필로티 건축물의 인공지능 기반 내진성능 평가를 위한 데이터 기반 부재의 단면 형상비 연구

Abstract

Structures compromised by a seismic event may be susceptible to aftershocks or subsequent occurrences within a particular duration. Considering that the shape ratios of sections, such as column shape ratio (CSR) and wall shape ratio (WSR), significantly influence the behavior of reinforced concrete (RC) piloti structures, it is essential to determine the best appropriate methodology for these structures. The seismic evaluation of piloti structures was conducted to measure seismic performance based on section shape ratios and inter-story drift ratio (IDR) standards. The diverse machine-learning models were trained and evaluated using the dataset, and the optimal model was chosen based on the performance of each model. The optimal model was employed to predict seismic performance by adjusting section shape ratios and output parameters, and a recommended approach for section shape ratios was presented. The optimal section shape ratios for the CSR range from 1.0 to 1.5, while the WSR spans from 1.5 to 3.33, regardless of the inter-story drift ratios.