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Optimum design for smoke-control system in buildings considering robustness using CFD and Genetic Algorithms

机译:基于CFD和遗传算法的鲁棒性建筑烟雾控制系统的优化设计

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摘要

In fire-prevention designs for buildings, the major concerns are ensuring safe evacuation in the event of a fire and preventing the fire from spreading. Fire inevitably involves many uncertainties, such as the site of the fire source, whether or not a window is open, erroneous operation of prevention systems, and so on, which increases the risk leading to a large disaster. It is very important to consider these uncertainties to design a safe fire-prevention system. In this research, the optimum design method considering the robustness of smoke-control systems in buildings is developed using an approach that couples Computational Fluid Dynamics (CFD) with Genetic Algorithms (GA). The general optimum design and robust design for a vestibule pressurization smoke-control system in an office are conducted. As a result, although the airflow rate through the doorway of the vestibule, intended to ensure that smoke does not escape into the vestibule during evacuation, is a little lower than the general optimum design, the safety performance of the system is more stable in the robust case. The optimum design method proved to be useful in terms of the fire-prevention system design. The approach will be conducted for other urban safety design.
机译:在建筑物的防火设计中,主要的考虑是确保在发生火灾时安全疏散并防止火灾蔓延。火灾不可避免地涉及许多不确定性,例如火源的位置,是否打开窗户,预防系统的错误操作等,这增加了导致大灾难的风险。设计安全的防火系统时,考虑这些不确定因素非常重要。在这项研究中,使用将计算流体动力学(CFD)与遗传算法(GA)相结合的方法,开发了考虑建筑物中烟雾控制系统的鲁棒性的最佳设计方法。进行了办公室前庭增压烟气控制系统的总体优化设计和坚固设计。结果,尽管旨在确保烟尘在疏散过程中不会逸出到前庭中的流经前庭门口的气流速率比一般的最佳设计要低一些,但系统的安全性能在通风系统中更为稳定。稳健的案例。在防火系统设计方面,最佳设计方法被证明是有用的。该方法将用于其他城市安全设计。

著录项

  • 来源
    《Building and Environment》 |2009年第11期|2218-2227|共10页
  • 作者单位

    Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan;

    Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan;

    School of Architecture and Urban Planning, Huazhong University of Science & Technology, 1037 Luoyu Road, Hongshan-qu, Wuhan 430074, China;

    Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    smoke-control system; robust design; genetic algorithms; CFD; building design;

    机译:烟雾控制系统;坚固的设计;遗传算法;差价合约建筑设计;
  • 入库时间 2022-08-17 23:54:55

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