Assessing Urban Post-Earthquake Community Recovery to Inform Pre-Disaster Planning
评估城市震后社区恢复情况,为灾前规划提供信息
基本信息
- 批准号:2053014
- 负责人:
- 金额:$ 30.94万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-11-01 至 2025-10-31
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
Significant effort has been devoted to predicting physical damage to the built environment from disasters, but much less is understood about simulating disaster recovery, and how mitigation actions influence recovery. Further, it is well understood that there are existing socioeconomic inequalities in disaster risk and resilience. This Disaster Resilience Research Grants (DRRG) project aims to develop models to simulate housing and business operations recovery after a disaster. New insights will be gained into how a community's physical/demographic/economic characteristics interact in the recovery process. The models will be used to quantify a region's current ability to recover from disaster and evaluate the efficacy of actions that could be taken before disasters occur. Given the enormous costs of post-disaster disruption, and the significant resources committed for mitigation, insights on improving recovery will significantly benefit society, by improving disaster resilience and efficiently allocating limited societal resources to promote equity. Programs to involve underrepresented researchers, engage with city planners, and publicly release the modeling software will also contribute to the broader impacts of this work.This project will develop a new generation of high-resolution computational simulation tools for disaster recovery simulation, to support enhanced and more equitable housing recovery. High-resolution simulations of the built, natural, and human environment (including household and company behavior) will be combined with mechanisms to quantify the benefits of resilience-enhancing policies. The housing recovery will be jointly simulated with the recovery of infrastructure and businesses, constrained by the availability of resources and affected by socioeconomic factors. The recovery process of individual households will be simulated, providing great flexibility in examining results and assessing the benefits for different groups of resilience-enhancing policies. This work will enable a holistic understanding of the community recovery process after earthquakes. The research will advance our capabilities to assess, before a disaster, the extent to which disaster preparedness interventions can reduce initial disaster consequences, speed recovery, and ensure that all groups participate in the benefits. This project's deliverables will be a modeling framework for assessing post-earthquake recovery and case-study analysis of recovery in San Francisco.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
人们投入了大量精力来预测灾难对建筑环境造成的物理损害,但对模拟灾难恢复以及缓解措施如何影响恢复的了解却少之又少。此外,众所周知,灾害风险和复原力方面存在社会经济不平等。该灾难恢复研究补助金 (DRRG) 项目旨在开发模型来模拟灾难后的住房和商业运营恢复。将获得关于社区的自然/人口/经济特征如何在恢复过程中相互作用的新见解。这些模型将用于量化一个地区当前从灾难中恢复的能力,并评估灾难发生前可以采取的行动的有效性。考虑到灾后破坏的巨大成本以及用于减灾的大量资源,通过提高抗灾能力和有效分配有限的社会资源以促进公平,改善恢复的见解将极大地造福社会。涉及代表性不足的研究人员、与城市规划者合作以及公开发布建模软件的计划也将有助于这项工作产生更广泛的影响。该项目将开发新一代用于灾难恢复模拟的高分辨率计算模拟工具,以支持增强的灾难恢复模拟工具。以及更公平的住房复苏。对建筑、自然和人类环境(包括家庭和公司行为)的高分辨率模拟将与量化增强复原力政策的效益的机制相结合。住房复苏将与基础设施和商业的复苏共同模拟,受到资源可用性的约束和社会经济因素的影响。各个家庭的恢复过程将被模拟,为检查结果和评估不同群体的韧性增强政策的效益提供了很大的灵活性。这项工作将使人们全面了解地震后的社区恢复过程。该研究将提高我们在灾难发生前评估备灾干预措施在多大程度上可以减少灾难初期后果、加快恢复速度并确保所有群体都受益的能力。该项目的可交付成果将成为评估旧金山震后恢复和恢复案例研究分析的建模框架。该奖项反映了 NSF 的法定使命,并通过使用基金会的智力优点和更广泛的影响审查标准进行评估,被认为值得支持。
项目成果
期刊论文数量(3)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Simulating post-disaster temporary housing needs for displaced households and out-of-town contractors
- DOI:10.1177/87552930221112690
- 发表时间:2022-02
- 期刊:
- 影响因子:5
- 作者:Chenbo Wang;R. Costa;J. Baker
- 通讯作者:Chenbo Wang;R. Costa;J. Baker
Machine‐learning‐based optimization framework to support recovery‐based design
基于机器学习的优化框架,支持基于恢复的设计
- DOI:10.1002/eqe.3860
- 发表时间:2023
- 期刊:
- 影响因子:4.5
- 作者:Issa, Omar;Silva‐Lopez, Rodrigo;Baker, Jack W.;Burton, Henry V.
- 通讯作者:Burton, Henry V.
Integrating Place Attachment into Housing Recovery Simulations to Estimate Population Losses
将地方依恋融入住房恢复模拟中以估计人口损失
- DOI:10.1061/(asce)nh.1527-6996.0000571
- 发表时间:2022
- 期刊:
- 影响因子:2.7
- 作者:Costa, Rodrigo;Wang, Chenbo;Baker, Jack W.
- 通讯作者:Baker, Jack W.
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Jack Baker其他文献
Random Effect Models For Repairable System Reliability
可修复系统可靠性的随机效应模型
- DOI:
- 发表时间:
1997 - 期刊:
- 影响因子:0
- 作者:
Jack Baker - 通讯作者:
Jack Baker
Keeping Promises? Democracies’ Ability to Harmonize Their International and National Climate Commitments
民主国家有能力兑现其国际和国家气候承诺吗?
- DOI:
10.1162/glep_a_00709 - 发表时间:
2023 - 期刊:
- 影响因子:4.8
- 作者:
Jack Baker - 通讯作者:
Jack Baker
Language, sexuality and corpus linguistics
语言、性和语料库语言学
- DOI:
- 发表时间:
2018 - 期刊:
- 影响因子:2.1
- 作者:
Jack Baker - 通讯作者:
Jack Baker
sgmcmc: An R Package for Stochastic Gradient Markov Chain Monte Carlo
sgmcmc:随机梯度马尔可夫链蒙特卡罗的 R 包
- DOI:
10.18637/jss.v091.i03 - 发表时间:
2017 - 期刊:
- 影响因子:5.8
- 作者:
Jack Baker;P. Fearnhead;E. Fox;C. Nemeth - 通讯作者:
C. Nemeth
Jack Baker的其他文献
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{{ truncateString('Jack Baker', 18)}}的其他基金
Planning Grant: Engineering Research Center for Data for Socio-Physical Extreme Event Resilience (Data-SPEER)
规划拨款:社会物理极端事件恢复力数据工程研究中心(Data-SPEER)
- 批准号:
1840435 - 财政年份:2018
- 资助金额:
$ 30.94万 - 项目类别:
Standard Grant
CAREER: Assessment of Infrastructure Risk Under Natural Disasters in a Multiscale Probabilistic Framework
职业:在多尺度概率框架中评估自然灾害下的基础设施风险
- 批准号:
0952402 - 财政年份:2010
- 资助金额:
$ 30.94万 - 项目类别:
Standard Grant
A Comprehensive Approach for Incorporating the Effects of Near-Fault Directivity into Design Criteria
将近故障方向性影响纳入设计标准的综合方法
- 批准号:
0726684 - 财政年份:2008
- 资助金额:
$ 30.94万 - 项目类别:
Standard Grant
Collaborative Research: Characterization of Random Fields and their Impact on the Mechanics of Geosystems at Multiple Scales
合作研究:随机场的表征及其对多尺度地球系统力学的影响
- 批准号:
0727121 - 财政年份:2007
- 资助金额:
$ 30.94万 - 项目类别:
Standard Grant
NSF East Asia Summer Institutes for US Graduate Students
美国研究生 NSF 东亚暑期学院
- 批准号:
0405003 - 财政年份:2004
- 资助金额:
$ 30.94万 - 项目类别:
Fellowship
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