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

Forge4Flame: An intuitive dashboard for designing GPU agent-based models to simulate infectious disease spread Forge4Flame：一个直观的仪表板，用于设计基于GPU代理的模型来模拟传染病的传播

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

Simulation Modelling Practice and Theory

Pub Date : 2025-09-12 DOI: 10.1016/j.simpat.2025.103205

Daniele Baccega , Irene Terrone , Peter Heywood , Robert Chisholm , Paul Richmond , Sandro Gepiro Contaldo , Lorenzo Bosio , Simone Pernice , Marco Beccuti

Agent-based models are computational models that simulate the dynamic interactions, behaviours, and communication protocols among agents in a shared environment. The use of such models in the field of epidemiology has attracted much attention, allowing the evaluation of the effectiveness of possible interventions and vaccination strategies. However, setting up these environments typically requires a manual and technical process that can be both time-consuming and complex. To address this challenge, we introduce Forge4Flame, a novel and user-friendly dashboard that simplifies the definition of agent-based models for FLAME GPU 2. Our goal is to make this modelling framework more accessible to a broader audience of researchers and public health professionals. Specifically, the tool streamlines model design, execution, and analysis by automatically generating the required FLAME GPU 2 code and incorporating valuable visualisation and post-processing features. Moreover, the integration of two different levels of population model was explored, allowing a detailed analysis of disease dynamics. This shows the tool’s potential to enhance both the accessibility and scalability of agent-based models through Docker and Slurm for efficient distributed computing on high-performance computing systems. Finally, the effectiveness of this tool is demonstrated through a case study that investigates the COVID-19 emergency in a generic Italian middle school.

基于代理的模型是模拟共享环境中代理之间的动态交互、行为和通信协议的计算模型。这种模型在流行病学领域的使用引起了很大的注意，可以对可能的干预措施和疫苗接种战略的有效性进行评估。然而，设置这些环境通常需要一个人工和技术过程，既耗时又复杂。为了应对这一挑战，我们引入了Forge4Flame，这是一个新颖且用户友好的仪表板，它简化了FLAME GPU 2基于代理的模型的定义。我们的目标是使更广泛的研究人员和公共卫生专业人员更容易使用这个建模框架。具体来说，该工具通过自动生成所需的FLAME GPU 2代码并结合有价值的可视化和后处理功能，简化了模型设计，执行和分析。此外，还探索了两个不同层次的种群模型的整合，从而可以详细分析疾病动态。这表明该工具有潜力通过Docker和Slurm增强基于代理的模型的可访问性和可伸缩性，从而在高性能计算系统上实现高效的分布式计算。最后，通过调查意大利一所普通中学的COVID-19紧急情况的案例研究，证明了该工具的有效性。

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引用次数: 0

Peridynamics modeling of underground borehole instability: Collapse mechanism and stabilization strategy 地下钻孔失稳的周动力学建模：坍塌机理与稳定策略

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

Simulation Modelling Practice and Theory

Pub Date : 2025-09-09 DOI: 10.1016/j.simpat.2025.103203

Haoran Xu , Yongsheng Liu , Fei Li , Shuaipeng Wang , Shangyu Yang

Borehole instability is a critical challenge that affects safety and efficiency in deep drilling. Classical continuum mechanics struggles to accurately capture the discontinuous processes of crack initiation and propagation around boreholes. This paper develops and validates a nonlocal borehole damage model based on peridynamics. The borehole collapse mechanism is explored, and the regulatory role of drilling fluid pressure in maintaining borehole stability is evaluated. The results show that borehole collapse initiates along the direction of minimum horizontal pressure, characterized by a crescent-shaped shear failure accompanied by tensile fractures. The borehole eventually evolves into a butterfly-shaped damage pattern with a central fragmented zone. Increasing the elastic modulus of the surrounding rock and reducing the borehole radius effectively inhibits damage propagation. As the elastic modulus increases from 6 to 30 GPa, the areas of the collapse zones are reduced by 87.50%, indicating a substantial enhancement in the material’s resistance to both microcrack initiation and macroscopic instability. Low-modulus rocks are more prone to form continuous shear-fracture zones. In contrast, the horizontal pressure difference emerges as the primary driver of damage evolution; once it exceeds 30 MPa, the crack growth resistance deteriorates rapidly, leading to accelerated crack coalescence and the formation of a connected fracture network. An optimal drilling fluid pressure window can suppress up to 85.05% of the damaged area. However, excessive pressure may induce radial tensile fractures. The findings revealed the mechanisms of borehole collapse and confirmed the superiority of the peridynamics model in predicting borehole instability. This study provides theoretical insight and methodological support for stability control in deep drilling operations.

井眼失稳是影响深井钻井安全性和效率的关键问题。经典连续介质力学难以准确地捕捉井眼周围裂纹萌生和扩展的不连续过程。本文建立并验证了基于周动力学的非局部井眼损伤模型。探讨了井眼坍塌机理，评价了钻井液压力对维持井眼稳定性的调节作用。结果表明：井眼塌陷沿最小水平压力方向开始，以月牙形剪切破坏伴张性破裂为特征；钻孔最终演变成蝴蝶形的破坏模式，中心有破碎带。增加围岩弹性模量和减小钻孔半径可以有效抑制损伤的传播。当弹性模量从6 GPa增加到30 GPa时，坍塌区面积减少了87.50%，表明材料的抗微裂纹萌生和抗宏观失稳能力都有了显著增强。低模量岩石更容易形成连续剪切破碎带。水平压差是损伤演化的主要驱动力；一旦超过30 MPa，裂纹扩展阻力迅速恶化，导致裂纹加速合并，形成连通的裂缝网络。最佳钻井液压力窗可抑制85.05%的损伤面积。然而，过大的压力可能诱发径向张性骨折。研究结果揭示了井眼坍塌的机理，证实了周动力学模型在预测井眼失稳方面的优越性。该研究为深部钻井作业的稳定性控制提供了理论见解和方法支持。

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引用次数: 0

From pedestrian simulation to security screening checkpoint planning: Simulation-enhanced optimization method 从行人模拟到安检检查站规划：仿真增强优化方法

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

Simulation Modelling Practice and Theory

Pub Date : 2025-09-02 DOI: 10.1016/j.simpat.2025.103202

Xiaoting Yuan , Tieqiao Tang , Tao Wang , Nikolai Bode

Modeling pedestrian flow through security checkpoints is critical for efficient airport operations. In this study, we develop a discrete event simulation model to describe queue dynamics at security screening checkpoints. Focusing on queue lengths, waiting times, and passenger arrival rates, we investigate how dynamically changing the number of open checkpoints affects system performance. Building on these insights, we formulate a mixed-integer linear programming model that incorporates system performance states derived from simulations to optimize checkpoint planning over time. Finally, we validate our approach through simulations based on arrival data from Guangzhou Baiyun International Airport, China. Compared with a stand-alone mixed-integer linear programming formulation, the simulation-enhanced method achieves fewer total and peak lanes while meeting the same service-level targets. By providing an accurate representation of pedestrian flows, this research offers airports a practical decision tool for dynamic resource allocation and improved checkpoint performance.

模拟通过安检点的人流对机场的高效运营至关重要。在这项研究中，我们开发了一个离散事件模拟模型来描述安全检查检查点的队列动态。我们关注队列长度、等待时间和乘客到达率，研究动态改变开放检查点的数量如何影响系统性能。在这些见解的基础上，我们制定了一个混合整数线性规划模型，该模型结合了从模拟中获得的系统性能状态，以优化检查点规划。最后，我们通过广州白云国际机场的到达数据进行了仿真验证。与独立的混合整数线性规划公式相比，仿真增强方法在满足相同服务水平目标的情况下实现了更少的总车道和峰值车道。通过提供行人流量的准确表示，本研究为机场动态资源分配和改善检查站性能提供了实用的决策工具。

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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 : 2025-08-30 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。

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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 : 2025-08-23 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":"2025-08-23","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

Numerical study of presplit blasting in rock masses with a closed and filled joint using coupled finite-discrete element method 采用有限-离散元耦合方法对封闭充填岩体预裂爆破进行数值研究

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

Simulation Modelling Practice and Theory

Pub Date : 2025-08-22 DOI: 10.1016/j.simpat.2025.103199

Mansour Sharafisafa , Zeinab Aliabadian , Luming Shen

The optimized performance of rock blasting heavily relies on the presence of discontinuities. These geological features play an important role in wave and fracture propagation in rocks and can be considered a barrier against the blast wave and fracture propagation. Blasting has many applications, but one of the important aspects is presplitting blasting, in which light blasts are operated to create a continuous plane prior to the main blasting. The goal of this particular blast operation is mainly to inhibit damage to the reserved rock. In the presplit blastingin underground rocks, the magnitude of the ground in-situ stresses plays a vital role and dominates the performance of the presplitting, which can lead to an unsuccessful detonation if mismeasured. There is much evidence that, in many cases, the joints are not closed but instead are filled with a different material. Thus, in this study, the performance of presplit blasting in a rock domain with a closed or filled joint is analysed using the combined finite-discrete element method (FDEM) with a gas in fracture logic. First, the applicability of the method is verified against some experiments. Once verified, 2D FDEM models are analysed to evaluate the influence of an inclined closed or filled flaw on blast-induced fracture development. The FDEM results confirm the strong impact of joint inclination angle on the fragmentation degree. Furthermore, it is shown that the performance of the presplit blasting is remarkably dependent on the magnitude of ground in-situ stresses. The results also show that the filling material and its orientation angle with respect to the maximum principal stress have an imposing effect on the success of the presplitting blasting. Also, it is revealed that in the presplit blasting with filled joint, the failure of the filling is a mode failure, while the connecting fractures are of tensile mode.

岩体爆破的优化性能在很大程度上依赖于不连续面的存在。这些地质特征对岩石中的波和裂缝传播起着重要作用，可以被认为是阻止爆炸波和裂缝传播的屏障。爆破有许多应用，其中一个重要的方面是预裂爆破，在主爆破之前进行轻爆以形成一个连续的平面。这种特殊爆破作业的目的主要是抑制对储备岩石的破坏。在地下岩石预裂爆破中，地应力的大小起着至关重要的作用，它决定着预裂爆破的性能，如果测量不当可能导致爆轰不成功。有很多证据表明，在许多情况下，关节并没有闭合，而是被不同的材料填充。因此，在本研究中，采用结合裂隙内气体逻辑的有限-离散单元法（FDEM）对具有闭合或充填节理的岩石域中的预裂爆破性能进行了分析。首先，通过实验验证了该方法的适用性。验证后，分析二维FDEM模型，以评估倾斜闭合或填充缺陷对爆致裂缝发育的影响。FDEM结果证实节理倾角对破碎程度的影响较大。此外，研究表明，预裂爆破的效果与地应力的大小有显著的关系。结果还表明，充填材料及其相对于最大主应力的取向角对预裂爆破的成功与否有重要影响。结果表明，在填缝预裂爆破中，填缝破坏为模态破坏，连接裂缝为拉伸破坏。

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引用次数: 0

Failure mechanisms of block-flexural toppling: An extensive numerical study 块体弯曲倾倒破坏机制：广泛的数值研究

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

Simulation Modelling Practice and Theory

Pub Date : 2025-08-20 DOI: 10.1016/j.simpat.2025.103198

Mohammad Seyfaddini , Mojtaba Bahaaddini , Saeed Karimi Nasab , Mohammad Hossein Khosravi , Hossein Masoumi

Toppling failure is a common instability in natural rock slopes. The common approaches for investigating toppling failure mechanisms are physical and analytical methods, which encounter special difficulties for the test set-up and limitation in the number of physical experiments as well as complicated governing equations in analytical models. Recent advances in numerical modeling, particularly the discrete element method (DEM), have opened new avenues for understanding the complex mechanisms behind toppling failure. In this work, the ability of numerical method in reproducing toppling mechanism was first investigated through an extensive comparative analysis with physical and analytical methods. Hence, the validated numerical models were employed to statistically examine the individual and interactive effects of different parameters on the block-flexural toppling failure mechanism using the response surface methodology (RSM). To explore the statistical significance of effective parameters, the central composite design (CCD) was employed. The analysis revealed that aspect ratio constitutes the most influential parameter governing block-flexural toppling failure, while block unit weight found to be the least significant factor. Also, it was found out that the block unit weight and the block aspect ratio can cause a decrease in the failure initiation angle. It was concluded that an increase in the joint friction angle and block tensile strength can increase the stability of slope where the joint friction angle can change the shape and location of failure surface. Finally, evaluation of interaction effects showed that the impact of block tensile strength on block-flexural failure increases with an increase in block slenderness.

倾倒破坏是天然岩质边坡中常见的失稳形式。研究倾倒破坏机制的常用方法是物理方法和分析方法，但由于物理实验数量的限制以及分析模型中控制方程的复杂性，这些方法在试验设置上遇到了特殊的困难。数值模拟的最新进展，特别是离散元法（DEM），为理解倾覆破坏背后的复杂机制开辟了新的途径。在这项工作中，通过与物理方法和分析方法的广泛对比分析，首次研究了数值方法在再现倾倒机理方面的能力。在此基础上，采用响应面法（RSM）统计分析了不同参数对块体弯曲倾倒破坏机制的个体效应和交互效应。为探讨有效参数的统计学意义，采用中心组合设计（CCD）。分析表明，长径比是影响块体弯曲倾倒破坏的最重要参数，而块体单元重量是影响最小的因素。同时，还发现砌块单元重量和砌块长径比都能减小破坏起裂角。结果表明，节理摩擦角的增大和块体抗拉强度的增大均能提高边坡的稳定性，其中节理摩擦角会改变破坏面的形状和位置。最后，相互作用效应的评价表明，块体抗拉强度对块体弯曲破坏的影响随着块体长细比的增加而增加。

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引用次数: 0

A graph-based laser path solver algorithm for virtual reality laboratory simulations 一种基于图形的虚拟现实实验室仿真激光路径求解算法

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

Simulation Modelling Practice and Theory

Pub Date : 2025-08-09 DOI: 10.1016/j.simpat.2025.103194

Andreas Müller , Stefan Mueller , Tobias Brixner , Sebastian von Mammen

femtoPro is an interactive virtual reality (VR) laser laboratory balancing the contrasting challenges of accuracy and computational efficiency in optics simulations. It can simulate linear and nonlinear optical phenomena in real time, a task that pushes the boundaries of current consumer hardware. This paper details the concept, implementation, and evaluation of a dynamic graph-based solution tailored to the specific requirements and challenges of the simulation. Resource usage is optimized through a selective updating strategy that identifies and preserves laser paths unchanged between simulation frames, eliminating the need for unnecessary recalculations. Benchmarking of real-world scenarios confirms that our approach delivers a smooth user experience, even on mobile VR platforms with limited computing power. The methodologies, solutions and insights outlined in this paper may be applicable to other interactive, dynamic graph-based real-time simulations.

femtoPro是一个交互式虚拟现实（VR）激光实验室，平衡了光学模拟中精度和计算效率的对比挑战。它可以实时模拟线性和非线性光学现象，这一任务突破了当前消费类硬件的极限。本文详细介绍了针对仿真的特定需求和挑战量身定制的基于动态图的解决方案的概念、实现和评估。通过选择性更新策略来优化资源使用，该策略可以识别和保持模拟帧之间的激光路径不变，从而消除不必要的重新计算的需要。现实场景的基准测试证实，我们的方法提供了流畅的用户体验，即使在计算能力有限的移动VR平台上也是如此。本文概述的方法、解决方案和见解可能适用于其他交互式、动态的基于图形的实时仿真。

引用次数: 0

Modeling proactive effects of connected autonomous vehicles on urban traffic in adverse weather 在恶劣天气条件下，联网自动驾驶汽车对城市交通的主动影响建模

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

Simulation Modelling Practice and Theory

Pub Date : 2025-08-07 DOI: 10.1016/j.simpat.2025.103193

Yueting Wang, Zhiqun Hu, Zhaoming Lu, Qinrui An, Xiangming Wen

Adverse weather conditions significantly degrade the environmental perception capabilities of autonomous vehicles (AVs), thereby compromising both traffic safety and operational efficiency. Connected autonomous vehicles (CAVs), leveraging vehicle-to-vehicle (V2V) communication technology, have the potential to mitigate these challenges through cooperative perception mechanisms. Before large-scale deployment of CAVs, it is essential to understand the significant impacts of CAV application on urban traffic characteristics, especially in adverse weather conditions. However, building a realistic simulation for CAV traffic system in adverse weather conditions can be challenging. On the one hand, adverse weather, with chaotic atmosphere behaviors and rapid complex interactions with electromagnetic waves, imposes unpredictable effects on automotive sensors. On the other hand, the dynamic interplay between sensor physics, communication networks, and multi-agent data fusion contributes to uncertainty in CAV driving decisions. To address the challenges, this paper firstly introduces radar theories and builds a physics-based model to realistically simulate weather impacts on sensors at scale. Then, a novel simulation model is proposed for CAV traffic system in rainy conditions, which includes weather-related degraded sensor, unreliable V2V communication, and cooperative perception-based decision making module. Finally, simulations in different levels of rainy conditions are conducted based on a large-scale road network (in the City of Luxembourg) with real traffic data. Results show that CAVs are more effective in improving traffic safety and efficiency under challenging weather conditions. The limits of CAVs in adverse weather are also discussed.

恶劣的天气条件会大大降低自动驾驶汽车的环境感知能力，从而影响交通安全和运营效率。利用车对车（V2V）通信技术的联网自动驾驶汽车（cav）有可能通过合作感知机制缓解这些挑战。在大规模部署自动驾驶汽车之前，有必要了解自动驾驶汽车的应用对城市交通特性的重大影响，特别是在恶劣天气条件下。然而，在恶劣天气条件下建立CAV交通系统的真实模拟可能具有挑战性。一方面，恶劣天气具有混乱的大气行为和与电磁波快速复杂的相互作用，对汽车传感器产生不可预测的影响。另一方面，传感器物理、通信网络和多智能体数据融合之间的动态相互作用增加了自动驾驶汽车驾驶决策的不确定性。为了应对这些挑战，本文首先介绍了雷达理论，并建立了一个基于物理的模型来真实地模拟天气对传感器的影响。在此基础上，提出了一种基于天气相关退化传感器、不可靠V2V通信和基于协同感知的决策模块的雨天CAV交通系统仿真模型。最后，基于大型道路网络（在卢森堡市）和真实交通数据，在不同程度的降雨条件下进行了模拟。结果表明，在恶劣天气条件下，自动驾驶汽车在提高交通安全和效率方面更为有效。本文还讨论了自动驾驶汽车在恶劣天气条件下的局限性。

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引用次数: 0

A flexible hybrid simulation model for hospital capacity management through multimodal transfers of COVID-19 patients 基于COVID-19患者多式联运的医院容量管理灵活混合仿真模型

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

Simulation Modelling Practice and Theory

Pub Date : 2025-08-06 DOI: 10.1016/j.simpat.2025.103192

Sven Watzinger , David Olave-Rojas , Janina Bathe , Hanna-Joy Renner , Jan Wnent , Leonie Hannappel , Jan-Thorsten Gräsner , Stefan Nickel

The global pandemic provoked by the SARS-CoV-2 virus in recent years has presented new challenges to health care systems. One major issue is the risk of overloading hospital capacities during regional surges, especially in intensive care units. Strategic patient transfers between regions with different loads can mitigate this risk. To coordinate such nationwide strategic patient transfers in Germany, the clover-leaf system was initiated. The transfer decision consists of allocating patients to destination hospitals as well as scheduling patients on transport vehicles which includes the possibility of combining different modes of transport, for instance ground-based with an ambulance and air-based with a helicopter, during one transfer. As potentially conflicting objective dimensions the impact of the transfers on the transferred patients and the impact on loads in intensive care units have to be considered. To support the decision makers a hybrid simulation model combining agent-based and discrete-event modeling is developed by an interdisciplinary team of medical and operations research experts. The main contribution of the simulation model is the modeling of multimodal patient transfers which to the best of our knowledge has not been considered in the existing literature. Next to the simulation model, several transfer strategies in the form of decision rules are proposed. These transfer strategies are used to benchmark transfer plans created by the decision makers in a test scenario based on nationwide data of the German health care system. Using simulation allowed to evaluate the transfer plans in different objective dimensions and informed the decision-making process.

近年来，由SARS-CoV-2病毒引发的全球大流行给卫生保健系统带来了新的挑战。一个主要问题是，在区域激增期间，医院的能力可能会超载，特别是在重症监护病房。有策略地在不同负荷地区之间转移病人可以减轻这种风险。为了在德国协调这种全国性的战略性病人转移，三叶草系统被启动。转移决定包括将病人分配到目的地医院以及安排病人乘坐运输车辆，其中包括在一次转移期间结合不同运输方式的可能性，例如地面与救护车和空中与直升机。作为潜在冲突的客观维度，转移对转移患者的影响和对重症监护病房负荷的影响必须加以考虑。为了支持决策者，由医学和运筹学专家组成的跨学科团队开发了基于智能体和离散事件建模相结合的混合仿真模型。模拟模型的主要贡献是多模式患者转移的建模，据我们所知，在现有文献中尚未考虑到这一点。在仿真模型的基础上，以决策规则的形式提出了几种迁移策略。这些转移策略用于在基于德国医疗保健系统全国数据的测试场景中对决策者制定的转移计划进行基准测试。通过仿真可以在不同的客观维度上对迁移方案进行评估，为决策过程提供信息。

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