Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Zhenzhou Lu"'
Publikováno v:
Reliability Engineering & System Safety. 189:99-108
Borgonovo moment-independent sensitivity index (BMSI) was proposed to measure the sensitivity of model inputs according to the whole distribution of model output not only a specific moment. The main computational difficulty of the BMSI is to estimate
Publikováno v:
Reliability Engineering & System Safety. 188:23-35
For efficiently estimating the time-dependent failure probability, two new methods named as the active learning Kriging (AK) coupled with importance sampling (AK-co-IS) and AK coupled with subset simulation (AK-co-SS) are proposed. The proposed metho
Autor:
Zhenzhou Lu, Kai Cheng
Publikováno v:
Reliability Engineering & System Safety. 188:310-319
Time-variant reliability analysis aims at estimating the probability that an engineering system successfully performs intended missions over a certain period of time under various sources of uncertainty. In order to perform the time-variant reliabili
Publikováno v:
Reliability Engineering & System Safety. 187:174-182
Probability density function (PDF)-based and failure probability (FP)-based moment-independent global sensitivity indices can commendably reflect the influence of model input on the whole distribution and partial distribution (or called FP) of model
Publikováno v:
Reliability Engineering & System Safety. 170:20-30
Dynamic models with time-dependent output are widely used in engineering for risk assessment and decision making. Global sensitivity analysis for these models is very useful for simplifying the model, improving the model performance, etc. The existen
Publikováno v:
Reliability Engineering & System Safety. 202:107025
Surrogate model techniques have been widely used for structural systems with expensively evaluated simulations. However, their application to system reliability problems meets the challenge since approximating multiple implicit performance functions
Autor:
Zhenzhou Lu, Luyi Li
Publikováno v:
International Journal of Systems Science. 47:3065-3077
Importance analysis is aimed at finding the contributions by the inputs to the uncertainty in a model output. For structural systems involving inputs with distribution parameter uncertainty, the contributions by the inputs to the output uncertainty a
Autor:
Kai Cheng, Zhenzhou Lu
Publikováno v:
Structural Safety. 83:101905
Assessing the failure probability of complex structure is a difficult task in presence of various uncertainties. In this paper, a new adaptive approach is developed for reliability analysis by ensemble learning of multiple competitive surrogate model
Publikováno v:
Structural Safety. 82:101891
The pivotal problem in reliability analysis is how to use a smaller number of model evaluations to get more accurate failure probabilities. To achieve this aim, an iterative method based on the Monte Carlo simulation and the adaptive Kriging (AK) mod
Publikováno v:
Reliability Engineering & System Safety. 193:106644
For efficiently estimating the failure probability of the structure with multiple implicit failure domains, a method abbreviated as Meta-IS-AK is proposed by combining the adaptive Kriging Meta model Importance Sampling (Meta-IS) and Importance Sampl