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

这个教师早期职业发展（CAREER）计划将进行基础研究，推进弹性分析领域，并提高民用基础设施系统科普自然灾害的能力。该研究将通过开发一种整体方法来定义和量化基础设施损坏和功能完整性（在灾害事件后继续运作的能力），从而推动基础设施弹性的前沿，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，为灾害易发地区的设计、适应和缓解战略提供信息，从而大大减少自然灾害的经济损失和负面社会影响。此外，通过整合基础设施子系统（如建筑物）内部和之间的依赖关系，可以系统地描述损害和中断的类型和程度、供应链的应对措施以及如何在社区范围内实现恢复的估计之间的关系。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学者的弹性工程，重点强调计算和经验，并通过利用PI对包容性和多样性的有效承诺的良好记录来扩大STEM领域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理论和计算研究来推进基础设施弹性的边界，从而对弹性的各个方面进行全面，系统和有效的评估。㈠采用统计物理学和离散建模技术，模拟结构和非结构元件和子系统的损坏类型和程度，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，在建模复杂的故障机制和他们的能力，在定义性能和脆弱性之间的精确关联。对复杂结构行为建模的适应性与对局部和全局结构阻尼机制建模的策略相补充;（ii）开发基于智能和最佳采样以及多保真度信息融合的新型学习策略，从而能够准确有效地估计损伤统计数据（和损失）在低概率极端事件的存在;（三）设计一个系统动力学平台，用于模拟供应链反应，该平台通过整合内部和外部资源，该奖项反映了NSF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。

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.