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A particle swarm optimization based multi-agent stochastic evacuation simulation model.

机译:基于粒子群优化的多主体随机疏散仿真模型。

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摘要

How do we evaluate the evacuation efficiency of a building floor plan or an aircraft cabin? The most direct approach is to arrange evacuation drills for the evaluation purpose. However, several disadvantages have been associated with these drills. Firstly, these drills are usually considered dangerous, especially when a large number of participants are involved. Secondly, these drills usually require relatively long time and a large amount of money to prepare. Furthermore, the cost increases dramatically when the number of participants increases or when the drill fails and a new one needs to be redesigned. Lastly but not least, it is typically the case that only limited number of trials can be performed in each evacuation drill due to the time-consuming planning and enormous cost. Therefore, the trial results could easily be biased if the number of trials is not sufficient. The other approach to guarantee the evacuation efficiency is to keep floor plan designs in compliance with relevant prescriptive Building Code or Aircraft Safety Code. However, these codes are typically conservative in nature therefore hinder the innovation of floor plan designs. Performance-Based Code, on the other hand, allows engineers to design fire protection individually for each new building or aircraft using alternative methods other than prescriptive ones, with a maximum design freedom. To evaluate the evacuation efficiency conveniently and efficiently in performance-based design, computer simulation models, besides being cost efficient and eliminating the need of involving real participants, can perform repeated tests fairly easily with a built-in stochastic feature that enables a reasonable representation of appropriate behaviors across a spectrum of situations.;This dissertation research introduces a Particle Swarm Optimization (PSO) based multiagent stochastic evacuation simulation model incorporating fire hazards and critical human behaviors. The model has two sub-models: Vacate and VacateAir. The former one is for building evacuation simulation and the latter one is for aircraft evacuation simulation. The model utilizes a modified PSO Algorithm as a path finding algorithm that directs evacuees to the final exit as well as dynamically adjusts evacuees' direction according to fire hazards and crowd movements. The fire data are pre-calculated in Fire Dynamics Simulator (FDS) and imported in the model for the use of conducting Human Tenability Analysis (HTA). Critical human behaviors that identified in building and aircraft evacuation are simulated and their impact on the evacuation efficiency is evaluated.;There are numerous advantages in applying modified PSO as the path finding algorithm. Application of this strategy overcomes several limitations of existing evacuation models, e.g. eliminating the need to divide the entire floor plan layout into grids and nodes therefore saving substantial computational expense and enabling a simulation of the continuous movement of evacuees, which outperforms the jagged and often unrealistic movement generated by traditional grid-based path finding algorithms. With these improved features and validations against published evacuation experimental data, Vacate (for building evacuation) and VacateAir (for aircraft evacuation) can help designers and fire protection engineers conduct the performance-based design of buildings and aircraft more conveniently. The parametric study of the effects of physical factors such as exit width, aisle width, seat pitch and evacuation motivation (competitive or cooperative), on evacuation efficiency not only provides valuable information to building and aircraft designers, but also opens a potentially new avenue in the future research work on the System-of-Systems (SoS) design approach by coupling the evacuation system with aerodynamic system, weight system, and airline resource allocation system.
机译:我们如何评估建筑物平面图或机舱的疏散效率?最直接的方法是安排疏散演习以进行评估。但是,这些钻头有几个缺点。首先,这些演习通常被认为是危险的,特别是当涉及大量参与者时。其次,这些演习通常需要相对较长的时间和大量的准备资金。此外,当参与者人数增加或演习失败并且需要重新设计新的演习时,成本将急剧增加。最后但并非最不重要的是,由于费时的计划和巨大的成本,通常只能在每个疏散演练中进行有限数量的试验。因此,如果试验数量不足,则试验结果很容易产生偏差。保证疏散效率的另一种方法是使楼层平面图设计符合相关的规定性建筑规范或飞机安全规范。但是,这些规范通常本质上是保守的,因此阻碍了平面图设计的创新。另一方面,基于性能的规范允许工程师使用规定性以外的替代方法,为每座新建筑物或飞机分别设计防火设计,并具有最大的设计自由度。为了在基于性能的设计中方便,高效地评估疏散效率,计算机仿真模型不仅具有成本效益,而且消除了让真正的参与者参与的需求,还可以通过内置的随机功能相当容易地执行重复测试,从而能够合理地表示本论文研究引入了一种基于粒子群优化(PSO)的多代理随机疏散模拟模型,该模型包含火灾隐患和严重的人类行为。该模型具有两个子模型:Vacate和VacateAir。前者用于建筑物疏散模拟,而后者用于飞机疏散模拟。该模型利用改进的PSO算法作为路径查找算法,该算法将撤离人员引导到最终出口,并根据火灾隐患和人群移动动态调整撤离人员的方向。火灾数据在火灾动态模拟器(FDS)中进行了预先计算,并导入到模型中,以进行人员可维持性分析(HTA)。模拟了在建筑物和飞机撤离中识别出的关键人类行为,并评估了它们对撤离效率的影响。;将改进的PSO用作寻路算法具有许多优势。该策略的应用克服了现有疏散模型的一些限制,例如消除了将整个平面图布局划分为网格和节点的需要,从而节省了可观的计算费用,并能够模拟撤离人员的连续运动,这胜过了传统的基于网格的路径查找算法产生的锯齿状且通常不切实际的运动。通过这些改进的功能和针对已发布的疏散实验数据的验证,Vacate(用于建筑物疏散)和VacateAir(用于飞机疏散)可以帮助设计人员和消防工程师更方便地进行基于性能的建筑物和飞机设计。对诸如出口宽度,过道宽度,座椅间距和疏散动机(竞争性或合作性)等物理因素对疏散效率的影响进行参数研究,不仅为建筑物和飞机设计人员提供了有价值的信息,而且还为飞机和飞机设计人员提供了潜在的新途径。通过将疏散系统与空气动力学系统,重量系统和航空公司资源分配系统结合起来,对系统设计(SoS)设计方法的未来研究工作。

著录项

  • 作者

    Xue, Zhendan.;

  • 作者单位

    State University of New York at Buffalo.;

  • 授予单位 State University of New York at Buffalo.;
  • 学科 Engineering Mechanical.;Engineering Robotics.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 207 p.
  • 总页数 207
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 机械、仪表工业;
  • 关键词

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