RAPID: Post-Earthquake Fires in the March 2011 Japan Earthquake and Tsunami

这一快速反应研究奖助金(RAPID)提供资金，用于研究2011年3月日本地震的火灾相关方面，旨在提高对火灾发生地点、时间和方式的了解；火灾如何在社区蔓延；以及它们如何在工业设施中点燃和被扑灭。托霍库地震和海啸引发了345起火灾，比历史上任何一次地震都要多。相比之下，神户(1995年)、北岭(1994年)、圣费尔南多(1971年)和洛马·普里埃塔(1989年)分别记录了大约110起和36起。该项目将涉及三个主要步骤：(1)通过实地考察、与主要线人的访谈和二次数据来源收集与火灾有关的数据；(2)将数据汇编成易于使用的综合数据库，其中以一致的格式包括每一场火灾的所有数据和相关辅助数据；以及(3)通过描述性统计分析数据，将广义线性统计模型与点火数据拟合，并将对蔓延的观测结果与新的基于物理学的城市火灾蔓延模型估计的结果进行比较。该项目的PI和顾问在震后火灾研究方面拥有广泛的背景，包括对过去事件的实地调查以及点火、传播和灭火模型的开发。这项研究将在震后火灾的三个主要方面提供知识，包括通过社区蔓延的火灾和工业设施的火灾。它将提高对地震后点火的数量、地点、原因和时间的理解。这一现象本质上固有的随机性要求使用统计方法，这些方法高度依赖于现有数据的数量和质量。该项目将极大地改进现有的点火数据，其方法是：将以往地震中记录的观测次数增加近一倍；记录发生地面震动足以引发点火但并未引发点火的地区，从而大大提高我们预测点火的能力；提供比现有数据更一致和全面的数据；提供关于地面震动和海啸引发点火的数据。将进行统计建模，以确定数据对点火发生的地点、时间和原因提出了什么建议，并改进了对未来点火的预测。通过收集数据，可以与新兴的基于物理的新一代城市火灾模型进行更有意义的比较，从而增强对火灾通过社区蔓延的理解。这些模型可能很强大，但它们需要更多地与真实事件进行比较，以改进它们并建立它们的可信度。最后，该项目承诺提供新的见解，了解地震后火灾是如何在工业设施中特别开始、蔓延和被扑灭的。我们将研究现有的消防安全系统在面对大地震极端共同原因失效模式时的表现。对震后点火和城市火灾蔓延的更多知识将直接融入到更好的震后火灾模型的开发中。然后，这些模型可以被集成到区域地震损失模型中，如HAZUS-MH，这些模型通过支持长期应急规划、城市规划和损失估计，对社会具有巨大的示范价值。研究结果将被整合到PIS研究生风险分析课程中，并将在专业会议上展示。一名研究生研究助理将参与该项目的所有方面，这项研究将成为他关于地震后火灾模型的论文的组成部分。

This Grant for Rapid Response Research (RAPID) award provides funds to study the fire-related aspects of the March 2011 Japan earthquake with the aims to improve understanding of where, when, and how fires ignite; how fires spread through a neighborhood; and how they ignite and are suppressed in industrial facilities. The Tôhoku earthquake and tsunami caused 345 fires more recorded fires than any other earthquake in history. By comparison, there were about 110 recorded in Kobe (1995), 110 in Northridge (1994), 128 in San Fernando (1971), and 36 in Loma Prieta (1989). This project will involve three main steps: (1) collecting data on the fire-related aspects of the event through site visits, interviews with key informants, and secondary data sources; (2) compiling the data into easily usable, comprehensive databases that includes all data on each fire and relevant auxiliary data in a consistent format; and (3) analyzing the data through descriptive statistics, fitting generalized linear statistical models to the ignition data, and comparing observations of spread to that estimated by a new physics-based urban fire spread model. The PI and consultant on the project have extensive background in the study of post-earthquake fires, including field investigation of past events and development of models of ignitions, spread, and suppression. This research will contribute knowledge on three main aspects of post-earthquake fires ignitions, spread through a neighborhood, and fires in industrial facilities. It will improve understanding of the number, locations, causes, and timing of post-earthquake ignitions. The substantial inherent randomness in the phenomenon requires use of statistical approaches that are highly dependent on the amount and quality of available data. This project will greatly improve the available ignition data by almost doubling the number of observations documented in previous earthquakes; documenting areas in which ground shaking was strong enough to induce ignitions but did not, substantially improving our ability to forecast ignitions; by providing more consistent and comprehensive data than currently available; and by providing data on both ground shaking and tsunami-induced ignitions. Statistical modeling will be conducted to determine what the data suggests about where, when, why ignitions occur and to improve forecasting of ignitions in the future. Understanding of fire spread through a neighborhood will be enhanced by collection of data that allows more meaningful comparison with the emerging new generation of physics-based urban fire models. These models are potentially powerful but they need more comparisons to real events to improve them and build their credibility. Finally, the project promises to provide new insights into how post-earthquake fires start, spread, and are suppressed in industrial facilities specifically. We will examine how the fire safety systems in place perform in the face of extreme common cause failure mode of a major earthquake.The improved knowledge of post-earthquake ignitions and urban fire spread will be directly integrated into the development of better post-earthquake fire models. Those models can then in turn be integrated into regional earthquake loss models like HAZUS-MH, which have great demonstrated value to society by supporting long-term emergency response planning, urban planning, and loss estimation. The research results will be integrated into the PIs graduate Risk Analysis course and will be presented at professional conferences. A graduate student research assistant will participate in all aspects of the project and the research will form an integral part of his dissertation on post-earthquake fire modeling.