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.
{"title":"Optimization of passenger evacuation path in flood scenarios considering companion behaviors","authors":"Xiaoxia Yang , Jiahui Wan , Haojie Zhu , Chuan-Zhi (Thomas) Xie , Botao Zhang","doi":"10.1016/j.simpat.2025.103212","DOIUrl":"10.1016/j.simpat.2025.103212","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"145 ","pages":"Article 103212"},"PeriodicalIF":3.5,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145266850","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 : 2025-09-29DOI: 10.1016/j.simpat.2025.103209
Lars T. Kyllingstad , Severin Sadjina , Stian Skjong
We review error estimation methods for co-simulation, in particular methods that are applicable when the subsystems provide minimal interfaces. By this, we mean that subsystems do not support rollback of time steps, do not output derivatives, and do not provide any other information about their internals besides the output variables that are required for coupling with other subsystems. Such “black-box” subsystems are common in industrial applications, and the ability to couple them and run large-system simulations is one of the major attractions of the co-simulation paradigm. We also describe how the resulting error indicators may be used to automatically control macro time step sizes to strike a good balance between simulation speed and accuracy. The various elements of the step size control algorithm are presented in pseudocode so that readers may implement them and test them in their own applications. We provide practicable advice on how to use error indicators to judge the quality of a co-simulation, how to avoid common pitfalls, and how to configure the step size control algorithm.
{"title":"Error estimation and step size control with minimal subsystem interfaces","authors":"Lars T. Kyllingstad , Severin Sadjina , Stian Skjong","doi":"10.1016/j.simpat.2025.103209","DOIUrl":"10.1016/j.simpat.2025.103209","url":null,"abstract":"<div><div>We review error estimation methods for co-simulation, in particular methods that are applicable when the subsystems provide minimal interfaces. By this, we mean that subsystems do not support rollback of time steps, do not output derivatives, and do not provide any other information about their internals besides the output variables that are required for coupling with other subsystems. Such “black-box” subsystems are common in industrial applications, and the ability to couple them and run large-system simulations is one of the major attractions of the co-simulation paradigm. We also describe how the resulting error indicators may be used to automatically control macro time step sizes to strike a good balance between simulation speed and accuracy. The various elements of the step size control algorithm are presented in pseudocode so that readers may implement them and test them in their own applications. We provide practicable advice on how to use error indicators to judge the quality of a co-simulation, how to avoid common pitfalls, and how to configure the step size control algorithm.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"145 ","pages":"Article 103209"},"PeriodicalIF":3.5,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145220742","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 : 2025-09-29DOI: 10.1016/j.simpat.2025.103211
Ana Larrañaga-Zumeta , Neco Villegas , Katerina Koutlia , Luis Diez , Ramón Agüero , Sandra Lagén
Virtualized Radio Access Networks (vRAN) allow the disaggregation of the RAN protocol stack into different network units. This disaggregation depends on the selected Functional Split (FS), ranging from Option 1 to Option 8. The possible combination of this virtualization paradigm with different FS configurations could enhance the agility, flexibility, and scalability of 5G and beyond networks. Several studies exploring FSs use open-source platforms such as srsRAN, which provide full-stack 4G and 5G RAN software. However, these platforms have limitations for large-scale network analysis and usually require hardware for realistic testing. In contrast, system-level simulators such as ns-3 5G-LENA accurately model key 5G RAN functionalities and provide a flexible, scalable, and entirely software-based environment to implement, test, and evaluate a wide range of features. Based on the above, in this work we present a software-based model for the ns-3 5G-LENA simulator that allows simulating various FS options. We study and evaluate these FS options, specifically Options 6, 7.3, 7.2, and 7.1. Moreover, we analyze their impact on the end-to-end system performance using eXtended Reality (XR) traffic and under diverse network conditions. Our analysis shows that an appropriate FS selection can improve overall performance, helping the system more effectively handle XR traffic demands across different network conditions. Specifically, when Fronthaul (FH) and bandwidth are not limiting, all FS configurations yield similar throughput and latency, with XR delays mostly below 11 ms and data rates closely matching the offered load. Under FH constraints, lower FSs (e.g., Options 6 or 7.3) are preferable due to large, bursty XR packets. Otherwise, for standardized Open RAN (O-RAN) 7.2 or 7.1 FSs, delays may exceed 50 ms and data rates degrade, significantly affecting XR traffic performance. This work provides the research community with an accessible tool for studying FSs in realistic 5G environments.
{"title":"Analysis of different functional split options for XR traffic in 5G-LENA","authors":"Ana Larrañaga-Zumeta , Neco Villegas , Katerina Koutlia , Luis Diez , Ramón Agüero , Sandra Lagén","doi":"10.1016/j.simpat.2025.103211","DOIUrl":"10.1016/j.simpat.2025.103211","url":null,"abstract":"<div><div>Virtualized Radio Access Networks (vRAN) allow the disaggregation of the RAN protocol stack into different network units. This disaggregation depends on the selected Functional Split (FS), ranging from Option 1 to Option 8. The possible combination of this virtualization paradigm with different FS configurations could enhance the agility, flexibility, and scalability of 5G and beyond networks. Several studies exploring FSs use open-source platforms such as srsRAN, which provide full-stack 4G and 5G RAN software. However, these platforms have limitations for large-scale network analysis and usually require hardware for realistic testing. In contrast, system-level simulators such as ns-3 5G-LENA accurately model key 5G RAN functionalities and provide a flexible, scalable, and entirely software-based environment to implement, test, and evaluate a wide range of features. Based on the above, in this work we present a software-based model for the ns-3 5G-LENA simulator that allows simulating various FS options. We study and evaluate these FS options, specifically Options 6, 7.3, 7.2, and 7.1. Moreover, we analyze their impact on the end-to-end system performance using eXtended Reality (XR) traffic and under diverse network conditions. Our analysis shows that an appropriate FS selection can improve overall performance, helping the system more effectively handle XR traffic demands across different network conditions. Specifically, when Fronthaul (FH) and bandwidth are not limiting, all FS configurations yield similar throughput and latency, with XR delays mostly below 11 ms and data rates closely matching the offered load. Under FH constraints, lower FSs (e.g., Options 6 or 7.3) are preferable due to large, bursty XR packets. Otherwise, for standardized Open RAN (O-RAN) 7.2 or 7.1 FSs, delays may exceed 50 ms and data rates degrade, significantly affecting XR traffic performance. This work provides the research community with an accessible tool for studying FSs in realistic 5G environments.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"145 ","pages":"Article 103211"},"PeriodicalIF":3.5,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145220744","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 : 2025-09-25DOI: 10.1016/j.simpat.2025.103208
Mohammad Heravi, Amirmasoud Molaei, Reza Ghabcheloo
In this paper, the problem of predicting the motion of large rocks during excavation is addressed. During excavation, complex interactions are observed among the excavator bucket, rock, and soil, which are not effectively captured using analytical models due to nonlinearities and unknown phenomena. To address this, a physics-informed, data-driven framework is proposed, in which a predictive model of the rock dynamics is learned using data obtained from a high-fidelity physics-based simulator. Specifically, a physics-informed neural network is employed, structured as a multilayer perceptron that receives the state variables and control inputs from a fixed-length temporal window. A kinematic constraint is incorporated into the loss function to enforce physical consistency. The model is trained and evaluated using data from 200 experiments. The effect of the look-back window length is examined, and a window length of two is found to yield the minimum prediction error. The prediction error distributions are statistically evaluated for different soil and rock scenarios, as well as across different prediction horizons (1–20). The model’s accuracy is shown to be within the desired threshold.
{"title":"Physics-informed data-driven modeling of rock motion dynamics in excavation using a high-fidelity simulator","authors":"Mohammad Heravi, Amirmasoud Molaei, Reza Ghabcheloo","doi":"10.1016/j.simpat.2025.103208","DOIUrl":"10.1016/j.simpat.2025.103208","url":null,"abstract":"<div><div>In this paper, the problem of predicting the motion of large rocks during excavation is addressed. During excavation, complex interactions are observed among the excavator bucket, rock, and soil, which are not effectively captured using analytical models due to nonlinearities and unknown phenomena. To address this, a physics-informed, data-driven framework is proposed, in which a predictive model of the rock dynamics is learned using data obtained from a high-fidelity physics-based simulator. Specifically, a physics-informed neural network is employed, structured as a multilayer perceptron that receives the state variables and control inputs from a fixed-length temporal window. A kinematic constraint is incorporated into the loss function to enforce physical consistency. The model is trained and evaluated using data from 200 experiments. The effect of the look-back window length is examined, and a window length of two is found to yield the minimum prediction error. The prediction error distributions are statistically evaluated for different soil and rock scenarios, as well as across different prediction horizons (1–20). The model’s accuracy is shown to be within the desired threshold.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"145 ","pages":"Article 103208"},"PeriodicalIF":3.5,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145220745","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 : 2025-09-24DOI: 10.1016/j.simpat.2025.103210
Houzhe Xie , Zhiyong Ji , Xianqiong Zhao , Wei Ke , Jing Xiao , Mei Yang
Due to its high tunneling efficiency under steep conditions, the directed pilot hole in conjunction with the Tunnel Boring Machine (TBM) conical cutterhead has been widely utilized in inclined openings. However, the key factor influencing TBM tunneling efficiency, the mucking efficiency of the conical cutterhead, is significantly affected by unavoidable pilot hole deviations. In this study, the muck flow characteristics of the conical cutterhead with a pilot hole under steep conditions were analyzed using a comprehensive Discrete Element Method simulation that encompassed the stages of falling, shoveling, and discharging. Then the muck discharge efficiency and residual muck efficiency were employed as quantitative indicators to evaluate the cutterhead’s mucking performance and secondary cutter wear. Furthermore, the interactive effects of deviation distance of the pilot hole (DD) and deviation angle of the pilot hole (DA) on mucking performance were investigated. Based on various engineering requirements, a weighted multi-factor analysis method is proposed for determining the allowable deviations of the pilot hole. For a specific inclined shaft with the following characteristics: a cutterhead with a diameter of 7690 mm, a conical angle of 15°, a 2500 mm pilot hole and a tunneling inclination of 55°, the results indicate that DD reaches a minimum value, when DA=112.5°. Specifically, the minimum DD=183 mm when minimizing secondary cutter wear, and 401 mm when enhancing mucking performance. These findings offer theoretical guidance for determining positional parameters of the pilot hole in inclined openings.
{"title":"Research on allowable deviations of the pilot hole based on TBM conical cutterhead muck discharging simulation in inclined openings","authors":"Houzhe Xie , Zhiyong Ji , Xianqiong Zhao , Wei Ke , Jing Xiao , Mei Yang","doi":"10.1016/j.simpat.2025.103210","DOIUrl":"10.1016/j.simpat.2025.103210","url":null,"abstract":"<div><div>Due to its high tunneling efficiency under steep conditions, the directed pilot hole in conjunction with the Tunnel Boring Machine (TBM) conical cutterhead has been widely utilized in inclined openings. However, the key factor influencing TBM tunneling efficiency, the mucking efficiency of the conical cutterhead, is significantly affected by unavoidable pilot hole deviations. In this study, the muck flow characteristics of the conical cutterhead with a pilot hole under steep conditions were analyzed using a comprehensive Discrete Element Method simulation that encompassed the stages of falling, shoveling, and discharging. Then the muck discharge efficiency and residual muck efficiency were employed as quantitative indicators to evaluate the cutterhead’s mucking performance and secondary cutter wear. Furthermore, the interactive effects of deviation distance of the pilot hole (<em>DD</em>) and deviation angle of the pilot hole (<em>DA</em>) on mucking performance were investigated. Based on various engineering requirements, a weighted multi-factor analysis method is proposed for determining the allowable deviations of the pilot hole. For a specific inclined shaft with the following characteristics: a cutterhead with a diameter of 7690 mm, a conical angle of 15°, a 2500 mm pilot hole and a tunneling inclination of 55°, the results indicate that <em>DD</em> reaches a minimum value, when <em>DA</em>=112.5°. Specifically, the minimum <em>DD</em>=183 mm when minimizing secondary cutter wear, and 401 mm when enhancing mucking performance. These findings offer theoretical guidance for determining positional parameters of the pilot hole in inclined openings.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"145 ","pages":"Article 103210"},"PeriodicalIF":3.5,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145220743","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}
Underground mines rely on a ground support system (i.e. reinforcement and surface support elements such as welded wire mesh) to control rock deformation and maintain excavation stability under dynamic loading conditions. Designing an effective ground support system requires a detailed understanding of the mechanical behaviour of these support components and their response to impact scenarios. This study investigates the influence of drop mass geometry on the deformation and failure mechanisms of welded wire mesh utilising a 3D finite element analysis (FEA) based on geometries used in laboratory testing. Five drop mass configurations, prism, spherical, cylindrical, ETAG 027, and irregular, were evaluated under the same energy input to explore their effects on mesh behaviour. Although the developed dynamic testing setup offers valuable insights into mesh performance, the lack of standardised drop mass shapes remains a significant challenge, as it causes inconsistencies in test results and complicates data comparison across different studies or reliable experiment replication. The FEA model was developed and calibrated using experimental data. The results demonstrated that the drop mass shape strongly affects load distribution, displacement patterns and the extent of damage in the mesh. The prism shape, used for calibration, provided a good match with the laboratory result. Cylindrical geometries demonstrated more favourable energy dissipation, absorbing 5.69 kJ, whereas the irregular and spherical shapes exhibited lower energy absorption, 2.83 kJ and 2.55 kJ, respectively, due to the concentrated nature of the initial impact load being distributed over a smaller contact area. The ETAG 027 geometry produced a balanced response, with a peak displacement of approximately 152.77 mm and an energy absorption of 3.06 kJ, accompanied by moderately distributed plastic deformation. This study can support the development of more reliable testing procedures and energy-based design approaches for support systems in dynamic underground environments.
{"title":"Numerical modelling of drop mass shape influence on energy absorption of welded wire mesh in dynamic impact conditions","authors":"Ceren Karatas Batan , Selahattin Akdag , Chengguo Zhang , Joung Oh , Serkan Saydam","doi":"10.1016/j.simpat.2025.103207","DOIUrl":"10.1016/j.simpat.2025.103207","url":null,"abstract":"<div><div>Underground mines rely on a ground support system (i.e. reinforcement and surface support elements such as welded wire mesh) to control rock deformation and maintain excavation stability under dynamic loading conditions. Designing an effective ground support system requires a detailed understanding of the mechanical behaviour of these support components and their response to impact scenarios. This study investigates the influence of drop mass geometry on the deformation and failure mechanisms of welded wire mesh utilising a 3D finite element analysis (FEA) based on geometries used in laboratory testing. Five drop mass configurations, prism, spherical, cylindrical, ETAG 027, and irregular, were evaluated under the same energy input to explore their effects on mesh behaviour. Although the developed dynamic testing setup offers valuable insights into mesh performance, the lack of standardised drop mass shapes remains a significant challenge, as it causes inconsistencies in test results and complicates data comparison across different studies or reliable experiment replication. The FEA model was developed and calibrated using experimental data. The results demonstrated that the drop mass shape strongly affects load distribution, displacement patterns and the extent of damage in the mesh. The prism shape, used for calibration, provided a good match with the laboratory result. Cylindrical geometries demonstrated more favourable energy dissipation, absorbing 5.69 kJ, whereas the irregular and spherical shapes exhibited lower energy absorption, 2.83 kJ and 2.55 kJ, respectively, due to the concentrated nature of the initial impact load being distributed over a smaller contact area. The ETAG 027 geometry produced a balanced response, with a peak displacement of approximately 152.77 mm and an energy absorption of 3.06 kJ, accompanied by moderately distributed plastic deformation. This study can support the development of more reliable testing procedures and energy-based design approaches for support systems in dynamic underground environments.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"145 ","pages":"Article 103207"},"PeriodicalIF":3.5,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145118471","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 : 2025-09-15DOI: 10.1016/j.simpat.2025.103206
Guanglie Wang , Zhijia Zhang , Aleksandra Nazarova
With the rapid development of autonomous driving technology, there is an increasing demand for safety, reliability, and optimization efficiency in path planning algorithms. However, traditional physical testing is often costly, time-consuming, and subject to environmental uncertainties, making it difficult to efficiently verify and optimize these algorithms. To address this issue, this paper proposes a high-fidelity digital twin-based platform for testing and optimizing path planning algorithms. By constructing a simulation environment that mirrors the physical world, the platform minimizes the gap between simulation and real-world scenarios, enhancing the safety and stability of path planning. The platform integrates global path planning using the A* algorithm, local path planning with the Timed Elastic Band method, and optimization using Bézier curves to improve the smoothness, feasibility, and safety of the path. Additionally, it incorporates the vehicle’s physical characteristics — such as velocity, steering angle, and drive mode — into the parameter optimization process, ensuring consistency between the simulation and the real-world environment. Experiments were conducted by deploying identical path planning algorithms in both the simulation and the physical environments. The results demonstrate that algorithms optimized through the digital twin platform can be reliably transferred to real-world scenarios, improving obstacle avoidance and overall path planning safety. The planned paths in the physical environment closely matched those in simulation, confirming the effectiveness of the digital twin approach for path planning testing and optimization. This research provides new insights into environmental adaptability, safety assurance, and engineering deployment of path planning in autonomous driving.
{"title":"A digital twin-based platform for testing and optimization of path planning algorithms","authors":"Guanglie Wang , Zhijia Zhang , Aleksandra Nazarova","doi":"10.1016/j.simpat.2025.103206","DOIUrl":"10.1016/j.simpat.2025.103206","url":null,"abstract":"<div><div>With the rapid development of autonomous driving technology, there is an increasing demand for safety, reliability, and optimization efficiency in path planning algorithms. However, traditional physical testing is often costly, time-consuming, and subject to environmental uncertainties, making it difficult to efficiently verify and optimize these algorithms. To address this issue, this paper proposes a high-fidelity digital twin-based platform for testing and optimizing path planning algorithms. By constructing a simulation environment that mirrors the physical world, the platform minimizes the gap between simulation and real-world scenarios, enhancing the safety and stability of path planning. The platform integrates global path planning using the A* algorithm, local path planning with the Timed Elastic Band method, and optimization using Bézier curves to improve the smoothness, feasibility, and safety of the path. Additionally, it incorporates the vehicle’s physical characteristics — such as velocity, steering angle, and drive mode — into the parameter optimization process, ensuring consistency between the simulation and the real-world environment. Experiments were conducted by deploying identical path planning algorithms in both the simulation and the physical environments. The results demonstrate that algorithms optimized through the digital twin platform can be reliably transferred to real-world scenarios, improving obstacle avoidance and overall path planning safety. The planned paths in the physical environment closely matched those in simulation, confirming the effectiveness of the digital twin approach for path planning testing and optimization. This research provides new insights into environmental adaptability, safety assurance, and engineering deployment of path planning in autonomous driving.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"145 ","pages":"Article 103206"},"PeriodicalIF":3.5,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145105825","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}
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