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

快速反应研究基金（Rapid）为研究2011年3月日本地震的火灾相关方面提供资金，旨在提高对火灾在何时何地以及如何点燃的理解；火灾如何在社区蔓延；以及它们是如何在工业设施中被点燃和抑制的。Tôhoku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，1995年在神户有110只，1994年在北岭有110只，1971年在圣费尔南多有128只，1989年在洛马普里塔有36只。该项目将包括三个主要步骤：(1)通过实地考察、采访主要举报人和二手数据来源，收集与火灾有关的数据；(2)将数据编制成易于使用的综合数据库，以一致的格式包括每次火灾的所有数据和相关辅助数据；(3)通过描述性统计方法对数据进行分析，对着火数据进行广义线性统计模型拟合，并将火灾蔓延观测值与基于物理的城市火灾蔓延模型估算值进行比较。项目负责人和顾问在地震后火灾研究方面具有广泛的背景，包括对过去事件的实地调查和开发起火、蔓延和扑灭模型。本研究将提供三个主要方面的知识，地震后火灾点火，在社区蔓延，火灾在工业设施。它将提高对震后点火的数量、位置、原因和时间的理解。这种现象固有的随机性要求使用统计方法，这种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，使以前地震记录的观测数据几乎增加一倍；记录了那些地面震动强到足以引发火灾但没有引发火灾的地区，这大大提高了我们预测火灾的能力；提供比目前更一致和全面的数据；通过提供地面震动和海啸引燃的数据。统计建模将进行，以确定什么数据表明，何时何地，为什么点火发生，并提高对未来点火的预测。通过收集数据，可以与新兴的新一代基于物理的城市火灾模型进行更有意义的比较，从而增强对火灾在社区传播的理解。这些模型具有潜在的强大功能，但它们需要与真实事件进行更多的比较，以改进它们，并建立它们的可信度。最后，该项目有望为震后火灾如何在工业设施中发生、蔓延和扑灭提供新的见解。我们将研究消防安全系统在面对大地震的极端共因失效模式时的表现。对地震后火源和城市火灾蔓延的进一步了解将直接用于开发更好的地震后火灾模型。然后，这些模型可以被整合到HAZUS-MH等区域地震损失模型中，通过支持长期应急响应规划、城市规划和损失估计，对社会有很大的示范价值。研究成果将被纳入pi研究生风险分析课程，并将在专业会议上发表。一名研究生研究助理将参与该项目的各个方面，该研究将成为他的地震后火灾建模论文的组成部分。

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.