Pub Date : 2025-09-22DOI: 10.1016/j.jestch.2025.102197
Yuzhao Zhang , Shenyingze Gao , Xuan Ji
This study proposes an energy-efficient operation diagram optimization method for high-speed trains considering the deployment of energy storage devices. A hybrid PSO-SA algorithm is developed to solve the model, incorporating constraints such as departure times, dwell durations, and safety headways. Validated on the Baoji-Lanzhou section, results demonstrate an immediate regenerative energy utilization rate of 47.26 %, rising to 62.79 % with energy storage deployment. The hybrid algorithm reduces computation time by 74.59 % compared to traditional SA algorithm while maintaining solution quality. Compared with the GA algorithm, the optimal result obtained by the PSO-SA algorithm improved by 4.76 %. Economic analysis highlights prioritizing storage deployment in key power supply zones for optimal cost-effectiveness, offering actionable strategies for sustainable railway operations. This research provides theoretical and practical insights into energy-efficient high-speed rail systems.
{"title":"Energy-efficient operation diagram optimization for high-speed trains considering energy storage device deployment","authors":"Yuzhao Zhang , Shenyingze Gao , Xuan Ji","doi":"10.1016/j.jestch.2025.102197","DOIUrl":"10.1016/j.jestch.2025.102197","url":null,"abstract":"<div><div>This study proposes an energy-efficient operation diagram optimization method for high-speed trains considering the deployment of energy storage devices. A hybrid PSO-SA algorithm is developed to solve the model, incorporating constraints such as departure times, dwell durations, and safety headways. Validated on the Baoji-Lanzhou section, results demonstrate an immediate regenerative energy utilization rate of 47.26 %, rising to 62.79 % with energy storage deployment. The hybrid algorithm reduces computation time by 74.59 % compared to traditional SA algorithm while maintaining solution quality. Compared with the GA algorithm, the optimal result obtained by the PSO-SA algorithm improved by 4.76 %. Economic analysis highlights prioritizing storage deployment in key power supply zones for optimal cost-effectiveness, offering actionable strategies for sustainable railway operations. This research provides theoretical and practical insights into energy-efficient high-speed rail systems.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"71 ","pages":"Article 102197"},"PeriodicalIF":5.4,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145119166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-20DOI: 10.1016/j.jestch.2025.102196
Rongliang Shi , Junming Li , Xing Zhang , Junhui Li , Zheng Dong
Transient damping has emerged as a key technique for mitigating active power oscillations in grid-forming virtual synchronous generator (GFVSG) systems, whether operating in grid-connected or parallel configurations. This study first elucidates the operating principles and primary functions of transient damping within GFVSG control, drawing on the electromechanical analogy and an energy reconstruction perspective. Typical transient damping approaches are then classified, followed by the proposal of a systematic parameter design strategy and an evaluation of their dynamic performance. Building on the limitations of existing research, this work contributes by identifying the research prospects, highlighting critical technical challenges, and suggesting structured pathways for further improvement. Finally, the paper provides a comprehensive synthesis intended to deepen understanding of the advantages and limitations of transient damping control in GFVSGs, while offering theoretical insights to support sustained advances in this field.
{"title":"A comprehensive review and prospect of transient damping methods for grid-forming virtual synchronous generator","authors":"Rongliang Shi , Junming Li , Xing Zhang , Junhui Li , Zheng Dong","doi":"10.1016/j.jestch.2025.102196","DOIUrl":"10.1016/j.jestch.2025.102196","url":null,"abstract":"<div><div>Transient damping has emerged as a key technique for mitigating active power oscillations in grid-forming virtual synchronous generator (GFVSG) systems, whether operating in grid-connected or parallel configurations. This study first elucidates the operating principles and primary functions of transient damping within GFVSG control, drawing on the electromechanical analogy and an energy reconstruction perspective. Typical transient damping approaches are then classified, followed by the proposal of a systematic parameter design strategy and an evaluation of their dynamic performance. Building on the limitations of existing research, this work contributes by identifying the research prospects, highlighting critical technical challenges, and suggesting structured pathways for further improvement. Finally, the paper provides a comprehensive synthesis intended to deepen understanding of the advantages and limitations of transient damping control in GFVSGs, while offering theoretical insights to support sustained advances in this field.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"71 ","pages":"Article 102196"},"PeriodicalIF":5.4,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145097407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-19DOI: 10.1016/j.jestch.2025.102185
Abdullah Talha Sözer
Falls, often causing injuries in older individuals, involve an unintentional descent to a lower level, like the ground. With the aging global population, addressing fall risks is crucial. Besides falls, delayed medical services post-fall may cause secondary complications. Automated fall detection (FD) systems can promptly identify falls and alert responders. Among automated FD systems, wearable sensor-based ones seem most viable for widespread use. These effectively distinguish falls from daily activities using machine learning techniques. However, their high computational complexity increases power consumption, requires powerful processors, and consequently raises costs. This underscores the need for affordable, embeddable algorithms. Developing highly accurate embeddable algorithms with manageable computational costs remains a current research challenge. This study introduces an algorithm tailored specifically for embedded systems, focusing on ease of implementation and reliance solely on accelerometer data. Empowered by a novel feature, the algorithm integrates thresholding and machine learning techniques, resulting in low computational complexity while maintaining highly effective FD capabilities. Evaluations of the algorithm on comprehensive public fall datasets, KFall and SisFall, demonstrate accuracies exceeding 99% and 97%, respectively. Furthermore, validation on real-world fall events from the FARSEEING dataset yielded an accuracy of 77.3%. Additionally, the proposed algorithm underwent real-time offline analysis on a low-power embedded device. The computational complexity of the proposed method is assessed by comparing it with another low-cost algorithm. Comparative evaluations against a low-cost algorithm, deep learning-based methods, and findings from the literature emphasize the superior performance and cost-effectiveness of this algorithm. Furthermore, the algorithm’s robustness is confirmed through testing at various sampling frequencies, highlighting its ability to achieve successful FD independent of sampling frequency.
{"title":"A cost-effective embeddable algorithm for accelerometer-based fall detector","authors":"Abdullah Talha Sözer","doi":"10.1016/j.jestch.2025.102185","DOIUrl":"10.1016/j.jestch.2025.102185","url":null,"abstract":"<div><div>Falls, often causing injuries in older individuals, involve an unintentional descent to a lower level, like the ground. With the aging global population, addressing fall risks is crucial. Besides falls, delayed medical services post-fall may cause secondary complications. Automated fall detection (FD) systems can promptly identify falls and alert responders. Among automated FD systems, wearable sensor-based ones seem most viable for widespread use. These effectively distinguish falls from daily activities using machine learning techniques. However, their high computational complexity increases power consumption, requires powerful processors, and consequently raises costs. This underscores the need for affordable, embeddable algorithms. Developing highly accurate embeddable algorithms with manageable computational costs remains a current research challenge. This study introduces an algorithm tailored specifically for embedded systems, focusing on ease of implementation and reliance solely on accelerometer data. Empowered by a novel feature, the algorithm integrates thresholding and machine learning techniques, resulting in low computational complexity while maintaining highly effective FD capabilities. Evaluations of the algorithm on comprehensive public fall datasets, KFall and SisFall, demonstrate accuracies exceeding 99% and 97%, respectively. Furthermore, validation on real-world fall events from the FARSEEING dataset yielded an accuracy of 77.3%. Additionally, the proposed algorithm underwent real-time offline analysis on a low-power embedded device. The computational complexity of the proposed method is assessed by comparing it with another low-cost algorithm. Comparative evaluations against a low-cost algorithm, deep learning-based methods, and findings from the literature emphasize the superior performance and cost-effectiveness of this algorithm. Furthermore, the algorithm’s robustness is confirmed through testing at various sampling frequencies, highlighting its ability to achieve successful FD independent of sampling frequency.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"71 ","pages":"Article 102185"},"PeriodicalIF":5.4,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145097393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-17DOI: 10.1016/j.jestch.2025.102187
Bin Tang, Jufang Yao, Haobin Jiang, Wei Mi
Due to the current limitations of autonomous driving technology, human–machine co-driving is viewed as a viable and practical intermediary solution to bridge the gap between assisted driving and fully automated driving. To address challenges related to the allocation of lateral and longitudinal driving authority, as well as the interaction between the driver and the autonomous system, this paper proposes a game-sharing control strategy that operates at both the decision-making and control levels. At the decision level, a bargaining game-based approach is employed to allocate lateral and longitudinal driving authority dynamically, adjusting the distribution in accordance with a benefit function. At the control level, a lateral controller based on an extended game is developed to compute the optimal control manoeuvres by combining the driver’s inputs and reference tracking commands. This controller smoothly combines control inputs from both the driver and the automated system to ensure vehicle stability and minimize human–machine conflict. Simulation results show that, under a double lane-change scenario, the proposed strategy reduces yaw rate, lateral velocity, and lateral deviation by 0.35 rad/s, 0.6 m/s, and 0.6 m, respectively, compared with the fuzzy authority allocation method. Additionally, under cornering conditions, lateral deviation is reduced by 0.7 m. Finally, the proposed human–machine co-driving control strategy is verified by the experiment. The results indicate that the proposed strategy not only enhances trajectory tracking accuracy but also improves vehicle stability. Furthermore, by comparing the lateral and longitudinal authority allocation between the proposed and fuzzy strategies, it is evident that the approach significantly alleviates human–machine conflict, especially by reducing the frequent transfer of authority.
{"title":"Lateral and longitudinal human–machine co-driving of intelligent vehicle based on driving authorities game","authors":"Bin Tang, Jufang Yao, Haobin Jiang, Wei Mi","doi":"10.1016/j.jestch.2025.102187","DOIUrl":"10.1016/j.jestch.2025.102187","url":null,"abstract":"<div><div>Due to the current limitations of autonomous driving technology, human–machine co-driving is viewed as a viable and practical intermediary solution to bridge the gap between assisted driving and fully automated driving. To address challenges related to the allocation of lateral and longitudinal driving authority, as well as the interaction between the driver and the autonomous system, this paper proposes a game-sharing control strategy that operates at both the decision-making and control levels. At the decision level, a bargaining game-based approach is employed to allocate lateral and longitudinal driving authority dynamically, adjusting the distribution in accordance with a benefit function. At the control level, a lateral controller based on an extended game is developed to compute the optimal control manoeuvres by combining the driver’s inputs and reference tracking commands. This controller smoothly combines control inputs from both the driver and the automated system to ensure vehicle stability and minimize human–machine conflict. Simulation results show that, under a double lane-change scenario, the proposed strategy reduces yaw rate, lateral velocity, and lateral deviation by 0.35 rad/s, 0.6 m/s, and 0.6 m, respectively, compared with the fuzzy authority allocation method. Additionally, under cornering conditions, lateral deviation is reduced by 0.7 m. Finally, the proposed human–machine co-driving control strategy is verified by the experiment. The results indicate that the proposed strategy not only enhances trajectory tracking accuracy but also improves vehicle stability. Furthermore, by comparing the lateral and longitudinal authority allocation between the proposed and fuzzy strategies, it is evident that the approach significantly alleviates human–machine conflict, especially by reducing the frequent transfer of authority.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"71 ","pages":"Article 102187"},"PeriodicalIF":5.4,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145097394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-16DOI: 10.1016/j.jestch.2025.102188
Ivana Radonjić , M. Asim Amin , Milutin Petronijević , Plamen Tsankov , Martin Ćalasan
Urban Photovoltaics (PVs) plays an important role in harnessing power generation for sustainable development, but its performance is impaired under an increasing level of environmental pollutants. This paper presents the development and verification of a Stacked Ensemble Learning (SEL) and Decision Trees (DTs) based algorithm for forecasting PV output under conditions of significant air pollution. It uses a small dataset for training and validation, including data on the production of an urban PV system and meteorological data commonly available from local weather services. The developed algorithm was tested on data collected from an urban location in Niš, Serbia, which is exposed to significant air pollution during the regular heating season, for three different panel mounting configurations. The SEL model achieves a near-zero error metric in predicting PV yield for vertical monocrystalline panels, maintaining high accuracy even under soiling, which is a key feature for real-world applications. Similar conclusions can be drawn for the cases of horizontal and optimally positioned panels. Using the developed SEL algorithm, it is shown that the soiling ratio obtained from the estimation of PV production of clean and soiled panels can be used as a reliable indicator for scheduling the optimal period for cleaning PV panels.
{"title":"Soiling identification and forecasting in urban environment","authors":"Ivana Radonjić , M. Asim Amin , Milutin Petronijević , Plamen Tsankov , Martin Ćalasan","doi":"10.1016/j.jestch.2025.102188","DOIUrl":"10.1016/j.jestch.2025.102188","url":null,"abstract":"<div><div>Urban Photovoltaics (PVs) plays an important role in harnessing power generation for sustainable development, but its performance is impaired under an increasing level of environmental pollutants. This paper presents the development and verification of a Stacked Ensemble Learning (SEL) and Decision Trees (DTs) based algorithm for forecasting PV output under conditions of significant air pollution. It uses a small dataset for training and validation, including data on the production of an urban PV system and meteorological data commonly available from local weather services. The developed algorithm was tested on data collected from an urban location in Niš, Serbia, which is exposed to significant air pollution during the regular heating season, for three different panel mounting configurations. The SEL model achieves a near-zero error metric in predicting PV yield for vertical monocrystalline panels, maintaining high accuracy even under soiling, which is a key feature for real-world applications. Similar conclusions can be drawn for the cases of horizontal and optimally positioned panels. Using the developed SEL algorithm, it is shown that the soiling ratio obtained from the estimation of PV production of clean and soiled panels can be used as a reliable indicator for scheduling the optimal period for cleaning PV panels.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"71 ","pages":"Article 102188"},"PeriodicalIF":5.4,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145097395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-16DOI: 10.1016/S2215-0986(25)00247-2
{"title":"Front Matter 1 - Full Title Page (regular issues)/Special Issue Title page (special issues)","authors":"","doi":"10.1016/S2215-0986(25)00247-2","DOIUrl":"10.1016/S2215-0986(25)00247-2","url":null,"abstract":"","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"70 ","pages":"Article 102192"},"PeriodicalIF":5.4,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145104796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-16DOI: 10.1016/j.jestch.2025.102184
MD Jiabul Hoque , Md. Saiful Islam , Istiaque Ahmed
Wireless Sensor Networks (WSNs) play a pivotal role in numerous Internet of Things (IoT) applications; however, their performance remains constrained by limited energy resources, inefficient clustering, suboptimal routing, and redundant data transmissions. To address these persistent challenges, this study hypothesizes that integrating intelligent optimization techniques can simultaneously improve energy efficiency, network longevity, and data reliability in WSNs. Accordingly, we propose a novel AI-driven framework titled Neural-optimized Clustering, Routing, and Data Aggregation Protocol (NCRDAP). The framework combines an Artificial Neural Network (ANN)-based Cluster Head (CH) selection mechanism, an enhanced Quantum Particle Swarm Optimization (QPSO) for multi-hop routing, and a dual-step data aggregation strategy using edge computing to reduce redundancy and minimize communication overhead. The methodology was implemented and evaluated through extensive simulations using MATLAB R2022a, incorporating widely accepted radio energy models and comparative benchmarks including Low Energy Adaptive Clustering Hierarchy (LEACH), LEACH-Centralized (LEACH-C), LEACH with Genetic Algorithm (LEACH-GA), Cluster-Based Data Aggregation (CBDA), Power-efficient and Scalable Adaptive Network (PSAN), and Energy-aware Network Selection (ENS) protocols. The experimental results demonstrate that NCRDAP extends network lifetime by 19–23 %, enhances throughput by 20–30 %, and reduces overall energy consumption and packet loss ratio compared to existing techniques. Furthermore, QPSO exhibited faster convergence behavior and superior routing efficiency, while the dual-step edge processing strategy significantly reduced redundant transmissions without imposing substantial computational overhead. These findings confirm that the proposed NCRDAP framework offers a scalable, energy-efficient, and reliable solution for real-time, resource-constrained WSN applications.
{"title":"NCRDAP: An AI-driven clustering routing and data aggregation protocol for energy-efficient wireless sensor networks","authors":"MD Jiabul Hoque , Md. Saiful Islam , Istiaque Ahmed","doi":"10.1016/j.jestch.2025.102184","DOIUrl":"10.1016/j.jestch.2025.102184","url":null,"abstract":"<div><div>Wireless Sensor Networks (WSNs) play a pivotal role in numerous Internet of Things (IoT) applications; however, their performance remains constrained by limited energy resources, inefficient clustering, suboptimal routing, and redundant data transmissions. To address these persistent challenges, this study hypothesizes that integrating intelligent optimization techniques can simultaneously improve energy efficiency, network longevity, and data reliability in WSNs. Accordingly, we propose a novel AI-driven framework titled Neural-optimized Clustering, Routing, and Data Aggregation Protocol (NCRDAP). The framework combines an Artificial Neural Network (ANN)-based Cluster Head (CH) selection mechanism, an enhanced Quantum Particle Swarm Optimization (QPSO) for multi-hop routing, and a dual-step data aggregation strategy using edge computing to reduce redundancy and minimize communication overhead. The methodology was implemented and evaluated through extensive simulations using MATLAB R2022a, incorporating widely accepted radio energy models and comparative benchmarks including Low Energy Adaptive Clustering Hierarchy (LEACH), LEACH-Centralized (LEACH-C), LEACH with Genetic Algorithm (LEACH-GA), Cluster-Based Data Aggregation (CBDA), Power-efficient and Scalable Adaptive Network (PSAN), and Energy-aware Network Selection (ENS) protocols. The experimental results demonstrate that NCRDAP extends network lifetime by 19–23 %, enhances throughput by 20–30 %, and reduces overall energy consumption and packet loss ratio compared to existing techniques. Furthermore, QPSO exhibited faster convergence behavior and superior routing efficiency, while the dual-step edge processing strategy significantly reduced redundant transmissions without imposing substantial computational overhead. These findings confirm that the proposed NCRDAP framework offers a scalable, energy-efficient, and reliable solution for real-time, resource-constrained WSN applications.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"71 ","pages":"Article 102184"},"PeriodicalIF":5.4,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145097406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-13DOI: 10.1016/j.jestch.2025.102182
Eduardo Hernández Huerta , Armando Irvin Martínez Pérez , Rafael Campos Amezcua , Edgar Ernesto Vera Cárdenas , Marisa Moreno Ríos
The use of mathematical models and computational flow dynamics (CFD) in erosive wear studies can provide an approximation of the material performance under different conditions of the temperature, impact angle, and particle velocity. For this reason, the use of these analysis tools is essential for applications in specialized areas such as renewable energy, automotive and aerospace. This research work reports the results of erosive wear using use results of erosive wear using a validated numerical CFD tool based on the behavior and characteristics of the erosive SiC particles on the surface of a laminated composite material. In addition, the use of the Patnaik and Oka models is presented to obtain an approximation of the erosion rate, using the properties of the matrix and the reinforcing material that constitute the laminated composite evaluated, as well as the erosion conditions. The numerical results obtained compared to the experimental results had an approximation in of 94% in the erosion rate, 93.5% in the mass loss and 96.1% in the wear zone depth. These findings not only validate the combined use of CFD simulation and theoretical models, as an accurate alternative to traditional experimental testing, also accelerate the materials evaluation process, reduce development costs and improve the design of components with greater resistance to erosive wear. Therefore, these results provide a solid basis for integrating erosive wear resistance criteria into the structural design of composite components, optimizing their service life and performance under severe operating conditions.
{"title":"Integrated CFD and Theoretical Modeling of Erosive Wear in Composite Laminates","authors":"Eduardo Hernández Huerta , Armando Irvin Martínez Pérez , Rafael Campos Amezcua , Edgar Ernesto Vera Cárdenas , Marisa Moreno Ríos","doi":"10.1016/j.jestch.2025.102182","DOIUrl":"10.1016/j.jestch.2025.102182","url":null,"abstract":"<div><div>The use of mathematical models and computational flow dynamics (CFD) in erosive wear studies can provide an approximation of the material performance under different conditions of the temperature, impact angle, and particle velocity. For this reason, the use of these analysis tools is essential for applications in specialized areas such as renewable energy, automotive and aerospace. This research work reports the results of erosive wear using use results of erosive wear using a validated numerical CFD tool based on the behavior and characteristics of the erosive SiC particles on the surface of a laminated composite material. In addition, the use of the Patnaik and Oka models is presented to obtain an approximation of the erosion rate, using the properties of the matrix and the reinforcing material that constitute the laminated composite evaluated, as well as the erosion conditions. The numerical results obtained compared to the experimental results had an approximation in of 94% in the erosion rate, 93.5% in the mass loss and 96.1% in the wear zone depth. These findings not only validate the combined use of CFD simulation and theoretical models, as an accurate alternative to traditional experimental testing, also accelerate the materials evaluation process, reduce development costs and improve the design of components with greater resistance to erosive wear. Therefore, these results provide a solid basis for integrating erosive wear resistance criteria into the structural design of composite components, optimizing their service life and performance under severe operating conditions.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"71 ","pages":"Article 102182"},"PeriodicalIF":5.4,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145049874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-13DOI: 10.1016/j.jestch.2025.102179
Lin Zhang , Tingting Peng , Yongshi Song , Yandong Li , Yanzheng Zhao
This systematic review examines the preparation and encapsulation processes for Ionic Polymer-Metal Composites (IPMCs) and evaluates methods for suppressing their characteristic hysteresis and creep. The analysis investigates the relationship between various base membrane and electrode preparation techniques, including their optimization approaches, and the resulting mechanical properties of IPMCs. Additionally, the review categorizes and compares conventional encapsulation techniques according to their fundamental processes and application scenarios. Persistent hysteresis and creep phenomena have significantly constrained the long-term development of IPMCs. While classical modeling approaches have been applied to address these issues, they often fall short in effectively characterizing IPMC behavior. Recently, data-driven methodologies, particularly deep learning techniques, have emerged as promising alternatives for improving modeling accuracy of IPMC hysteresis and creep. Accordingly, this review compiles and analyzes current data-driven suppression methods. The paper concludes with insights into future development pathways for IPMCs within smart materials and soft robotics applications. By synthesizing existing research, this work provides a comprehensive foundation to advance IPMC technology and enhance its practical performance capabilities.
{"title":"Fabrication, encapsulation, and hysteresis creep mitigation in Ionic Polymer-Metal Composites: A review","authors":"Lin Zhang , Tingting Peng , Yongshi Song , Yandong Li , Yanzheng Zhao","doi":"10.1016/j.jestch.2025.102179","DOIUrl":"10.1016/j.jestch.2025.102179","url":null,"abstract":"<div><div>This systematic review examines the preparation and encapsulation processes for Ionic Polymer-Metal Composites (IPMCs) and evaluates methods for suppressing their characteristic hysteresis and creep. The analysis investigates the relationship between various base membrane and electrode preparation techniques, including their optimization approaches, and the resulting mechanical properties of IPMCs. Additionally, the review categorizes and compares conventional encapsulation techniques according to their fundamental processes and application scenarios. Persistent hysteresis and creep phenomena have significantly constrained the long-term development of IPMCs. While classical modeling approaches have been applied to address these issues, they often fall short in effectively characterizing IPMC behavior. Recently, data-driven methodologies, particularly deep learning techniques, have emerged as promising alternatives for improving modeling accuracy of IPMC hysteresis and creep. Accordingly, this review compiles and analyzes current data-driven suppression methods. The paper concludes with insights into future development pathways for IPMCs within smart materials and soft robotics applications. By synthesizing existing research, this work provides a comprehensive foundation to advance IPMC technology and enhance its practical performance capabilities.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"71 ","pages":"Article 102179"},"PeriodicalIF":5.4,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145049872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-13DOI: 10.1016/j.jestch.2025.102180
Adil Sayyouri , Karim El-khanchouli , Ahmed Bencherqui , Hicham Karmouni , Mhamed Sayyouri , Abderrahim Bourkane , Abdeljabbar Cherkaoui , Doaa Sami Khafaga , Eman Abdullah Aldakheel
The protection of medical images, often transmitted over unsecured networks in telemedicine contexts, requires techniques that ensure data confidentiality, integrity, and reversibility. To meet these requirements, we introduce a novel reversible and integer-based transform called the Quaternionic Integer Reversible Meixner Transform (QIRMT). This method enables a compact and accurate representation of multidimensional data 1D, 2D and 3D, while guaranteeing lossless reconstruction (MSE = 0, PSNR = ∞), thereby overcoming the numerical limitations of classical Meixner moments. Based on QIRMT, we have designed a robust zero-watermarking scheme for the authentication of medical images. This approach combines the extraction of features via QIRMT with a chaotic hybrid system by logistic-sine map and a generalized Arnold transform to ensure secure scrambling and spatial dispersion of the watermark-without altering the original image. Experimental results on benchmark medical images demonstrate high robustness against geometric and image processing attacks (BER < 0.03; NC > 0.97), even under combined distortions such as noise, JPEG compression, cropping, and rotation. Moreover, the proposed scheme achieves a significantly reduced execution time, outperforming existing comparative methods. These results confirm that the proposed method offers a reliable, efficient, and practical solution for protecting sensitive medical imaging data, in line with the stringent requirements of modern healthcare and telemedicine systems.
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