CAREER: An Integrated Framework for Resilience Analytics: From Physics-based Modeling of Building Components to Dynamics of Community Level Recovery

职业：弹性分析的综合框架：从基于物理的建筑组件建模到社区层面恢复的动态

• 批准号: 2347722
• 负责人: Arghavan Louhghalam
• 金额: $ 52.49万
• 依托单位: University of Massachusetts Lowell
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2347722&HistoricalAwards=false
• 关键词: CAREER; Integrated; Framework; Resilience; Analytics

This Faculty Early Career Development (CAREER) program will perform fundamental research that advances the field of resilience analytics and enhances the ability of civil infrastructure systems to cope with natural disasters. The research will push the frontier on infrastructure resilience by developing a holistic methodology to define and quantify infrastructure damage and functional integrity (the ability to continue to function after a hazard event) at multiple scales ranging from a single building to an entire community. The research will account for the probabilistic nature of resilience. The research will provide quantitative data that inform design, adaptation and mitigation strategies in hazard prone areas, and as such lead to significant reductions in economic loss and negative societal impacts of natural hazards. Furthermore, the integration of dependencies within and between infrastructure subsystems (e.g. buildings) allows for systematic characterization of the relationship between the type and extent of damage and disruption, the supply chain response, and the estimation of how recovery can be achieved at the community scale. In addition, this proposal provides opportunities for positive societal impacts from the perspectives of education and outreach. Relevant activities include training the next generation of scholars in resilience engineering with strong emphasis and experience on computation, and broadening the participation of underrepresented groups in STEM fields by capitalizing on the PIs strong track record on impactful commitment to inclusiveness and diversity. The specific goal of this research is to advance the boundaries of infrastructure resilience through integration of a combined theoretical and computational study that allows for a holistic, systematic and efficient evaluation of all dimensions of resilience. The activities to achieve this goal include: (i) Adapting statistical physics and discrete modeling techniques to model the type and extent of damage in structural and non-structural elements and subsystems, as well as to predict the functional integrity of the system. The primary idea is to leverage the versatility of statistical physics and discrete modeling techniques in modeling complex failure mechanisms and their capability in defining precise associations between performance and vulnerability. The adaptation to modeling complex structural behavior is complemented with strategies for modeling local and global structural damping mechanisms; (ii) Development of novel learning strategies that rest on smart and optimal sampling and multi-fidelity information fusion allowing for accurate and efficient estimation of the statistics of damage (and loss) in the presence of low-probability extreme events; (iii) Devising a systems dynamics platform for modeling supply chain response that feeds from integration of inter- and intra-building dependencies for estimation of aggregated community level damage and recovery trajectory.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.

该教师早期职业发展（职业）计划将进行基础研究，以提高弹性分析领域，并增强民用基础设施系统应对自然灾害的能力。这项研究将通过开发整体方法来定义和量化基础设施损害和功能完整性（危险事件后继续运作的能力），从而推动基础设施弹性的边界，从单个建筑物到整个社区的多个量表。该研究将解释弹性的概率性质。这项研究将提供定量数据，以使危险区域的设计，适应和缓解策略为危险区域提供依据，从而导致经济损失和自然危害的负面影响显着减少。此外，基础架构子系统内和之间的依赖关系的整合（例如，建筑物）可以系统地表征损害和破坏的类型和程度之间的关系，供应链响应以及如何在社区规模上实现恢复的估计。此外，该提案从教育和外展的角度为积极的社会影响提供了机会。相关活动包括培训下一代学者在弹性工程方面，强烈重视和对计算的经验，并通过利用PIS强大的往绩记录对包容性和多样性的有影响力的承诺来扩大代表性不足的群体的参与。这项研究的具体目标是通过整合合并的理论和计算研究来提高基础设施弹性的界限，该研究允许对弹性的所有维度进行整体，系统和有效的评估。实现此目标的活动包括：（i）调整统计物理和离散建模技术，以建模结构和非结构元素和子系统中损害的类型和程度，并预测系统的功能完整性。主要思想是利用统计物理学和离散建模技术在建模复杂故障机制中的多功​​能性及其在定义性能与脆弱性之间的精确关联方面的能力。对建模复杂的结构行为的改编与对局部和全球结构阻尼机制进行建模的策略相辅相成。 （ii）制定新的学习策略，这些策略基于智能和最佳抽样和多保真信息融合，从而可以在存在低概率的极端事件的情况下准确有效地估算损害（和损失）的统计数据； （iii）设计一个用于建模供应链响应的系统动态平台，该平台从整合和内部和内部构建依赖性的整合来估算，以估算汇总的社区级别损害和恢复轨迹。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子的智力和宽广的影响来通过评估来评估的，并被认为是值得的。