Abstract:Traditional probabilistic seismic demand analysis generally adopts the assumption of lognormal distribution, and most researchers adopt fixed threshold for limit state definition. These simplified strategies often deviate from the reality. This paper presents a probabilistic seismic demand analysis method based on Gaussian mixture model (GMM). Multi-dimensional performance limit state equation is used to measure the structure damage degree. Engineering demand parameter (EDP) is calculated based on the increment dynamic analysis (IDA). Structure thresholds under different seismic waves are obtained based on the slope of IDA curves. The probability density functions of EDP and threshold are established by GMM respectively without lognormal assumption. Traditional triple integral of probabilistic seismic demand analysis is extended to the quintuple integral, and the randomness of threshold is fully considered. Monte Carlo (MC) method is adopted, and the annual average exceeding probability of structural demand is obtained. A reinforced concrete (RC) frame-shear wall structure and a frame structure are established respectively as research objects. Maximum story displacement angle and maximum story acceleration are selected as two EDPs. The results show that: the randomness of the threshold is strong, and it will increase with the increase of the damage degree. Ignoring the threshold randomness will lead to large deviation of the results. The annual average exceeding probability of structural demand based on GMM is smaller, which indicates that the lognormal distribution assumption will get inaccurate evaluation results.
Key words: probabilistic seismic demand analysis; multi-dimensional performance limit state; Gaussian mixture model; threshold randomness; increment dynamic analysis
贾大卫,吴子燕,何乡. 基于高斯混合模型和极限状态阈值随机性的概率地震需求分析[J]. 振动与冲击, 2022, 41(20): 225-234.
JIA Dawei,WU Ziyan,HE Xiang. Probabilistic seismic demand analysis based on a Gaussian mixture model and limit state threshold randomness. JOURNAL OF VIBRATION AND SHOCK, 2022, 41(20): 225-234.
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