Simulation Modelling Practice and Theory最新文献_第6页

Numerical modelling of drop mass shape influence on energy absorption of welded wire mesh in dynamic impact conditions 动态冲击条件下跌落质量形状对焊接网吸能影响的数值模拟

IF 3.5 2区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Simulation Modelling Practice and Theory

Pub Date : 2025-12-01 Epub Date: 2025-09-17 DOI: 10.1016/j.simpat.2025.103207

Ceren Karatas Batan , Selahattin Akdag , Chengguo Zhang , Joung Oh , Serkan Saydam

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.

地下矿山在动载条件下，依靠地面支护系统（即钢筋和焊接钢丝网等地表支护元件）控制岩石变形，维持开挖稳定。设计一个有效的地面支撑系统需要详细了解这些支撑部件的机械行为及其对冲击情景的响应。本研究利用基于实验室测试中使用的几何形状的三维有限元分析（FEA）研究了下落质量几何形状对焊接钢丝网变形和破坏机制的影响。在相同的能量输入下，评估了棱镜、球形、圆柱形、ETAG 027和不规则五种水滴质量构型，以探索它们对网格行为的影响。尽管开发的动态测试设置为网格性能提供了有价值的见解，但缺乏标准化的下落质量形状仍然是一个重大挑战，因为它会导致测试结果不一致，并使不同研究之间的数据比较复杂化或可靠的实验复制。利用实验数据建立了有限元模型并进行了标定。结果表明，降质量形状对载荷分布、位移模式和网格损伤程度有较大影响。用于标定的棱镜形状与实验室结果吻合良好。由于初始冲击载荷集中分布在较小的接触面积上，圆柱形结构的能量消耗更有利，吸收了5.69 kJ，而不规则形状和球形结构的能量吸收较低，分别为2.83 kJ和2.55 kJ。ETAG 027的几何形状产生了平衡的响应，峰值位移约为152.77 mm，能量吸收为3.06 kJ，并伴有适度分布的塑性变形。该研究可以为动态地下环境中支撑系统开发更可靠的测试程序和基于能量的设计方法提供支持。

{"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":"2025-12-01","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}

引用次数: 0

Optimization of start-up strategies of gas injection compressor in underground gas storage using deep reinforcement learning 基于深度强化学习的地下储气库注气压缩机启动策略优化

IF 3.5 2区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Simulation Modelling Practice and Theory

Pub Date : 2025-12-01 Epub Date: 2025-08-30 DOI: 10.1016/j.simpat.2025.103204

Xingyu Zhao , Changhe Li , Pengzhi Lu , Wei Li , Weiwei Qiu , Wuchang Wang , Yuxing Li

Injection compressors, as the core equipment in the gas injection process of underground gas storage (UGS) facilities, play a vital role in ensuring the safe and efficient operation of UGS systems. However, traditional optimization methods often struggle to adapt dynamically under complex operating conditions and may lead to excessive energy consumption. To address these challenges, this study proposes a deep reinforcement learning (DRL)-based approach to optimize compressor start-up strategies. First, a high-fidelity hybrid simulation model is developed by integrating thermodynamic equations of reciprocating compressors with a residual correction network based on a multilayer perceptron, forming a Mechanism-Data fusion Model framework. This model achieves prediction errors of <5 % for power and <3 % for discharge flow rate. Based on the accurate simulation model, an optimization framework is constructed using the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm. Within this framework, continuous control variables—such as the number of operating compressors, inlet throttling levels, and relative clearance volume adjustments—are mapped to the action space of the reinforcement learning agent. A multi-objective reward function is designed to incorporate penalties for gas injection deviations, the number of active compressors, inlet pressure constraints, and clearance volume limits. By introducing delayed updates to the target network and applying an adaptive noise clipping mechanism, the proposed strategy ensures optimal parameter control across the entire gas injection cycle while satisfying operational and safety requirements. Experimental results demonstrate that the proposed method reduces compressor energy consumption by 5.18 %, offering a precise, adaptive, and intelligent decision-making solution for dynamic optimization of UGS compressor operations.

注气压缩机作为地下储气库设施注气过程中的核心设备，对保证地下储气库系统安全高效运行起着至关重要的作用。然而，传统的优化方法往往难以动态适应复杂的运行条件，并且可能导致过多的能量消耗。为了应对这些挑战，本研究提出了一种基于深度强化学习（DRL）的方法来优化压缩机启动策略。首先，将往复式压缩机热力学方程与基于多层感知器的残差校正网络相结合，建立了高保真混合仿真模型，形成了机制-数据融合模型框架；该模型对功率的预测误差为5%，对流量的预测误差为3%。在精确仿真模型的基础上，采用双延迟深度确定性策略梯度（TD3）算法构建了优化框架。在这个框架中，连续的控制变量——如运行压缩机的数量、进口节流水平和相对间隙量调整——被映射到强化学习代理的动作空间。设计了一个多目标奖励函数，包括对注气偏差、活动压缩机数量、进口压力约束和间隙容积限制的惩罚。通过向目标网络引入延迟更新，并应用自适应噪声抑制机制，该策略确保在满足操作和安全要求的同时，在整个注气周期内实现最优参数控制。实验结果表明，该方法可将压缩机能耗降低5.18%，为UGS压缩机运行动态优化提供了精确、自适应、智能的决策解决方案。

{"title":"Optimization of start-up strategies of gas injection compressor in underground gas storage using deep reinforcement learning","authors":"Xingyu Zhao , Changhe Li , Pengzhi Lu , Wei Li , Weiwei Qiu , Wuchang Wang , Yuxing Li","doi":"10.1016/j.simpat.2025.103204","DOIUrl":"10.1016/j.simpat.2025.103204","url":null,"abstract":"<div><div>Injection compressors, as the core equipment in the gas injection process of underground gas storage (UGS) facilities, play a vital role in ensuring the safe and efficient operation of UGS systems. However, traditional optimization methods often struggle to adapt dynamically under complex operating conditions and may lead to excessive energy consumption. To address these challenges, this study proposes a deep reinforcement learning (DRL)-based approach to optimize compressor start-up strategies. First, a high-fidelity hybrid simulation model is developed by integrating thermodynamic equations of reciprocating compressors with a residual correction network based on a multilayer perceptron, forming a Mechanism-Data fusion Model framework. This model achieves prediction errors of <5 % for power and <3 % for discharge flow rate. Based on the accurate simulation model, an optimization framework is constructed using the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm. Within this framework, continuous control variables—such as the number of operating compressors, inlet throttling levels, and relative clearance volume adjustments—are mapped to the action space of the reinforcement learning agent. A multi-objective reward function is designed to incorporate penalties for gas injection deviations, the number of active compressors, inlet pressure constraints, and clearance volume limits. By introducing delayed updates to the target network and applying an adaptive noise clipping mechanism, the proposed strategy ensures optimal parameter control across the entire gas injection cycle while satisfying operational and safety requirements. Experimental results demonstrate that the proposed method reduces compressor energy consumption by 5.18 %, offering a precise, adaptive, and intelligent decision-making solution for dynamic optimization of UGS compressor operations.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"145 ","pages":"Article 103204"},"PeriodicalIF":3.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145010686","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}

引用次数: 0

Multi-objectives optimization of evacuation path based on improved matrix translation model and exit balance algorithm 基于改进矩阵平移模型和出口平衡算法的疏散路径多目标优化

IF 3.5 2区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Simulation Modelling Practice and Theory

Pub Date : 2025-12-01 Epub Date: 2025-08-23 DOI: 10.1016/j.simpat.2025.103201

Chun Sheng , Qize He , Liping Yu , Jiacheng Wang , Haoming Xie , Zhiming Fang , Zhongyi Huang

Emergency evacuation planning requires balancing multiple objectives like minimizing time, avoiding hazards, and ensuring fairness. Traditional methods struggle to strike a balance between macroscopic efficiency and microscopic realism. This study proposes a new multi-objective optimization framework based on an improved Matrix Translation Model (MTM) and Exit Balance Algorithm (EBA): the improved MTM efficiently simulates the evacuation process and obtains individual objectives, thereby deriving group evacuation time objective

f_{t}

, detour objective

f_{d}

; crowding objective

f_{c}

, injury objective

f_{i}

and fatality objective

f_{f}

.

f_{d}

,

f_{c}

,

f_{i}

and

f_{f}

are converted into penalty terms for

f_{t}

, and the improved EBA algorithm balances evacuation times across different exits to solve the multi-objective problem. This framework ensures precise statistical analysis of individual evacuation parameters while guaranteeing that each iteration moves closer to the optimal solution, enabling rapid convergence. Optimization results from a scenario with 2 floors, 42 rooms, and 1688 evacuees demonstrate that the algorithm can complete the simulation within 8–15 s, and the evacuation time reduced by 16 % while controlling detour and crowding duration in the scenario without fire, and the cumulative injury probability cut by 42 % in the fire scenario. This work bridges macroscopic efficiency and microscopic realism, offering a practical solution for dynamic evacuation planning.

紧急疏散计划需要平衡多个目标，如最小化时间、避免危险和确保公平性。传统的方法努力在宏观效率和微观现实主义之间取得平衡。本文提出了一种基于改进矩阵平移模型（MTM）和出口平衡算法（EBA）的多目标优化框架：改进的矩阵平移模型有效地模拟疏散过程并获得个体目标，从而得到群体疏散时间目标ft、绕行目标fd；拥挤目标fc，伤害目标fi，死亡目标ff。将fd、fc、fi、ff转换为ft的惩罚项，改进的EBA算法平衡不同出口的疏散时间，解决多目标问题。该框架确保对单个疏散参数进行精确的统计分析，同时保证每次迭代都更接近最佳解决方案，从而实现快速收敛。以2层、42间、1688人的疏散场景为例进行优化，结果表明，该算法可在8 ~ 15 s内完成模拟，在不发生火灾的情况下，在控制绕行和拥挤时间的情况下，疏散时间减少16%，在发生火灾的情况下，累计伤害概率减少42%。这项工作在宏观效率和微观真实性之间架起了桥梁，为动态疏散规划提供了实用的解决方案。

{"title":"Multi-objectives optimization of evacuation path based on improved matrix translation model and exit balance algorithm","authors":"Chun Sheng , Qize He , Liping Yu , Jiacheng Wang , Haoming Xie , Zhiming Fang , Zhongyi Huang","doi":"10.1016/j.simpat.2025.103201","DOIUrl":"10.1016/j.simpat.2025.103201","url":null,"abstract":"<div><div>Emergency evacuation planning requires balancing multiple objectives like minimizing time, avoiding hazards, and ensuring fairness. Traditional methods struggle to strike a balance between macroscopic efficiency and microscopic realism. This study proposes a new multi-objective optimization framework based on an improved Matrix Translation Model (MTM) and Exit Balance Algorithm (EBA): the improved MTM efficiently simulates the evacuation process and obtains individual objectives, thereby deriving group evacuation time objective <span><math><msub><mi>f</mi><mi>t</mi></msub></math></span>, detour objective <span><math><msub><mi>f</mi><mi>d</mi></msub></math></span>; crowding objective <span><math><msub><mi>f</mi><mi>c</mi></msub></math></span>, injury objective <span><math><msub><mi>f</mi><mi>i</mi></msub></math></span> and fatality objective <span><math><msub><mi>f</mi><mi>f</mi></msub></math></span>. <span><math><msub><mi>f</mi><mi>d</mi></msub></math></span>, <span><math><msub><mi>f</mi><mi>c</mi></msub></math></span>, <span><math><msub><mi>f</mi><mi>i</mi></msub></math></span> and <span><math><msub><mi>f</mi><mi>f</mi></msub></math></span> are converted into penalty terms for <span><math><msub><mi>f</mi><mi>t</mi></msub></math></span>, and the improved EBA algorithm balances evacuation times across different exits to solve the multi-objective problem. This framework ensures precise statistical analysis of individual evacuation parameters while guaranteeing that each iteration moves closer to the optimal solution, enabling rapid convergence. Optimization results from a scenario with 2 floors, 42 rooms, and 1688 evacuees demonstrate that the algorithm can complete the simulation within 8–15 s, and the evacuation time reduced by 16 % while controlling detour and crowding duration in the scenario without fire, and the cumulative injury probability cut by 42 % in the fire scenario. This work bridges macroscopic efficiency and microscopic realism, offering a practical solution for dynamic evacuation planning.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"145 ","pages":"Article 103201"},"PeriodicalIF":3.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144907974","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}

引用次数: 0

Optimization of passenger evacuation path in flood scenarios considering companion behaviors 考虑同伴行为的洪水情景下乘客疏散路径优化

IF 3.5 2区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Simulation Modelling Practice and Theory

Pub Date : 2025-12-01 Epub Date: 2025-10-01 DOI: 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.

地下轨道交通枢纽乘客应急疏散路径优化已成为城市防洪减灾系统面临的重要挑战。以往的疏散路径优化方法大多假设乘客作为个体独立移动，而不考虑社会联系群体的共同移动。针对这一问题，本文提出了一种考虑同伴行为的地铁车站洪水事件乘客疏散路径优化方法，并开发了一种创新的ETACO算法来求解路径优化模型。以实际地铁车站为例，利用PathFinder构建的车站仿真系统对乘客疏散过程进行仿真，验证了所提路径优化方案的有效性。引入改进的熵权法对疏散性能进行多维评价。结果表明：(1)同伴行为显著抑制疏散效率，组团疏散比例增大，导致疏散时间增加，平均移动速度降低；(2)提出的ETACO动态优化策略显著提高了路径优化模型解的收敛性能，与常规蚁群算法相比，平均最优目标改进率提高了16%，同时生成了更高效的路径优化策略；(3)越来越多的中断路段逐渐减缓了乘客的疏散；(4)疏散效果评价进一步验证了路径优化策略对车站安全性能的提升。该研究为复杂洪水场景下考虑同伴行为的疏散路径优化提供了更为现实的解决方案。

{"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":"2025-12-01","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}

引用次数: 0

A digital twin-based platform for testing and optimization of path planning algorithms 基于数字孪生的路径规划算法测试与优化平台

IF 3.5 2区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Simulation Modelling Practice and Theory

Pub Date : 2025-12-01 Epub Date: 2025-09-15 DOI: 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.

随着自动驾驶技术的快速发展，对路径规划算法的安全性、可靠性和优化效率的要求越来越高。然而，传统的物理测试通常是昂贵的，耗时的，并且受到环境不确定性的影响，使得很难有效地验证和优化这些算法。为了解决这一问题，本文提出了一种高保真的基于数字孪生的路径规划算法测试和优化平台。该平台通过构建反映现实世界的仿真环境，最大限度地减少了仿真与现实场景之间的差距，增强了路径规划的安全性和稳定性。该平台采用A*算法进行全局路径规划，采用定时弹性带法进行局部路径规划，采用bsamzier曲线进行优化，提高了路径的平滑性、可行性和安全性。此外，它还将车辆的物理特性（如速度、转向角度和驾驶模式）纳入参数优化过程，以确保模拟与现实环境之间的一致性。通过在仿真和物理环境中部署相同的路径规划算法进行了实验。结果表明，通过数字孪生平台优化的算法可以可靠地转移到现实场景中，提高了避障和整体路径规划的安全性。物理环境下规划的路径与仿真环境下的路径非常吻合，验证了数字孪生方法在路径规划测试和优化方面的有效性。该研究为自动驾驶道路规划的环境适应性、安全保障和工程部署提供了新的见解。

{"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":"2025-12-01","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}

引用次数: 0

Guest Editors’ Introduction on Cloud and Fog Computing for Real-Time IoT Applications 客座编辑介绍实时物联网应用中的云计算和雾计算

IF 3.5 2区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Simulation Modelling Practice and Theory

Pub Date : 2025-11-01 Epub Date: 2025-08-05 DOI: 10.1016/j.simpat.2025.103196

Helen D. Karatza

引用次数: 0

Simulation model and performance evaluation of automated valet parking technologies in parking lots 停车场自动代客泊车技术仿真模型及性能评价

IF 3.5 2区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Simulation Modelling Practice and Theory

Pub Date : 2025-11-01 Epub Date: 2025-07-06 DOI: 10.1016/j.simpat.2025.103175

Ning Ma , Angjun Tang , Jingxin Hai , Fang Yuan

Autonomous valet parking (AVP) is widely employed among parking lots and city logistics worldwide, expanding the applications of autonomous driving technologies. Auto companies are promoting three technology roadmaps to improve the implementation of AVP: AVP with autonomous driving system (AVP-ADS), AVP with Intelligent Infrastructure Systems (AVP-IS), and AVP with cooperative vehicle infrastructure systems (AVP-CVIS). Specifically, AVP-ADS can further be divided into LIDAR solution (AVP-ADS-LIDAR) and visual solution (AVP-ADS-VISUAL). This paper presents a simulation model to evaluate and compare the performances of AVP-CVIS, AVP-IS, AVP-ADS-LIDAR, AVP-ADS-VISUAL and Manual Parking (MP) in the real parking lot. The vehicle parking system is modeled as a discrete event simulation model, in which the controller module simulates driving behavior and defines the control logics of these three parking solutions. Extensive experiments are conducted and metrics are presented to evaluate the performance of these AVP technical solutions. The results indicate that AVP-CVIS exhibits more efficient parking performance. Management insights are provided to facilitate a more effective implementation of AVP.

自动代客泊车（AVP）在全球停车场和城市物流领域得到广泛应用，拓展了自动驾驶技术的应用领域。汽车公司正在推广三种技术路线图，以改善AVP的实施：AVP与自动驾驶系统（AVP- ads）， AVP与智能基础设施系统（AVP- is）， AVP与合作车辆基础设施系统（AVP- cvis）。具体来说，AVP-ADS可进一步分为激光雷达解决方案（AVP-ADS-LIDAR）和视觉解决方案（AVP-ADS- visual）。本文建立了仿真模型，对AVP-CVIS、AVP-IS、AVP-ADS-LIDAR、AVP-ADS-VISUAL和手动泊车（MP）在实际停车场中的性能进行了评价和比较。将车辆停车系统建模为离散事件仿真模型，其中控制器模块模拟驾驶行为，并定义这三种停车方案的控制逻辑。进行了大量的实验，并提出了指标来评估这些AVP技术解决方案的性能。结果表明，AVP-CVIS具有更高的停车效率。提供管理见解，以促进更有效地实施AVP。

{"title":"Simulation model and performance evaluation of automated valet parking technologies in parking lots","authors":"Ning Ma , Angjun Tang , Jingxin Hai , Fang Yuan","doi":"10.1016/j.simpat.2025.103175","DOIUrl":"10.1016/j.simpat.2025.103175","url":null,"abstract":"<div><div>Autonomous valet parking (AVP) is widely employed among parking lots and city logistics worldwide, expanding the applications of autonomous driving technologies. Auto companies are promoting three technology roadmaps to improve the implementation of AVP: AVP with autonomous driving system (AVP-ADS), AVP with Intelligent Infrastructure Systems (AVP-IS), and AVP with cooperative vehicle infrastructure systems (AVP-CVIS). Specifically, AVP-ADS can further be divided into LIDAR solution (AVP-ADS-LIDAR) and visual solution (AVP-ADS-VISUAL). This paper presents a simulation model to evaluate and compare the performances of AVP-CVIS, AVP-IS, AVP-ADS-LIDAR, AVP-ADS-VISUAL and Manual Parking (MP) in the real parking lot. The vehicle parking system is modeled as a discrete event simulation model, in which the controller module simulates driving behavior and defines the control logics of these three parking solutions. Extensive experiments are conducted and metrics are presented to evaluate the performance of these AVP technical solutions. The results indicate that AVP-CVIS exhibits more efficient parking performance. Management insights are provided to facilitate a more effective implementation of AVP.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"144 ","pages":"Article 103175"},"PeriodicalIF":3.5,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144571579","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}

引用次数: 0

CoFANN: A collaborative framework for accelerating DNN inference in drone-based agricultural monitoring systems CoFANN：在基于无人机的农业监测系统中加速DNN推理的协作框架

IF 3.5 2区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Simulation Modelling Practice and Theory

Pub Date : 2025-11-01 Epub Date: 2025-07-11 DOI: 10.1016/j.simpat.2025.103176

Nhu-Y Tran-Van, Kim-Hung Le

Plant leaf diseases pose a major threat to global agricultural productivity, causing substantial crop losses annually. While drone-based monitoring systems equipped with deep neural networks (DNNs) offer a promising solution for large-scale disease detection, their deployment is hindered by the computational limitations of IoT devices and the latency issues associated with cloud and edge computing. Existing collaborative inference approaches aim to mitigate end-to-end latency by offloading computation across devices. However, these methods often compromise model accuracy and add computing latency in generating inference strategies. To address these challenges, we present CoFANN, a novel collaborative framework to accelerate DNN inference in dynamic IoT environments. Our framework includes two key advances: a differentiable strategy search space with a gradient-based optimization algorithm for efficiently identify optimal partitioning strategies, and an adaptive model partitioning algorithm that effectively divides and allocates DNN components across computing devices based on their capabilities and network conditions. Experimental results in the plant disease dataset demonstrate that CoFANN reduces the total inference latency by up to 70% compared to device-only and 50% compared to edge-only approaches under varying network conditions, while maintaining comparable accuracy from 93.7% to 95.8%.

植物叶片病害对全球农业生产力构成重大威胁，每年造成大量作物损失。虽然配备深度神经网络（dnn）的无人机监测系统为大规模疾病检测提供了一个很有前途的解决方案，但它们的部署受到物联网设备的计算限制以及与云和边缘计算相关的延迟问题的阻碍。现有的协同推理方法旨在通过跨设备卸载计算来减轻端到端延迟。然而，这些方法往往会损害模型的准确性，并在生成推理策略时增加计算延迟。为了应对这些挑战，我们提出了CoFANN，这是一个新的协作框架，可以在动态物联网环境中加速DNN推理。我们的框架包括两个关键的进展：一个可微分的策略搜索空间，一个基于梯度的优化算法，用于有效地识别最优分区策略；一个自适应模型分区算法，根据计算设备的能力和网络条件，有效地在计算设备之间划分和分配DNN组件。植物病害数据集的实验结果表明，在不同的网络条件下，CoFANN比纯设备方法减少了70%的总推理延迟，比纯边缘方法减少了50%，同时保持了93.7%到95.8%的相当准确率。

{"title":"CoFANN: A collaborative framework for accelerating DNN inference in drone-based agricultural monitoring systems","authors":"Nhu-Y Tran-Van, Kim-Hung Le","doi":"10.1016/j.simpat.2025.103176","DOIUrl":"10.1016/j.simpat.2025.103176","url":null,"abstract":"<div><div>Plant leaf diseases pose a major threat to global agricultural productivity, causing substantial crop losses annually. While drone-based monitoring systems equipped with deep neural networks (DNNs) offer a promising solution for large-scale disease detection, their deployment is hindered by the computational limitations of IoT devices and the latency issues associated with cloud and edge computing. Existing collaborative inference approaches aim to mitigate end-to-end latency by offloading computation across devices. However, these methods often compromise model accuracy and add computing latency in generating inference strategies. To address these challenges, we present CoFANN, a novel collaborative framework to accelerate DNN inference in dynamic IoT environments. Our framework includes two key advances: a differentiable strategy search space with a gradient-based optimization algorithm for efficiently identify optimal partitioning strategies, and an adaptive model partitioning algorithm that effectively divides and allocates DNN components across computing devices based on their capabilities and network conditions. Experimental results in the plant disease dataset demonstrate that CoFANN reduces the total inference latency by up to 70% compared to device-only and 50% compared to edge-only approaches under varying network conditions, while maintaining comparable accuracy from 93.7% to 95.8%.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"144 ","pages":"Article 103176"},"PeriodicalIF":3.5,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144611623","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}

引用次数: 0

Preference-based D2D offloading in IoT-edge-cloud continuum 物联网边缘云连续体中基于偏好的D2D卸载

IF 3.5 2区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Simulation Modelling Practice and Theory

Pub Date : 2025-11-01 Epub Date: 2025-07-19 DOI: 10.1016/j.simpat.2025.103188

Haripriya Chaturvedi, Gaurav Baranwal

Computation tasks are offloaded to the edge server from the Internet of Things (IoT) and mobile devices due to their restricted computation capacity and battery life. However, the fixed capacity of edge servers makes serving multiple IoT and mobile devices challenging for edge servers. The collaborative architecture, i.e. Device-to-Device (D2D)-edge computing, plays a great role in solving this resource gap problem between the IoT and mobile devices and edge servers. The architecture allows the offloading from IoT and mobile devices with restricted resources to IoT and mobile devices with resource-rich resources instead of only edge servers. This collaborative architecture also provides solutions to other edge server-related problems like workload, congestion, bandwidth consumption, and energy consumption along with the utilization of idle resources of nearby IoT and mobile devices. This paper proposes a preference-based D2D offloading model in IoT-Edge-Cloud Continuum. The proposed business model introduces the concept of surcharges to increase the utilization of computing resources. Compared to state-of-the-art work, the model generates more social welfare, increases the number of allocations, and increases participants' utility. With the help of simulation work, we have shown that the work is effective and outperforms.

由于物联网（IoT）和移动设备的计算能力和电池寿命有限，计算任务被转移到边缘服务器。然而，边缘服务器的固定容量使得为多个物联网和移动设备提供服务对边缘服务器来说具有挑战性。协同架构，即设备到设备（Device-to-Device, D2D）边缘计算，在解决物联网与移动设备和边缘服务器之间的资源缺口问题方面发挥了重要作用。该架构允许从资源有限的物联网和移动设备卸载到资源丰富的物联网和移动设备，而不仅仅是边缘服务器。这种协作架构还为其他与边缘服务器相关的问题提供解决方案，如工作负载、拥塞、带宽消耗和能耗，以及附近物联网和移动设备的空闲资源的利用。本文提出了一种基于偏好的物联网边缘云连续体D2D卸载模型。提出的商业模式引入了附加费的概念，以提高计算资源的利用率。与最先进的工作相比，该模型产生了更多的社会福利，增加了分配的数量，并增加了参与者的效用。通过仿真工作，证明了该方法的有效性和优越性。

{"title":"Preference-based D2D offloading in IoT-edge-cloud continuum","authors":"Haripriya Chaturvedi, Gaurav Baranwal","doi":"10.1016/j.simpat.2025.103188","DOIUrl":"10.1016/j.simpat.2025.103188","url":null,"abstract":"<div><div>Computation tasks are offloaded to the edge server from the Internet of Things (IoT) and mobile devices due to their restricted computation capacity and battery life. However, the fixed capacity of edge servers makes serving multiple IoT and mobile devices challenging for edge servers. The collaborative architecture, i.e. Device-to-Device (D2D)-edge computing, plays a great role in solving this resource gap problem between the IoT and mobile devices and edge servers. The architecture allows the offloading from IoT and mobile devices with restricted resources to IoT and mobile devices with resource-rich resources instead of only edge servers. This collaborative architecture also provides solutions to other edge server-related problems like workload, congestion, bandwidth consumption, and energy consumption along with the utilization of idle resources of nearby IoT and mobile devices. This paper proposes a preference-based D2D offloading model in IoT-Edge-Cloud Continuum. The proposed business model introduces the concept of surcharges to increase the utilization of computing resources. Compared to state-of-the-art work, the model generates more social welfare, increases the number of allocations, and increases participants' utility. With the help of simulation work, we have shown that the work is effective and outperforms.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"144 ","pages":"Article 103188"},"PeriodicalIF":3.5,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144724918","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}

引用次数: 0

MBMRF: A modified bidirectional IPv6 multicast protocol with mixed upward and downward forwarding for TSCH-enabled WSANs MBMRF：一种改进的双向IPv6组播协议，用于使能tsch的wwsans，具有混合向上和向下转发

IF 3.5 2区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Simulation Modelling Practice and Theory

Pub Date : 2025-11-01 Epub Date: 2025-06-20 DOI: 10.1016/j.simpat.2025.103172

Eden Teshome Hunde , Shereen Ismail

Wireless Sensor and Actuator Networks (WSANs) consist of numerous embedded devices that collaborate to perform complex tasks, surpassing the capabilities of traditional wired networks. This collaboration is efficiently enabled through multicast protocols. While multicast protocols offer significant advantages for WSANs, many fail to meet certain performance requirements. To address these challenges, we propose the Modified Bidirectional Multicast RPL Forwarding (MBMRF) protocol.

This study tackles limitations in existing Internet Protocol version 6 (IPv6) multicast protocols, including the Routing Protocol for Low Power and Lossy Networks (RPL) and Bidirectional Multicast RPL Forwarding (BMRF). The proposed MBMRF protocol introduces a novel mixed upward and downward multicast packet forwarding mechanism optimized for multi-channel Time Slotted Channel Hopping (TSCH) networks. Furthermore, to ensure sufficient timeslot allocation for scheduling mixed up-and-down packet transmissions, the protocol incorporates a modified version of the Orchestra scheduling algorithm.

The proposed MBMRF protocol was implemented and simulated on Zolertia (Z1) motes using the Contiki operating system and evaluated against existing IPv6 multicast protocols, including Stateless Multicast RPL Forwarding (SMRF), Enhanced Stateless Multicast RPL Forwarding (ESMRF), and BMRF. Results show that MBMRF significantly reduces buffer overflow and network-wide energy consumption compared to SMRF, ESMRF, and BMRF, with only a marginal increase in memory usage.

无线传感器和执行器网络（wsan）由许多嵌入式设备组成，这些设备协作执行复杂任务，超越了传统有线网络的能力。这种协作通过多播协议有效地实现。虽然多播协议为无线局域网提供了显著的优势，但许多协议无法满足某些性能要求。为了解决这些挑战，我们提出了改进的双向多播RPL转发（MBMRF）协议。本研究解决了现有互联网协议版本6 （IPv6）多播协议的局限性，包括低功耗和有损网络路由协议（RPL）和双向多播RPL转发（BMRF）。提出的MBMRF协议引入了一种针对多通道时隙跳频（TSCH）网络进行优化的新型混合向上和向下多播分组转发机制。此外，为了确保有足够的时隙分配用于调度混合上下包传输，该协议包含了Orchestra调度算法的修改版本。提出的MBMRF协议在Zolertia （Z1）上使用Contiki操作系统进行了实现和仿真，并与现有的IPv6组播协议进行了比较，包括无状态组播RPL转发（SMRF）、增强无状态组播RPL转发（ESMRF）和BMRF。结果表明，与SMRF、ESMRF和BMRF相比，MBMRF显著减少了缓冲区溢出和网络范围的能量消耗，而内存使用仅略有增加。

{"title":"MBMRF: A modified bidirectional IPv6 multicast protocol with mixed upward and downward forwarding for TSCH-enabled WSANs","authors":"Eden Teshome Hunde , Shereen Ismail","doi":"10.1016/j.simpat.2025.103172","DOIUrl":"10.1016/j.simpat.2025.103172","url":null,"abstract":"<div><div>Wireless Sensor and Actuator Networks (WSANs) consist of numerous embedded devices that collaborate to perform complex tasks, surpassing the capabilities of traditional wired networks. This collaboration is efficiently enabled through multicast protocols. While multicast protocols offer significant advantages for WSANs, many fail to meet certain performance requirements. To address these challenges, we propose the Modified Bidirectional Multicast RPL Forwarding (MBMRF) protocol.</div><div>This study tackles limitations in existing Internet Protocol version 6 (IPv6) multicast protocols, including the Routing Protocol for Low Power and Lossy Networks (RPL) and Bidirectional Multicast RPL Forwarding (BMRF). The proposed MBMRF protocol introduces a novel mixed upward and downward multicast packet forwarding mechanism optimized for multi-channel Time Slotted Channel Hopping (TSCH) networks. Furthermore, to ensure sufficient timeslot allocation for scheduling mixed up-and-down packet transmissions, the protocol incorporates a modified version of the Orchestra scheduling algorithm.</div><div>The proposed MBMRF protocol was implemented and simulated on Zolertia (Z1) motes using the Contiki operating system and evaluated against existing IPv6 multicast protocols, including Stateless Multicast RPL Forwarding (SMRF), Enhanced Stateless Multicast RPL Forwarding (ESMRF), and BMRF. Results show that MBMRF significantly reduces buffer overflow and network-wide energy consumption compared to SMRF, ESMRF, and BMRF, with only a marginal increase in memory usage.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"144 ","pages":"Article 103172"},"PeriodicalIF":3.5,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144482452","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}

引用次数: 0