Pub Date : 2025-11-01DOI: 10.1016/j.simpat.2025.103221
Hang Thi Pham , Tien-Thinh Le , Panagiotis G. Asteris
The aim of this study is to investigate the influence of main machining parameters during the turning process of AISI304 stainless steel through experimental work and finite element simulation employing a realistic 3D cylindrical workpiece model. The application of a realistic 3D model facilitates a strong correlation between simulation and experimental findings concerning chip morphology and temperature distribution. Both experimental and simulation results reveal the formation of elongated helical-shaped chips. An increase in cutting depth induces higher stress and equivalent plastic deformation. Meanwhile, a higher cutting speed leads to lower stress distributed on the chip and the machined workpiece. The temperature trends near the cutting tool nose and along the main cutting edge differ considerably. The highest temperature is concentrated on the main cutting edge of the cutting tool during the machining process, reaching up to 1000 °K in the case of high cutting speed and large cutting depth. In contrast, the temperature on the chip and machined surface are about 330 °K and 300 °K, respectively.
{"title":"Experimental investigation and 3D finite element simulation of the turning process for AISI304 stainless steel","authors":"Hang Thi Pham , Tien-Thinh Le , Panagiotis G. Asteris","doi":"10.1016/j.simpat.2025.103221","DOIUrl":"10.1016/j.simpat.2025.103221","url":null,"abstract":"<div><div>The aim of this study is to investigate the influence of main machining parameters during the turning process of AISI304 stainless steel through experimental work and finite element simulation employing a realistic 3D cylindrical workpiece model. The application of a realistic 3D model facilitates a strong correlation between simulation and experimental findings concerning chip morphology and temperature distribution. Both experimental and simulation results reveal the formation of elongated helical-shaped chips. An increase in cutting depth induces higher stress and equivalent plastic deformation. Meanwhile, a higher cutting speed leads to lower stress distributed on the chip and the machined workpiece. The temperature trends near the cutting tool nose and along the main cutting edge differ considerably. The highest temperature is concentrated on the main cutting edge of the cutting tool during the machining process, reaching up to 1000 °K in the case of high cutting speed and large cutting depth. In contrast, the temperature on the chip and machined surface are about 330 °K and 300 °K, respectively.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"146 ","pages":"Article 103221"},"PeriodicalIF":3.5,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145475187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-30DOI: 10.1016/j.simpat.2025.103217
Martina Umlauft, Wilfried Elmenreich, Udo Schilcher
The topology model is an important aspect of wireless mesh network simulation. To test a new protocol typically several different topologies are necessary to perform a statistically significant number of simulation runs. Simply using topologies of real-world networks directly is not sufficient because the number of topology data available is less than the number of topologies required for simulation. Therefore, artificially generated topologies are used. Unfortunately, many simulators use either a uniform node distribution or even just a simple grid topology which both differ significantly from real-world topologies.
We first revisit the differences between uniform and grid topologies vs. real-world topologies using four different real-world networks to motivate the need for such a tool and then present EvoTopo, a new approach to generate more realistic topologies. EvoTopo uses a genetic algorithm to create the desired number of simulation topologies from the node positions of one real-world network. The generated topologies are evolved to be “similar” w.r.t. homogeneity of the node distribution, nearest neighbor distance, and node density. We evaluate our algorithm analyzing average overall node distance, the degree distribution of nodes, and the performance of a simple flooding algorithm and compare our algorithm to other approaches. The EvoTopo tool and the four sample topologies can be downloaded from our homepage; generated topologies are written to a simple text file which can be imported into a simulator of choice.
{"title":"Evolving realistic topologies for wireless mesh network simulation with EvoTopo","authors":"Martina Umlauft, Wilfried Elmenreich, Udo Schilcher","doi":"10.1016/j.simpat.2025.103217","DOIUrl":"10.1016/j.simpat.2025.103217","url":null,"abstract":"<div><div>The topology model is an important aspect of wireless mesh network simulation. To test a new protocol typically several different topologies are necessary to perform a statistically significant number of simulation runs. Simply using topologies of real-world networks directly is not sufficient because the number of topology data available is less than the number of topologies required for simulation. Therefore, artificially generated topologies are used. Unfortunately, many simulators use either a uniform node distribution or even just a simple grid topology which both differ significantly from real-world topologies.</div><div>We first revisit the differences between uniform and grid topologies vs. real-world topologies using four different real-world networks to motivate the need for such a tool and then present <span>EvoTopo</span>, a new approach to generate more realistic topologies. <span>EvoTopo</span> uses a genetic algorithm to create the desired number of simulation topologies from the node positions of one real-world network. The generated topologies are evolved to be “similar” w.r.t. homogeneity of the node distribution, nearest neighbor distance, and node density. We evaluate our algorithm analyzing average overall node distance, the degree distribution of nodes, and the performance of a simple flooding algorithm and compare our algorithm to other approaches. The <span>EvoTopo</span> tool and the four sample topologies can be downloaded from our homepage; generated topologies are written to a simple text file which can be imported into a simulator of choice.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"146 ","pages":"Article 103217"},"PeriodicalIF":3.5,"publicationDate":"2025-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145475186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-29DOI: 10.1016/j.simpat.2025.103219
Laura De Natale, Georgia Fargetta, Laura R.M. Scrimali, Sebastiano Battiato
Global disasters increasingly disrupt agricultural commodity flows, with food insecurity as a major consequence. Quantitative tools to assess such impacts are essential for resilience. We propose a hybrid Multi-Agent Reinforcement Learning (MARL) architecture to solve Variational Inequality (VI) problems in multi-commodity trade equilibria. While variational inequalities offer a rigorous method, their resolution via MARL faces stability and convergence challenges. Our actor–critic approach integrates a Gradient-based Learning Rate (GLR) scheduler, adaptive epsilon decay, prioritized replay, and a dual reward combining individual and centralized feedback. Agents representing supply and demand learn optimal strategies to reach equilibrium in simulated markets. Experiments, spanning stable conditions, dynamic price shifts, and route blockages, show faster convergence and stronger robustness than Multi-Agent Proximal Policy Optimization (MAPPO) and Multi-Agent Deep Deterministic Policy Gradient (MADDPG). Results highlight the promise of MARL for simulating economic behavior and optimizing decentralized decision-making in complex systems.
{"title":"Multi-agent reinforcement learning and variational inequality models for international trade networks under crisis","authors":"Laura De Natale, Georgia Fargetta, Laura R.M. Scrimali, Sebastiano Battiato","doi":"10.1016/j.simpat.2025.103219","DOIUrl":"10.1016/j.simpat.2025.103219","url":null,"abstract":"<div><div>Global disasters increasingly disrupt agricultural commodity flows, with food insecurity as a major consequence. Quantitative tools to assess such impacts are essential for resilience. We propose a hybrid Multi-Agent Reinforcement Learning (MARL) architecture to solve Variational Inequality (VI) problems in multi-commodity trade equilibria. While variational inequalities offer a rigorous method, their resolution via MARL faces stability and convergence challenges. Our actor–critic approach integrates a Gradient-based Learning Rate (GLR) scheduler, adaptive epsilon decay, prioritized replay, and a dual reward combining individual and centralized feedback. Agents representing supply and demand learn optimal strategies to reach equilibrium in simulated markets. Experiments, spanning stable conditions, dynamic price shifts, and route blockages, show faster convergence and stronger robustness than Multi-Agent Proximal Policy Optimization (MAPPO) and Multi-Agent Deep Deterministic Policy Gradient (MADDPG). Results highlight the promise of MARL for simulating economic behavior and optimizing decentralized decision-making in complex systems.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"146 ","pages":"Article 103219"},"PeriodicalIF":3.5,"publicationDate":"2025-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145398229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-28DOI: 10.1016/j.simpat.2025.103218
Yuanchen Li , Lin Guan , Ziyang Zhang , George Vogiatzis
Vehicular Ad Hoc Networks (VANETs) are an important component of modern network systems, supporting applications such as real-time entertainment, traffic notifications, and emergency services. However, the highly dynamic and rapidly changing topology of VANETs presents serious challenges for conventional data retrieval mechanisms designed for Mobile Ad Hoc Networks (MANETs), resulting in degraded performance. To address this issue, a novel Density-Based Probability VANET Caching Framework Built Upon the Named Data Networking (NDN) was proposed, namely DPNVC. This original framework dynamically calculates caching probabilities based on local traffic density, enabling to adapt to frequent topology changes. Additionally, the NDN communication model is applied to effectively suppress redundant packet forwarding in VANET environments. Empirical simulation results show that DPNVC significantly enhances Quality of Service (QoS) in various scenarios, including urban, highway, and city settings. Compared to baseline methods, it reduces link load by up to 25 %, decreases data retrieval time by up to 30 %, and improves the local satisfaction ratio by up to 66 %. It also maintains a competitive one-hop hit ratio performance.
{"title":"DPNVC: A novel density-based probability VANET caching framework built upon the NDN","authors":"Yuanchen Li , Lin Guan , Ziyang Zhang , George Vogiatzis","doi":"10.1016/j.simpat.2025.103218","DOIUrl":"10.1016/j.simpat.2025.103218","url":null,"abstract":"<div><div>Vehicular Ad Hoc Networks (VANETs) are an important component of modern network systems, supporting applications such as real-time entertainment, traffic notifications, and emergency services. However, the highly dynamic and rapidly changing topology of VANETs presents serious challenges for conventional data retrieval mechanisms designed for Mobile Ad Hoc Networks (MANETs), resulting in degraded performance. To address this issue, a novel Density-Based Probability VANET Caching Framework Built Upon the Named Data Networking (NDN) was proposed, namely DPNVC. This original framework dynamically calculates caching probabilities based on local traffic density, enabling to adapt to frequent topology changes. Additionally, the NDN communication model is applied to effectively suppress redundant packet forwarding in VANET environments. Empirical simulation results show that DPNVC significantly enhances Quality of Service (QoS) in various scenarios, including urban, highway, and city settings. Compared to baseline methods, it reduces link load by up to 25 %, decreases data retrieval time by up to 30 %, and improves the local satisfaction ratio by up to 66 %. It also maintains a competitive one-hop hit ratio performance.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"146 ","pages":"Article 103218"},"PeriodicalIF":3.5,"publicationDate":"2025-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145398230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-28DOI: 10.1016/j.simpat.2025.103220
Doudou Si, Zuanfeng Pan, Wendi Li
The quantification of blast load on a building constitutes a pivotal determinant in blast-resistant structural engineering. When the explosion occurs in a complex urban environment, the blast load on the building surface is conventionally obtained through scaled explosion tests or computational fluid dynamics simulations. Given the significant expenses of explosion tests and numerical simulations, this study innovatively applies the long short-term memory (LSTM) network to predict the blast load time history in urban explosion scenarios. The main idea is to establish an LSTM network to learn the temporal and spatial variations of blast loads from limited training data and predict the time history of blast loads at unmonitored locations or unknown explosion scenarios. In particular, a unidirectional multi-layer stacked LSTM architecture was used, and recursive computation was performed using a sliding window. The optimal hyperparameters for the model were determined through Bayesian optimization. The performance of the LSTM network was validated through numerical simulations of an explosion in a straight urban street. The results demonstrate that the LSTM network can accurately predict the multi-peak characteristics of blast loads in the street and the arrival times of each peak, demonstrating significant potential for blast load time histories prediction in complex environments.
{"title":"Prediction of load time histories on building facades under urban explosion environment","authors":"Doudou Si, Zuanfeng Pan, Wendi Li","doi":"10.1016/j.simpat.2025.103220","DOIUrl":"10.1016/j.simpat.2025.103220","url":null,"abstract":"<div><div>The quantification of blast load on a building constitutes a pivotal determinant in blast-resistant structural engineering. When the explosion occurs in a complex urban environment, the blast load on the building surface is conventionally obtained through scaled explosion tests or computational fluid dynamics simulations. Given the significant expenses of explosion tests and numerical simulations, this study innovatively applies the long short-term memory (LSTM) network to predict the blast load time history in urban explosion scenarios. The main idea is to establish an LSTM network to learn the temporal and spatial variations of blast loads from limited training data and predict the time history of blast loads at unmonitored locations or unknown explosion scenarios. In particular, a unidirectional multi-layer stacked LSTM architecture was used, and recursive computation was performed using a sliding window. The optimal hyperparameters for the model were determined through Bayesian optimization. The performance of the LSTM network was validated through numerical simulations of an explosion in a straight urban street. The results demonstrate that the LSTM network can accurately predict the multi-peak characteristics of blast loads in the street and the arrival times of each peak, demonstrating significant potential for blast load time histories prediction in complex environments.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"146 ","pages":"Article 103220"},"PeriodicalIF":3.5,"publicationDate":"2025-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145475185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-28DOI: 10.1016/j.simpat.2025.103216
Isabelle M. van Schilt , Jan H. Kwakkel , Jelte P. Mense , Alexander Verbraeck
Data on supply chains is often sparse due to reluctance among actors to share their data, making supply chain simulation modeling difficult. As a result, supply chain simulation models suffer from parametric and structural uncertainties, and there is a large variety of plausible simulation models that would align with the sparse observations about the real-world supply chain. Constructing a diverse set of models that fit sparse data is not an easy task. A relatively unknown approach to generating this diverse set of plausible models is the Quality Diversity (QD) algorithm. This study evaluates the feasibility of using QD to generate a diverse ensemble of supply chain simulation models for a varying degree of data sparseness. The results show that QD is able to generate a diverse ensemble of supply chain models, including the ground truth. As expected, QD successfully identifies the structure of the ground truth most frequently for a low level of data sparseness. When the sparseness of the data increases, QD is prone to overfitting, identifying supply chain structures that are more complex than the ground truth. Further research should focus on reviewing the calibration metric for sparse data, to reduce the overfitting of complex network structures.
{"title":"A simulation-based approach for reconstructing a diverse set of supply chain models with sparse data using a quality diversity algorithm","authors":"Isabelle M. van Schilt , Jan H. Kwakkel , Jelte P. Mense , Alexander Verbraeck","doi":"10.1016/j.simpat.2025.103216","DOIUrl":"10.1016/j.simpat.2025.103216","url":null,"abstract":"<div><div>Data on supply chains is often sparse due to reluctance among actors to share their data, making supply chain simulation modeling difficult. As a result, supply chain simulation models suffer from parametric and structural uncertainties, and there is a large variety of plausible simulation models that would align with the sparse observations about the real-world supply chain. Constructing a diverse set of models that fit sparse data is not an easy task. A relatively unknown approach to generating this diverse set of plausible models is the Quality Diversity (QD) algorithm. This study evaluates the feasibility of using QD to generate a diverse ensemble of supply chain simulation models for a varying degree of data sparseness. The results show that QD is able to generate a diverse ensemble of supply chain models, including the ground truth. As expected, QD successfully identifies the structure of the ground truth most frequently for a low level of data sparseness. When the sparseness of the data increases, QD is prone to overfitting, identifying supply chain structures that are more complex than the ground truth. Further research should focus on reviewing the calibration metric for sparse data, to reduce the overfitting of complex network structures.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"146 ","pages":"Article 103216"},"PeriodicalIF":3.5,"publicationDate":"2025-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145529383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-11DOI: 10.1016/j.simpat.2025.103214
Martin Opat , Julian Koellermeier , Christian Kehl
Simulating the transport of plastics, nutrients and pollutants in the ocean is important to address societal questions in environmental management and sustainability. Many Lagrangian transport simulators have been introduced in the past decades, yet they all share two distinct limitations, namely, long compute times and reliance on large compute equipment. These limitations hinder a transient incorporation of outdoor observations for Lagrangian physical simulations. This paper introduces a novel particle advection approach for Lagrangian ocean transport simulations, specifically designed for mobile devices and field use. A proof-of-concept for particle advection via 4th order Runge–Kutta time integration is presented and validated across different datasets. The approach is parallelized for SIMD architectures on mobile platforms. The results demonstrate a time-integration of 500,000 particles in approximately 10.2 ms per timestep, enabling an interactive co-visualization of the simulation. Achieved runtimes on mobile devices are within the same order of magnitude as established non-portable Lagrangian ocean-transport simulators, such as TRACMASS and OceanParcels, with comparable scalability. Consequently, this novel simulation approach opens new possibilities for field-conducted simulations in the future.
{"title":"Lagrangian fluid transport simulation using mobile devices","authors":"Martin Opat , Julian Koellermeier , Christian Kehl","doi":"10.1016/j.simpat.2025.103214","DOIUrl":"10.1016/j.simpat.2025.103214","url":null,"abstract":"<div><div>Simulating the transport of plastics, nutrients and pollutants in the ocean is important to address societal questions in environmental management and sustainability. Many Lagrangian transport simulators have been introduced in the past decades, yet they all share two distinct limitations, namely, long compute times and reliance on large compute equipment. These limitations hinder a transient incorporation of outdoor observations for Lagrangian physical simulations. This paper introduces a novel particle advection approach for Lagrangian ocean transport simulations, specifically designed for mobile devices and field use. A proof-of-concept for particle advection via 4th order Runge–Kutta time integration is presented and validated across different datasets. The approach is parallelized for SIMD architectures on mobile platforms. The results demonstrate a time-integration of 500,000 particles in approximately 10.2 ms per timestep, enabling an interactive co-visualization of the simulation. Achieved runtimes on mobile devices are within the same order of magnitude as established non-portable Lagrangian ocean-transport simulators, such as TRACMASS and OceanParcels, with comparable scalability. Consequently, this novel simulation approach opens new possibilities for field-conducted simulations in the future.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"145 ","pages":"Article 103214"},"PeriodicalIF":3.5,"publicationDate":"2025-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145320469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-08DOI: 10.1016/j.simpat.2025.103215
Renyu Wang , Gang Zhang , Hong Yu , Jiaqi Yang , Wei Xiong , Wei Wei
Urban rail system is a complex integrated system that combines trains and traction power supply system (TPSS). However, existing simulation method overlooks deep coupling between operation status of trains and power flow status of TPSS, impeding accurate deduction and analysis of overall operational status. Therefore, this paper delves into the bidirectional coupling characteristics between trains and TPSS, and then proposes a dual-circulation strategy for integrated simulation. Firstly, fluctuations of power flow are analyzed under traction and braking conditions, while exploring the reverse impact of voltage fluctuations on train operational performance. This reveals bidirectional coupling between trains and TPSS, leading to the development of an integrated system model. Subsequently, a dual-circulation strategy is designed. It enables integrated simulation considering bidirectional coupling characteristics under different operational conditions. Finally, verification is conducted based on actual line parameters, with comparative analysis of simulation results from 7 node types. It is demonstrated that the dual-circulation strategy effectively captures bidirectional coupling characteristics under different conditions. This paper establishes a crucial foundation for comprehensive and accurate deduction of train-TPSS integrated system, paving the way for overall analysis and decision-making of urban rail transit.
{"title":"A dual-circulation train-TPSS integrated simulation strategy for urban rail system","authors":"Renyu Wang , Gang Zhang , Hong Yu , Jiaqi Yang , Wei Xiong , Wei Wei","doi":"10.1016/j.simpat.2025.103215","DOIUrl":"10.1016/j.simpat.2025.103215","url":null,"abstract":"<div><div>Urban rail system is a complex integrated system that combines trains and traction power supply system (TPSS). However, existing simulation method overlooks deep coupling between operation status of trains and power flow status of TPSS, impeding accurate deduction and analysis of overall operational status. Therefore, this paper delves into the bidirectional coupling characteristics between trains and TPSS, and then proposes a dual-circulation strategy for integrated simulation. Firstly, fluctuations of power flow are analyzed under traction and braking conditions, while exploring the reverse impact of voltage fluctuations on train operational performance. This reveals bidirectional coupling between trains and TPSS, leading to the development of an integrated system model. Subsequently, a dual-circulation strategy is designed. It enables integrated simulation considering bidirectional coupling characteristics under different operational conditions. Finally, verification is conducted based on actual line parameters, with comparative analysis of simulation results from 7 node types. It is demonstrated that the dual-circulation strategy effectively captures bidirectional coupling characteristics under different conditions. This paper establishes a crucial foundation for comprehensive and accurate deduction of train-TPSS integrated system, paving the way for overall analysis and decision-making of urban rail transit.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"145 ","pages":"Article 103215"},"PeriodicalIF":3.5,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145320470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-04DOI: 10.1016/j.simpat.2025.103213
Hongcheng Lu , Siming Wang , Ran Ye , Yulong Li , Jinghong Wang , Jialin Wu , Yan Wang
During emergency evacuation, dense crowd aggregation in passages can trigger instability and stampede accidents, impairing evacuation and rescue effectiveness. This paper proposes an analytical method integrating computer vision and simulation to quantify crowd instability thresholds. Initially, accurate pedestrian detection is achieved using the YOLOv8n model trained on the CrowdHuman dataset, combined with the Deepsort algorithm to extract parameters (density, speed, and system entropy) from perspective-corrected accident scenes. Through analysis, a multi-dimensional instability criterion is derived. Video monitoring data is analyzed in simulation software (using AnyLogic state diagrams). Dynamic evaluation of multiple critical parameter thresholds is conducted through state diagram models, thereby enabling the technical integration mechanism between the two to be established. Analysis of incidents like the Itaewon stampede identifies critical thresholds: density (6.875 - 6.971 ped/m²), speed (0.177 - 0.179 m/s), and system entropy (555.796 - 582.194). Compared to single-density metrics, system entropy as a composite indicator more precisely captures multi-mechanism instability precursors, providing critical data support for early warning systems. Simulations indicate that passages with widths of 2.9 - 3.4 meters and lengths greater than or equal to 30 meters exhibit lower instability risks and higher pedestrian capacity. Sensitivity analysis reveals that the critical crowd size is more affected by passage width in flat areas and by length in sloped areas. The transition time from critical to safe pedestrian levels follows a linear distribution, with sloped passages exhibiting longer transition times and higher risks.
{"title":"Research on critical criteria for crowd instability based on system entropy","authors":"Hongcheng Lu , Siming Wang , Ran Ye , Yulong Li , Jinghong Wang , Jialin Wu , Yan Wang","doi":"10.1016/j.simpat.2025.103213","DOIUrl":"10.1016/j.simpat.2025.103213","url":null,"abstract":"<div><div>During emergency evacuation, dense crowd aggregation in passages can trigger instability and stampede accidents, impairing evacuation and rescue effectiveness. This paper proposes an analytical method integrating computer vision and simulation to quantify crowd instability thresholds. Initially, accurate pedestrian detection is achieved using the YOLOv8n model trained on the CrowdHuman dataset, combined with the Deepsort algorithm to extract parameters (density, speed, and system entropy) from perspective-corrected accident scenes. Through analysis, a multi-dimensional instability criterion is derived. Video monitoring data is analyzed in simulation software (using AnyLogic state diagrams). Dynamic evaluation of multiple critical parameter thresholds is conducted through state diagram models, thereby enabling the technical integration mechanism between the two to be established. Analysis of incidents like the Itaewon stampede identifies critical thresholds: density (6.875 - 6.971 ped/m²), speed (0.177 - 0.179 m/s), and system entropy (555.796 - 582.194). Compared to single-density metrics, system entropy as a composite indicator more precisely captures multi-mechanism instability precursors, providing critical data support for early warning systems. Simulations indicate that passages with widths of 2.9 - 3.4 meters and lengths greater than or equal to 30 meters exhibit lower instability risks and higher pedestrian capacity. Sensitivity analysis reveals that the critical crowd size is more affected by passage width in flat areas and by length in sloped areas. The transition time from critical to safe pedestrian levels follows a linear distribution, with sloped passages exhibiting longer transition times and higher risks.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"145 ","pages":"Article 103213"},"PeriodicalIF":3.5,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145266849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-01DOI: 10.1016/j.simpat.2025.103212
Xiaoxia Yang , Jiahui Wan , Haojie Zhu , Chuan-Zhi (Thomas) Xie , Botao Zhang
The optimization of emergency evacuation paths for passengers in underground rail transit hubs has become a critical challenge in urban flood prevention and disaster mitigation systems. Most previous evacuation path optimization methods assume passengers move independently as individuals without considering socially connected groups traveling together. To address this, this paper proposes a novel passenger evacuation path optimization method considering companion behavior during subway station flooding incidents, and develops an innovative ETACO algorithm to solve the path optimization model. Taking an actual subway station as a case study, a station simulation system constructed using PathFinder is employed to simulate passenger evacuation processes, demonstrating the effectiveness of the proposed path optimization scheme. An improved entropy weight method is introduced to conduct a multidimensional evaluation of evacuation performance. The results indicate that: (1) Companion behavior significantly inhibits evacuation efficiency, with higher proportions of grouped evacuees leading to increased evacuation time and reduced average movement speed; (2) The proposed ETACO dynamic optimization strategy remarkably enhances the convergence performance of the path optimization model solution, achieving a 16% improvement in average optimal objective improvement rate compared to conventional ACO, while generating more efficient path optimization strategies; (3) Increasing numbers of interrupted road sections progressively slow down passenger evacuation; (4) Evacuation effectiveness evaluation further verifies the enhancement of station safety performance through the path optimization strategy. This research provides a more realistic solution for evacuation path optimization considering companion behavior in complex flood scenarios.
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