A dual-parameter method for seismic resilience assessment of buildings

Abstract

To quantify the seismic resilience of buildings, a method for evaluating functional loss from the component level to the overall building is proposed, and the dual-parameter seismic resilience assessment method based on postearthquake loss and recovery time is improved. A three-level function tree model is established, which can consider the dynamic changes in weight coefficients of different category of components relative to their functional losses. Bayesian networks are utilized to quantify the impact of weather conditions, construction technology levels, and worker skill levels on component repair time. A method for determining the real-time functional recovery curve of buildings based on the component repair process is proposed. Taking a three-story teaching building as an example, the seismic resilience indices under basic earthquakes and rare earthquakes are calculated. The results show that the seismic resilience grade of the teaching building is comprehensively judged as Grade Ⅲ, and its resilience grade is more significantly affected by postearthquake loss. The proposed method can be used to predict the seismic resilience of buildings prior to earthquakes, identify weak components within buildings, and provide guidance for taking measures to enhance the seismic resilience of buildings.

Keywords

seismic resilience assessment / dual-parameter method / functional loss / recovery time / Bayesian networks

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Funding

The National Key Research and Development Program of China(023YFC3805003)