首页|A Framework to Guide Performance-Based Assessment of Buildings Following Extreme Events
A Framework to Guide Performance-Based Assessment of Buildings Following Extreme Events
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NETL
NSTL
Asce-Amer Soc Civil Engineers
Abstract Following an extreme event, there is a brief window of opportunity to collect crucial data essential for developing valuable insights on the built environment’s performance. Recent investments in postevent performance assessments have significantly expanded the research community’s capacity to gather such perishable data. To enhance structural performance in future extreme events, there is a pressing need to explicitly connect these data with established performance metrics, e.g., economic loss. In response, the present study introduces a post-extreme-event performance assessment framework. This framework aims to streamline the acquisition of perishable data on building performance by illuminating which data should be prioritized in the field to inform targeted performance and/or functionality metrics. The study focuses on three key efforts: (1) inventorying the perishable data necessary to estimate typical performance metrics like economic loss and unsafe placarding; (2) developing transfer functions that enable the conversion of perishable data collected during post-extreme-event assessments into these performance/functionality metrics; and (3) downscaling the universe of perishable data through sensitivity analysis to optimize the efficient collection of field data to enable objective assignment of targeted performance metrics. Central to the sensitivity analysis is the development of performance metric/damage state emulators—fault trees that assess performance metrics using rule-based procedures that can be applied to the perishable data commonly collected in the field. This paper demonstrates the operationalization of the proposed framework using commonly used platforms for seismic and wind hazards. The framework is applied to a testbed in the Caribbean islands, showcasing its extensibility to multiple hazards and actual data collected in Puerto Rico as well as the US Virgin Islands after 2017’s Hurricane Maria and in Puerto Rico’s 2020 earthquakes.
Amir Safiey、David Roueche、Brandon Rittelmeyer、Tracy Kijewski-Correa、Khalid M. Mosalam
NETL
NSTL
Asce-Amer Soc Civil Engineers
