Affiliation of Author(s):航空学院
Journal:Mech Syst Signal Process
Abstract:A new sampling-based method is proposed for high-dimensional time-variant reliability analysis with both random variables and random process as inputs. The new method employs the series expansion methods, e.g., the Karhunen-Loève expansion, to represent the input random process into a set of random variables. Based on the concepts of composite limit state, the time-variant reliability analysis is converted into a series system reliability problem with multiple responses. Then the generalized subset simulation is applied to compute cumulative failure probabilities which are further used to interpolate a completely cumulative failure probability curve for a given time interval. The advantage of the proposed method is that only a single run can provide a cumulative failure probability curve instead of repeated runs. Two high-dimensional time-variant reliability problems with input random process are used to demonstrate the performance of the proposed method. © 2019 Elsevier Ltd
ISSN No.:0888-3270
Translation or Not:no
Date of Publication:2019-01-01
Co-author:Wang, Tao,Tao Wang,Yuan, Jiao-Yang,Zhang, Hang
Correspondence Author:lhs
Date of Publication:2019-01-01