건축도시공간연구소

Architecture & Urban Research Institute

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한국공간구조학회|한국공간구조학회지 2024년 6월

기사명 경년열화를 고려한 전단벽 구조물의 기계학습 기반 지진응답 예측모델 개발 / Development of Machine Learning Based Seismic Response Prediction Model for Shear Wall Structure considering Aging Deteriorations
저자명 김현수 ; 김유경 ; 이소연 ; 장준수
발행사 한국공간구조학회
수록사항 한국공간구조학회지 , Vol. 24, No. 2 (통권 96호)(2024-06)
페이지 시작페이지(83) 총페이지(8)
ISSN 15984095
주제분류 구조
주제어 ; Concrete Aging degradation; Machine learning; Seismic response prediction; Shear wall structure
요약2 Machine learning is widely applied to various engineering fields. In structural engineering area, machine learning is generally used to predict structural responses of building structures. The aging deterioration of reinforced concrete structure affects its structural behavior. Therefore, the aging deterioration of R.C. structure should be consider to exactly predict seismic responses of the structure. In this study, the machine learning based seismic response prediction model was developed. To this end, four machine learning algorithms were employed and prediction performance of each algorithm was compared. A 3-story coupled shear wall structure was selected as an example structure for numerical simulation. Artificial ground motions were generated based on domestic site characteristics. Elastic modulus, damping ratio and density were changed to considering concrete degradation due to chloride penetration and carbonation, etc. Various intensity measures were used input parameters of the training database. Performance evaluation was performed using metrics like root mean square error, mean square error, mean absolute error, and coefficient of determination. The optimization of hyperparameters was achieved through k-fold cross-validation and grid search techniques. The analysis results show that neural networks and extreme gradient boosting algorithms present good prediction performance.
소장처 한국공간구조학회
언어 한국어
DOI http://dx.doi.org/10.9712/KASS.2024.24.2.83