A novel projection outline based active learning method and its combination with Kriging metamodel for hybrid reliability analysis with random and interval variables

作者：Zhang, Jinhao; Xiao, Mi^*; Gao, Liang; Fu, Junjian

来源：Computer Methods in Applied Mechanics and Engineering, 2018, 341: 32-52.

DOI：10.1016/j.cma.2018.06.032

• Hybrid reliability analysis
• Random and interval variables
• Projection outlines
• Active learning
• Kriging metamodel

This paper focuses on the hybrid reliability analysis with both random and interval variables (HRA-RI). It is determined that a metamodel only accurately approximating the projection outlines on the limit-state surface can precisely estimate the lower and upper bounds of failure probability in HRA-RI. According to this idea, a novel projection outline based active learning (POAL) method is proposed to sequentially update design of experiments (DoE). Then, a HRA-RI method combining POAL and Kriging metamodel (POAL-Kriging) is developed. In this method, Kriging metamodel is refined based on the update samples, which are sequentially chosen using POAL from the vicinity of the projection outlines on the limit-state surface. In the end, the lower and upper bounds of failure probability in HRA-RI are precisely estimated. Compared to the approximation of the whole limit-state surface, the proposed method only approximates the projection outlines on the limit-state surface, and therefore few DoE are needed to build a high quality metamodel. The accuracy, efficiency and robustness of the proposed method for HRA-RI are illustrated by four examples.

• 出版日期2018-11-1
• 单位华中科技大学; 数字制造装备与技术国家重点实验室