Processes

37 pages, 1295 KiB

Open AccessReview

Optimal Operation of Combined Cooling, Heating, and Power Systems with High-Penetration Renewables: A State-of-the-Art Review

by Yunshou Mao, Jingheng Yuan and Xianan Jiao

Processes 2025, 13(8), 2595; https://doi.org/10.3390/pr13082595 (registering DOI) - 16 Aug 2025

Abstract

Under the global decarbonization trend, combined cooling, heating, and power (CCHP) systems are critical for improving regional energy efficiency. However, the integration of high-penetration variable renewable energy (RE) sources introduces significant volatility and multi-dimensional uncertainties, challenging conventional operation strategies designed for stable energy [...] Read more.

Under the global decarbonization trend, combined cooling, heating, and power (CCHP) systems are critical for improving regional energy efficiency. However, the integration of high-penetration variable renewable energy (RE) sources introduces significant volatility and multi-dimensional uncertainties, challenging conventional operation strategies designed for stable energy inputs. This review systematically examines recent advances in CCHP optimization under high-RE scenarios, with a focus on flexibility-enabled operation mechanisms and uncertainty-aware optimization strategies. It first analyzes the evolving architecture of variable RE-driven CCHP systems and core challenges arising from RE intermittency, demand volatility, and multi-energy coupling. Subsequently, it categorizes key flexibility resources and clarifies their roles in mitigating uncertainties. The review further elaborates on optimization methodologies tailored to high-RE contexts, along with their comparative analysis and selection criteria. Additionally, it details the formulation of optimization models, model formulation, and solution techniques. Key findings include the following: Generalized energy storage, which integrates physical and virtual storage, increases renewable energy utilization by 12–18% and reduces costs by 45%. Hybrid optimization strategies that combine robust optimization and deep reinforcement learning lower operational costs by 15–20% while strengthening system robustness against renewable energy volatility by 30–40%. Multi-energy synergy and exergy-efficient flexibility resources collectively improve system efficiency by 8–15% and reduce carbon emissions by 12–18%. Overall, this work provides a comprehensive technical pathway for enhancing the efficiency, stability, and low-carbon performance of CCHP systems in high-RE environments, supporting their scalable contribution to global decarbonization efforts. Full article

(This article belongs to the Special Issue Distributed Intelligent Energy Systems)

14 pages, 1964 KiB

Open AccessArticle

Rapid Joule-Heating Synthesis of Efficient Low-Crystallinity Ru-Mo Oxide Catalysts for Alkaline Hydrogen Evolution Reaction

by Tao Shi, Xiaoling Huang, Zhan Zhao, Zizhen Li, Kelei Huang and Xiangchao Meng

Processes 2025, 13(8), 2594; https://doi.org/10.3390/pr13082594 (registering DOI) - 16 Aug 2025

Abstract

Electrocatalytic water splitting has been demonstrated to be a highly efficient and promising technology for green hydrogen production. However, the inefficiency and instability of the cathode hinder its wide application in water electrolysis. Herein, we report a rapid Joule heating method for synthesizing [...] Read more.

Electrocatalytic water splitting has been demonstrated to be a highly efficient and promising technology for green hydrogen production. However, the inefficiency and instability of the cathode hinder its wide application in water electrolysis. Herein, we report a rapid Joule heating method for synthesizing the Ru-Mo oxide catalyst. Comprehensive characterization results confirmed that the as-prepared catalyst featured an internal porous structure with low crystallinity, which weakened the strength of Ru-H bonds through structural and electronic modulation. The enhanced HER performance was attributed to the incorporation of Mo⁴⁺ species, which strengthened Ru-O-Mo interactions. As tested, the optimized catalyst exhibited ultralow overpotentials (25.08 mV and 120.52 mV @ 10 and 100 mA cm⁻², respectively) and excellent stability (100 h @ 100 mA cm⁻²) in a 1 M KOH solution. Meanwhile, the as-prepared catalyst was equipped in an anion exchange membrane (AEM) alkaline water electrolyzer, which could deliver 185 mA cm⁻² at only 2.16 V with 100% Faradaic efficiency. This study provides a feasible strategy for constructing highly efficient low-crystallinity electrocatalysts. Full article

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

20 pages, 4551 KiB

Open AccessArticle

Intelligent Optimization of Single-Stand Control in Directional Drilling with Single-Bent-Housing Motors

by Hu Yin, Yihao Long, Qian Li, Tong Zhao and Xianzhu Wu

Processes 2025, 13(8), 2593; https://doi.org/10.3390/pr13082593 (registering DOI) - 16 Aug 2025

Abstract

Borehole trajectory control is a fundamental task for directional well engineers. Now that there are inevitable errors about single-stand control in the field situation, it is difficult to deal with the complex underground problems in real time. In order to improve the efficiency [...] Read more.

Borehole trajectory control is a fundamental task for directional well engineers. Now that there are inevitable errors about single-stand control in the field situation, it is difficult to deal with the complex underground problems in real time. In order to improve the efficiency of directional operation and the accuracy of wellbore trajectory control, this paper presents an improved Sparrow Search algorithm by integrating the multi-strategy model and Constant-Toolface models to calculate the single-stand control scheme for single-bent-housing motors in directional drilling. To evaluate the performance of the algorithm, the Particle Swarm algorithm, the Sparrow Search algorithm, and the improved Sparrow Search algorithm (LCSSA) are used to optimize the process parameters for each drilling, respectively. Numerical tests based on drilling data show that all three algorithms can predict the drilling parameters. In contrast, the LCSSA exhibits the fastest convergence and the smallest error after optimizing single-stand control, attaining an average convergence time of 0.08 s. It accurately back-calculated theoretical model parameters with high accuracy and met engineering requirements when applied to actual drilling data. In field applications, the LCSSA reduces the deviation from the planned trajectory by over 25%, restricting the deviation to within 0.005 m per stand; additionally the total drilling time was reduced by at least 18% compared to previous methods. The integration of the LCSSA with the drilling system significantly enhances drilling operations by optimizing trajectory accuracy and boosting efficiency and serves as an advanced tool for designing process parameters. Full article

(This article belongs to the Section Automation Control Systems)

► Show Figures

Figure 1

23 pages, 4479 KiB

Open AccessArticle

Optimizing Texture and Drying Behavior of Squid (Todarodes pacificus) for Elder-Friendly Applications Using Alkaline Pretreatment and Intermittent Drying: An Experimental and Numerical Study

by Timilehin Martins Oyinloye and Won Byong Yoon

Processes 2025, 13(8), 2592; https://doi.org/10.3390/pr13082592 (registering DOI) - 16 Aug 2025

Abstract

This study addresses the increasing demand for texture-modified seafood products suitable for elderly consumers by focusing on dried squid, a popular protein source. The aim was to optimize the softening and drying procedures to produce a dried squid product with improved chewability and [...] Read more.

This study addresses the increasing demand for texture-modified seafood products suitable for elderly consumers by focusing on dried squid, a popular protein source. The aim was to optimize the softening and drying procedures to produce a dried squid product with improved chewability and quality. Fresh squid was pretreated using sodium bicarbonate or potassium carbonate solutions (0, 0.3, 0.6, and 0.9 mol/kg) and dried at 40 °C using either continuous (CD) or intermittent drying (ID) until the final moisture content reached 18.34 ± 0.44%. Hardness generally increased with higher alkaline concentrations, with the potassium carbonate-treated samples showing better softening effects. Based on standards for elderly-friendly foods targeting chewable hardness (10,000–50,000 N/m²), low water activity (<0.58), and limited color change (ΔE = 14.32), the optimal result was achieved with 0.3 mol/kg potassium carbonate and ID. Among the thin-layer drying models, the Midilli–Kucuk model showed the best fit, with the highest average R² (0.9974), and lowest SSE (0.0481) and RMSE (0.1688), effectively capturing the drying kinetics. Scanning electron microscopy (SEM) revealed smoother surfaces and consistent porosity in samples dried intermittently, indicating less structural degradation. Finite element analysis showed that ID improved internal moisture distribution, reduced surface crusting, and alleviated internal stresses. These results support mild alkaline soaking combined with ID as an effective strategy for enhancing dried squid quality for elderly individuals. Full article

(This article belongs to the Special Issue Feature Papers in the "Food Process Engineering" Section)

► Show Figures

Figure 1

21 pages, 978 KiB

Open AccessArticle

Optimization and Practice of Deep Carbonate Gas Reservoir Acidizing Technology in the Sinian System Formation of Sichuan Basin

by Song Li, Jian Yang, Weihua Chen, Zhouyang Wang, Hongming Fang, Yang Wang and Xiong Zhang

Processes 2025, 13(8), 2591; https://doi.org/10.3390/pr13082591 (registering DOI) - 16 Aug 2025

Abstract

The gas reservoir of the Sinian Dengying Formation (Member 4) in Sichuan Basin exhibits extensive development of inter-clast dissolution pores and vugs within its carbonate reservoirs, characterized by low porosity (average 3.21%) and low permeability (average 2.19 mD). With the progressive development of [...] Read more.

The gas reservoir of the Sinian Dengying Formation (Member 4) in Sichuan Basin exhibits extensive development of inter-clast dissolution pores and vugs within its carbonate reservoirs, characterized by low porosity (average 3.21%) and low permeability (average 2.19 mD). With the progressive development of the Moxi (MX)structure, the existing stimulation techniques require further optimization based on the specific geological characteristics of these reservoirs. Through large-scale true tri-axial physical simulation experiments, this study systematically evaluated the performance of three principal acid systems in reservoir stimulation: (1) Self-generating acid systems, which enhance etching through the thermal decomposition of ester precursors to provide sustained reactive capabilities. (2) Gelled acid systems, characterized by high viscosity and effectiveness in reducing breakdown pressure (18%~35% lower than conventional systems), are ideal for generating complex fracture networks. (3) Diverting acid systems, designed to improve fracture branching density by managing fluid flow heterogeneity. This study emphasizes hybrid acid combinations, particularly self-generating acid prepad coupled with gelled acid systems, to leverage their synergistic advantages. Field trials implementing these optimized systems revealed that conventional guar-based fracturing fluids demonstrated 40% higher breakdown pressures compared to acid systems, rendering hydraulic fracturing unsuitable for MX reservoirs. Comparative analysis confirmed gelled acid’s superiority over diverting acid in tensile strength reduction and fracture network complexity. Field implementations using reservoir-quality-adaptive strategies—gelled acid fracturing for main reservoir sections and integrated self-generating acid prepad + gelled acid systems for marginal zones—demonstrated the technical superiority of the hybrid system under MX reservoir conditions. This optimized protocol enhanced fracture length by 28% and stimulated reservoir volume by 36%, achieving a 36% single-well production increase. The technical framework provides an engineered solution for productivity enhancement in deep carbonate gas reservoirs within the G-M structural domain, with particular efficacy for reservoirs featuring dual low-porosity and low-permeability characteristics. Full article

(This article belongs to the Special Issue Exploration, Exploitation and Utilization of Coal and Gas Resources, 2nd Edition)

25 pages, 4673 KiB

Open AccessArticle

Dynamic Monitoring and Evaluation of Fracture Stimulation Volume Based on Machine Learning

by Xiaodong He, Weibang Wang, Luyao Wang, Jinliang Xie, Chang Li, Lu Chen, Qinzhuo Liao and Shouceng Tian

Processes 2025, 13(8), 2590; https://doi.org/10.3390/pr13082590 (registering DOI) - 16 Aug 2025

Abstract

Traditional hydraulic-fracturing models are restricted by low computational efficiency, insufficient field data, and complex physical mechanisms, causing evaluation delays and failing to meet practical engineering needs. To address these challenges, this study innovatively develops a dynamic hydraulic-fracturing monitoring method that integrates machine learning [...] Read more.

Traditional hydraulic-fracturing models are restricted by low computational efficiency, insufficient field data, and complex physical mechanisms, causing evaluation delays and failing to meet practical engineering needs. To address these challenges, this study innovatively develops a dynamic hydraulic-fracturing monitoring method that integrates machine learning with numerical simulation. Firstly, this study uses GOHFER 9.5.6 software to generate 12,000 sets of fracture geometry data and constructs a big dataset for hydraulic fracturing. In order to improve the efficiency of the simulation, a macro command is used in combination with a Python 3.11 code to achieve the automation of the simulation process, thereby expanding the data samples for the surrogate model. On this basis, a parameter sensitivity analysis is carried out to identify key input parameters, such as reservoir parameters and fracturing fluid properties, that significantly affect fracture geometry. Next, a neural-network surrogate model is established, which takes fracturing geological parameters and pumping parameters as inputs and fracture geometric parameters as outputs. Data are preprocessed using the min–max normalization method. A neural-network structure with two hidden layers is chosen, and the model is trained with the Adam optimizer to improve its predictive accuracy. The experimental results show that the efficiency of automated numerical simulation for hydraulic fracturing is significantly improved. The surrogate model achieved a prediction accuracy of over 90% and a response time of less than 10 s, representing a substantial efficiency improvement compared to traditional fracturing models. Through these technical approaches, this study not only enhances the effectiveness of fracturing but also provides a new, efficient, and accurate solution for oilfield fracturing operations. Full article

(This article belongs to the Section Energy Systems)

► Show Figures

Figure 1

14 pages, 4297 KiB

Open AccessArticle

Numerical Simulation of Natural Gas Waste Heat Recovery Through Hydrated Salt Particle Desorption in a Full-Size Moving Bed

by Liang Wang, Minghui Li, Yu Men, Yun Jia and Bin Ding

Processes 2025, 13(8), 2589; https://doi.org/10.3390/pr13082589 - 15 Aug 2025

Abstract

To achieve energy conservation, emission reduction, and green low-carbon goals for gas storage facilities, it is crucial to efficiently recover and utilize waste heat during gas injection while maintaining natural gas cooling rates. However, existing sensible and latent heat storage technologies cannot sustain [...] Read more.

To achieve energy conservation, emission reduction, and green low-carbon goals for gas storage facilities, it is crucial to efficiently recover and utilize waste heat during gas injection while maintaining natural gas cooling rates. However, existing sensible and latent heat storage technologies cannot sustain long-term thermal storage or seasonal utilization of waste heat. Thermal chemical energy storage, with its high energy density and low thermal loss during prolonged storage, offers an effective solution for efficient recovery and long-term storage of waste heat in gas storage facilities. This study proposes a novel heat recovery method by combining a moving bed with mixed hydrated salts (CaCl₂·6H₂O and MgSO₄·7H₂O). By constructing both small-scale and full-scale three-dimensional models in Fluent, which couple the desorption and endothermic processes of hydrated salts, the study analyzes the temperature and flow fields within the moving bed during heat exchange, thereby verifying the feasibility of this approach. Furthermore, the effects of key parameters, including the inlet temperatures of hydrated salt particles and natural gas, flow velocity, and mass flow ratio on critical performance indicators such as the outlet temperatures of natural gas and hydrated salts, the overall heat transfer coefficient, the waste heat recovery efficiency, and the mass fraction of hydrated salt desorption are systematically investigated. The results indicate that in the small-scale model (1164 × 312 × 49 mm) the outlet temperatures of natural gas and mixed hydrated salts are 79.8 °C and 49.3 °C, respectively, with a waste heat recovery efficiency of only 33.6%. This low recovery rate is primarily due to the insufficient residence time of high-velocity natural gas (10.5 m·s⁻¹) and hydrated salt particles (2 mm·s⁻¹) in the moving bed, which limits heat exchange efficiency. In contrast, the full-scale moving bed (3000 × 1500 × 90 mm) not only accounts for variations in natural gas inlet temperature during the three-stage compression process but also allows for optimized operational adjustments. These optimizations ensure a natural gas outlet temperature of 41.3 °C, a hydrated salt outlet temperature of 82.5 °C, a significantly improved waste heat recovery efficiency of 94.2%, and a hydrated salt desorption mass fraction of 69.2%. This configuration enhances the safety of the gas injection system while maximizing both natural gas waste heat recovery and the efficient utilization of mixed hydrated salts. These findings provide essential theoretical guidance and data support for the effective recovery and seasonal utilization of waste heat in gas storage reservoirs. Full article

(This article belongs to the Special Issue Multiphase Flow Process and Separation Technology)

► Show Figures

Figure 1

23 pages, 11598 KiB

Open AccessArticle

Characteristics of Load-Bearing Rupture of Rock–Coal Assemblages with Different Height Ratios and Multivariate Energy Spatiotemporal Evolution Laws

by Bo Wang, Guilin Wu, Guorui Feng, Zhuocheng Yu and Yingshi Gu

Processes 2025, 13(8), 2588; https://doi.org/10.3390/pr13082588 - 15 Aug 2025

Abstract

The destabilizing damage of rock structures in coal beds engineering is greatly influenced by the bearing rupture features and energy evolution laws of rock–coal assemblages with varying height ratios. In this study, we used PFC3D to create rock–coal assemblages with rock–coal height ratios [...] Read more.

The destabilizing damage of rock structures in coal beds engineering is greatly influenced by the bearing rupture features and energy evolution laws of rock–coal assemblages with varying height ratios. In this study, we used PFC3D to create rock–coal assemblages with rock–coal height ratios of 2:8, 4:6, 6:4, and 8:2. Uniaxial compression simulation was then performed, revealing the expansion properties and damage crack dispersion pattern at various bearing phases. The dispersion and migration law of cemented strain energy zoning; the size and location of the destructive energy level and its spatiotemporal evolution characteristics; and the impact of height ratio on the load-bearing characteristics, crack extension, and evolution of multiple energies (strain, destructive, and kinetic energies) were all clarified with the aid of a self-developed destructive energy and strain energy capture and tracking Fish program. The findings indicate that the assemblage’s elasticity modulus and compressive strength slightly increase as the height ratio increases, that the assemblage’s cracks begin in the coal body, and that the number of crack bands inside the coal body increases as the height ratio increases. Also, the phenomenon of crack bands penetrating the rock through the interface between the coal and rock becomes increasingly apparent. The total number of cracks, including both tensile and shear cracks, decreases as the height ratio increases. Among these, tensile cracks are consistently more abundant than shear cracks, and the proportion between the two types remains relatively stable regardless of changes in the height ratio. The acoustic emission ringing counts of the assemblage were not synchronized with the development of bearing stress, and the ringing counts started to increase from the yield stage and reached a peak at the damage stage (0.8

σ_{c}

) after the peak of bearing stress. The larger the rock–coal height ratio, the smaller the peak and the earlier the timing of its appearance. The main body of strain energy accumulation was transferred from the coal body to the rock body when the height ratio exceeded 1.5. The peak values of the assemblage’s strain energy, destructive energy, and kinetic energy curves decreased as the height ratio increased, particularly the energy amplitude of the largest destructive energy event. In order to prevent and mitigate engineering disasters during deep mining of coal resources, the research findings could serve as a helpful reference for the destabilizing properties of rock–coal assemblages. Full article

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

► Show Figures

Figure 1

21 pages, 7884 KiB

Open AccessArticle

Multi-Objective Optimization Inverse Analysis for Characterization of Petroleum Geomechanical Properties During Hydraulic Fracturing

by Shike Zhang, Zhongliang Ru, Lihong Zhao, Bangxiang Li, Hongbo Zhao and Xianglong Wang

Processes 2025, 13(8), 2587; https://doi.org/10.3390/pr13082587 - 15 Aug 2025

Abstract

To address the difficulty in the characterization of the geomechanical properties of reservoirs in petroleum engineering using the traditional formula, due to the complexity of the reservoir, this study proposes a framework of inverse analysis to characterize the geomechanical properties of reservoirs formed [...] Read more.

To address the difficulty in the characterization of the geomechanical properties of reservoirs in petroleum engineering using the traditional formula, due to the complexity of the reservoir, this study proposes a framework of inverse analysis to characterize the geomechanical properties of reservoirs formed through hydraulic fracturing by combining the XGBoost, multi-objective particle swarm optimization (MOPSO), and numerical models. XGBoost was used to generate a surrogate model to approximate the physical model, and the numerical model was used to generate a dataset for XGBoost. MOPSO is regarded as an optimal technology to deal with the conflict between multi-objective functions in inverse analysis. On comparing the results between the actual geomechanical properties and those obtained by using traditional inverse analysis, the proposed framework accurately characterizes the geomechanical parameters of reservoirs obtained through hydraulic fracturing. This provides a feasible, scientific, and promising way to characterize reservoir formation in petroleum engineering, as well as a reference for other fields of engineering. Full article

(This article belongs to the Special Issue Recent Developments in Low-Carbon and Efficient Extraction Technologies of Deep Unconventional Reservoirs)

► Show Figures

Figure 1

18 pages, 796 KiB

Open AccessReview

Research Progress and Prospects of Methods for Estimating Methane Reserves in Closed Coal Mines in China

by Ying Han, Chenxiang Wang, Feiyan Zhang and Qingchao Li

Processes 2025, 13(8), 2586; https://doi.org/10.3390/pr13082586 - 15 Aug 2025

Abstract

The accurate estimation of methane reserves in closed coal mines is crucial for supporting clean energy recovery and reducing greenhouse gas emissions. This study addresses the technical challenges associated with complex geological conditions and limited post-closure data in China’s closed mines. Three mainstream [...] Read more.

The accurate estimation of methane reserves in closed coal mines is crucial for supporting clean energy recovery and reducing greenhouse gas emissions. This study addresses the technical challenges associated with complex geological conditions and limited post-closure data in China’s closed mines. Three mainstream estimation methods—the material balance, resource composition, and decline curve—are systematically reviewed and applied to a case study in the Huoxi Coalfield. Results indicate that the material balance method provides upper-bound estimates but is highly sensitive to incomplete historical data, whereas the resource composition method yields more conservative and geologically realistic values. Although the decline curve method is not applied in this case, it offers potential for forecasting when long-term monitoring data are available. A multi-method integration approach, supported by enhanced data archiving and uncertainty assessments, is recommended to improve the accuracy and reliability of methane reserve evaluations in post-mining environments. Full article

(This article belongs to the Special Issue Coalbed Methane Development Process)

1 pages, 113 KiB

Open AccessCorrection

Correction: Cai et al. Acoustic Characterization of Leakage in Buried Natural Gas Pipelines. Processes 2025, 13, 2274

by Yongjun Cai, Xiaolong Gu, Xiahua Zhang, Ke Zhang, Huiye Zhang and Zhiyi Xiong

Processes 2025, 13(8), 2585; https://doi.org/10.3390/pr13082585 - 15 Aug 2025

Abstract

In the original publication [...] Full article

18 pages, 8590 KiB

Open AccessArticle

Tensile and Fracture Properties Evaluation of Additively Manufactured Different Stainless Steels via Small Punch Testing

by Ran Li, Wenshu Wei, Mengyu Wu, Fengcai Liu, Wenbo Li, Yuehua Lai, Rongming Chen, Hao Liu, Jian Ye, Jianfeng Li and Tianze Cao

Processes 2025, 13(8), 2584; https://doi.org/10.3390/pr13082584 - 15 Aug 2025

Abstract

Laser powder bed fusion (LPBF) can fabricate hydraulic components with significant weight reduction, and in this study, small punch tests (SPTs) evaluated the tensile and fracture properties of four stainless steels (30Cr13, 316L, 15-5PH, 17-4PH), alongside metallographic, scanning electron microscope (SEM), and Electron [...] Read more.

Laser powder bed fusion (LPBF) can fabricate hydraulic components with significant weight reduction, and in this study, small punch tests (SPTs) evaluated the tensile and fracture properties of four stainless steels (30Cr13, 316L, 15-5PH, 17-4PH), alongside metallographic, scanning electron microscope (SEM), and Electron Backscatter Diffraction (EBSD) analyses which examined their fracture modes, grain orientation, phase distribution, and grain boundary distribution. The tensile property results showed ductility rankings as 316L > 17-4PH > 15-5PH > 30Cr13, with correlations between R_p0.2 and R_m from SPT and uniaxial tensile tests for all four, while high-magnification SEM fractographs revealed ductile dimples on 15-5PH, 17-4PH, and 316L SPT specimens versus distinct cleavage fracture in 30Cr13. EBSD analysis indicated austenite content order as 316L > 17-4PH > 30Cr13 > 15-5PH, grain size order as 316L > 17-4PH > 15-5PH > 30Cr13, and high-angle grain boundaries ranking as 15-5PH > 30Cr13 > 17-4PH > 316L; additionally, notched SPT specimens inspected per EN 10371 for fracture toughness showed J-integral (J_IC) values in the order 316L > 17-4PH > 15-5PH > 30Cr13, consistent with ductility and grain size results. Full article

(This article belongs to the Special Issue Welding and Additive Manufacturing Processes)

► Show Figures

Figure 1

21 pages, 4415 KiB

Open AccessArticle

Small-Signal Stability Analysis of Converter-Interfaced Systems in DC Voltage Timescale Based on Amplitude/Frequency Operating Points

by Jin Lv, Sicheng Wang and Jiabing Hu

Processes 2025, 13(8), 2583; https://doi.org/10.3390/pr13082583 - 15 Aug 2025

Abstract

The oscillations induced by voltage source converters (VSCs) in DC voltage timescale dynamics pose significant challenges to the safe and stable operation of VSC-dominated power systems. However, previous studies have conducted simplified analyses without fully understanding the fundamental roles of different timescale control [...] Read more.

The oscillations induced by voltage source converters (VSCs) in DC voltage timescale dynamics pose significant challenges to the safe and stable operation of VSC-dominated power systems. However, previous studies have conducted simplified analyses without fully understanding the fundamental roles of different timescale control loops in converter-interfaced systems. In light of this, this study first identifies the key state variables and operating points that directly characterize the energy storage levels of devices and networks in AC systems. A model for the converter-interfaced system is then established in the specified DC voltage timescale. The key contribution of this work is the proposal of an analytical framework that decomposes system stability into self-stabilizing (Self-stable) and externally coupled stabilizing (En-stable) paths based on internal voltage amplitude and frequency, aiming to reveal the physical mechanisms behind internal voltage amplitude and frequency oscillations in DC voltage timescale dynamics. Based on this framework, the Self-stable path and En-stable path of the internal voltage amplitude/frequency of converter-interfaced systems are derived. This novel analytical method mathematically decouples the stability of a single variable into a direct self-influence path and an indirect path coupled through other system variables. Subsequently, the causes of internal voltage amplitude/frequency oscillations in the specified voltage timescale are explained using the Self-stability and En-stability analysis method. A key finding of this study is that the stability of the internal voltage amplitude and frequency exhibits a dual relationship: for amplitude stability, the Self-stable path is stabilizing, whereas the coupled path is destabilizing; for frequency stability, the roles are reversed. Finally, the results are verified through simulations. Full article

(This article belongs to the Special Issue Operation and Control of New Power System with Large-Scale Renewable Energy Integration)

► Show Figures

Figure 1

22 pages, 1967 KiB

Open AccessReview

Carbon-Based Heterogeneous Catalysis for Biomass Conversion to Levulinic Acid: A Special Focus on the Catalyst

by Laura G. Covinich, Nicolás M. Clauser and María C. Area

Processes 2025, 13(8), 2582; https://doi.org/10.3390/pr13082582 - 15 Aug 2025

Abstract

The conversion of cellulosic biomass into renewable chemicals can serve as a sustainable resource for levulinic acid (LA) production. LA yield is significantly influenced by reaction temperature, reaction time, substrate concentration, active sites, catalyst amount, catalyst porosity, and durability. Beyond the features of [...] Read more.

The conversion of cellulosic biomass into renewable chemicals can serve as a sustainable resource for levulinic acid (LA) production. LA yield is significantly influenced by reaction temperature, reaction time, substrate concentration, active sites, catalyst amount, catalyst porosity, and durability. Beyond the features of the catalyst, such as acidity, porosity, functional groups, and catalytic efficiency, the contact between the solid acid catalyst and the solid substrate is of vital importance. Solid-based catalysts show remarkable catalytic activity for cellulose-derived LA production, thanks to the incorporation of functional groups. For a solid carbon-based catalyst to be effective, a synergistic interaction between the binding domain (functional groups capable of anchoring cellulose to the catalyst surface, such as chloride groups, COOH, or OH) and the hydrolysis domain (due to their ability to cleave glycosidic bonds, such as in SO₃H) is essential. As a relatively new market niche, carbon-based catalyst supports are projected to reach a market value of nearly USD 125 million by 2030. This review aims to highlight the advantages and limitations of carbon-based materials compared to conventional catalysts (including metal oxides or supported noble metals, among others) in features like catalytic activity, thermal stability, and cost, examine recent advancements in catalyst development, and identify key challenges and future research directions to enable more efficient, sustainable, and scalable processes for LA production. The novelty of this review lies in its focus on carbon-based catalysts for LA production, emphasizing their physical and chemical characteristics. Full article

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

► Show Figures

Figure 1

11 pages, 4515 KiB

Open AccessArticle

Promotion Effect and Mechanism Analysis of Different Strain Pre-Treatment on Methane Conversion from Lignite

by Yongchen Li, Zebin Wang, Hongyu Guo, Qiang Xu, Shuai Wang, Xiujia Bai, Zhengguang Zhang, Haorui Yang, Zheng Wang, Shan Ren, Guojun Zhao and Bin Zhang

Processes 2025, 13(8), 2581; https://doi.org/10.3390/pr13082581 - 15 Aug 2025

Abstract

To evaluate lignite degradation efficiency and the enhancement of biogas production by different microbial treatments, lignite was pre-treated with Streptomyces viridosporus (actinomycete), Phanerochaete chrysosporium (fungus), and Pseudomonas sp. (bacterium), followed by biogasification experiments. Among the three, Phanerochaete chrysosporium exhibited the highest lignite degradation [...] Read more.

To evaluate lignite degradation efficiency and the enhancement of biogas production by different microbial treatments, lignite was pre-treated with Streptomyces viridosporus (actinomycete), Phanerochaete chrysosporium (fungus), and Pseudomonas sp. (bacterium), followed by biogasification experiments. Among the three, Phanerochaete chrysosporium exhibited the highest lignite degradation rate. All microbial treatments improved both cumulative biogas yield and methane conversion, with Phanerochaete chrysosporium again demonstrating the most significant enhancement. Ultimate analysis after degradation showed the following consistent trends across all treatments: increases in carbon, hydrogen, and nitrogen contents, and reductions in sulfur and oxygen contents. A linear correlation was observed between the H/C atomic ratio and total biogas yield. Functional group analysis revealed the greatest reductions in key functional groups with Phanerochaete chrysosporium, followed by moderate changes with Pseudomonas and Streptomyces viridosporus. Pore structure characterization indicated that all microorganisms influenced lignite porosity, particularly in mesopore and micropore regions. Increases in pore volume and connectivity were associated with improved biogas production efficiency. Full article

(This article belongs to the Special Issue Theoretical Progress in the Exploration and Development of Deep Coal-Measure Gas)

► Show Figures

Figure 1

13 pages, 3025 KiB

Open AccessArticle

Numerical Study on the Effect of Baffle Structures on the Diesel Conditioning Process

by Lanqi Zhang, Chenping Wu, Tianyi Sun, Botao Yu, Xiangnan Chu, Qi Ma, Yulong Yin, Haotian Ye and Xiangyu Meng

Processes 2025, 13(8), 2580; https://doi.org/10.3390/pr13082580 - 15 Aug 2025

Abstract

Emergency diesel is prone to degradation during long-term storage, and experimental evaluations are costly and slow. Three-dimensional computational fluid dynamics (CFD) simulations were employed to model the diesel conditioning process. A physical model based on the actual dimensions of the storage tank was [...] Read more.

Emergency diesel is prone to degradation during long-term storage, and experimental evaluations are costly and slow. Three-dimensional computational fluid dynamics (CFD) simulations were employed to model the diesel conditioning process. A physical model based on the actual dimensions of the storage tank was constructed. The volume of fraction (VOF) model tracked the gas–liquid interface, and the species transport model handled mixture transport. A UDF then recorded inlet and outlet flow rates and velocities in each cycle. The study focused on the effects of different baffle structures and numbers on conditioning efficiency. Results showed that increasing the baffle flow area significantly delays the mixing time but reduces the cycle time. Openings at the bottom of baffles effectively mitigate the accumulation of high-concentration conditioning oil caused by density differences. Increasing the number of baffles decreases the effective volume of the tank and amplifies density differences across the baffles, which shortens the mixing time. However, excessive baffle numbers diminish these benefits. These findings provide essential theoretical guidance for optimizing baffle design in practical diesel tanks, facilitating rapid achievement of emergency diesel quality standards while reducing costs and improving efficiency. Full article

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

► Show Figures

Figure 1

12 pages, 610 KiB

Open AccessArticle

High-Accuracy Harmonic Source Localization in Transmission Networks Using Voltage Difference Features and Random Forest

by Sijia Liu, Pengchao Lei and Bo Zhao

Processes 2025, 13(8), 2579; https://doi.org/10.3390/pr13082579 - 15 Aug 2025

Abstract

This paper proposes a harmonic source localization method for power systems, combining voltage difference features with a random forest classifier. The method captures harmonic propagation patterns and optimizes network topology handling to ensure accurate and efficient identification across various configurations. Validated on IEEE [...] Read more.

This paper proposes a harmonic source localization method for power systems, combining voltage difference features with a random forest classifier. The method captures harmonic propagation patterns and optimizes network topology handling to ensure accurate and efficient identification across various configurations. Validated on IEEE standard transmission networks, it achieves high accuracy and scalability. While effective in transmission systems, distribution networks pose challenges due to complex topologies and high impedance. Future enhancements will focus on advanced feature engineering, data augmentation, and real-time processing to improve adaptability in diverse power system environments. Full article

(This article belongs to the Special Issue AI-Driven Innovations for Enhancing Power System Stability and Operational Efficiency)

► Show Figures

Figure 1

11 pages, 1639 KiB

Open AccessArticle

Application of EPR Spectroscopy to Determine the Influence of Simvastatin Concentration on Free Radicals in G-361 Human Melanoma malignum Cells

by Ewa Chodurek, Magdalena Zdybel and Barbara Pilawa

Processes 2025, 13(8), 2578; https://doi.org/10.3390/pr13082578 - 14 Aug 2025

Abstract

Free radicals in G-361 human melanoma malignum control cells and the cells cultured with simvastatin were examined by EPR spectroscopy. The proliferation of the cells was determined. The aim of this work was to examine the influence of simvastatin used at different concentrations [...] Read more.

Free radicals in G-361 human melanoma malignum control cells and the cells cultured with simvastatin were examined by EPR spectroscopy. The proliferation of the cells was determined. The aim of this work was to examine the influence of simvastatin used at different concentrations in the G-361 cell culture on its free radicals. The concentrations of simvastatin—0.1 μM, 1 μM, 3 μM, and 5 μM—were tested. EPR spectra of free radicals were measured by an X-band (9.3 GHz) spectrometer. Amplitudes, integral intensities, linewidths, and g factors were determined. Melanin biopolymers are the main source of o-semiquinone free radicals in G-361 human melanoma malignum cells, for which the EPR lines show characteristic g values of 2.0046–2.0059, but also, free radicals occurring in other cellular structures may contribute to these signals. The amount of free radicals decreases after interactions of simvastatin with the G-361 cells, and this effect depends on the concentration of simvastatin. The highest amounts of free radicals exist in G-361 cells cultured with simvastatin at concentrations of 3 μM and 5 μM. The relatively lower amounts of free radicals occur in G-361 cells cultured with simvastatin at concentrations of 0.1 μM and 1 μM. The fast spin–lattice relaxation processes exist in the control G-361 cells and in the cells cultured with simvastatin, regardless of simvastatin concentration. Full article

(This article belongs to the Special Issue Studies of the Dosage Form and Stability of the Drug by Various Techniques, 2nd Edition)

► Show Figures

Figure 1

21 pages, 3303 KiB

Open AccessArticle

ResNet + Self-Attention-Based Acoustic Fingerprint Fault Diagnosis Algorithm for Hydroelectric Turbine Generators

by Wei Wang, Jiaxiang Xu, Xin Li, Kang Tong, Kailun Shi, Xin Mao, Junxue Wang, Yunfeng Zhang and Yong Liao

Processes 2025, 13(8), 2577; https://doi.org/10.3390/pr13082577 - 14 Aug 2025

Abstract

To address the issues of reduced operational efficiency, shortened equipment lifespan, and significant safety hazards caused by bearing wear and blade cavitation in hydroelectric turbine generators due to prolonged high-load operation, this paper proposes a ResNet + self-attention-based acoustic fingerprint fault diagnosis algorithm [...] Read more.

To address the issues of reduced operational efficiency, shortened equipment lifespan, and significant safety hazards caused by bearing wear and blade cavitation in hydroelectric turbine generators due to prolonged high-load operation, this paper proposes a ResNet + self-attention-based acoustic fingerprint fault diagnosis algorithm for hydroelectric turbine generators. First, to address the issue of severe noise interference in acoustic signature signals, the ensemble empirical mode decomposition (EEMD) is employed to decompose the original signal into multiple intrinsic mode function (IMF) components. By calculating the correlation coefficients between each IMF component and the original signal, effective components are selected while noise components are removed to enhance the signal-to-noise ratio; Second, a fault identification network based on ResNet + self-attention fusion is constructed. The residual structure of ResNet is used to extract features from the acoustic signature signal, while the self-attention mechanism is introduced to focus the model on fault-sensitive regions, thereby enhancing feature representation capabilities. Finally, to address the challenge of model hyperparameter optimization, a Bayesian optimization algorithm is employed to accelerate model convergence and improve diagnostic performance. Experiments were conducted in the real working environment of a pumped-storage power station in Zhejiang Province, China. The results show that the algorithm significantly outperforms traditional methods in both single-fault and mixed-fault identification, achieving a fault identification accuracy rate of 99.4% on the test set. It maintains high accuracy even in real-world scenarios with superimposed noise and environmental sounds, fully validating its generalization capability and interference resistance, and providing effective technical support for the intelligent maintenance of hydroelectric generator units. Full article

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

14 pages, 2685 KiB

Open AccessArticle

Assessing the Effects of Green Surface Coatings on the Corrosion-Related Mechanical Attributes of Materials

by Mohammed A. Albadrani

Processes 2025, 13(8), 2576; https://doi.org/10.3390/pr13082576 - 14 Aug 2025

Abstract

This study investigates the effectiveness of an environmentally friendly coating in mitigating corrosion and preserving the mechanical properties of carbon steel, copper, and aluminium. The coated and uncoated samples were subjected to a 20-day immersion in 5% NaCl solution. Corrosion behaviour was assessed [...] Read more.

This study investigates the effectiveness of an environmentally friendly coating in mitigating corrosion and preserving the mechanical properties of carbon steel, copper, and aluminium. The coated and uncoated samples were subjected to a 20-day immersion in 5% NaCl solution. Corrosion behaviour was assessed using Linear Sweep Voltammetry (LSV), Open Circuit Potential (OCP), and Electrochemical Impedance Spectroscopy (EIS), while mechanical performance was evaluated through tensile testing. The coating’s thickness, surface roughness, water contact angle, and composition were characterised to understand its protective behaviour. The results show that the coating significantly reduced corrosion rates, with carbon steel exhibiting a 99.99% inhibition efficiency and aluminium showing the lowest corrosion rate due to a synergistic effect between the coating and native oxide layer. Mechanical testing revealed that coated carbon steel retained higher tensile strength and stiffness compared to its uncoated counterpart, while aluminium showed notable recovery in elastic modulus. Copper displayed minimal mechanical changes due to its inherent corrosion resistance. This work highlights the potential of eco-friendly coatings in enhancing both the corrosion resistance and mechanical durability of metallic materials in aggressive environments. Full article

(This article belongs to the Section Materials Processes)

► Show Figures

Figure 1

36 pages, 8425 KiB

Open AccessFeature PaperArticle

Multifactorial Analysis of Defects in Oil Storage Tanks: Implications for Structural Performance and Safety

by Alexandru-Adrian Stoicescu, Razvan George Ripeanu, Maria Tănase, Costin Nicolae Ilincă and Liviu Toader

Processes 2025, 13(8), 2575; https://doi.org/10.3390/pr13082575 - 14 Aug 2025

Abstract

This article investigates the combined effects of different common defects on the structural integrity and operational and environmental safety in the operation of an existing Light Cycle Oil (LCO) storage tank. This study correlates all the tank defects (like corrosion and local plate [...] Read more.

This article investigates the combined effects of different common defects on the structural integrity and operational and environmental safety in the operation of an existing Light Cycle Oil (LCO) storage tank. This study correlates all the tank defects (like corrosion and local plate thinning, deformations, and local stress concentrators) against the loads and their combinations that occur during the tank’s lifetime. All the information gathered by various inspection techniques is used together to create a digital twin of the equipment that will be further analyzed by Finite Element Analysis. A tank condition assessment is a complex activity, and it is based on the experience of the engineer performing it. Since there are multiple methods for performing a comprehensive analysis, starting from the basic visual inspection (which is the most important) and some measurements followed by analytical calculations, up to full wall thickness measurements, 3D scan of deformations and FEA analysis of the tank digital twin, it depends on the engineer performing the evaluation to chose the best method for each particular case from technical and economical point of views. The goal of this article is to demonstrate that analytical and FEA methods have the same result and also to establish a well-determined standard calculation model for future applications. Full article

(This article belongs to the Section Materials Processes)

► Show Figures

Figure 1

32 pages, 9222 KiB

Open AccessArticle

Thermodynamic Modeling of Multilayer Insulation Schemes Coupling Liquid Nitrogen Cooled Shield and Vapour Hydrogen Cooled Shield for LH₂ Tank

by Jingyang Lu, Liqiong Chen and Xingyu Zhou

Processes 2025, 13(8), 2574; https://doi.org/10.3390/pr13082574 - 14 Aug 2025

Abstract

The thermal insulation performance of liquid hydrogen (LH₂) storage tanks is critical for long-distance transportation. The active cooled shield (ACS) technologies, such as the liquid nitrogen cooled shield (LNCS) and the vapor hydrogen cooled shield (VHVCS) are important thermal insulation methods. [...] Read more.

The thermal insulation performance of liquid hydrogen (LH₂) storage tanks is critical for long-distance transportation. The active cooled shield (ACS) technologies, such as the liquid nitrogen cooled shield (LNCS) and the vapor hydrogen cooled shield (VHVCS) are important thermal insulation methods. Many researchers installed the VHVCS inside the multilayer insulation (MLI) and obtained the optimal position. However, the MLI layer is often thinner than the vacuum interlayer between the inner and outer tanks, and there is a large vacuum interlayer between the outermost side of MLI and the inner wall of the outer tank. It is unknown whether the insulation performance can be improved if we install ACS in the mentioned vacuum interlayer and separate a portion of the MLI to be installed on the outer surface of ACS. In this configuration, the number of inner MLI (IMLI) layers and the ACS position are interdependent, a coupling that has not been thoroughly investigated. Therefore, thermodynamic models for MLI, MLI-LNCS, and MLI-VHVCS schemes were developed based on the Layer-by-Layer method. By applying Robin boundary conditions, the temperature distribution and heat leakage of the MLI scheme were predicted. Considering the coupled effects of IMLI layer count and ACS position, a co-optimization strategy was adopted, based on an alternating iterative search algorithm. The results indicate that for the MLI-LNCS scheme, the optimal number of IMLI layers and LNCS position are 36 layers and 49%, respectively. For the MLI-VHVCS scheme, the optimal values are 21 layers and 39%, respectively. Compared to conventional MLI, the MLI-LNCS scheme achieves an 88.09% reduction in heat leakage. However, this improvement involves increased system complexity and higher operational costs from LN₂ circulation. In contrast, the MLI-VHVCS scheme achieves a 62.74% reduction in heat leakage, demonstrating that using sensible heat from cryogenic vapor can significantly improve the thermal insulation performance of LH₂ storage tanks. The work of this paper provides a reference for the design and optimization of the insulation scheme of LH₂ storage tanks. Full article

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

► Show Figures

Figure 1

22 pages, 2556 KiB

Open AccessArticle

The Elastic Vibration Behavior of a Springboard in Gymnastics

by Daniel-Mirel Dumitrescu, Gheorghe Voicu, Nicolaie Orasanu, Irina-Aura Istrate and Gabriel-Alexandru Constantin

Processes 2025, 13(8), 2573; https://doi.org/10.3390/pr13082573 - 14 Aug 2025

Abstract

The paper presents aspects of the elastic behavior of a springboard in school gyms after contact with a basketball (0.500 kg) falling from a height of 1 m or a volunteer student jumping from 30 or 60 cm in three different areas at [...] Read more.

The paper presents aspects of the elastic behavior of a springboard in school gyms after contact with a basketball (0.500 kg) falling from a height of 1 m or a volunteer student jumping from 30 or 60 cm in three different areas at the end of the springboard. The results recorded obtained from three accelerometers mounted under the main plate of the springboard are presented, primarily focusing on the accelerations and vertical displacements after contact. The springboard has a special construction, the upper plate and the curved support plates being provided with two pairs of conical and cylindrical truncated helical springs, respectively. The accelerometers were placed at different points, centrally on the upper plate and on the support plates. It was found that in the dynamic process of a body falling on the springboard, the coefficient of elasticity/rigidity of the elastic system changes, presenting values of 22.14–71.12 kN/m. Normally, both accelerations and displacements are greater on the upper plate, but its vibratory motion also induces additional movements and vibrations on the two lower plates. The results may be useful both for manufacturers of such equipment and for coaches to give appropriate instructions to athletes. Full article

(This article belongs to the Special Issue Product Design and the Optimization of Technologies for Manufacturing Processes)

► Show Figures

Figure 1

19 pages, 4394 KiB

Open AccessArticle

Research on Optimized YOLOv5s Algorithm for Detecting Aircraft Landing Runway Markings

by Wei Huang, Hongrui Guo, Xiangquan Li, Xi Tan and Bo Liu

Processes 2025, 13(8), 2572; https://doi.org/10.3390/pr13082572 - 14 Aug 2025

Abstract

During traditional aircraft landings, pilots face significant challenges in identifying runway numbers with the naked eye, particularly at decision height under adverse weather conditions. To address this issue, this study proposes a novel detection algorithm based on an optimized version of the YOLOv5s [...] Read more.

During traditional aircraft landings, pilots face significant challenges in identifying runway numbers with the naked eye, particularly at decision height under adverse weather conditions. To address this issue, this study proposes a novel detection algorithm based on an optimized version of the YOLOv5s model (You Only Look Once, version 5) for recognizing runway markings during civil aircraft landings. By integrating a data augmentation strategy with external datasets, the method effectively reduces both false detections and missed targets through expanded feature representation. An Alpha Complete Intersection over Union (CIOU) Loss function is introduced in place of the original CIOU Loss function, offering improved gradient optimization. Additionally, the model incorporates several advanced modules and techniques, including a Convolutional Block Attention Module (CBAM), Soft Non-Maximum Suppression (Soft-NMS), cosine annealing learning rate scheduling, the FReLU activation function, and deformable convolutions into the backbone and neck of the YOLOv5 architecture. To further enhance detection, a specialized small-target detection layer is added to the head of the network and the resolution of feature maps is improved. These enhancements enable better feature extraction and more accurate identification of smaller targets. As a result, the optimized model shows significantly improved recall (R) and precision (P). Experimental results, visualized using custom-developed software, demonstrate that the proposed optimized YOLOv5s model achieved increases of 5.66% in P, 2.99% in R, and 2.74% in mean average precision (mAP) compared to the baseline model. This study provides valuable data and a theoretical foundation to support the accurate visual identification of runway numbers and other reference markings during aircraft landings. Full article

(This article belongs to the Special Issue Modelling and Optimizing Process in Industry 4.0)

► Show Figures

Figure 1

27 pages, 654 KiB

Open AccessArticle

The Interplay of Network Architecture and Performance in Supply Chains: A Multi-Tier Analysis of Visible and Invisible Ties

by Myung Kyo Kim and Tobias Schoenherr

Processes 2025, 13(8), 2571; https://doi.org/10.3390/pr13082571 - 14 Aug 2025

Abstract

While supply chain competition increasingly occurs at the network level, most research remains limited to dyadic or triadic relationships, failing to capture the full complexity of multi-tier supply networks. This research investigates the influence of four distinct types of network ties—contractual, transactional, professional, [...] Read more.

While supply chain competition increasingly occurs at the network level, most research remains limited to dyadic or triadic relationships, failing to capture the full complexity of multi-tier supply networks. This research investigates the influence of four distinct types of network ties—contractual, transactional, professional, and personal—on supply chain performance, evaluated across five dimensions: cost, quality, delivery, flexibility, and innovation. The analysis draws on data gathered from 153 component-level supply networks, encompassing a total of 1852 entities within South Korea’s automotive and electronics manufacturing sectors. We employed social network analysis with a directed-valued network approach to capture asymmetric relationships. Results reveal that network architecture affects performance dimensions differently: centralized professional knowledge sharing enhances delivery performance, while concentrated personal ties prove detrimental; for innovation, dense network connections and dominant transactional hubs unexpectedly hinder performance by fostering conformity; cost performance shows mixed effects, with transactional centralization impeding efficiency while professional and personal leadership facilitates cost reduction. The influence of the original equipment manufacturer on supplier selection moderates these relationships, particularly mitigating negative impacts of personal tie centralization. These findings challenge conventional assumptions about network density benefits and demonstrate that supply network competence—the ability to configure and leverage network architecture—requires careful consideration of multiple tie types and their distinct effects on different performance outcomes. Full article

(This article belongs to the Special Issue Innovation and Optimization of Production Processes in Industry 4.0)

► Show Figures

Figure 1

19 pages, 4892 KiB

Open AccessArticle

Deformation, Failure Mechanism and Control Technology of Soft Rock Roadways Buried Under Coal Pillars: A Case Study

by Yewu Bi, Yichen Li, Feng Xu and Lihua Zhu

Processes 2025, 13(8), 2570; https://doi.org/10.3390/pr13082570 - 14 Aug 2025

Abstract

Close-distance coal seam mining in Danhou coal mine has caused serious deformation in the underlying soft rock roadways. The mechanism of this type of deformation is explored through theoretical analysis and numerical simulation, and corresponding control measures are proposed. Firstly, the mechanical model [...] Read more.

Close-distance coal seam mining in Danhou coal mine has caused serious deformation in the underlying soft rock roadways. The mechanism of this type of deformation is explored through theoretical analysis and numerical simulation, and corresponding control measures are proposed. Firstly, the mechanical model of abutment stress transfer along the underlying rock stratum is established, and the analytical solution of abutment stress at any point of the underlying rock stratum is derived. Secondly, the impact of upper working face mining on the underlying soft rock roadway is investigated through numerical simulation. Subsequently, the stress distribution characteristics of the surrounding rock of the rectangular roadway and straight- wall arch roadway are compared and analyzed. Finally, a support scheme for the underlying soft rock roadway is presented and implemented in engineering practice. Field engineering application results demonstrate that, after the combined support of high-strength bolts and grouting, the average deformation on both sides of the roadway is reduced by 63.4%, and the average floor heave is decreased by 93%. This indicates that the technology effectively controls the deformation of the surrounding rock in soft rock roadways during close-distance coal seam mining. Full article

(This article belongs to the Special Issue Monitoring, Process Control and Prevention Measures for Safety Problems in Coal Mining)

► Show Figures

Figure 1

29 pages, 7152 KiB

Open AccessReview

Application of Large AI Models in Safety and Emergency Management of the Power Industry in China

by Wenxiang Guang, Yin Yuan, Shixin Huang, Fan Zhang, Jingyi Zhao and Fan Hu

Processes 2025, 13(8), 2569; https://doi.org/10.3390/pr13082569 - 14 Aug 2025

Abstract

Under the framework of the “dual-carbon” goals of China (“carbon peak” by 2030 and “carbon neutrality” by 2060), the escalating complexity of emerging power systems presents significant challenges to safety governance. Traditional management models are now confronting bottlenecks, notably in knowledge inheritance breakdown [...] Read more.

Under the framework of the “dual-carbon” goals of China (“carbon peak” by 2030 and “carbon neutrality” by 2060), the escalating complexity of emerging power systems presents significant challenges to safety governance. Traditional management models are now confronting bottlenecks, notably in knowledge inheritance breakdown and lagging risk prevention and control. This paper explores the application of large AI models in safety and emergency management in the power industry. Through core capabilities—such as natural language processing (NLP), knowledge reasoning, multimodal interaction, and auxiliary decision making—it achieves full-process optimization from data fusion to intelligent decision making. The study, anchored by 18 cases across five core scenarios, identifies three-dimensional challenges (including “soft”—dimension computing power, algorithm, and data bottlenecks; “hard”—dimension inspection equipment and wearable device constraints; and “risk”—dimension responsibility ambiguity, data bias accumulation, and model “hallucination” risks). It further outlines future directions for large-AI-model application innovation in power industry safety and management from a four-pronged outlook, covering technology, computing power, management, and macro-level perspectives. This work aims to provide theoretical and practical guidance for the industry’s shift from “passive response” to “intelligent proactive prevention”, leveraging quantified scenario-case analysis. Full article

(This article belongs to the Special Issue Environmental Governance and Sustainable Development: Multipollutant Control and Resource-Energy Transition)

► Show Figures

Figure 1

26 pages, 4742 KiB

Open AccessArticle

Design and Evaluation of LLDPE/Epoxy Composite Tiles with YOLOv8-Based Defect Detection for Flooring Applications

by I. Infanta Mary Priya, Siddharth Anand, Aravindan Bishwakarma, M. Uma, Sethuramalingam Prabhu and M. M. Reddy

Processes 2025, 13(8), 2568; https://doi.org/10.3390/pr13082568 - 14 Aug 2025

Abstract

With the increasing demand for sustainable and cost-effective alternatives in the construction industry, polymer composites have emerged as a promising solution. This study focuses on the development of innovative composite tiles using Linear Low-Density Polyethylene (LLDPE) powder blended with epoxy resin and a [...] Read more.

With the increasing demand for sustainable and cost-effective alternatives in the construction industry, polymer composites have emerged as a promising solution. This study focuses on the development of innovative composite tiles using Linear Low-Density Polyethylene (LLDPE) powder blended with epoxy resin and a hardener as a green substitute for conventional ceramic and cement tiles. LLDPE is recognized for its flexibility, durability, and chemical resistance, making it an effective filler within the epoxy matrix. To optimize its material properties, composite samples were fabricated using three different LLDPE-to-epoxy ratios: 30:70, 40:60, and 50:50. Flexural strength testing revealed that while the 50:50 blend achieved the highest maximum value (29.887 MPa), it also exhibited significant variability, reducing its reliability for practical applications. In contrast, the 40:60 ratio demonstrated more consistent and repeatable flexural strength, ranging from 16 to 20 MPa, which is ideal for flooring applications where mechanical performance under repeated loading is critical. Scanning Electron Microscopy (SEM) images confirmed uniform filler dispersion in the 40:60 mix, further supporting its mechanical consistency. The 30:70 composition showed irregular and erratic behaviour, with values ranging from 11.596 to 25.765 MPa, indicating poor dispersion and increased brittleness. To complement the development of the materials, deep learning techniques were employed for real-time defect detection in the manufactured tiles. Utilizing the YOLOv8 (You Only Look Once version 8) algorithm, this study implemented an automated, vision-based surface monitoring system capable of identifying surface deterioration and defects. A dataset comprising over 100 annotated images was prepared, featuring various surface defects such as cracks, craters, glaze detachment, and tile lacunae, alongside defect-free samples. The integration of machine learning not only enhances quality control in the production process but also offers a scalable solution for defect detection in large-scale manufacturing environments. This research demonstrates a dual approach to material innovation and intelligent defect detection to improve the performance and quality assurance of composite tiles, contributing to sustainable construction practices. Full article

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

► Show Figures

Figure 1

21 pages, 313 KiB

Open AccessFeature PaperReview

Valorization of Food Industry Waste for Biodegradable Biopolymer-Based Packaging Films

by Kristina Cvetković, Ivana Karabegović, Simona Dordevic, Dani Dordevic and Bojana Danilović

Processes 2025, 13(8), 2567; https://doi.org/10.3390/pr13082567 - 14 Aug 2025

Abstract

In recent years, food waste management has become one of the key challenges faced by modern society. The significant ecological footprint left by this type of waste can be mitigated through proper valorization. Directing food waste towards the production of biopolymers has attracted [...] Read more.

In recent years, food waste management has become one of the key challenges faced by modern society. The significant ecological footprint left by this type of waste can be mitigated through proper valorization. Directing food waste towards the production of biopolymers has attracted considerable attention from researchers. Plant- and animal-based by-products from the food industry are the valuable materials which can be utilized for the production of biopolymer-based films. Although the use of food waste in biopolymer film production holds great potential, various factors such as the type of source and extraction methods significantly affect the physicochemical properties of the films. With the addition of various compounds that enhance their antioxidant and antimicrobial effects, these films can prolong the freshness and safety of packaged products, making them comparable to plastic derived from fossil fuels. This review highlights the potential of biopolymers from food waste for the production of biopolymer-based films and the possibilities of their modification in order to improve their properties for use in the food packaging industry. Full article

(This article belongs to the Special Issue Resource Utilization of Food Industry Byproducts)

19 pages, 6352 KiB

Open AccessArticle

Laboratory Investigation of Miscible CO₂-Induced Enhanced Oil Recovery from the East-Southern Pre-Caspian Region

by Ainur B. Niyazbayeva, Rinat B. Merbayev, Yernazar R. Samenov, Assel T. Zholdybayeva, Ashirgul A. Kozhagulova and Ainash D. Shabdirova

Processes 2025, 13(8), 2566; https://doi.org/10.3390/pr13082566 - 14 Aug 2025

Abstract

Enhanced oil recovery (EOR) techniques are essential for maximizing hydrocarbon extraction from mature reservoirs. CO₂ injection (CO₂-EOR) is a promising technology that improves oil recovery while contributing to greenhouse gas reduction. This study investigates the potential of miscible CO₂ [...] Read more.

Enhanced oil recovery (EOR) techniques are essential for maximizing hydrocarbon extraction from mature reservoirs. CO₂ injection (CO₂-EOR) is a promising technology that improves oil recovery while contributing to greenhouse gas reduction. This study investigates the potential of miscible CO₂-enhanced oil recovery (CO₂-EOR) in the MakXX oilfield of southeastern Kazakhstan. The aim is to assess oil displacement efficiency and its impact on key rock properties, including porosity, permeability, and mineral composition, under reservoir conditions. Core flooding experiments were conducted at 13 MPa and 42 °C using high-precision equipment to replicate reservoir conditions. The core was analyzed before and after CO₂ injection using SEM, EDS, and XRD. The results revealed a 54% oil recovery efficiency, accompanied by a 19% decrease in permeability and 8% reduction in porosity due to mineral precipitation and clay transformation. These findings provide insight into the performance and limitations of CO₂-EOR and support its application in similar lithology. To confirm and upscale laboratory observations, numerical simulation was conducted using a compositional model. The results demonstrated improved oil recovery, pressure stabilization, and enhanced sweep efficiency under CO₂ injection, supporting the scalability and field applicability of the proposed EOR approach. Full article

(This article belongs to the Special Issue Unconventional Energy, Clean Energy and Carbon Sequestration: Progress in Technology)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Processes, Volume 13, Issue 8 (August 2025) – 274 articles

Further Information

Guidelines

MDPI Initiatives

Follow MDPI