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}
Pub Date : 2025-12-06DOI: 10.1016/j.simpat.2025.103242
Lianbo Deng , Jingshuang Li , Huaru Liu , Xiaoshan Zhu , Xinlei Hu
The spatiotemporal rules of passenger flow in urban rail transit (URT) hubs are complex, meaning that simulation modeling and analysis of passenger flow distributions in hubs are very important in terms of scientifically organizing passenger flow and improving travel efficiency. In this study, an analysis was conducted of passengers' travel processes and behaviors, and a simulation model combining cellular automata (CA) and agent-based modeling (ABM) was proposed. A CA grid environment was used to describe the spatial constraints and movement logic, whereas ABM was employed to construct passenger agents. This approach included a visual perception model, a behavior decision-making model that took into consideration the influence of multiple factors, a fuzzy logic-based multi-channel selection model, and a group-competition-based action execution model, in order to finely characterize the individual microscopic behaviors. Tiyu Xilu Station of Guangzhou Metro in China was taken as a case study, and the simulation results were used to verify the effectiveness of the model. The key findings were as follows: the simulation results for escalator passenger throughput were close to the design capacity, with a difference of -4.2%; the service level for the west platform of Line 3 was lower than for the east platform, with the lowest being Level E; during peak hours, for every 10% increase in the degree of bidirectional pedestrian flow, the average dwell time increased by approximately 6.8%. These research results provide decision support for optimizing passenger flow organization in URT hubs.
{"title":"Passenger flow simulation model for urban rail transit hubs based on cellular automata and multi-agent systems","authors":"Lianbo Deng , Jingshuang Li , Huaru Liu , Xiaoshan Zhu , Xinlei Hu","doi":"10.1016/j.simpat.2025.103242","DOIUrl":"10.1016/j.simpat.2025.103242","url":null,"abstract":"<div><div>The spatiotemporal rules of passenger flow in urban rail transit (URT) hubs are complex, meaning that simulation modeling and analysis of passenger flow distributions in hubs are very important in terms of scientifically organizing passenger flow and improving travel efficiency. In this study, an analysis was conducted of passengers' travel processes and behaviors, and a simulation model combining cellular automata (CA) and agent-based modeling (ABM) was proposed. A CA grid environment was used to describe the spatial constraints and movement logic, whereas ABM was employed to construct passenger agents. This approach included a visual perception model, a behavior decision-making model that took into consideration the influence of multiple factors, a fuzzy logic-based multi-channel selection model, and a group-competition-based action execution model, in order to finely characterize the individual microscopic behaviors. Tiyu Xilu Station of Guangzhou Metro in China was taken as a case study, and the simulation results were used to verify the effectiveness of the model. The key findings were as follows: the simulation results for escalator passenger throughput were close to the design capacity, with a difference of -4.2%; the service level for the west platform of Line 3 was lower than for the east platform, with the lowest being Level E; during peak hours, for every 10% increase in the degree of bidirectional pedestrian flow, the average dwell time increased by approximately 6.8%. These research results provide decision support for optimizing passenger flow organization in URT hubs.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"147 ","pages":"Article 103242"},"PeriodicalIF":3.5,"publicationDate":"2025-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145738580","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 : 2025-12-05DOI: 10.1016/j.simpat.2025.103241
G. Xiroudakis , G. Saratsis , G.E. Exadaktylos , E. Machairas , E.A. Varouchakis , S. Mavrigiannakis
The room-and-pillar mining method is an ancient technique used in the extraction of underground deposits. Even today, it remains one of the most widespread and productive methods of underground mining, where the abandoned pillars ensure the stability of the opening. The mechanical behavior of the pillar plays an important role in its sizing and the estimation of ore recovery. In this paper, the rock material from a historical ancient underground quarry in Gortyna, Crete, Greece, was numerically investigated. This material, composed of limestone, that exhibits pronounced layering and is very soft, allowed the ancient Romans to excavate underground tunnels with a total length of >2.5 km. A high-resolution 3D X Phase Pro S2 360 camera, was used to capture panoramic photos in both horizontal and vertical planes. These photos were used to estimate the dimensions of the chambers and the central pillar of the accessible underground area of the site (the large underground quarry has been closed). The effect of micro-cracking of the rock on the behavior of the room and pillar excavation method was investigated using Linear Elastic Fracture Mechanics (LEFM) theory. For this purpose, a numerical model was created using the FLAC2D software to estimate the effective elastic parameters of the material based on its density and the arrangement of cracks within it. This analysis revealed that the presence of microcracks introduces an anisotropy similar to that of a transversely isotropic material. The observed anisotropy results in larger deformations in the main chamber crown than those obtained using average elastic properties from experimental, literature, and field investigations of limestone rock.
房柱采矿法是一种用于开采地下矿床的古老技术。即使在今天，它仍然是最广泛和最有效的地下采矿方法之一，其中废弃的支柱确保了开口的稳定性。矿柱的力学行为对矿柱的尺寸确定和回采率的估计起着重要的作用。本文对希腊克里特岛Gortyna一个历史悠久的地下采石场的岩石材料进行了数值研究。这种由石灰石组成的材料，具有明显的分层性，非常柔软，古罗马人因此得以挖掘总长2.5公里的地下隧道。高分辨率3D X Phase Pro S2 360相机，用于捕捉水平和垂直平面的全景照片。这些照片被用来估计墓室的尺寸和可到达的地下区域的中央柱子（大型地下采石场已经关闭）。采用线弹性断裂力学（LEFM）理论，研究了岩石微裂纹对硐室和矿柱开挖行为的影响。为此，利用FLAC2D软件建立数值模型，根据材料的密度和材料内部裂纹的排列来估计材料的有效弹性参数。这一分析表明，微裂纹的存在引入了类似于横向各向同性材料的各向异性。观察到的各向异性导致主室顶部的变形比通过实验、文献和现场调查石灰石的平均弹性特性获得的变形更大。
{"title":"The effect of microstructure on the behavior of an underground excavation","authors":"G. Xiroudakis , G. Saratsis , G.E. Exadaktylos , E. Machairas , E.A. Varouchakis , S. Mavrigiannakis","doi":"10.1016/j.simpat.2025.103241","DOIUrl":"10.1016/j.simpat.2025.103241","url":null,"abstract":"<div><div>The room-and-pillar mining method is an ancient technique used in the extraction of underground deposits. Even today, it remains one of the most widespread and productive methods of underground mining, where the abandoned pillars ensure the stability of the opening. The mechanical behavior of the pillar plays an important role in its sizing and the estimation of ore recovery. In this paper, the rock material from a historical ancient underground quarry in Gortyna, Crete, Greece, was numerically investigated. This material, composed of limestone, that exhibits pronounced layering and is very soft, allowed the ancient Romans to excavate underground tunnels with a total length of >2.5 km. A high-resolution 3D X Phase Pro S2 360 camera, was used to capture panoramic photos in both horizontal and vertical planes. These photos were used to estimate the dimensions of the chambers and the central pillar of the accessible underground area of the site (the large underground quarry has been closed). The effect of micro-cracking of the rock on the behavior of the room and pillar excavation method was investigated using Linear Elastic Fracture Mechanics (LEFM) theory. For this purpose, a numerical model was created using the FLAC2D software to estimate the effective elastic parameters of the material based on its density and the arrangement of cracks within it. This analysis revealed that the presence of microcracks introduces an anisotropy similar to that of a transversely isotropic material. The observed anisotropy results in larger deformations in the main chamber crown than those obtained using average elastic properties from experimental, literature, and field investigations of limestone rock.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"147 ","pages":"Article 103241"},"PeriodicalIF":3.5,"publicationDate":"2025-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145738584","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 : 2025-12-04DOI: 10.1016/j.simpat.2025.103239
Chengpu Peng , Lin Geng , Jiaxiang Liu , Liang Tang , Xianzhang Ling
To investigate the anchorage performance of split-grouted rock bolt in fractured rock slopes, a computational model was developed that accounts for rock bolt failure modes and the nonlinear mechanical behavior of the anchorage interface. Field pullout tests were conducted on three sets of split-grouted rock bolts, with ultimate strengths of 250.73 kN, 254.45 kN, and 253.66 kN, respectively. The computational model was then used to fit the experimental data, determining a peak shear strength of the anchorage interface as 0.55 MPa with a corresponding shear displacement of 3.31 mm and a residual shear strength of 0.17 MPa. The nonlinear mechanical characteristics of the anchorage interface were incorporated into numerical simulations to examine the effectiveness of split-grouted rock bolts in slopes with varying joint spacing and grouting radius. Results demonstrated that the combined reinforcement of rock bolts and grouting effectively enhanced the integrity of fragmented rock masses, significantly improving slope stability and altering the failure mode of fractured rock slopes. These conclusions provide valuable insights and practical guidance for the engineering design of split-grouted rock bolt reinforcement systems in fractured rock slope stabilization.
{"title":"Anchorage performance of split-grouted rock bolt in fractured rock slope","authors":"Chengpu Peng , Lin Geng , Jiaxiang Liu , Liang Tang , Xianzhang Ling","doi":"10.1016/j.simpat.2025.103239","DOIUrl":"10.1016/j.simpat.2025.103239","url":null,"abstract":"<div><div>To investigate the anchorage performance of split-grouted rock bolt in fractured rock slopes, a computational model was developed that accounts for rock bolt failure modes and the nonlinear mechanical behavior of the anchorage interface. Field pullout tests were conducted on three sets of split-grouted rock bolts, with ultimate strengths of 250.73 kN, 254.45 kN, and 253.66 kN, respectively. The computational model was then used to fit the experimental data, determining a peak shear strength of the anchorage interface as 0.55 MPa with a corresponding shear displacement of 3.31 mm and a residual shear strength of 0.17 MPa. The nonlinear mechanical characteristics of the anchorage interface were incorporated into numerical simulations to examine the effectiveness of split-grouted rock bolts in slopes with varying joint spacing and grouting radius. Results demonstrated that the combined reinforcement of rock bolts and grouting effectively enhanced the integrity of fragmented rock masses, significantly improving slope stability and altering the failure mode of fractured rock slopes. These conclusions provide valuable insights and practical guidance for the engineering design of split-grouted rock bolt reinforcement systems in fractured rock slope stabilization.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"147 ","pages":"Article 103239"},"PeriodicalIF":3.5,"publicationDate":"2025-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791291","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 : 2025-12-03DOI: 10.1016/j.simpat.2025.103238
Jixin Shi , Maoyu Li , Nan Jiang , Hanchen Yu , Hongyun Yang , Xiaodong Zhou , Lizhong Yang
Efficient evacuation in complex building environments remains a fundamental challenge in simulation modeling and public safety. Traditional models based on static path-finding or rule-based decision-making often result in unbalanced exit utilization and congestion, limiting their ability to represent adaptive human behavior in emergencies. To address these shortcomings, this study proposes a Collaborative Decision-Making Framework based on Multi-Agent Deep Reinforcement Learning (CDF-MADRL). The framework introduces a dynamic multi-objective reward mechanism that adaptively balances individual evacuation time and collective efficiency, and a localized observation strategy that significantly reduces computational burden in large-scale multi-agent environments. Implemented using the MAPPO algorithm, the model was validated in a complex asymmetric multi-exit scenario with varying population sizes. Results show that CDF-MADRL improves training stability by over 70% and reduces average evacuation time by 2–11% compared with baseline models. Beyond improving evacuation efficiency, this research contributes methodologically by demonstrating how reinforcement learning can be systematically embedded into simulation modeling practice, offering a scalable and intelligent framework for evacuation analysis. These findings highlight the potential of integrating artificial intelligence with simulation modeling to enhance resilience in complex built environments.
{"title":"A multi-agent deep reinforcement learning model for crowd coordinated evacuation simulation in complex environments","authors":"Jixin Shi , Maoyu Li , Nan Jiang , Hanchen Yu , Hongyun Yang , Xiaodong Zhou , Lizhong Yang","doi":"10.1016/j.simpat.2025.103238","DOIUrl":"10.1016/j.simpat.2025.103238","url":null,"abstract":"<div><div>Efficient evacuation in complex building environments remains a fundamental challenge in simulation modeling and public safety. Traditional models based on static path-finding or rule-based decision-making often result in unbalanced exit utilization and congestion, limiting their ability to represent adaptive human behavior in emergencies. To address these shortcomings, this study proposes a Collaborative Decision-Making Framework based on Multi-Agent Deep Reinforcement Learning (CDF-MADRL). The framework introduces a dynamic multi-objective reward mechanism that adaptively balances individual evacuation time and collective efficiency, and a localized observation strategy that significantly reduces computational burden in large-scale multi-agent environments. Implemented using the MAPPO algorithm, the model was validated in a complex asymmetric multi-exit scenario with varying population sizes. Results show that CDF-MADRL improves training stability by over 70% and reduces average evacuation time by 2–11% compared with baseline models. Beyond improving evacuation efficiency, this research contributes methodologically by demonstrating how reinforcement learning can be systematically embedded into simulation modeling practice, offering a scalable and intelligent framework for evacuation analysis. These findings highlight the potential of integrating artificial intelligence with simulation modeling to enhance resilience in complex built environments.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"147 ","pages":"Article 103238"},"PeriodicalIF":3.5,"publicationDate":"2025-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145738582","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}
Sustainable scheduling and resource management becomes very important in edge–fog–cloud environments, especially when hybrid renewable energy resources have been highly integrated with IoT applications. The work proposed in this paper introduces a simulation system for optimizing sustainable energy in several operating conditions, it highlights intelligent scheduling and resource allocation as well. Generative AI (GenAI) with edge intelligence have been employed in the proposed system to create synthetic simulated data. This enables efficient performance modelling and improves energy scheduling strategies testing. The experiments which are based on Simulation, improve sustainability metrics (over 30% gains in scheduling efficiency), proved higher Mean Time Between Failures (MTBF) which indicates increased reliability, and energy consumption where significantly reduced keeping workload deadlines. These results emphasize the importance of the proposed systems. Moreover, this work highlight the possibility of expanding the proposed system for emerging computing models such as 6G and the Industrial IoT.
{"title":"Simulation based sustainable optimization in edge–fog–cloud energy systems","authors":"Shadi Alzu’bi , Basem Alokush , Leila Jamel , Fahd N. Al-Wesabi , Randa Allafi","doi":"10.1016/j.simpat.2025.103237","DOIUrl":"10.1016/j.simpat.2025.103237","url":null,"abstract":"<div><div>Sustainable scheduling and resource management becomes very important in edge–fog–cloud environments, especially when hybrid renewable energy resources have been highly integrated with IoT applications. The work proposed in this paper introduces a simulation system for optimizing sustainable energy in several operating conditions, it highlights intelligent scheduling and resource allocation as well. Generative AI (GenAI) with edge intelligence have been employed in the proposed system to create synthetic simulated data. This enables efficient performance modelling and improves energy scheduling strategies testing. The experiments which are based on Simulation, improve sustainability metrics (over 30% gains in scheduling efficiency), proved higher Mean Time Between Failures (MTBF) which indicates increased reliability, and energy consumption where significantly reduced keeping workload deadlines. These results emphasize the importance of the proposed systems. Moreover, this work highlight the possibility of expanding the proposed system for emerging computing models such as 6G and the Industrial IoT.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"147 ","pages":"Article 103237"},"PeriodicalIF":3.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145665650","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 : 2025-11-27DOI: 10.1016/j.simpat.2025.103236
Lin Zhang , Yuteng Zhang , Dusit Niyato , Lei Ren , Pengfei Gu , Zhen Chen , Yuanjun Laili , Wentong Cai , Agostino Bruzzone
Generative AI (GenAI) has demonstrated remarkable capabilities in code generation, and its integration into model-based systems engineering for complex product modeling and simulation code generation can significantly enhance the efficiency of product design and modeling. In this study, we introduce a generative system modeling framework, offering a practical approach for the intelligent generation of simulation models for system physical properties. First, we fine-tune the language model used for simulation model generation on an existing library of simulation models and additional datasets generated through generative modeling. Subsequently, we employ BERT-based inference techniques, generative models, and integrated modeling and simulation languages to construct simulation models for system physical properties of products based on product design documents. Thereafter, we introduce evaluation metrics for the generated simulation models for system physical properties. Finally, we propose a validation and simulation framework for generated simulation models. Our proposed approach to simulation model generation presents the innovative concept of scalable templates for simulation models. Using these templates, GenAI generates simulation models for system physical properties through code completion. The experimental results demonstrate that, for mainstream open-source Transformer-based models, the quality of the simulation model is improved by 21.4% using the simulation model generation method proposed in this paper.
{"title":"Intelligent system modeling using GenAI: A methodology for automated simulation model generation","authors":"Lin Zhang , Yuteng Zhang , Dusit Niyato , Lei Ren , Pengfei Gu , Zhen Chen , Yuanjun Laili , Wentong Cai , Agostino Bruzzone","doi":"10.1016/j.simpat.2025.103236","DOIUrl":"10.1016/j.simpat.2025.103236","url":null,"abstract":"<div><div>Generative AI (GenAI) has demonstrated remarkable capabilities in code generation, and its integration into model-based systems engineering for complex product modeling and simulation code generation can significantly enhance the efficiency of product design and modeling. In this study, we introduce a generative system modeling framework, offering a practical approach for the intelligent generation of simulation models for system physical properties. First, we fine-tune the language model used for simulation model generation on an existing library of simulation models and additional datasets generated through generative modeling. Subsequently, we employ BERT-based inference techniques, generative models, and integrated modeling and simulation languages to construct simulation models for system physical properties of products based on product design documents. Thereafter, we introduce evaluation metrics for the generated simulation models for system physical properties. Finally, we propose a validation and simulation framework for generated simulation models. Our proposed approach to simulation model generation presents the innovative concept of scalable templates for simulation models. Using these templates, GenAI generates simulation models for system physical properties through code completion. The experimental results demonstrate that, for mainstream open-source Transformer-based models, the quality of the simulation model is improved by 21.4% using the simulation model generation method proposed in this paper.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"147 ","pages":"Article 103236"},"PeriodicalIF":3.5,"publicationDate":"2025-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145665649","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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