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Using microsimulation software to model large-scale evacuation scenarios. The case of Sangiiesa and the Yesa dam collapse

机译:利用微仿软件模拟大规模疏散方案。 Sangiiesa和Yesa坝崩溃的情况

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摘要

The use of computer models to analyse evacuation scenarios and human behaviours in emergencies has greatly increased due to their capabilities to simulate these processes. These models have been commonly applied to different types of infrastructures in isolation, and little is known about their use for large-scale evacuation. This paper explores the capabilities of micro-simulation tools for modelling large-scale evacuation, and also presents the development and application of a computer based large-scale modelling tool. A novel methodology is proposed here in which different sub-models are connected to represent the different levels of the evacuation scenario. The methodology has been applied to a real case study: a small town in Spain, Sangiiesa, which is in risk of flooding as a consequence of a potential collapse of the Yesa dam. The inputs used were taken from survey data, census data, plans of the town, data obtained from the emergency plan, data from other research studies (flooding models and acoustic models), and a literature review process on human behaviour in emergencies. The study was focused on the evacuation scenario at night (2:00 AM assuming the majority of residents are sleeping) as one worst-case scenarios. Four scenarios were developed in order to analyse the impact of (1) two pre evacuation time distributions identified for residential evacuation at night and (2) group behaviours (with and without) during the evacuation process. Results showed that the time needed to evacuate the whole town (between 33 and 44 min) is not sufficient, as in case of a dam collapse the water could reach Sangiiesa in about 23 min.
机译:由于它们的功能模拟这些过程,使用计算机模型来分析紧急情况下的疏散情景和人类行为的利用大大增加。这些型号通常应用于不同类型的基础设施,并且关于它们用于大规模疏散的用途很少。本文探讨了微型仿真工具的功能,用于建模大规模疏散,并提出了基于计算机的大型建模工具的开发和应用。这里提出了一种新的方法,其中不同的子模型连接以表示疏散方案的不同级别。该方法已应用于真正的案例研究:西班牙的一个小镇,Sangiiesa,这是由于YEA水坝潜在崩溃的影响而受到洪水的风险。所使用的投入从调查数据,人口普查数据,城镇计划,从紧急计划中获得的数据,来自其他研究研究(洪水模型和声学模型)的数据,以及紧急情况下的人类行为的文献综述过程。该研究专注于夜间疏散情景(凌晨2点,假设大多数居民正在睡觉)作为一个最坏的情况。开发了四种情况,以分析(1)夜间疏散的两个预疏散时间分布的影响,(2)疏散过程中的住宿疏散结果表明,疏散全镇(33至44分钟)所需的时间是不够的,因为如果坝崩塌,水可以在大约23分钟内达到Sangiiesa。

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  • 来源
    《Safety science》 |2018年第2018期|共18页
  • 作者

    Alvarez Pablo; Alonso Virginia;

  • 作者单位

    Univ Publ Navarra Dept Stat &

    OR Inst Smart Cities Los Magnolios Blg First Floor Campus Arrosadia Pamplona 31006 Spain;

    Imperial Coll London Dept Mech Engn London England;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 安全科学基础理论;
  • 关键词

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