

Open AccessArticle

A TRIZ-Based Experimental Design Approach to Enhance Wave Soldering Efficiency in Electronics Manufacturing

by Chia-Nan Wang, Nai-Chi Shiue, Van-Thanh Phan and Dang-Quy Hong

Processes 2025, 13(11), 3733; https://doi.org/10.3390/pr13113733 - 19 Nov 2025

Abstract

Wave soldering is a technological process that allows for the simultaneous soldering of multiple locations on the same circuit board. Its major defects, such as tin bridging and insufficient tin filling, continue to challenge manufacturers, resulting in increased rework, labor, and operational costs. [...] Read more.

Wave soldering is a technological process that allows for the simultaneous soldering of multiple locations on the same circuit board. Its major defects, such as tin bridging and insufficient tin filling, continue to challenge manufacturers, resulting in increased rework, labor, and operational costs. Therefore, reducing errors in wave soldering is crucial to ensure the best quality for customers and achieve cost savings for the company. This study aims to enhance wave soldering performance by using an integrated approach that combines Teoriya Resheniya Izobreatatelskikh Zadatch (TRIZ) and Design of Experiment (DOE) for empirical improvement in an Original Equipment Manufacturer (OEM) factory, a subsidiary of a global OEM company. The results are sound: we eliminated tin till bridge defects by 88%, achieved a 33% reduction in manpower, and increased production volumes by 6%. This proposed framework can be utilized in other electronics manufacturing factories and related industries. Full article

(This article belongs to the Special Issue Recent Trends in Advanced Manufacturing Technologies for Materials Processing and Production)

19 pages, 4050 KB

Open AccessArticle

Experimental and Simulation Research on Straight-Through Cyclone Water Separator: Effects of Structural and Operational Parameters on Separation Performance

by Yihan Chen, Xingjuan Zhang, Chao Wang and Han Yang

Processes 2025, 13(11), 3732; https://doi.org/10.3390/pr13113732 - 19 Nov 2025

Abstract

The aircraft air-cycle system (ACS) provides cabin cooling, dehumidification, and pressurization. As a key component, the water separator removes free moisture from the air, preventing turbine icing/blockage under high humidity and avoiding humidity-induced electronics failures, thus ensuring reliable ACS operation. Existing studies focus [...] Read more.

The aircraft air-cycle system (ACS) provides cabin cooling, dehumidification, and pressurization. As a key component, the water separator removes free moisture from the air, preventing turbine icing/blockage under high humidity and avoiding humidity-induced electronics failures, thus ensuring reliable ACS operation. Existing studies focus mainly on oil and chemical applications, with limited work for aircraft ACS. To address this research gap, this study investigates a straight-through cyclone water separator for aircraft ACS applications. We built a test platform to measure separation efficiency and conducted experiments at swirl angles of 20°, 30°, and 40°. A simulation model based on the Reynolds Stress turbulence model and a discrete phase model was established, and its simulation efficiency agreed with experiments within 4.1%. Simulation on water separator under high-pressure and low-pressure conditions were conducted, revealing internal flow fields and droplet dynamics. Results show each swirl angle has a distinct high-efficiency operating range, enabling selection according to system parameters across air mass flow rates; under varying humidification rate, the 40° swirl generator performed best. Simulations further indicate that higher operating pressure markedly improves performance: pressure loss decreased from 4.5 kPa to 0.7 kPa, while separation efficiency increased by 30.7%. Full article

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

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34 pages, 1873 KB

Open AccessFeature PaperReview

Artificial Intelligence in Rice Quality and Milling: Technologies, Applications, and Future Prospects

by Benjamin Ilo, Abraham Badjona, Yogang Singh, Alex Shenfield and Hongwei Zhang

Processes 2025, 13(11), 3731; https://doi.org/10.3390/pr13113731 - 19 Nov 2025

Abstract

The global demand for high-quality rice necessitates advancements in milling technologies and quality assessment techniques that are rapid, accurate, and scalable. Traditional methods of rice evaluation are time-consuming and subjective, and are increasingly being replaced by artificial intelligence driven solutions that offer non-destructive, [...] Read more.

The global demand for high-quality rice necessitates advancements in milling technologies and quality assessment techniques that are rapid, accurate, and scalable. Traditional methods of rice evaluation are time-consuming and subjective, and are increasingly being replaced by artificial intelligence driven solutions that offer non-destructive, real-time monitoring capabilities. This review presents a comprehensive synthesis of current AI applications including machine vision, deep learning, spectroscopy, thermal imaging, and hyperspectral imaging for the assessment and classification of rice quality across various stages of processing. Major emphasis is put on the recent advances in convolutional neural networks (CNNs), YOLO architectures, and Mask R-CNN models, and their integration into industrial rice milling systems is discussed. Additionally, the review highlights next steps, notably designing lean AI architectures suitable for edge computing, hybrid imaging systems, and the creation of open-access datasets. Across recent rice-focused studies, classification accuracies for grading and varietal identification are typically ≥

90 %

using machine vision and CNNs, while NIR–ANN models for physicochemical properties (e.g., moisture/protein proxies) commonly report strong fits (

R^{2} \approx 0.90 – 0.99

). End-to-end detectors/segmenters (e.g., YOLO/YO-LACTS) achieve high precision suitable for near real-time inspection. These results indicate that AI-based approaches can substantially outperform conventional evaluation in both accuracy and throughput. Full article

(This article belongs to the Special Issue Machine Learning, Control, and Optimization in Manufacturing and Industry 4.0)

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18 pages, 1335 KB

Open AccessArticle

Impact of Oil on the Bacterial Community of the Sierozems of the ‘Daulet Asia’ Landfill in Southern Kazakhstan

by Roza Narmanova, Yanina Delegan, Yulia Kocharovskaya, Alexander Bogun, Irina Puntus, Lenar Akhmetov, Anna Vetrova, Angelina Baraboshkina, Nelly Chayka, Svetlana Kuzhamberdieva, Nurhan Suleymenov, Saken Kanzhar, Dinara Niyazova, Indira Yespanova, Bekhzan Alimkhan, Meruert Tolegenkyzy, Klara Darmagambet, Karima Arynova, Nurbol Appazov and Andrey Filonov

Processes 2025, 13(11), 3730; https://doi.org/10.3390/pr13113730 - 19 Nov 2025

Abstract

In the Republic of Kazakhstan (one of the top 10 oil-producing countries in the world), the remediation of oil pollution found in unproductive soils under the conditions of a sharply continental arid climate is a highly relevant problem. The aims of this work [...] Read more.

In the Republic of Kazakhstan (one of the top 10 oil-producing countries in the world), the remediation of oil pollution found in unproductive soils under the conditions of a sharply continental arid climate is a highly relevant problem. The aims of this work are to study the biodegradation capacity of the gray soil of the ‘Daulet Asia’ landfill, assess the degradative potential of indigenous oil-degrading strains and changes in the composition of the soil microbial community. Analytical chemistry methods, distillation and chromatographic mass spectrometry were used for oil analysis; gravimetry and IR spectroscopy were used to evaluate oil degradation. Standard microbiological techniques were employed to isolate and cultivate microorganisms and metagenomic sequencing was carried out using Oxford Nanopore technology. Raw data processing and subsequent analysis were performed using modern software packages. Three isolated strains of interest were identified based on the analysis of 16S rRNA gene fragment sequences. The studied soil has low biodegradation capacity (oil loss was 6.2% on day 60), possibly due to the low abundance and weak activity of indigenous hydrocarbon-oxidizing microorganisms. The taxonomic composition of the microbiome in the studied soil suggests some potential for oil degradation. Assessment of the effectiveness of oil degradation by the indigenous microbiome indicates that this potential can be realized only marginally in situ. Isolated oil-degrading strains were identified as belonging to the Rhodococcus and Kocuria genera. Effective oil removal from the studied soil requires the introduction of active microorganisms (e.g., as part of biopreparations). Considering the characteristics of the hot arid climate, for bioremediation of contaminated sierozems of Southern Kazakhstan, it is advisable to use halotolerant oil-degrading microorganisms with a wide temperature range that are capable of degrading hydrocarbons under moisture deficiency. Full article

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

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15 pages, 2412 KB

Open AccessArticle

Isolation of Bioactive Metabolites from Fusarium fujikuroi: GC-MS Profiling and Bioactivity Assessment

by Zainab Farooq, Sobia Nisa, Eman Y. Santali, Ruwida M. K. Omar and Ashraf Ali

Processes 2025, 13(11), 3729; https://doi.org/10.3390/pr13113729 - 19 Nov 2025

Abstract

In the present study, the endophytic fungus Fusarium fujikuroi was isolated from the medicinal plant Debregeasia salicifolia and cultivated for the extraction of bioactive metabolites. The crude extract was fractionated via gravity column chromatography using solvents of increasing polarity (n-hexane, n-hexane/chloroform 1:1 v [...] Read more.

In the present study, the endophytic fungus Fusarium fujikuroi was isolated from the medicinal plant Debregeasia salicifolia and cultivated for the extraction of bioactive metabolites. The crude extract was fractionated via gravity column chromatography using solvents of increasing polarity (n-hexane, n-hexane/chloroform 1:1 v/v, chloroform, ethyl acetate, and methanol) to isolate bioactive compounds. The antimicrobial activity of these fractions was evaluated against pathogenic bacteria (Bacillus subtilis, Staphylococcus aureus, Pseudomonas aeruginosa, and Escherichia coli). Most extracts exhibited significant antimicrobial activity, with the n-hexane/chloroform fraction (HCF) showing the highest efficacy (18 mm inhibition zone), followed by the n-hexane fraction while Ciprofloxacin was used as a positive control. Fractions were tested in triplicate; antibacterial activities (p < 0.05) were highest in the HCF. Bioactive compounds from the most potent fractions were further purified and analyzed using gas chromatography-mass spectrometry (GC-MS). The GC-MS profiling revealed the presence of diverse bioactive metabolites, including polycyclic aromatic hydrocarbons (PAHs), phenols, and fatty acids. Notably, several of these compounds have not been previously reported in Fusarium fujikuroi, highlighting the potential for novel antimicrobial agents from this endophytic strain. In silico toxicity prediction using the ProTox-II tool indicated that the major compounds possess low to moderate toxicity profiles, supporting their potential safety for further biological evaluation. Full article

(This article belongs to the Special Issue Technologies for Production, Processing, and Extraction of Natural Products, 3rd Edition)

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24 pages, 850 KB

Open AccessArticle

Spatio-Temporal Artificial Intelligence for Multi-Hazard-Aware Renewable Energy Site Selection Using Integrated Geospatial and Climate Data

by Katleho Moloi, Kwabena Addo and Ernest Mnkandla

Processes 2025, 13(11), 3728; https://doi.org/10.3390/pr13113728 - 19 Nov 2025

Abstract

The siting of renewable energy systems (RESs) in regions vulnerable to multiple climate hazards presents a critical challenge for sustainable infrastructure planning. Traditional approaches, primarily driven by static assessments of solar and wind potential, often neglect the compounded risks posed by floods, droughts, [...] Read more.

The siting of renewable energy systems (RESs) in regions vulnerable to multiple climate hazards presents a critical challenge for sustainable infrastructure planning. Traditional approaches, primarily driven by static assessments of solar and wind potential, often neglect the compounded risks posed by floods, droughts, and windstorms, resulting in investments that are operationally vulnerable and economically unsustainable. This study proposes a novel spatio-temporal artificial intelligence (AI) framework for multi-objective RES deployment that integrates satellite-derived resource maps, high-resolution hazard data, and dynamic climate time series into a unified optimization pipeline. The methodology employs a gated recurrent unit (GRU)-based encoder to capture temporal hazard dynamics, combined with a multi-objective evolutionary algorithm (NSGA-II) to balance energy yield and resilience. A case study in South Africa’s Vhembe District demonstrates the framework’s effectiveness: the proposed model reduces the average hazard exposure by 31.6% while preserving 96.4% of the baseline energy output. Attention-based saliency analysis reveals that flood and windstorm hazards are the dominant drivers of site exclusion. Compared to conventional siting methods, the proposed framework achieves superior trade-offs between performance and risk, ensuring alignment with South Africa’s Just Energy Transition and Climate Adaptation strategies. The results confirm the value of spatio-temporal embeddings and hazard-aware multi-objective optimization in guiding resilient, data-driven energy infrastructure development. This model offers direct benefits to energy planners, climate adaptation agencies, and policymakers seeking to implement resilient, data-driven renewable energy strategies in hazard-prone regions. Full article

(This article belongs to the Section Energy Systems)

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20 pages, 3728 KB

Open AccessArticle

A Multi-Source Fusion-Based Material Tracking Method for Discrete–Continuous Hybrid Scenarios

by Kaizhi Yang, Xiong Xiao, Yongjun Zhang, Guodong Liu, Xiaozhan Li and Fei Zhang

Processes 2025, 13(11), 3727; https://doi.org/10.3390/pr13113727 - 19 Nov 2025

Abstract

Special steel manufacturing involves both discrete processing events and continuous physical flows, forming a representative discrete–continuous hybrid production system. However, due to the visually homogeneous surfaces of steel products, the highly dynamic production environment, and frequent disturbances or anomalies, traditional single-source tracking approaches [...] Read more.

Special steel manufacturing involves both discrete processing events and continuous physical flows, forming a representative discrete–continuous hybrid production system. However, due to the visually homogeneous surfaces of steel products, the highly dynamic production environment, and frequent disturbances or anomalies, traditional single-source tracking approaches struggle to maintain accurate and consistent material identification. To address these challenges, this paper proposes a multi-source fusion-based material tracking method tailored for discrete–continuous hybrid scenarios. First, a state–event system (SES) is constructed based on process rules, enabling interpretable reasoning of material states through event streams and logical constraints. Second, on the visual perception side, a YOLOv8-SE detection network embedded with the squeeze-and-excitation (SE) channel attention mechanism is designed, while the DeepSORT tracking framework is improved to enhance weak feature extraction and dynamic matching for visually similar targets. Finally, to handle information conflicts and cooperation in multi-source fusion, an improved Dempster–Shafer (D-S) evidence fusion strategy is developed, integrating customized anomaly handling and fault-tolerance mechanisms to boost decision reliability in conflict-prone regions. Experiments conducted on real special steel production lines demonstrate that the proposed method significantly improves detection accuracy, ID consistency, and trajectory integrity under complex operating conditions, while enhancing robustness against modal conflicts and abnormal scenarios. This work provides an interpretable and engineering-feasible solution for end-to-end material tracking in hybrid manufacturing systems, offering theoretical and methodological insights for the practical deployment of multi-source collaborative perception in industrial environments. Full article

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

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27 pages, 6086 KB

Open AccessArticle

Application of Hybrid Cellular Automata Method for High-Precision Transient Stiffness Design of a Press Machine Frame

by Zeqi Tong, Chenlei Lin, Feng Li and Tingting Chen

Processes 2025, 13(11), 3726; https://doi.org/10.3390/pr13113726 - 18 Nov 2025

Abstract

It is crucial to investigate methods for improving the stiffness performance of machine tools according to their specific dynamic working conditions. This paper presents a complete computer-aided workflow for structural transient topology optimization (TO) design, which is applied to the structural design issue [...] Read more.

It is crucial to investigate methods for improving the stiffness performance of machine tools according to their specific dynamic working conditions. This paper presents a complete computer-aided workflow for structural transient topology optimization (TO) design, which is applied to the structural design issue of the JH31-250 press machine (Zhejiang Weili Forging Machinery Co., Ltd., Shaoxing, China). The stiffness influenced by the shape of the press frame under long-term dynamic impact load is analyzed, and an optimal design for the frame structure of the press machine is explored. In order to reduce the iteration time of the dynamic analysis, we also proposed a way to simplify the physical structure of the machine tool into a thin-walled structure model with artificial pseudo-density and introduced the hybrid cellular automata (HCA) criterion to obtain the topological iteration direction. This simplified model can be transformed back into 3D solid design of the press. The maximum relative displacement of the worktable in this optimized press model is 0.4896 mm, which is reduced by 31.02% compared to the original press model, which shows that the transient dynamic stiffness of the press machine frame is improved. This work presents a topological optimization method and path, which can be used for the optimization of dynamic stiffness in forging machine tools, and proves the correctness and effectiveness of the design for the transient dynamic stiffness of the frame. Full article

(This article belongs to the Special Issue 2nd Edition of Control Design and Numerical Computation in Manufacturing Process System)

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19 pages, 3375 KB

Open AccessArticle

Bioactive Properties of Polyphenolic Extracts from Flourensia cernua Obtained by Emerging Technologies Under a Taguchi L18 Orthogonal Array

by Andrea G. Valero-Mendoza, Alberto Nuncio, Mayela Govea Salas, Alejandro Zugasti-Cruz, Leopoldo J. Ríos-González, Juan A. Ascacio-Valdés, Thelma K. Morales-Martínez, Marisol Cruz-Requena and Miguel A. Medina-Morales

Processes 2025, 13(11), 3725; https://doi.org/10.3390/pr13113725 - 18 Nov 2025

Abstract

Flourensia cernua, commonly known as hojasén, is an endemic species from northern Mexico used in herbal medicine as a remedy for various stomach and respiratory ailments. In addition to its medicinal applications, this plant has notable antioxidant potential, making it a promising [...] Read more.

Flourensia cernua, commonly known as hojasén, is an endemic species from northern Mexico used in herbal medicine as a remedy for various stomach and respiratory ailments. In addition to its medicinal applications, this plant has notable antioxidant potential, making it a promising area of study. A crucial aspect in plant studies is the extraction method used, as conventional approaches can diminish the bioactivities present and affect the environment. This study aims to compare two sustainable extraction techniques, ultrasound and microwave-assisted (UAE/MAE), to maximize the yield of polyphenolic compounds from F. cernua. The Taguchi L18 orthogonal array was employed to evaluate total polyphenols and to examine independent variables, such as solvent concentration, temperature, and time. Additionally, the total flavonoid content and antioxidant activity were evaluated using the radicals ABTS^●+ and DPPH^●, and the compounds were identified using RP-HPLC-ESI-MS. The results indicated that ultrasound showed better performance in recovering total bioactive compounds, correlating with antioxidant activity. Moreover, the in vitro, hemolytic, and antihemolytic assays demonstrated that F. cernua extracts are biocompatible and exhibit significant protective activity against oxidative damage in erythrocytes, supporting their potential cytoprotective and antioxidant properties. This suggests that ultrasound-assisted extraction (UAE) is an effective method for extracting phenolic compounds from F. cernua, with potential for optimizing conditions and facilitating biotechnological and therapeutic applications. Full article

(This article belongs to the Special Issue Extraction and Application Process of Bioactive Substances)

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23 pages, 1635 KB

Open AccessArticle

Active–Reactive Coordination Optimal Dispatch of Active Distribution Network Considering Grid Balance Degree

by Xin Yang, Fan Zhou, Ran Xu, Yongjie Wang and Jingjing Zhang

Processes 2025, 13(11), 3724; https://doi.org/10.3390/pr13113724 - 18 Nov 2025

Abstract

To address the impact of source-load uncertainty on voltage security and power flow distribution, this study proposes an active distribution network (ADN) active–reactive power coordinated optimal dispatch strategy that incorporates the grid balance degree (GBD). First, we analyzed GBD by defining it across [...] Read more.

To address the impact of source-load uncertainty on voltage security and power flow distribution, this study proposes an active distribution network (ADN) active–reactive power coordinated optimal dispatch strategy that incorporates the grid balance degree (GBD). First, we analyzed GBD by defining it across three key dimensions: power flow, voltage, and network structure. We combined GBD with economic indicators to establish a pre-assessment indicators system to determine grid operational status. Second, to address source-load uncertainty, a dispatch model is established, incorporating a load factor penalty term into the optimal objective. Nonlinear terms in the model are linearized for efficient solution using the Gurobi solver. Finally, GBD is adjusted through measures such as load factor penalty threshold, voltage constraint upper/lower limits, and network restructuring. The optimal dispatch strategy is selected by comparing pre-assessment indicators of operational states across different dispatch schemes. Case studies demonstrate that compared to the baseline dispatch scheme, the proposed strategy achieves a 17.4% reduction in heavy load rates, a 5.7% decrease in power flow entropy, a 5.2% reduction in voltage peak-to-valley difference rates, and a 3% decrease in network losses. Although operating costs slightly increase by 0.56%, the operation reliability of the distribution network and power quality are further optimized. This fully demonstrates the gain value of GBD optimization and provides a reference for the optimization of ADN dispatch to achieve high operational reliability. Full article

(This article belongs to the Section Energy Systems)

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24 pages, 4157 KB

Open AccessFeature PaperArticle

Physiological and Metabolic Challenges of Flocculating Saccharomyces cerevisiae in D-Lactic Acid Fermentation Under High-Glucose and Inhibitory Conditions

by Dianti Rahmasari, Prihardi Kahar, Filemon Jalu Nusantara Putra and Chiaki Ogino

Processes 2025, 13(11), 3723; https://doi.org/10.3390/pr13113723 - 18 Nov 2025

Abstract

Lactic acid is an important biobased chemical widely used in the production of biodegradable plastics, food, and pharmaceuticals. However, the application of flocculant Saccharomyces cerevisiae remains limited in addressing stresses such as high-glucose and inhibitor-rich conditions derived from biomass, particularly in D-lactic acid [...] Read more.

Lactic acid is an important biobased chemical widely used in the production of biodegradable plastics, food, and pharmaceuticals. However, the application of flocculant Saccharomyces cerevisiae remains limited in addressing stresses such as high-glucose and inhibitor-rich conditions derived from biomass, particularly in D-lactic acid (D-LA) production. This study investigates two genetically engineered S. cerevisiae F118 strains, ΔCYB2::LpDLDH and ΔPDC1::LpDLDH, for D-LA production under high-glucose and inhibitor-stress conditions that mimic lignocellulosic hydrolysates in shake-flask fermentation. At 150 g/L glucose, ΔCYB2::LpDLDH produced 41 ± 0.73 g/L D-LA, whereas ΔPDC1::LpDLDH yielded 80 ± 1.78 g/L, corresponding to 27% and 53% of the theoretical yield, respectively. Calcium carbonate (CaCO₃) supplementation enhanced glucose consumption and strengthened flocculation in ΔPDC1::LpDLDH. The addition of 5% inhibitory chemical compounds (ICCs) consisting of furfural, HMF, and weak acids redirected carbon flux in ΔCYB2::LpDLDH toward D-LA formation and reduced ethanol byproduct accumulation. Transcriptomic analysis revealed the upregulation of stress-response genes (HOG1, TPS1) and cell-wall remodeling genes (CRH1, SCW10) in response to high-glucose stress. The strongly flocculent F118ΔCYB2::LpDLDH strain exhibited greater tolerance to weak acids and furfural than the weakly flocculent F118ΔPDC1::LpDLDH strain. Metabolomic profiling indicated that under inhibitor stress, carbon flux was diverted from the TCA cycle toward lactate synthesis to maintain redox balance. These findings highlight the multifaceted benefits of flocculation in enhancing strain robustness and D-LA productivity under harsh fermentation environments, providing insights for developing resilient yeast platforms for lignocellulosic bioprocessing. Full article

(This article belongs to the Special Issue Advances in Synthetic Biological Approaches to Microbial Engineering)

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14 pages, 3369 KB

Open AccessArticle

Modeling of Surfactant Enhanced Drying of Polymeric Coatings Using Random Forest Regressor

by Chitresh Kumar Bhargava, Rahul Shrivastava, Bhavya Tiwari, Kaushiki Dubey, Aman Pathania, Kaushal Naresh Gupta, Manju Rawat, Rahul Kumar, Amit Thakur, George D. Verros and Raj Kumar Arya

Processes 2025, 13(11), 3722; https://doi.org/10.3390/pr13113722 - 18 Nov 2025

Abstract

Surfactant-based drying of polymeric coatings is a highly non-linear complex process due to the involvement of simultaneous heat and mass transfer. It is quite challenging to model this type of system mathematically. We resorted to a data-driven technique to model this type of [...] Read more.

Surfactant-based drying of polymeric coatings is a highly non-linear complex process due to the involvement of simultaneous heat and mass transfer. It is quite challenging to model this type of system mathematically. We resorted to a data-driven technique to model this type of system. A potent machine learning approach called the random forest (RF) regressor was introduced in this work to model the drying of poly(styrene)-p-xylene coatings improved by surfactants. This model was developed using experimental data. A substantial number of samples were collected by conducting experiments at a wide range of operating conditions. Apart from the accuracy of predicting coating weight loss for given values of inputs, model performance was also evaluated for the variation in the number of samples, and feature extraction was also done, which is an additional advantage of the random forest. Our results demonstrate that the random forest model trained with 80% samples is able to predict coating weight loss with less than

\pm 0.5 %

error, and even a model trained with just 20% samples is able to predict the remaining 80% samples with just

\pm 2 %

error. It also outperformed the regression tree and the artificial neural network (ANN) used in previous studies for the same dataset. Full article

(This article belongs to the Special Issue Advances in Polymer Films and Coatings: Preparation, Characterization and Applications)

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31 pages, 9364 KB

Open AccessFeature PaperArticle

Inducing Interconnected Fractures in Granite via Pulsed Power Plasma Using Nanoparticles: A Waterless Stimulation Approach for Enhanced Geothermal Systems

by Son T. Nguyen, Mohamed Y. Soliman, Mohamed Adel Gabry, Mohamed E.-S. El-Tayeb, Michael Myers, Yanming Chen, Gabriel Unomah and Lori Hathon

Processes 2025, 13(11), 3721; https://doi.org/10.3390/pr13113721 - 18 Nov 2025

Abstract

This study introduces nanoparticle-enhanced pulsed power plasma stimulation (NP-3PS) as a waterless fracturing technology for enhanced geothermal systems (EGS), employing ultrafast high-pressure plasma discharges from a 20 kJ capacitor charged to 40 kV to initiate and propagate complex fractures in 8-inch (20.32 cm) [...] Read more.

This study introduces nanoparticle-enhanced pulsed power plasma stimulation (NP-3PS) as a waterless fracturing technology for enhanced geothermal systems (EGS), employing ultrafast high-pressure plasma discharges from a 20 kJ capacitor charged to 40 kV to initiate and propagate complex fractures in 8-inch (20.32 cm) granite cubes via single pulses of 10, 12, and 16 kJ and a staged 4 + 6 kJ sequence. A 2-inch (5.03 cm) borehole was filled with nanofluid containing 0.3 wt % aluminum NP (60–80 nm) suspended in 7 wt % potassium chloride (KCl) + 0.18 wt % guar gum to sustain thermite reactions and multi-cycle shockwaves, generating peak pressures exceeding 100,000 psi (690 MPa) within microseconds. Post-stimulation diagnostics using 13 µm micro-CT, thin-section microscopy, and acoustic velocity analysis revealed dense branched fractures, porosity increase from 1.3% to 4.6% (~250%), and thermal conductivity reduction of 9–16%, indicating enhanced permeability and convective heat-transfer potential. The NP-driven multi-pulse mechanism reactivated existing fractures at lower energy without wire replacement, establishing a quantitative framework linking plasma dynamics, rock damage evolution, and thermal response, thus confirming NP-3PS as a scalable and sustainable alternative to hydraulic fracturing for geothermal reservoir stimulation. Full article

(This article belongs to the Special Issue Engineered Geothermal Systems (EGS): Advances in Exploration, Thermal Storage, and Energy Utilization)

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15 pages, 1869 KB

Open AccessArticle

Bioinspired Fractal Design of (Reverse) Electrodialysis Stacks

by Joost Veerman

Processes 2025, 13(11), 3720; https://doi.org/10.3390/pr13113720 - 18 Nov 2025

Abstract

This paper offers a perspective on the future of energy harvesting through reverse electrodialysis (RED), particularly in systems using seawater and river water as feed solutions. Although significant progress has been made in membrane development and in optimizing flow configurations—through the introduction of [...] Read more.

This paper offers a perspective on the future of energy harvesting through reverse electrodialysis (RED), particularly in systems using seawater and river water as feed solutions. Although significant progress has been made in membrane development and in optimizing flow configurations—through the introduction of alternative spacers and profiled membranes that enhance mixing and reduce polarization—the overall advancement of RED technology has stagnated for nearly a decade. A persistent negative scale factor continues to favor small-scale applications while limiting the feasibility of large-scale power generation. We propose that renewed progress may arise from fractal-inspired system architectures, in which the efficiency of small RED units is preserved and amplified through hierarchical organization and cooperative operation of many such elements. Two conceptual approaches are outlined. The first explores fractal geometries within the intermembrane compartments, focusing particularly on the river water compartment, which typically exhibits the highest ohmic resistance. The second envisions the modular aggregation of numerous cross-flow stacks into large-scale assemblies whose overall performance scales constructively with the number of units. Together, these ideas suggest a new design paradigm in which scalability and efficiency are reconciled through fractal system organization. Full article

(This article belongs to the Special Issue Development of Materials and Processes for Integration of Reaction and Separation Operations)

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