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Exploring Recent Advances in Lignocellulosic Biomass Waste Delignification Through the Combined Use of Eutectic Solvents and Intensification Techniques
Comparative Techno-Economic Analysis of Parabolic Trough and Linear Fresnel Collectors with Evacuated and Non-Evacuated Receiver Tubes in Different Geographical Regions
Modelling Approach for the Continuous Biocatalytic Synthesis of N-Acetylneuraminic Acid in Packed Bed Reactors

Journal Description

Processes

Processes is an international, peer-reviewed, open access journal on processes/systems in chemistry, biology, material, energy, environment, food, pharmaceutical, manufacturing, automation control, catalysis, separation, particle and allied engineering fields published monthly online by MDPI. The Systems and Control Division of the Canadian Society for Chemical Engineering (CSChE S&C Division) and the Brazilian Association of Chemical Engineering (ABEQ) are affiliated with Processes and their members receive discounts on the article processing charges. Please visit Society Collaborations for more details.

Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
High Visibility: indexed within Scopus, SCIE (Web of Science), Ei Compendex, Inspec, AGRIS, and other databases.
Journal Rank: JCR - Q2 (Engineering, Chemical) / CiteScore - Q2 (Chemical Engineering (miscellaneous))
Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 14.9 days after submission; acceptance to publication is undertaken in 2.7 days (median values for papers published in this journal in the second half of 2024).
Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.

Impact Factor: 2.8 (2023); 5-Year Impact Factor: 3.0 (2023)

Imprint Information Journal Flyer Open Access ISSN: 2227-9717

Latest Articles

17 pages, 786 KiB

Open AccessArticle

Orthogonal Test Optimization of Swelling Performance in Kitchen Waste Carbon Source Hydrogels

by Yu Huang, Xing Zhang, Dan Shi, Hongyi Qian, Jingyi Zhao, Shasha Xu, Tingting Dong, Mingyan Qin, Liwei Deng and Yalin Li

Processes 2025, 13(1), 110; https://doi.org/10.3390/pr13010110 - 3 Jan 2025

To address the challenges of food waste disposal and promote carbon emission reduction, this study synthesizes hydrogels using nano-calcium peroxide (nano-CaO₂) as an oxidant to activate carbon components in food waste. With acrylamide (AM), cross-linking agent N,N′-methylene bisacrylamide (MBA), and initiator [...] Read more.

To address the challenges of food waste disposal and promote carbon emission reduction, this study synthesizes hydrogels using nano-calcium peroxide (nano-CaO₂) as an oxidant to activate carbon components in food waste. With acrylamide (AM), cross-linking agent N,N′-methylene bisacrylamide (MBA), and initiator sodium persulfate (SPS), hydrogels were formed via oxidative excitation and free-radical polymerization. A one-factor experiment investigated the factors affecting hydrogel preparation, while a four-factor, three-level orthogonal test optimized the process. The hydrogel exhibited a swelling capacity of 703.1% under optimal conditions: 0.60 g SPS, 0.07 g MBA, reaction temperature of 70 °C, and 0.04 g nano-CaO₂. Characterization by SEM, XRD, and TGA showed that the swelling capacity was mainly due to the interlaced reticulated folded structure and microcrystalline formation, with polymer chain interactions contributing to excellent swelling properties and thermal stability. Full article

(This article belongs to the Special Issue Recent Advances in CO₂ Capture, CO₂ Utilization, and Green Chemistry for Sustainability)

25 pages, 3976 KiB

Open AccessArticle

Research on Multi-Scale Electricity–Carbon–Green Certificate Market Coupling Trading Based on System Dynamics

by Tiannan Ma, Lilin Peng, Gang Wu, Yuchen Wei and Xin Zou

Processes 2025, 13(1), 109; https://doi.org/10.3390/pr13010109 - 3 Jan 2025

While tradable green certificates (TGCs) and carbon emission trading (CET) play key roles in achieving peak carbon and carbon neutrality, the coupling effects between these two policies on the medium- and long-term electricity market and the spot market are still uncertain. In this [...] Read more.

While tradable green certificates (TGCs) and carbon emission trading (CET) play key roles in achieving peak carbon and carbon neutrality, the coupling effects between these two policies on the medium- and long-term electricity market and the spot market are still uncertain. In this study, we firstly construct a multi-scale market trading framework to sort out the information transfer of four markets. Secondly, we establish a multi-scale market system dynamics-coupled trading model with five sub-modules, including the medium- and long-term power markets, the spot market, and the carbon market. Subsequently, we adjust the policy parameters (carbon quota benchmark price, carbon quota auction ratio, and renewable energy quota ratio) and set up five policy scenarios to compare and analyze the impacts of the CET and TGC mechanisms on the power market and carbon emission reduction when they act alone or in synergy, in order to provide a theoretical basis for the adjustment of strategies of market entities and the setting of parameters. The results show that CET can increase spot electricity prices and promote renewable energy to enter the spot market, while TGCs can promote a high proportion of renewable energy consumption but lower spot electricity prices for a long time. The coordinated implementation of the CET and TGC mechanisms can improve the power market’s adaptability to high renewable energy penetration, but it may also result in policy redundancy. 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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21 pages, 1977 KiB

Open AccessReview

Advancements in Research on Alternative Protein Sources and Their Application in Food Products: A Systematic Review

by Leona Puljić, Marija Banožić, Nikolina Kajić, Višnja Vasilj, Kristina Habschied and Krešimir Mastanjević

Processes 2025, 13(1), 108; https://doi.org/10.3390/pr13010108 - 3 Jan 2025

To ensure food security amid dwindling natural resources, alternative proteins (APs) have been suggested as a sustainable solution. Yet, the adoption and consumption of APs remain limited. This review aims to delve into the latest progress (following PRISMA guidelines) concerning the utilization of [...] Read more.

To ensure food security amid dwindling natural resources, alternative proteins (APs) have been suggested as a sustainable solution. Yet, the adoption and consumption of APs remain limited. This review aims to delve into the latest progress (following PRISMA guidelines) concerning the utilization of proteins from alternative sources, particularly focusing on their effective incorporation into food products. Our findings reveal that insect proteins can improve amino acid profiles in bakery products. However, consumer acceptance remains low due to cultural biases, with optimal sensory results being achieved at lower substitution levels (5–10%). Mushroom proteins, when incorporated into meat analogs and bakery items, enhance nutritional value and offer favorable sensory properties, making them viable replacements in meat products. Plant-based proteins, such as pea and soy proteins, increase fiber and antioxidants and improve texture in meat alternatives, although formulation adjustments are necessary to meet consumer expectations for taste and overall experience. Microalgae offer unique benefits for bakery, confectionery, and dairy products by boosting protein, fatty acids, and probiotic growth while maintaining sensory acceptability. In conclusion, this study highlights that the effective incorporation of APs into food products can help in the development of healthier, more sustainable diets. That said, the success of AP acceptance will depend on continued innovations in formulation and consumer education. Full article

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

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23 pages, 2390 KiB

Open AccessArticle

An Innovative NOx Emissions Prediction Model Based on Random Forest Feature Selection and Evolutionary Reformer

by Xianyu Meng, Xi Li, Jialei Chen, Yongyan Fu, Chu Zhang, Muhammad Shahzad Nazir and Tian Peng

Processes 2025, 13(1), 107; https://doi.org/10.3390/pr13010107 - 3 Jan 2025

Developing more precise NOx emission prediction models is pivotal for effectively controlling NOx emissions from gas turbines. In this paper, a Reformer is combined with random forest (RF) feature selection and the chaos game optimization (CGO) algorithm to predict NOx in gas turbines. [...] Read more.

Developing more precise NOx emission prediction models is pivotal for effectively controlling NOx emissions from gas turbines. In this paper, a Reformer is combined with random forest (RF) feature selection and the chaos game optimization (CGO) algorithm to predict NOx in gas turbines. Firstly, RF evaluates the importance of data features and reduces the dimensionality of multidimensional data to improve the predictive performance of the model. Secondly, the Reformer model extracts the inherent pattern of different data and explores the intrinsic connection between gas turbine variables to establish a more accurate NOx emission prediction model. Thirdly, the CGO algorithm is a parameter-free meta-heuristic optimization algorithm used to find the best parameters for the prediction model. The CGO algorithm was improved using Chebyshev Chaos Mapping to improve the initial population quality of the CGO algorithm. To evaluate the efficiency of the proposed model, a dataset of gas turbines in north-western Turkey is studied, and the results obtained are compared with seven benchmark models. The final results of this paper show that RF can select appropriate input variables, and the Reformer can extract the intrinsic links of the data and build a more accurate NOx prediction model. At the same time, ICGO can optimize the parameters of the Reformer effectively. Full article

(This article belongs to the Special Issue Advances in Process Systems Engineering—Selected Papers From China PSE Annual Meeting)

26 pages, 6824 KiB

Open AccessArticle

Numerical Study to Optimize the Operating Parameters of a Real-Sized Industrial-Scale Micron Air Classifier Used for Manufacturing Fine Quartz Powder and a Comparison with the Prototype Model

by Nang Xuan Ho, Hoi Thi Dinh and Nhu The Dau

Processes 2025, 13(1), 106; https://doi.org/10.3390/pr13010106 - 3 Jan 2025

In this study, we successfully captured and compared the gas−particle flow field in a real-sized industrial-scale micron air classifier and in a prototype. All simulation calculations were performed using high-performance computing (HPC) systems and 3D transient simulations with the TWC-RSM–DPM (Two-Way Coupling–Reynolds Stress [...] Read more.

In this study, we successfully captured and compared the gas−particle flow field in a real-sized industrial-scale micron air classifier and in a prototype. All simulation calculations were performed using high-performance computing (HPC) systems and 3D transient simulations with the TWC-RSM–DPM (Two-Way Coupling–Reynolds Stress Model–Discrete Phase Model) in ANSYS Fluent (version 2022 R2). The following objectives were achieved: (i) a comparison of the simulation results was made between a real-size industrial-scale micron air classifier and a prototype model (scaled-down model) to show the differences between them and highlight the necessity of a simulation study on a real-size industrial-scale model for optimization purposes; (ii) a detailed analysis of the effects of the multiple vortices inside both the main and secondary classification zones provided a deeper understanding of the classification mechanism of the real-sized industrial-scale micron air classifier; and (iii) on the basis of the classifier’s key performance indicators (KPIs: d₅₀, K, η) and the constrained condition (i.e., the know-how particle size distribution curve (KHC) of quartz fine powder material of 0–45 µm) applied in manufacturing engineering stone, the relationship between the operating parameters and classification performance was addressed, and the optimal set of operating parameters for the production of quartz fine powder material (0–45 µm) was selected. The simulation results will be validated using experimental results at the Vicostone Plant, Phenikaa Group. Full article

(This article belongs to the Section Separation Processes)

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42 pages, 5230 KiB

Open AccessReview

A Review of Safety Valves: Standards, Design, and Technological Advances in Industry

by Petrică Cană, Razvan George Ripeanu, Alin Diniță, Maria Tănase, Alexandra Ileana Portoacă and Iulian Pătîrnac

Processes 2025, 13(1), 105; https://doi.org/10.3390/pr13010105 - 3 Jan 2025

This review synthesizes insights from the literature and incorporates computational and experimental analyses to explore various types of safety valves and their applications across industries such as oil and gas, chemical manufacturing, and power generation. Key areas of focus include global regulatory standards [...] Read more.

This review synthesizes insights from the literature and incorporates computational and experimental analyses to explore various types of safety valves and their applications across industries such as oil and gas, chemical manufacturing, and power generation. Key areas of focus include global regulatory standards from organizations like the American Society of Mechanical Engineers (ASME), International Organization for Standardization (ISO), Deutsches Institut für Normung (DIN), and American Petroleum Institute (API), which ensure stringent design and testing requirements. This paper examines the historical development of safety valves, recent technological advancements such as smart valves with integrated sensors, and predictive maintenance capabilities, along with ongoing challenges in high-pressure and corrosive environments. Additionally, it highlights the role of computational tools like CFD and FEA in optimizing valve designs and ensuring reliability under demanding conditions. By presenting a streamlined analysis of standards, innovations, and future directions, this review underscores the indispensable importance of safety valve technology in ensuring operational safety across various industrial applications. Full article

(This article belongs to the Special Issue Improving Process Safety in the Chemical Industry: Fundamental and Advanced Research)

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19 pages, 5982 KiB

Open AccessArticle

A Multigranularity Parallel Pyramidal Transformer Model for Ethylene Production Prediction and Energy Efficiency Optimization

by Biying Lu, Yingliang Bai and Jing Zhang

Processes 2025, 13(1), 104; https://doi.org/10.3390/pr13010104 - 3 Jan 2025

Ethylene production prediction is crucial for improving energy efficiency and optimizing processes in the petrochemical industry. However, the production process data of ethylene are highly complex, and the interaction relationships between variables vary at different time granularities. Ignoring these feature relationships can affect [...] Read more.

Ethylene production prediction is crucial for improving energy efficiency and optimizing processes in the petrochemical industry. However, the production process data of ethylene are highly complex, and the interaction relationships between variables vary at different time granularities. Ignoring these feature relationships can affect the accuracy of ethylene prediction. Traditional prediction methods model data at a single time granularity only and fail to effectively extract multigranularity features. Therefore, to address the complex multigranularity time-varying characteristics of ethylene production, a multigranularity parallel pyramidal Transformer (MPPT) model is proposed to capture and integrate features from ethylene production data at multiple time granularities, enabling accurate production prediction and energy efficiency optimization. The MPPT model integrates three key modules: multiscale decomposition (MSD), parallel pyramid Transformer (PPT), and multigranularity fusion (MF). The MSD converts industrial process data into multigranularity formats, while the PPT extracts both local and global interaction features across different time granularities using a parallel pyramid structure. Finally, the MF module fuses these features to establish a mapping for accurate prediction. We conducted comparative prediction experiments on an ethylene industrial production dataset, where the MPPT model achieved the best performance among all compared prediction models, with an MAE and RMSE of 0.006 and 0.1755, respectively. Furthermore, we leveraged the accuracy of MPPT in ethylene production prediction to optimize production inputs, achieving energy efficiency optimization in ethylene production. Full article

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

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12 pages, 6604 KiB

Open AccessFeature PaperArticle

Study on the Influence of the Type of Groove on the Inner Surface of the Casing on the Gas Sealing Performance of Sn58Bi Alloy Plugs

by Chunqing Zha, Tengfei Cui, Wei Wang and Gonghui Liu

Processes 2025, 13(1), 103; https://doi.org/10.3390/pr13010103 - 3 Jan 2025

Aiming at the problem of the cement hydration shrinkage phenomenon, which occurs when cement seals downhole casing in the process of Carbon Capture, Utilization, and Storage (CCUS) technology, this paper proposes a method of sealing the casing by combining threaded casing with bismuth–tin [...] Read more.

Aiming at the problem of the cement hydration shrinkage phenomenon, which occurs when cement seals downhole casing in the process of Carbon Capture, Utilization, and Storage (CCUS) technology, this paper proposes a method of sealing the casing by combining threaded casing with bismuth–tin alloy. The effect of different types of grooves (square-, trapezoidal-, and screw-threaded grooves) set on the inner surface of the casing on the gas sealing performance of the alloy plug was analyzed. And the effect of the overlay pressure on the gas sealing performance of the alloy plug during the molding process was analyzed. The experimental results show that under 0.2 MPa overlay pressure, the gas breakthrough pressure values of alloy plugs in square-threaded, screw-threaded, trapezoidal-threaded, and smooth hole casings are 5, 3.7, 2.9, and 1 MPa, respectively. When the pitch in the screw-threaded casing is half of the original, the gas breakthrough pressure value of the alloy plugs in the casing is 4.7 MPa. And after the application of 0.2 MPa overlay pressure, the gas sealing performance of the alloy plugs in the screw-threaded, trapezoidal-threaded, and light hole casings was improved by 220%, 230%, and 100%, respectively. The experimental results show that when the grooves are set on the inner surface of the casing, the gas flow path per unit length of the alloy plug-casing interface is prolonged, and the grooves increase the degree of zigzagging on the inner surface of the casing. The gas sealing performance of the alloy plugs is greatly enhanced. This research can provide theoretical support for the application of downhole Carbon Storage using Sn58Bi in casing. Full article

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

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24 pages, 5314 KiB

Open AccessArticle

A Methodological Framework for Business Decisions with Explainable AI and the Analytic Hierarchical Process

by Gabriel Marín Díaz, Raquel Gómez Medina and José Alberto Aijón Jiménez

Processes 2025, 13(1), 102; https://doi.org/10.3390/pr13010102 - 3 Jan 2025

In today’s data-driven business landscape, effective and transparent decision making becomes relevant to maintain a competitive advantage over the competition, especially in customer service in B2B environments. This study presents a methodological framework that integrates Explainable Artificial Intelligence (XAI), C-means clustering, and the [...] Read more.

In today’s data-driven business landscape, effective and transparent decision making becomes relevant to maintain a competitive advantage over the competition, especially in customer service in B2B environments. This study presents a methodological framework that integrates Explainable Artificial Intelligence (XAI), C-means clustering, and the Analytic Hierarchical Process (AHP) to improve strategic decision making in business environments. The framework addresses the need to obtain interpretable information from predictions based on machine learning processes and the prioritization of key factors for decision making. C-means clustering enables flexible customer segmentation based on interaction patterns, while XAI provides transparency into model outputs, allowing support teams to understand the factors influencing each recommendation. The AHP is then applied to prioritize criteria within each customer segment, aligning support actions with organizational goals. Tested with real customer interaction data, this integrated approach proved effective in accurately segmenting customers, predicting support needs, and optimizing resource allocation. The combined use of XAI and the AHP ensures that business decisions are data-driven, interpretable, and aligned with the company’s strategic objectives, making this framework relevant for companies seeking to improve their customer service in complex B2B contexts. Future research will explore the application of the proposed model in different business processes. Full article

(This article belongs to the Section Advanced Digital and Other Processes)

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20 pages, 1011 KiB

Open AccessArticle

Optimal Scheduling Method of Combined Wind–Photovoltaic–Pumped Storage System Based on Improved Bat Algorithm

by Hui Fan, Hongbo Wu, Shilin Li, Shengfeng Han, Jingtao Ren, Shuo Huang and Hongbo Zou

Processes 2025, 13(1), 101; https://doi.org/10.3390/pr13010101 - 3 Jan 2025

Pumped storage power stations not only serve as a special power load but also store excess electricity from the power system, significantly reducing the curtailment of wind and solar power. This dual function ensures the stable operation of the power grid and enhances [...] Read more.

Pumped storage power stations not only serve as a special power load but also store excess electricity from the power system, significantly reducing the curtailment of wind and solar power. This dual function ensures the stable operation of the power grid and enhances its economic benefits. The scheduling optimization problem of a combined wind–solar–pumped storage system is addressed in this study, and an optimization scheduling model is proposed with the objective of maximizing total system revenue. The model is designed to comprehensively account for the generation revenues from wind power, photovoltaic power, thermal power, and pumped storage, as well as the penalty costs associated with pollutant emissions. To address the limitations of traditional algorithms, which are prone to being trapped in local optima and exhibit slow convergence, an improved bat algorithm was developed. The algorithm is enhanced through the use of chaotic mapping to expand the initial solution space, the incorporation of adaptive step-size updates to improve convergence efficiency, and the integration of the Cauchy function to strengthen global search capabilities, thereby effectively avoiding local optima. Simulation results have demonstrated that the improved algorithm achieves significant improvements over traditional bat algorithms and particle swarm optimization (PSO) in terms of optimization efficiency, with total revenue increases of 21.9% and 24.6%, respectively. The optimized scheduling plan is shown to fully utilize the flexible regulation capabilities of pumped storage, mitigating the adverse effects of wind and photovoltaic output fluctuations on grid operations and achieving a balanced trade-off between economic and environmental objectives. Full article

(This article belongs to the Section Energy Systems)

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28 pages, 14215 KiB

Open AccessArticle

Strength Analysis and Reinforcement of 120 m³ Liquid Helium Storage Tank for Transportation Case

by Jianguo Zhang, Chao Li, Fa’an Liu, Jing Xu, Qinghua Liu, Shuhui Ma, Changjun Li, Wenlong Jia and Longjiang Li

Processes 2025, 13(1), 100; https://doi.org/10.3390/pr13010100 - 3 Jan 2025

To ensure the safe transportation of a 120 m³ liquid hel ium storage tank, based on the analysis of its structure, material, and load characteristics, a finite element model for stress and strength analysis is established and solved by using the coupled [...] Read more.

To ensure the safe transportation of a 120 m³ liquid hel ium storage tank, based on the analysis of its structure, material, and load characteristics, a finite element model for stress and strength analysis is established and solved by using the coupled thermo-mechanical analysis method for the accelerating and cornering cases experienced by the tank during transportation. The stress and deformation distributions in different transportation cases are analyzed in comparison to the finite element model, and the strength check is carried out for the tank. The study shows that under various working cases, the extreme value of stress of some parts is 267.5 MPa; this does not satisfy the strength requirement, and therefore requires structural reinforcement. The analysis of the reinforcing effect of the reinforcement structure shows that the stress extremes of the dangerous parts of the tanks after reinforcement decreased by 63.7% and 34.7%; the structural strength meets the standard requirements, and the new reinforcement structure only leads to an increase of 6% in the liquid nitrogen consumption of the cold screen, which is a better reinforcing effect. Full article

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

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26 pages, 16984 KiB

Open AccessArticle

An Enhanced Solar Battery Charger Using a DC-DC Single-Ended Primary-Inductor Converter and Fuzzy Logic-Based Control for Off-Grid Photovoltaic Applications

by Julio López Seguel, Samuel Zenteno, Crystopher Arancibia, José Rodríguez, Mokthar Aly, Seleme I. Seleme, Jr. and Lenin M. F. Morais

Processes 2025, 13(1), 99; https://doi.org/10.3390/pr13010099 - 3 Jan 2025

Battery charging systems are crucial for energy storage in off-grid photovoltaic (PV) installations. Since the power generated by a PV panel is conditioned by climatic conditions and load characteristics, a maximum power point tracking (MPPT) technique is required to maximize PV power and [...] Read more.

Battery charging systems are crucial for energy storage in off-grid photovoltaic (PV) installations. Since the power generated by a PV panel is conditioned by climatic conditions and load characteristics, a maximum power point tracking (MPPT) technique is required to maximize PV power and accelerate battery charging. On the other hand, a battery must be carefully charged, ensuring that its charging current and voltage limits are not exceeded, thereby preventing premature degradation. However, the voltage generated by the PV panel during MPPT operation fluctuates, which can harm the battery, particularly during periods of intense radiation when overvoltages are likely to occur. To address these issues, the design and construction of an enhanced solar battery charger utilizing a single-ended primary-inductor converter (SEPIC) and soft computing (SC)-based control is presented. A control strategy is employed that integrates voltage stabilization and MPPT functions through two dedicated fuzzy logic controllers (FLCs), which manage battery charging using a three-mode scheme: MPPT, Absorption, and Float. This approach optimizes available PV power while guaranteeing fast and safe battery charging. The developed charger leverages the SEPIC’s notable features for PV applications, including a wide input voltage range, minimal input current ripple, and an easy-to-drive switch. Moreover, unlike most PV charger control strategies in the literature that combine improved traditional MPPT methods with classical proportional integral (PI)-based control loops, the proposed control adopts a fully SC-based strategy, effectively addressing common drawbacks of conventional methods, such as slowness and inaccuracy during sudden atmospheric fluctuations. Simulations in MATLAB/Simulink compared the FLCs’ performance with conventional methods (P&O, IncCond, and PID). Additionally, a low-power hardware prototype using an Arduino Due microcontroller was built to evaluate the battery charger’s behavior under real weather conditions. The simulated and experimental results both demonstrate the robustness and effectiveness of the solar charger. Full article

(This article belongs to the Special Issue Advances in Renewable Energy Systems (2nd Edition))

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19 pages, 7266 KiB

Open AccessArticle

Experimental Study on Fracture Propagation in Carbonate Rocks by Acid Fracturing Using the Image-Based 3D Object Reconstruction Technique

by Chenhao Jin, Haijun Mao, Jun Zhou, Yiming Liu, Motao Duan, Zechen Guo and Kaijie Wang

Processes 2025, 13(1), 98; https://doi.org/10.3390/pr13010098 - 3 Jan 2025

Acid fracturing is an effective method of reservoir stimulation and has been widely used for carbonate reservoir development. However, knowledge on the propagation characteristics of acid-etched fracture is still poor due to the complexities of acidization and stress conditions, as well as the [...] Read more.

Acid fracturing is an effective method of reservoir stimulation and has been widely used for carbonate reservoir development. However, knowledge on the propagation characteristics of acid-etched fracture is still poor due to the complexities of acidization and stress conditions, as well as the limitations of the fracture network reconstruction method, especially when dealing with large specimens. In this paper, a new method based on image-based 3D object reconstruction is proposed to study the fracture networks of specimens after acid fracturing by cutting rock specimens into thin slices, scanning them, and reconstructing 3D fracture networks. This method is more precise than the method of separating specimens into pieces and scanning, and it has advantages over the method of CT X-ray scanning when dealing with large specimens. Using this approach, the effects of natural fractures, stress conditions, and acid systems on the fracture propagation of specimens after true triaxial acid-fracturing tests were investigated. The fracture initiation and propagation patterns of specimens under different conditions were summarized. The results of the study show that the presence of a natural fracture will induce the propagation of fractures, in addition to demonstrating the positive effect of high horizontal stress difference on fracture initiation and provide an acid system conducive to the formation of a fracture network. Full article

(This article belongs to the Topic Exploitation and Underground Storage of Oil and Gas)

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13 pages, 1260 KiB

Open AccessReview

Possibility of Using Alkali-Activated Phosphogypsum from the Production of Orthophosphoric Acid for the Building Materials—A Review

by Aleksandra Liczbińska and Jacek Gębicki

Processes 2025, 13(1), 97; https://doi.org/10.3390/pr13010097 - 3 Jan 2025

This paper focuses on the possibility of using phosphogypsum, which is a residue from the production of orthophosphoric acid as an additional source of calcium and the use of spent caustic as an alkaline activator for production of ceramic materials in construction industry. [...] Read more.

This paper focuses on the possibility of using phosphogypsum, which is a residue from the production of orthophosphoric acid as an additional source of calcium and the use of spent caustic as an alkaline activator for production of ceramic materials in construction industry. The use of the above-mentioned waste will allow to increase fraction of calcium, sodium and silicate needed for the geopolymerization process and improve properties of material. This review presents a description of the geopolymerization process and the influence of alkaline activator on the reactions occurring in ceramic materials. Collected information, which confirm the possibility of using post-production waste from chemical industry as components for the production of building materials. Full article

(This article belongs to the Special Issue Technological Processes for Chemical and Related Industries)

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21 pages, 16295 KiB

Open AccessArticle

An Equivalent Fracture Element-Based Semi-Analytical Approach to Evaluate Water-Flooding Recovery Efficiency in Fractured Carbonate Reservoirs

by Wenqi Zhao, Lun Zhao, Qianhui Wu, Qingying Hou, Pin Jia and Jue Hou

Processes 2025, 13(1), 96; https://doi.org/10.3390/pr13010096 - 3 Jan 2025

The productivity prediction of weakly volatile fractured reservoirs is influenced by reservoir parameters and fluid characteristics. To address the computational challenges posed by complex fractures, an equivalent fracture element method is proposed to calculate equivalent permeability in fractured zones. A three-phase seepage model [...] Read more.

The productivity prediction of weakly volatile fractured reservoirs is influenced by reservoir parameters and fluid characteristics. To address the computational challenges posed by complex fractures, an equivalent fracture element method is proposed to calculate equivalent permeability in fractured zones. A three-phase seepage model based on material balance is developed, using the Baker linear model to determine the relative permeabilities of oil, gas, and water while accounting for bound water saturation. Dynamic drainage distance and conductivity coefficients are introduced to calculate production at each stage, with the semi-analytical model solved iteratively for pressure and saturation. Validation against commercial simulation software confirms the model’s accuracy, enabling the construction of productivity curves and analysis of reservoir characteristics and injection scenarios. Results showed that the equivalent fracture element method effectively handled multiphase nonlinear seepage and predicted productivity during water flooding. Productivity was more sensitive to through-fracture models, with production increasing as the fracture extent expanded. Optimal water injection occurred when the formation pressure dropped to 80% of the bubble point pressure, and the recovery efficiency improved with periodic-injection strategies compared to conventional methods. These findings have significant implications for improving oil recovery, optimizing injection strategies, and advancing the design of efficient reservoir management techniques across scientific, practical, and technological domains. Full article

(This article belongs to the Section Energy Systems)

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23 pages, 960 KiB

Open AccessArticle

A Deep Reinforcement Advantage Actor-Critic-Based Co-Evolution Algorithm for Energy-Aware Distributed Heterogeneous Flexible Job Shop Scheduling

by Hua Xu, Juntai Tao, Lingxiang Huang, Chenjie Zhang and Jianlu Zheng

Processes 2025, 13(1), 95; https://doi.org/10.3390/pr13010095 - 3 Jan 2025

With the rapid advancement of the manufacturing industry and the widespread implementation of intelligent manufacturing systems, the energy-aware distributed heterogeneous flexible job shop scheduling problem (DHFJSP) has emerged as a critical challenge in optimizing modern production systems. This study introduces an innovative method [...] Read more.

With the rapid advancement of the manufacturing industry and the widespread implementation of intelligent manufacturing systems, the energy-aware distributed heterogeneous flexible job shop scheduling problem (DHFJSP) has emerged as a critical challenge in optimizing modern production systems. This study introduces an innovative method to reduce both the makespan and the total energy consumption (TEC) in the context of the DHFJSP. A deep reinforcement advantage Actor-Critic-based co-evolution algorithm (DRAACCE) is proposed to address the issue, which leverages the powerful decision-making and perception abilities of the advantage Actor-Critic (AAC) method. The DRAACCE algorithm consists of three main components: First, to ensure a balance between global and local search capabilities, we propose a new co-evolutionary strategy. This enables the algorithm to explore the solution space efficiently while maintaining robust exploration and exploitation. Next, a novel evolution strategy is introduced to improve the algorithm’s convergence rate and solution diversity, ensuring that the search process is both fast and effective. Finally, we integrate deep reinforcement learning with the advantage Actor-Critic framework to select elite solutions, enhancing the optimization process and leading to superior performance in minimizing both TEC and makespan. Extensive experiments validate the effectiveness of the proposed DRAACCE algorithm. The experimental results show that DRAACCE significantly outperforms existing state-of-the-art methods on all 20 instances and a real-world case, achieving better solutions in terms of both makespan and TEC. Full article

(This article belongs to the Section Advanced Digital and Other Processes)

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23 pages, 9476 KiB

Open AccessArticle

Investigation of Bolt Support Mechanisms and Parameter Optimization for Hard Roof Control in Underground Mining

by Cong Wang, Xigui Zheng, Wei Xin, Jiyu Wang and Longhe Liu

Processes 2025, 13(1), 94; https://doi.org/10.3390/pr13010094 - 3 Jan 2025

The control of hard roof conditions in underground coal mining is critical for ensuring mining safety and efficiency. Hard roof control remains a critical challenge in underground mining, particularly affecting mining safety and efficiency. Traditional support theories often show limitations in addressing the [...] Read more.

The control of hard roof conditions in underground coal mining is critical for ensuring mining safety and efficiency. Hard roof control remains a critical challenge in underground mining, particularly affecting mining safety and efficiency. Traditional support theories often show limitations in addressing the complex interactions between bolt spacing patterns and geological variability. This study focuses on the No. 10904 working face of Jingu Mine, where three distinct roof types are present: Type I (thick limestone roof, TLR, ≥1.2 m), Type II (moderate limestone roof, MLR, 0.5–1.2 m), and Type III (composite mudstone–limestone roof, CLR). Through FLAC3D numerical simulation and field validation, the mechanisms of bolt support under hard roof conditions were systematically investigated, and the optimization of bolt support parameters, including spacing, length, and pre-tension force, was conducted. The results indicate that: (1) when the ratio between lateral and row spacing approaches unity, reducing lateral spacing while increasing row spacing enhances support effectiveness, achieving 2 mm less roof subsidence with the 1.0 m × 1.5 m configuration compared to the 1.4 m × 0.8 m arrangement, despite a 21% reduction in bolt density; (2) an optimal rib bolt length of 1.8 m was determined, with support effectiveness diminishing beyond 2.0 m, and 1.5 m-long bolts reducing rib convergence by 15% compared to unsupported conditions; and (3) when the anchoring length exceeds 60% of the total bolt length, further increases in bolt length have minimal impact on deformation control under TLR, MLR, and CLR conditions. Field implementation of the optimized support scheme confirmed its effectiveness, with borehole television inspection showing no separation or fracturing within the monitored depth of 4 m in the roof strata. These findings provide practical guidelines for support design in similar geological settings, particularly for shallow-buried roadways with hard roof conditions. Full article

(This article belongs to the Section Separation Processes)

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34 pages, 2864 KiB

Open AccessReview

Natural Compounds from Food By-Products in Preservation Processes: An Overview

by Lucia Maddaloni, Laura Gobbi, Giuliana Vinci and Sabrina Antonia Prencipe

Processes 2025, 13(1), 93; https://doi.org/10.3390/pr13010093 - 2 Jan 2025

Food spoilage is a natural process that influences the quality and safety of food products, negatively affecting their nutritional and organoleptic composition. In these regards, traditional industrial food preservation processes often rely on the use of traditional preservation techniques to extend food shelf [...] Read more.

Food spoilage is a natural process that influences the quality and safety of food products, negatively affecting their nutritional and organoleptic composition. In these regards, traditional industrial food preservation processes often rely on the use of traditional preservation techniques to extend food shelf life, while ensuring microbiological and chemical stability without compromising the product’s sensory characteristics. However, in recent years, consumers have become increasingly wary of chemical food additives; they often associate their use with potential health risks and negative impact on product appeal. In addition, this is compounded by an increasingly compellent European regulatory framework, as well as efforts in the search of natural and sustainable alternatives for food preservation. In this context, this review explores the potential of natural additives, such as polyphenols, flavonoids, and antioxidants, derived from agro-industrial waste, including fruit peels, vegetable by-products, and seeds. These compounds exhibit strong antioxidant and antimicrobial properties, which not only extend the shelf life of food products but also enhance their safety and quality. Considering vegetable wastes (i.e., pomegranate peels, olive leaves, olive mill wastewater, and grape pomace) as the main by-products from which natural additives can be extracted, this study provides an overview of their efficacy in preventing lipid oxidation and reducing microbial growth, while maintaining sensory properties. This could represent an opportunity both for maintaining food quality and prolonging food shelf life by valorizing by-products to be otherwise disposed of, and also contribute to mitigating the environmental impact associated with the food industry and to optimize food preservation processes. In addition, it highlights the possibility of employing sustainable alternatives to synthetic additives, capable of extending the shelf life of food products while ensuring their safety for human consumption. Full article

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

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19 pages, 10729 KiB

Open AccessArticle

Development of MEA-Based and AEP-Based CO₂ Phase Change Absorbent

by Yongyan Wang, Fanghui Cheng, Jingsong Li, Yingshu Liu, Haihong Wang, Ziyi Li and Xiong Yang

Processes 2025, 13(1), 92; https://doi.org/10.3390/pr13010092 - 2 Jan 2025

In energy conservation and low-carbon environmental protection, separating and capturing CO₂ from blast furnace gas is a crucial strategy for the steel industry to achieve its dual carbon goals. This study conducts an experimental study on the phase change absorption of carbon [...] Read more.

In energy conservation and low-carbon environmental protection, separating and capturing CO₂ from blast furnace gas is a crucial strategy for the steel industry to achieve its dual carbon goals. This study conducts an experimental study on the phase change absorption of carbon dioxide for the low-energy capture of carbon dioxide in blast furnace gas in iron and steel enterprises. The experiment used 30%wt monoethanolamine (MEA) and 30%wt 1-(2-aminoethyl)piperazine (AEP) as a reference to blend different absorbents, and the CO₂ absorption effect of the absorbents was tested. The results indicated that the MEA system phase change absorbents have the best absorption effect when the mass ratio of additives to water is 5:5, and the AEP system has the best absorption effect at 7:3. The absorption effect of different phase separators is as follows: n-propanol > sulfolane > isopropanol. AEP/n-propanol/H₂O (7:3) has a maximum absorption load of 2.03 molCO₂·mol⁻¹ amine, a relatively low rich phase ratio of 0.46, and low regeneration energy consumption. The load capacity of different absorbents was calculated based on the load experiment results, and it was found that the loading capacity of the MEA system was greater than that of the AEP system, with the maximum load capacity of MEA/n-propanol/H₂O (5:5) being 4.02 mol/L. Different types of absorbents exhibited an increase in rich phase density with the increase in additive quality. The regeneration performance of the absorbent indicated that at a temperature of 393.15 K, the desorption load of n-propanol aqueous solution rich phase in the absorbent was high, and the desorption speed was the fastest. Full article

(This article belongs to the Special Issue CO₂ Capture and Conversion Processes: Recent Trends and Future Perspectives)

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19 pages, 2758 KiB

Open AccessFeature PaperArticle

Effect of UV Exposure Time on the Properties of Films Prepared from Biotechnologically Derived Chicken Gelatin

by Jakub Martinek, Lucie Polomíková, Michal Kudláček, Jana Navrátilová, Pavel Mokrejš, Jana Pavlačková and Robert Gál

Processes 2025, 13(1), 91; https://doi.org/10.3390/pr13010091 - 2 Jan 2025

Biomaterials (films, foils, fibers, coatings) based on proteins are becoming increasingly important due to the growing applications for which pork and beef gelatins are used. Alternative types of gelatins (poultry or fish), which have not yet been sufficiently tested, represent a high potential. [...] Read more.

Biomaterials (films, foils, fibers, coatings) based on proteins are becoming increasingly important due to the growing applications for which pork and beef gelatins are used. Alternative types of gelatins (poultry or fish), which have not yet been sufficiently tested, represent a high potential. This study looks at the effect of different UV exposure times on chicken gelatin films with added glycerol. The gelatin was prepared using a unique enzymatic hydrolysis process. The quality of the UV-exposed films was compared with gelatin films not exposed to UV light. Radiation-induced crosslinking improved the mechanical and physical properties of the films. The UV crosslinked films are stabilized at a degree of swelling from 700 to 900%; moreover, they extend their dissolution to more than 7 days while maintaining their original shape. In contrast, non-crosslinked films swell and dissolve in water faster. Further, the effect of UV radiation on the water vapor permeability and color of the films was monitored. Water vapor permeability decreased by 2.5 times with increasing crosslinking time for 30% and 40% glycerol content, and the yellowness of the irradiated samples increased with exposure time in the interval from 24 to 28. Using Fourier transform infrared spectroscopy, the differences in the amount of bonding based on irradiation time were analyzed. As a result of crosslinking, the intensity of existing bonds increased. Thermal properties were verified through differential scanning calorimetry and thermogravimetric analysis. The results proved that chicken gelatin is suitable for preparing films in foods and medicine. Applying UV radiation to crosslink gelatin films is an alternative to traditionally used chemical crosslinkers. Full article

(This article belongs to the Special Issue Features, Reviews and Perspectives for the 10th Anniversary of Processes)

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