I-Corps: An Innovative Framework for High Resolution Quantitative Assessment of Flood Resiliency

I-Corps:防洪能力高分辨率定量评估的创新框架

基本信息

  • 批准号:
    2015715
  • 负责人:
  • 金额:
    $ 1.66万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2019
  • 资助国家:
    美国
  • 起止时间:
    2019-08-31 至 2021-08-31
  • 项目状态:
    已结题

项目摘要

The broader impact/commercial potential of this I-Corps project is to provide technical services to homeowners, local municipalities, engineering and insurance companies to enhance community resilience and sustainability against multi-hazard events such as hurricane that can bring strong wind, storm surge and wide spread inundation. The proposed resilience technology contributes to a paradigm shift in practice from engineering design code methods to performance-based approach that considers structural resiliency concepts and quantifies property hazard risk and value over time. The in-house developed technology utilizes the hydrodynamic simulations to calculate the flood impacts and combines it with the structural and socioeconomic features of built environment. The multi-faceted tool will inform individuals, local municipalities, coastal building designers, increasing the performance and resiliency of this building stock and ensuring greater post-event community function, insurance companies underwriting flood insurances and calculating premiums. Progress and information to be gained through the I-Corps program, in interactions with hazard insurance and risk assessment companies as well as engineering and information service groups will enable our team to expedite the translation of the proposed technology to the market. The developed technologies will be scalable and broadly applicable to other hazard types and regions with potentials of expanding to at international markets.This I-Corps project aims to offer a comprehensive predictive tool that provides a pin-point quantitative assessment of the damage and resiliency scenarios of individual properties and up-scaling it to larger infrastructure cluster to introduce a new understanding of the community wide vulnerability considering available social and human capitals. The innovative and ground breaking aspect of this work is that this project for the first time consolidating hydrodynamic, structural and socioeconomic information through a massive big data campaign followed by interactive analysis to open a new window in understanding impacts of extreme events. Specifically, the intellectual merit of this approach resides in its (a) Holistic approach to performance-based design of building (b) Application of state-of-the-art data driven predictive models and advanced computational technologies in flood damage and resiliency assessment of buildings (c) High modularity in building design and prototyping process which supports expansion to other hazards and building types, and (d) Potential to create new knowledge regarding optimal multi-hazard building design. The approach provides comprehensive support to decision makers and designers by estimating building vulnerability and resiliency over construction property, operation and hazards, and by balancing competing objectives.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.
I-Corps项目的更广泛影响/商业潜力是为房主、当地市政当局、工程和保险公司提供技术服务,以增强社区抵御多种灾害事件的能力和可持续性,如飓风,可能带来强风、风暴潮和大面积淹没。所提出的弹性技术有助于实践中的范式转变,从工程设计规范方法到基于性能的方法,考虑结构弹性概念并量化财产危害风险和价值。内部开发的技术利用水动力学模拟来计算洪水的影响,并将其与建筑环境的结构和社会经济特征相结合。这个多方面的工具将为个人、当地市政当局、沿海建筑设计师提供信息,提高这些建筑的性能和弹性,确保更大的灾后社区功能,保险公司承保洪水保险并计算保费。通过I-Corps项目,在与灾害保险和风险评估公司以及工程和信息服务集团的互动中,所获得的进展和信息将使我们的团队能够加速将拟议的技术转化为市场。开发的技术将可扩展并广泛适用于其他危险类型和具有扩展到国际市场潜力的区域。I-Corps项目旨在提供一个全面的预测工具,对单个财产的损害和恢复情况进行精确的定量评估,并将其扩展到更大的基础设施集群,以引入对整个社区脆弱性的新认识,考虑到可用的社会和人力资本。这项工作的创新和突破性之处在于,该项目首次通过大规模的大数据活动整合了水动力、结构和社会经济信息,随后进行了互动分析,为了解极端事件的影响打开了一扇新的窗口。具体来说,这种方法的智力优点在于:(a)对基于性能的建筑设计的整体方法;(b)在建筑物的洪水破坏和弹性评估中应用最先进的数据驱动预测模型和先进的计算技术;(c)建筑设计和原型制作过程的高度模块化,支持扩展到其他危险和建筑类型;(d)创造关于最佳多灾害建筑设计的新知识的潜力。该方法为决策者和设计师提供了全面的支持,通过评估建筑的脆弱性和弹性,包括建筑属性、操作和危害,以及平衡相互竞争的目标。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值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(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Quantitative assessment of resilience for earthen structures using coupled plasticity-damage model
  • DOI:
    10.1016/j.engstruct.2018.06.050
  • 发表时间:
    2018-10
  • 期刊:
  • 影响因子:
    5.5
  • 作者:
    M. H. Motamedi;A. Iranmanesh;Rouzbeh Nazari
  • 通讯作者:
    M. H. Motamedi;A. Iranmanesh;Rouzbeh Nazari
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Rouzbeh Nazari其他文献

Optimization of Applied Water Depth Under Water Limiting Conditions
限水条件下应用水深的优化
  • DOI:
    10.1007/s11269-022-03241-x
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    4.3
  • 作者:
    Mohammad Ismaeil Kamali;H. Ansari;Rouzbeh Nazari
  • 通讯作者:
    Rouzbeh Nazari
Cluster-based downscaling of precipitation using Kolmogorov-Arnold Neural Networks and CMIP6 models: Insights from Oman
使用 Kolmogorov-Arnold 神经网络和 CMIP6 模型进行基于聚类的降水降尺度分析:来自阿曼的见解
  • DOI:
    10.1016/j.jenvman.2025.124971
  • 发表时间:
    2025-04-01
  • 期刊:
  • 影响因子:
    8.400
  • 作者:
    Ali Mardy;Mohammad Reza Nikoo;Mohammad G. Zamani;Ghazi Al-Rawas;Rouzbeh Nazari;Jiri Simunek;Ahmad Sana;Amir H. Gandomi
  • 通讯作者:
    Amir H. Gandomi
Analyzing reliability missteps: The collapse of the Francis Scott Key Bridge — Target reliability, redundancy, and extreme load combinations
分析可靠性失误:弗朗西斯·斯科特·基大桥的坍塌——目标可靠性、冗余和极端荷载组合
  • DOI:
    10.1016/j.istruc.2025.108590
  • 发表时间:
    2025-04-01
  • 期刊:
  • 影响因子:
    4.300
  • 作者:
    Seyed Hooman Ghasemi;Andrzej S. Nowak;Rouzbeh Nazari
  • 通讯作者:
    Rouzbeh Nazari
Hybrid deep learning downscaling of GCMs for climate impact assessment and future projections in Oman
用于阿曼气候影响评估和未来预测的 GCMs 混合深度学习降尺度
  • DOI:
    10.1016/j.jenvman.2025.124522
  • 发表时间:
    2025-03-01
  • 期刊:
  • 影响因子:
    8.400
  • 作者:
    Erfan Zarei;Mohammad Reza Nikoo;Ghazi Al-Rawas;Rouzbeh Nazari;Mingjie Chen;Badar Al Jahwari;Malik Al-Wardy
  • 通讯作者:
    Malik Al-Wardy
Advancing flood damage modeling for coastal Alabama residential properties: A multivariable machine learning approach
推进阿拉巴马州沿海住宅财产洪水损害建模:一种多变量机器学习方法
  • DOI:
    10.1016/j.scitotenv.2023.167872
  • 发表时间:
    2024-01-10
  • 期刊:
  • 影响因子:
    8.000
  • 作者:
    Mujungu Lawrence Museru;Rouzbeh Nazari;Abolfazl N. Giglou;Kofi Opare;Maryam Karimi
  • 通讯作者:
    Maryam Karimi

Rouzbeh Nazari的其他文献

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{{ truncateString('Rouzbeh Nazari', 18)}}的其他基金

I-Corps: An Innovative Framework for High Resolution Quantitative Assessment of Flood Resiliency
I-Corps:防洪能力高分辨率定量评估的创新框架
  • 批准号:
    1842959
  • 财政年份:
    2018
  • 资助金额:
    $ 1.66万
  • 项目类别:
    Standard Grant

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