Pub Date : 2026-01-13DOI: 10.1016/j.simpat.2026.103253
Marco Gribaudo , Mauro Iacono
When systems have to process a large number of entities, which can be stored in buffers during their operations, discrete models might suffer from a lot of drawbacks, and fluid approximations give several advantages. When flows are not constant, but affected by variability, second orders fluid models become handy due to their ability of including variance in flow rates. In this context, the simulation of second-order fluid models requires specific techniques especially when considering correlated flows in several dimensions. In this work, we consider arbitrary correlation and fluid barrier structure, and we provide procedures to generate simulation traces of the underlying stochastic process.
{"title":"Simulation of n-dimensional second order fluid models with custom oriented barriers","authors":"Marco Gribaudo , Mauro Iacono","doi":"10.1016/j.simpat.2026.103253","DOIUrl":"10.1016/j.simpat.2026.103253","url":null,"abstract":"<div><div>When systems have to process a large number of entities, which can be stored in buffers during their operations, discrete models might suffer from a lot of drawbacks, and fluid approximations give several advantages. When flows are not constant, but affected by variability, second orders fluid models become handy due to their ability of including variance in flow rates. In this context, the simulation of second-order fluid models requires specific techniques especially when considering correlated flows in several dimensions. In this work, we consider arbitrary correlation and fluid barrier structure, and we provide procedures to generate simulation traces of the underlying stochastic process.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"147 ","pages":"Article 103253"},"PeriodicalIF":3.5,"publicationDate":"2026-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145977320","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 : 2025-12-31DOI: 10.1016/j.simpat.2025.103251
Manuel D. Rossetti, Farid Hashemian, Maryam Aghamohammadghasem
Input distribution modeling remains an important task for practitioners of discrete-event stochastic simulation. This paper presents an automated input distribution recommendation procedure based on multiple statistical criteria for selecting an appropriate univariate probability distribution from data. Candidate distributions are evaluated using a collection of goodness-of-fit metrics, which are combined through a multi-criteria decision analysis framework to provide reliable recommendations across a wide range of sample sizes and distributional shapes. Extensive numerical experiments evaluate the accuracy, false positive rate, and false negative rate of both individual metrics and composite measures, leading to practical guidance for default metric selection in automated input modeling. The proposed methodology is implemented within the Kotlin Simulation Library (KSL), an open-source discrete-event simulation framework, to demonstrate its practical applicability; however, the approach itself is general and not tied to any specific software platform.
{"title":"Automated input distribution fitting based on multiple criteria for the Kotlin Simulation Library","authors":"Manuel D. Rossetti, Farid Hashemian, Maryam Aghamohammadghasem","doi":"10.1016/j.simpat.2025.103251","DOIUrl":"10.1016/j.simpat.2025.103251","url":null,"abstract":"<div><div>Input distribution modeling remains an important task for practitioners of discrete-event stochastic simulation. This paper presents an automated input distribution recommendation procedure based on multiple statistical criteria for selecting an appropriate univariate probability distribution from data. Candidate distributions are evaluated using a collection of goodness-of-fit metrics, which are combined through a multi-criteria decision analysis framework to provide reliable recommendations across a wide range of sample sizes and distributional shapes. Extensive numerical experiments evaluate the accuracy, false positive rate, and false negative rate of both individual metrics and composite measures, leading to practical guidance for default metric selection in automated input modeling. The proposed methodology is implemented within the Kotlin Simulation Library (KSL), an open-source discrete-event simulation framework, to demonstrate its practical applicability; however, the approach itself is general and not tied to any specific software platform.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"147 ","pages":"Article 103251"},"PeriodicalIF":3.5,"publicationDate":"2025-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145926347","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 : 2025-12-24DOI: 10.1016/j.simpat.2025.103249
Hui Sun , Honghui Song , Chaoye Fang , Qiaorui Si , Yu Wu , Shouqi Yuan
Pumped storage power stations face significant efficiency and safety challenges due to complex hydraulic and mechanical faults. While accurate fault diagnosis is critical for reliable operation, existing data-driven methods often lack generalizability and explicit integration of domain knowledge in multi-fault scenarios. To address this, we develop a novel simulation-knowledge hybrid framework that integrates physics-based representations from Computational Fluid Dynamics (CFD) / Finite Element Method (FEM) simulations with a data-driven Stacked Denoising Auto-Encoder (SDAE) model enhanced by RIME optimization algorithm. The framework introduces a systematic knowledge-formalization and feature-alignment mechanism that translates implicit physical fields into quantifiable indicators aligned with experimental features. Through detailed hydraulic and mechanical simulations, we characterize cavitation and bearing wear fault signatures, formalizing them into traceable diagnostic datasets. This establishes a transparent evidence chain linking fault diagnoses to underlying physical mechanisms. To improve generalization, the SDAE model undergoes autonomous hyperparameter adaptation via the RIME algorithm, enhancing its capability to interpret hybrid knowledge-data inputs. Experimental validation demonstrates that the knowledge-integrated RIME-SDAE model achieves near-perfect identification accuracy exceeding 99%, outperforming both baseline SDAE (93.3%) and SVM models. Field tests confirm the framework's robustness and accuracy, enabling real-time fault traceability without additional sensors. This research provides a scalable methodology for enhancing operational reliability and supporting design decisions in pumped storage power stations through explicit knowledge utilization and autonomous model adaptation.
{"title":"A simulation-knowledge traceability and data-driven framework with autonomous optimization for multi-fault diagnosis in the pumped storage power stations","authors":"Hui Sun , Honghui Song , Chaoye Fang , Qiaorui Si , Yu Wu , Shouqi Yuan","doi":"10.1016/j.simpat.2025.103249","DOIUrl":"10.1016/j.simpat.2025.103249","url":null,"abstract":"<div><div>Pumped storage power stations face significant efficiency and safety challenges due to complex hydraulic and mechanical faults. While accurate fault diagnosis is critical for reliable operation, existing data-driven methods often lack generalizability and explicit integration of domain knowledge in multi-fault scenarios. To address this, we develop a novel simulation-knowledge hybrid framework that integrates physics-based representations from Computational Fluid Dynamics (CFD) / Finite Element Method (FEM) simulations with a data-driven Stacked Denoising Auto-Encoder (SDAE) model enhanced by RIME optimization algorithm. The framework introduces a systematic knowledge-formalization and feature-alignment mechanism that translates implicit physical fields into quantifiable indicators aligned with experimental features. Through detailed hydraulic and mechanical simulations, we characterize cavitation and bearing wear fault signatures, formalizing them into traceable diagnostic datasets. This establishes a transparent evidence chain linking fault diagnoses to underlying physical mechanisms. To improve generalization, the SDAE model undergoes autonomous hyperparameter adaptation via the RIME algorithm, enhancing its capability to interpret hybrid knowledge-data inputs. Experimental validation demonstrates that the knowledge-integrated RIME-SDAE model achieves near-perfect identification accuracy exceeding 99%, outperforming both baseline SDAE (93.3%) and SVM models. Field tests confirm the framework's robustness and accuracy, enabling real-time fault traceability without additional sensors. This research provides a scalable methodology for enhancing operational reliability and supporting design decisions in pumped storage power stations through explicit knowledge utilization and autonomous model adaptation.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"147 ","pages":"Article 103249"},"PeriodicalIF":3.5,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884625","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 : 2025-12-23DOI: 10.1016/j.simpat.2025.103250
Shuchao Cao , Ying Zhou , Yunhe Tong , Rui Ye , Xiaoxia Yang , Yiping Zeng , Peng Wang
In recent years, flood disasters have frequently impacted urban areas, resulting in significant casualties and property loss worldwide. To ensure the safety of residents during flooding events, it is urgent to conduct large-scale evacuations in flood-prone areas. However, the impacts of flooding on urban evacuation are dynamically coupled with real-world conditions, which are often overlooked in current research. Therefore, a dynamic evacuation planning framework is proposed in this paper to provide safe and efficient evacuation routes for urban population under various flood scenarios. Firstly, the flood spreading process is accurately simulated across different rainfall patterns. Secondly, the dynamic influences of floods on travel speed, instability risk and road capacity are incorporated and quantified in the evacuation planning. Finally, the quickest evacuation routes are generated for evacuees in different residential areas to achieve both safety and efficiency objectives. Based on a case study, it is found that both the increased evacuation preparation time and larger rainfall intensity have an adverse effect on the evacuation safety and efficiency, significantly reducing the evacuation success rate under severe floods. The expressways carrying the largest traffic volume are crucial for ensuring the efficient evacuation during floods. Furthermore, the uneven utilization of shelters due to the flood impact and limited capacity should be considered in urban planning. The study can bring practical guidance for emergency departments and decision-makers to mitigate disaster losses and develop evacuation schemes in urban floods.
{"title":"Dynamic evacuation route planning for urban residents in flood disasters","authors":"Shuchao Cao , Ying Zhou , Yunhe Tong , Rui Ye , Xiaoxia Yang , Yiping Zeng , Peng Wang","doi":"10.1016/j.simpat.2025.103250","DOIUrl":"10.1016/j.simpat.2025.103250","url":null,"abstract":"<div><div>In recent years, flood disasters have frequently impacted urban areas, resulting in significant casualties and property loss worldwide. To ensure the safety of residents during flooding events, it is urgent to conduct large-scale evacuations in flood-prone areas. However, the impacts of flooding on urban evacuation are dynamically coupled with real-world conditions, which are often overlooked in current research. Therefore, a dynamic evacuation planning framework is proposed in this paper to provide safe and efficient evacuation routes for urban population under various flood scenarios. Firstly, the flood spreading process is accurately simulated across different rainfall patterns. Secondly, the dynamic influences of floods on travel speed, instability risk and road capacity are incorporated and quantified in the evacuation planning. Finally, the quickest evacuation routes are generated for evacuees in different residential areas to achieve both safety and efficiency objectives. Based on a case study, it is found that both the increased evacuation preparation time and larger rainfall intensity have an adverse effect on the evacuation safety and efficiency, significantly reducing the evacuation success rate under severe floods. The expressways carrying the largest traffic volume are crucial for ensuring the efficient evacuation during floods. Furthermore, the uneven utilization of shelters due to the flood impact and limited capacity should be considered in urban planning. The study can bring practical guidance for emergency departments and decision-makers to mitigate disaster losses and develop evacuation schemes in urban floods.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"147 ","pages":"Article 103250"},"PeriodicalIF":3.5,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884624","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 : 2025-12-23DOI: 10.1016/j.simpat.2025.103247
Haoyu Han , Yihao Qu , Hongyuan Liu , Daisuke Fukuda , Xuantao Liu , Huaming An , Yingyao Cheng , Andrew Chan
An in-house combined finite-discrete element method (FDEM) is implemented to analyze the toppling failure process of anti-dip slopes. A strength reduction method integrated with kinetic energy monitoring and failure surface detection is applied to not only simulate the progressive slope failure process but also reveal complex failure mechanisms in anti-dip slopes. The FDEM is first validated through reproducing the through-going failure surface formation stage and the flexural toppling stage observed in laboratory experiments on anti-dip slope instabilities. Then, 23 numerical models are built to investigate the effects of slope geometry, thick layer position and cross-joint on the stability of anti-dip slopes. It is concluded that increasing slope angle leads to increasing failure surface depth and system kinetic energy but, decreasing factor of safety (FOS). Increasing rock layer inclination results in decreasing failure surface inclination but increasing failure surface depth. Increasing rock layer thickness, however, exerts limited effects on slope failure characteristics but enhances FOS. Furthermore, thick layer position has rather limited influence on FOS while cross-joints dominate the failure mode of anti-dip slopes. The numerical findings are expected to advance our understanding of complex failure mechanisms in anti-dip slopes and provide theoretical foundations for relevant slope stability assessment and prediction.
{"title":"Analysis of toppling failure mechanisms in anti-dip slopes based on FDEM simulation","authors":"Haoyu Han , Yihao Qu , Hongyuan Liu , Daisuke Fukuda , Xuantao Liu , Huaming An , Yingyao Cheng , Andrew Chan","doi":"10.1016/j.simpat.2025.103247","DOIUrl":"10.1016/j.simpat.2025.103247","url":null,"abstract":"<div><div>An in-house combined finite-discrete element method (FDEM) is implemented to analyze the toppling failure process of anti-dip slopes. A strength reduction method integrated with kinetic energy monitoring and failure surface detection is applied to not only simulate the progressive slope failure process but also reveal complex failure mechanisms in anti-dip slopes. The FDEM is first validated through reproducing the through-going failure surface formation stage and the flexural toppling stage observed in laboratory experiments on anti-dip slope instabilities. Then, 23 numerical models are built to investigate the effects of slope geometry, thick layer position and cross-joint on the stability of anti-dip slopes. It is concluded that increasing slope angle leads to increasing failure surface depth and system kinetic energy but, decreasing factor of safety (FOS). Increasing rock layer inclination results in decreasing failure surface inclination but increasing failure surface depth. Increasing rock layer thickness, however, exerts limited effects on slope failure characteristics but enhances FOS. Furthermore, thick layer position has rather limited influence on FOS while cross-joints dominate the failure mode of anti-dip slopes. The numerical findings are expected to advance our understanding of complex failure mechanisms in anti-dip slopes and provide theoretical foundations for relevant slope stability assessment and prediction.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"147 ","pages":"Article 103247"},"PeriodicalIF":3.5,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145840478","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 : 2025-12-23DOI: 10.1016/j.simpat.2025.103248
Elif Ravza Özaras , Mahmut Tutam , Nadide Çağlayan Özaydın , Sinan Öztaş
As online buyers desire a wider variety of products in smaller quantities with faster delivery times, warehouse technology is evolving to meet their needs. The Robotic Compact Storage and Retrieval System (RCS/RS) provides a solution by offering improved flexibility, continuous operation, and efficient use of available space. This study focuses on a single-robot RCS/RS configuration, in which one robot moves horizontally across a grid-based storage area and accesses vertical stacks while performing storage and retrieval tasks. To access a specific bin, the robot first removes any blocking bins above it and temporarily repositions them to neighboring stacks before delivering the requested bin to the port. To support improved system design, this study implements a large-scale, full-factorial experimental framework to evaluate key factors, including total bin capacity, stack height, arrival rate, and robot velocity. A refined simulation model, incorporating detailed retrieval and storage operations, is developed using ARENA 16.0 under an academic license. ANOVA-based analysis using IBM SPSS Statistics 28.0 is applied to the simulation results to evaluate the effects of system factors and their interactions on performance. Results indicate that robot velocity is the dominant factor, followed by total bin capacity and arrival rate, while stack height has a comparatively minor effect. The analysis also shows that several factor interactions play a significant role, highlighting the importance of considering combined effects when designing RCS/RS systems.
{"title":"Simulation-based performance analysis of a Robotic Compact Storage and Retrieval System under single-robot operation","authors":"Elif Ravza Özaras , Mahmut Tutam , Nadide Çağlayan Özaydın , Sinan Öztaş","doi":"10.1016/j.simpat.2025.103248","DOIUrl":"10.1016/j.simpat.2025.103248","url":null,"abstract":"<div><div>As online buyers desire a wider variety of products in smaller quantities with faster delivery times, warehouse technology is evolving to meet their needs. The Robotic Compact Storage and Retrieval System (RCS/RS) provides a solution by offering improved flexibility, continuous operation, and efficient use of available space. This study focuses on a single-robot RCS/RS configuration, in which one robot moves horizontally across a grid-based storage area and accesses vertical stacks while performing storage and retrieval tasks. To access a specific bin, the robot first removes any blocking bins above it and temporarily repositions them to neighboring stacks before delivering the requested bin to the port. To support improved system design, this study implements a large-scale, full-factorial experimental framework to evaluate key factors, including total bin capacity, stack height, arrival rate, and robot velocity. A refined simulation model, incorporating detailed retrieval and storage operations, is developed using ARENA 16.0 under an academic license. ANOVA-based analysis using IBM SPSS Statistics 28.0 is applied to the simulation results to evaluate the effects of system factors and their interactions on performance. Results indicate that robot velocity is the dominant factor, followed by total bin capacity and arrival rate, while stack height has a comparatively minor effect. The analysis also shows that several factor interactions play a significant role, highlighting the importance of considering combined effects when designing RCS/RS systems.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"147 ","pages":"Article 103248"},"PeriodicalIF":3.5,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145840477","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 : 2025-12-16DOI: 10.1016/j.simpat.2025.103246
Pasquale Legato, Massimiliano Matteucci, Rina Mary Mazza
The (re)organization of existing and planned warehouse facilities typically seeks to balance system-centric performance indicators (e.g., resource productivity) with customer-focused metrics (e.g., order response time). In pursuit of this objective, there is a growing opportunity to transition from conventional simulation models toward digital twin solutions, which offer enhanced decision-support capabilities. This manuscript focuses on the reorganization of manually executed order picking within a real-world wholesale operation. A simulation-based framework is introduced within a digital shadow environment to optimize the order picking process, following an S-shaped, person-to-goods picking strategy. At the core of the modeling approach is an enriched event graph, which captures the manual picking process at a fine-grained level by representing operational events and their real-time interdependencies. To demonstrate the framework’s effectiveness, numerical results are presented for a typical workday in a major Italian retail cooperative. These results compare alternative control policies, examining their impact on queueing dynamics and picker interference, key contributors to service blocking, resource locking, and starvation within the warehouse’s parallel picking aisles.
{"title":"Towards a digital twin solution for manual order-picking operations in a wholesale distribution center","authors":"Pasquale Legato, Massimiliano Matteucci, Rina Mary Mazza","doi":"10.1016/j.simpat.2025.103246","DOIUrl":"10.1016/j.simpat.2025.103246","url":null,"abstract":"<div><div>The (re)organization of existing and planned warehouse facilities typically seeks to balance system-centric performance indicators (e.g., resource productivity) with customer-focused metrics (e.g., order response time). In pursuit of this objective, there is a growing opportunity to transition from conventional simulation models toward digital twin solutions, which offer enhanced decision-support capabilities. This manuscript focuses on the reorganization of manually executed order picking within a real-world wholesale operation. A simulation-based framework is introduced within a digital shadow environment to optimize the order picking process, following an S-shaped, person-to-goods picking strategy. At the core of the modeling approach is an enriched event graph, which captures the manual picking process at a fine-grained level by representing operational events and their real-time interdependencies. To demonstrate the framework’s effectiveness, numerical results are presented for a typical workday in a major Italian retail cooperative. These results compare alternative control policies, examining their impact on queueing dynamics and picker interference, key contributors to service blocking, resource locking, and starvation within the warehouse’s parallel picking aisles.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"147 ","pages":"Article 103246"},"PeriodicalIF":3.5,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791294","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 : 2025-12-15DOI: 10.1016/j.simpat.2025.103240
Yongxing Li , Xiaoxiao Fu , Jingxuan Peng , Xiaoxia Yang
Urban flood disasters have occurred frequently in recent years, posing significant risks to underground spaces with high pedestrian density such as subway stations. However, existing studies on exit selection by choosing the nearest exit oversimplify the decision-making process, while, the assumption of a globally shortest evacuation time is impractical, as pedestrians are unaware of the actual path conditions. Inspired by the success of the cellular automata (CA) model in the field of pedestrian emergency evacuation simulation, we propose a multi-exits selection-based multi-fields cellular automata (MEF-CA) framework for simulating pedestrians evacuation of subway station platforms under flood disasters, which incorporates three modules: flood spreading (FS) module, estimated evacuation time-based multi-exits selection (EMS) module, and multi-fields cellular automata (MCA) module. Specifically, we simulate flood spreading process through the FS module with MIKE software, and obtain the exit selection result through the EMS module. Furthermore, by fusing multiple fields, a MCA module is established to simulate pedestrians movement. In addition, we conduct a survey of the platform at Beijing University of Technology’s West Gate Station and select it as a case study. On this basis, a large number of simulation experiments are carried out, and the comparison with the traditional model demonstrates that our framework can more faithfully reproduce pedestrian evacuation under flood conditions. Based on the MEF-CA, three meaningful conclusions can be drawn: (1) The critical role of exit selection: the EMS module more realistically simulates pedestrian exit-choice behavior. (2) The significant impact of water inflow conditions: fewer inlets – especially when positioned on the same side – can reduce flood impact and lower the number of un-evacuated pedestrians. (3) The influence of train stopping patterns: parking trains on one side of the platform can significantly improve evacuation efficiency. These findings provide theoretical support and practical guidance for optimizing subway station design and emergency management under flood disaster.
{"title":"Which exit to choose? A multi-fields cellular automata model for simulating passenger evacuation of subway station platforms under flood disaster","authors":"Yongxing Li , Xiaoxiao Fu , Jingxuan Peng , Xiaoxia Yang","doi":"10.1016/j.simpat.2025.103240","DOIUrl":"10.1016/j.simpat.2025.103240","url":null,"abstract":"<div><div>Urban flood disasters have occurred frequently in recent years, posing significant risks to underground spaces with high pedestrian density such as subway stations. However, existing studies on exit selection by choosing the nearest exit oversimplify the decision-making process, while, the assumption of a globally shortest evacuation time is impractical, as pedestrians are unaware of the actual path conditions. Inspired by the success of the cellular automata (CA) model in the field of pedestrian emergency evacuation simulation, we propose a multi-exits selection-based multi-fields cellular automata (MEF-CA) framework for simulating pedestrians evacuation of subway station platforms under flood disasters, which incorporates three modules: flood spreading (FS) module, estimated evacuation time-based multi-exits selection (EMS) module, and multi-fields cellular automata (MCA) module. Specifically, we simulate flood spreading process through the FS module with MIKE software, and obtain the exit selection result through the EMS module. Furthermore, by fusing multiple fields, a MCA module is established to simulate pedestrians movement. In addition, we conduct a survey of the platform at Beijing University of Technology’s West Gate Station and select it as a case study. On this basis, a large number of simulation experiments are carried out, and the comparison with the traditional model demonstrates that our framework can more faithfully reproduce pedestrian evacuation under flood conditions. Based on the MEF-CA, three meaningful conclusions can be drawn: (1) <strong>The critical role of exit selection:</strong> the EMS module more realistically simulates pedestrian exit-choice behavior. (2) <strong>The significant impact of water inflow conditions:</strong> fewer inlets – especially when positioned on the same side – can reduce flood impact and lower the number of un-evacuated pedestrians. (3) <strong>The influence of train stopping patterns:</strong> parking trains on one side of the platform can significantly improve evacuation efficiency. These findings provide theoretical support and practical guidance for optimizing subway station design and emergency management under flood disaster.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"147 ","pages":"Article 103240"},"PeriodicalIF":3.5,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791295","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}
Claystone tends to swell and deform upon exposure to water, frequently causing adverse impacts on the stability of engineering excavations. Predicting the swelling behaviour remains challenging due to the combined effects of various influencing factors associated with mineral compositions and external conditions. This study conducts swelling tests on claystone to assess the one-dimensional swelling under different vertical loads. Laboratory tests reveal that external loads can impede the evolution of swelling pressure and reduce the swelling deformation. Based on the test results, a 3D hydro-mechanical model is developed by coupling time-dependent hydraulic process and mechanical response to simulate the swelling behaviour of the rock under varying loading conditions. A material diffusivity constant is introduced to quantify the nonlinear decay effects of external loading on the effective diffusion coefficient during the hydraulic process. Parametric sensitivity analyses evaluate the impact of clay mineral content and external loading on swelling behaviour. The results indicate that (i) higher clay mineral contents lead to greater swelling deformation due to the stiffness degradation, and (ii) greater external loads retard the water transport process and decrease swelling deformation. The combined effects of clay content and external loading are discussed. Furthermore, a long-term swelling prediction of 10,000 days is performed, revealing that an enhanced confinement can delay the timing of swelling stabilisation due to the decline in effective diffusion coefficient. The estimated swelling strain shows an inverse relationship with the confinement. Overall, this study enhances the understanding of rock behaviour under various mineral compositions and external loads, providing valuable insights into predicting and mitigating swelling.
{"title":"A hydro-mechanical model for predicting long-term swelling of claystone under constant loading","authors":"Wanqi Zhang, Honghao Chen, Chengguo Zhang, Joung Oh, Ismet Canbulat, Serkan Saydam","doi":"10.1016/j.simpat.2025.103245","DOIUrl":"10.1016/j.simpat.2025.103245","url":null,"abstract":"<div><div>Claystone tends to swell and deform upon exposure to water, frequently causing adverse impacts on the stability of engineering excavations. Predicting the swelling behaviour remains challenging due to the combined effects of various influencing factors associated with mineral compositions and external conditions. This study conducts swelling tests on claystone to assess the one-dimensional swelling under different vertical loads. Laboratory tests reveal that external loads can impede the evolution of swelling pressure and reduce the swelling deformation. Based on the test results, a 3D hydro-mechanical model is developed by coupling time-dependent hydraulic process and mechanical response to simulate the swelling behaviour of the rock under varying loading conditions. A material diffusivity constant is introduced to quantify the nonlinear decay effects of external loading on the effective diffusion coefficient during the hydraulic process. Parametric sensitivity analyses evaluate the impact of clay mineral content and external loading on swelling behaviour. The results indicate that (i) higher clay mineral contents lead to greater swelling deformation due to the stiffness degradation, and (ii) greater external loads retard the water transport process and decrease swelling deformation. The combined effects of clay content and external loading are discussed. Furthermore, a long-term swelling prediction of 10,000 days is performed, revealing that an enhanced confinement can delay the timing of swelling stabilisation due to the decline in effective diffusion coefficient. The estimated swelling strain shows an inverse relationship with the confinement. Overall, this study enhances the understanding of rock behaviour under various mineral compositions and external loads, providing valuable insights into predicting and mitigating swelling.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"147 ","pages":"Article 103245"},"PeriodicalIF":3.5,"publicationDate":"2025-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791292","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 : 2025-12-06DOI: 10.1016/j.simpat.2025.103243
Mingwei Liu , Tingting Wu , Yoshinao Oeda
During peak school commute times in China, both vehicle and pedestrian traffic increase significantly, which worsens road safety near rural schools that often lack adequate sidewalk infrastructure. This study introduces a two-phase simulation model to predict the likelihood that child pedestrians will avoid vehicles on specific road segments, particularly when their movements are parallel to those of the vehicles. In the first phase, a support vector machine (SVM) was used to analyze how pedestrians respond in different traffic scenarios on bi-directional, mixed-traffic roads and to assess the factors influencing pedestrian behavior during interactions with vehicles. In the second phase, a spatial-temporal simulation model was developed to examine the interaction between pedestrian and vehicle sequences on these road segments, providing a stochastic approach to evaluating pedestrian safety. The model incorporates several factors, including bidirectional traffic volume, traffic speed, vehicle type, on-street parking availability during commute time, and pedestrian movement patterns. The findings show that the impact of same-direction traffic on pedestrians' risk perception is greater than that of opposite-direction traffic. Additionally, reducing peak-time on-street parking near schools significantly improves pedestrian safety. By directly estimating pedestrian risk perception based on controllable traffic factors, the study provides valuable insights for traffic management strategies. This research presents a novel tool to enhance road safety, particularly in rural school areas, thereby helping mitigate risks during peak commuting times.
{"title":"Enhancing pedestrian safety on rural primary school roads in shanghai using machine learning and spatial-temporal simulation modeling","authors":"Mingwei Liu , Tingting Wu , Yoshinao Oeda","doi":"10.1016/j.simpat.2025.103243","DOIUrl":"10.1016/j.simpat.2025.103243","url":null,"abstract":"<div><div>During peak school commute times in China, both vehicle and pedestrian traffic increase significantly, which worsens road safety near rural schools that often lack adequate sidewalk infrastructure. This study introduces a two-phase simulation model to predict the likelihood that child pedestrians will avoid vehicles on specific road segments, particularly when their movements are parallel to those of the vehicles. In the first phase, a support vector machine (SVM) was used to analyze how pedestrians respond in different traffic scenarios on bi-directional, mixed-traffic roads and to assess the factors influencing pedestrian behavior during interactions with vehicles. In the second phase, a spatial-temporal simulation model was developed to examine the interaction between pedestrian and vehicle sequences on these road segments, providing a stochastic approach to evaluating pedestrian safety. The model incorporates several factors, including bidirectional traffic volume, traffic speed, vehicle type, on-street parking availability during commute time, and pedestrian movement patterns. The findings show that the impact of same-direction traffic on pedestrians' risk perception is greater than that of opposite-direction traffic. Additionally, reducing peak-time on-street parking near schools significantly improves pedestrian safety. By directly estimating pedestrian risk perception based on controllable traffic factors, the study provides valuable insights for traffic management strategies. This research presents a novel tool to enhance road safety, particularly in rural school areas, thereby helping mitigate risks during peak commuting times.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"147 ","pages":"Article 103243"},"PeriodicalIF":3.5,"publicationDate":"2025-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791293","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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