Collaborative Research: Modeling Post-Disaster Housing Recovery Integrating Performance Based Engineering and Urban Simulation

在美国发生自然灾害后，联邦、州和地方政府官员必须协助恢复受影响社区的功能和福祉。住房部门在恢复中发挥着至关重要的作用，因为学校、企业、社区和社区组织都依赖于拥有健康生活条件的居民，以便他们能够留在受影响的地区。现有的灾害风险建模方法不能充分反映住房恢复过程及其对社区的长期影响。该项目将通过开发和应用新的数据和计算机模型方法来模拟灾后住房恢复来解决这一问题。计算机模型将使政策制定者和规划者能够量化与可能的灾前和灾后住房干预相关的好处和权衡。他们将能够探索各种未来危险事件的潜在情景，以实现加强美国灾后住房恢复的目标。为了方便向其他研究人员和灾害风险管理人员转让技术，该项目的计算机模型和数据将是免费的、开源的，并可通过万维网获得。这项研究将为博士生提供培训，并提供机会向来自不同背景的本科生传授科学和工程在提高社区对自然灾害的抵御能力方面的作用。我们将使用一个集成了建筑性能信息和房主在空间和时间上的决策的灾后恢复模拟模型来研究与住房恢复相关的关键问题。这项研究的三个主要组成部分是(1)使用有关功能丧失、宜居性和可维修性的数据来计算建筑物损坏的概率模型(2)根据损坏程度、人口结构、邻里条件和公用事业服务来量化与房主决定是否修复、重新使用、出售或废弃受损房屋相关的影响和不确定性的模型，以及(3)灾后房屋恢复的模拟，该模型考虑了建筑、房主和资源属性的影响，如房屋存量和人口流动。我们将把模拟模型应用于大城市司法管辖区，目的是(A)评估、(B)假设检验、(C)评估促进恢复的潜在政策和其他干预措施。该项目将促进以绩效为基础的工程和城市建模的科学，以促进试验，以检查灾后住宅建筑功能和住房入住率的地理影响。

Following natural disasters in the United States, federal, state and local government officials must facilitate the recovery of the functionality and well-being of the affected communities. The housing sector plays a vital role in recovery because schools, businesses, neighborhoods and community-based organizations all rely on residents having healthy living conditions so that they can remain in the affected region. Existing disaster risk modeling methods are not able to adequately represent the housing recovery process and its long-term impacts to communities. This project will address this problem by developing and applying new data and computer model methods to simulate post-disaster housing recovery. The computer model will enable policy-makers and planners to quantify the benefits and tradeoffs associated with possible pre- and post-disaster housing interventions. They will be able to explore potential scenarios for various future hazard events towards the goal of enhancing housing recovery after disasters in the United States. To facilitate technology transfer to other researchers and disaster risk managers, the computer model and data from this project will be free, open source, and available over the World Wide Web. The research will provide training for a doctoral student and an opportunity to teach undergraduate students from different backgrounds about the role of science and engineering in improving the resilience of communities to natural disasters.We will investigate key questions related to housing recovery using a post-disaster recovery simulation model that integrates building performance information and homeowner decision making over space and time. The three main components of the research are (1) a probabilistic model that computes building damage using data about loss of functionality, habitability, and repairability (2) a model that quantifies the influences and uncertainty associated with homeowners' decisions whether to repair, reoccupy, sell, or abandon damaged homes based on the extent of damage, demographics, neighborhood conditions, and utility services and (3) a simulation of post-disaster housing recovery, that accounts for the influences of building, homeowner, and resource attributes, such as housing stock and population movement. We will apply the simulation model to a large urban jurisdiction for the purposes of (a) evaluation, (b) hypothesis testing, (c) and assessing potential policies and other interventions for enhancing recovery. The project will further the science in performance-based engineering and urban modeling to facilitate experiments for examining the geographic effects of post-disaster residential building functionality and housing occupancy.