Kriging-based reliability analysis considering predictive uncertainty reduction
نویسندگان
چکیده
Over the past decade, several acquisition functions have been proposed for kriging-based reliability analysis. Each of these can be used to identify an optimal sequence samples included in kriging model. However, no single function provides better performance over others all cases. Further, best-performing change at different iterations sequential sampling process. To address this problem, paper proposes a new function, namely expected uncertainty reduction (EUR), that serves as meta-criterion select best sample from set samples, each identified large number candidate according criterion function. EUR does not rely on local utility measure derived based posterior most existing do. Instead, directly quantifies prediction limit-state by adding sample. The is quantified posterior. In EUR-based process, portfolio consists four first employed suggest iteration sampling. with respect selection corresponding Then, among those samples. results two mathematical and one practical case studies show (1) perform well or outperform use any portfolio, (2) may problem another even next within problem.
منابع مشابه
Temperature Uncertainty Analysis of Injection Mechanism Based on Kriging Modeling
A kriging modeling method is proposed to conduct the temperature uncertainty analysis of an injection mechanism in squeeze casting. A mathematical model of temperature prediction with multi input and single output is employed to estimate the temperature spatiotemporal distributions of the injection mechanism. The kriging model applies different weights to the independent variables according to ...
متن کاملFast Parallel Kriging-Based Stepwise Uncertainty Reduction With Application to the Identification of an Excursion Set
Fast Parallel Kriging-Based Stepwise Uncertainty Reduction With Application to the Identification of an Excursion Set Clément Chevalier, David Ginsbourger, Julien Bect, Emmanuel Vazquez, Victor Picheny & Yann Richet a Institute of Mathematical Statistics and Actuarial Science University of Bern CH-3012 Bern, Switzerland (; ) b Department of Signal Processing & Electronic Systems Supelec, Gif-su...
متن کاملModified Bayesian Kriging for Noisy Response Problems for Reliability Analysis
This paper develops a new modified Bayesian Kriging (MBKG) surrogate modeling method for problems in which simulation analyses are inherently noisy and thus standard Kriging approaches fail to properly represent the responses. The purpose is to develop a method that can be used to carry out reliability analysis to predict probability of failure. The formulation of the MBKG surrogate modeling me...
متن کاملKriging-model-based uncertainty quantification in computational fluid dynamics
This paper proposes an efficient and accurate non-intrusive uncertainty quantification (UQ) method in computational fluid dynamics (CFD). Emphasis is placed on developing an UQ method that can accurately predict stochastic behaviors of output solution with small number of sampling simulations, and is also accurate for non-smooth output uncertainty responses. The proposed method is based on Krig...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Structural and Multidisciplinary Optimization
سال: 2021
ISSN: ['1615-1488', '1615-147X']
DOI: https://doi.org/10.1007/s00158-020-02831-w