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

这一学院早期职业发展(CALEAR)计划将进行基础研究，以促进弹性分析领域的发展，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一种整体方法来定义和量化基础设施破坏和功能完整性(在灾难事件发生后继续发挥作用的能力)，从而推动基础设施弹性的前沿，范围从单个建筑到整个社区。这项研究将解释弹性的概率性质。这项研究将提供量化数据，为灾害多发地区的设计、适应和缓解战略提供信息，从而显著减少自然灾害造成的经济损失和负面社会影响。此外，将基础设施子系统(例如建筑物)内部和之间的相关性结合起来，可以系统地描述破坏和破坏的类型和程度、供应链反应和估计如何在社区范围内实现恢复之间的关系。此外，该提案还从教育和外联的角度提供了产生积极社会影响的机会。相关活动包括培训下一代具有高度重视和计算经验的复原力工程学者，并通过利用私营部门在有效致力于包容性和多样性方面的良好记录，扩大代表不足的群体在科技、经济和经济领域的参与。这项研究的具体目标是通过整合理论和计算相结合的研究来推进基础设施复原力的边界，以便对复原力的所有方面进行全面、系统和有效的评估。实现这一目标的活动包括：(1)采用统计物理学和离散建模技术，对结构和非结构要素和子系统的损坏类型和程度进行建模，并预测系统的功能完整性。其主要思想是利用统计物理和离散建模技术的多功能性来对复杂的故障机制及其定义性能和脆弱性之间的精确关联的能力进行建模。对复杂结构行为建模的适应与对局部和全局结构减振机制建模的策略相辅相成；(Ii)开发新的学习策略，其依赖于智能和最佳采样和多保真信息融合，从而允许在存在低概率极端事件时准确和有效地估计损伤(和损失)的统计数据；(Iii)设计一个用于模拟供应链响应的系统动力学平台，该平台通过整合建筑物之间和建筑物内部的依赖关系来估计社区层面的累积损害和恢复轨迹。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.