TY - JOUR
T1 - Efficient sampling methods for global reliability sensitivity analysis
AU - Wei, Pengfei
AU - Lu, Zhenzhou
AU - Hao, Wenrui
AU - Feng, Jun
AU - Wang, Bintuan
PY - 2012/8
Y1 - 2012/8
N2 - An important problem in structure reliability analysis is how to reduce the failure probability. In this work, we introduce a main and total effect indices framework of global reliability sensitivity. By decreasing the uncertainty of input variables with high main effect indices, the most reduction of failure probability can be obtained. By decreasing the uncertainty of the input variables with small total effect indices (close to zero), the failure probability will not be reduced significantly. The efficient sampling methods for evaluating the main and total effect indices are presented. For the problem with large failure probability, a single-loop Monte Carlo simulation (MCS) is derived for computing these sensitivity indices. For the problem with small failure probability, the single-loop sampling methods combined with the importance sampling procedure (IS) and the truncated importance sampling procedure (TIS) respectively are derived for improving the calculation efficiency. Two numerical examples and one engineering example are introduced for demonstrating the efficiency and precision of the calculation methods and illustrating the engineering significance of the global reliability sensitivity indices.
AB - An important problem in structure reliability analysis is how to reduce the failure probability. In this work, we introduce a main and total effect indices framework of global reliability sensitivity. By decreasing the uncertainty of input variables with high main effect indices, the most reduction of failure probability can be obtained. By decreasing the uncertainty of the input variables with small total effect indices (close to zero), the failure probability will not be reduced significantly. The efficient sampling methods for evaluating the main and total effect indices are presented. For the problem with large failure probability, a single-loop Monte Carlo simulation (MCS) is derived for computing these sensitivity indices. For the problem with small failure probability, the single-loop sampling methods combined with the importance sampling procedure (IS) and the truncated importance sampling procedure (TIS) respectively are derived for improving the calculation efficiency. Two numerical examples and one engineering example are introduced for demonstrating the efficiency and precision of the calculation methods and illustrating the engineering significance of the global reliability sensitivity indices.
KW - Global reliability sensitivity analysis
KW - Importance sampling
KW - Main effect indices
KW - Total effect indices
KW - Truncated importance sampling
UR - http://www.scopus.com/inward/record.url?scp=84860282362&partnerID=8YFLogxK
U2 - 10.1016/j.cpc.2012.03.014
DO - 10.1016/j.cpc.2012.03.014
M3 - 文章
AN - SCOPUS:84860282362
SN - 0010-4655
VL - 183
SP - 1728
EP - 1743
JO - Computer Physics Communications
JF - Computer Physics Communications
IS - 8
ER -