A novel evidence-theory-based reliability analysis method for structures with epistemic uncertainty

2013 ◽  
Vol 129 ◽  
pp. 1-12 ◽  
Author(s):  
C. Jiang ◽  
Z. Zhang ◽  
X. Han ◽  
J. Liu
Keyword(s):  
Reliability Analysis ◽  
Epistemic Uncertainty ◽  
Evidence Theory ◽  
Analysis Method

An Efficient Reliability Analysis Method for Structures With Epistemic Uncertainty Using Evidence Theory

2014 ◽  
Author(s):  
Zhe Zhang ◽  
Chao Jiang ◽  
G. Gary Wang ◽  
Xu Han
Keyword(s):  
Reliability Analysis ◽  
Structural Reliability ◽  
Epistemic Uncertainty ◽  
Limit State ◽  
Computational Cost ◽  
Evidence Theory ◽  
State Function ◽  
Limited Information ◽  
Design Point ◽  
Engineering Problems

Evidence theory has a strong ability to deal with the epistemic uncertainty, based on which the uncertain parameters existing in many complex engineering problems with limited information can be conveniently treated. However, the heavy computational cost caused by its discrete property severely influences the practicability of evidence theory, which has become a main difficulty in structural reliability analysis using evidence theory. This paper aims to develop an efficient method to evaluate the reliability for structures with evidence variables, and hence improves the applicability of evidence theory for engineering problems. A non-probabilistic reliability index approach is introduced to obtain a design point on the limit-state surface. An assistant area is then constructed through the obtained design point, based on which a small number of focal elements can be picked out for extreme analysis instead of using all the elements. The vertex method is used for extreme analysis to obtain the minimum and maximum values of the limit-state function over a focal element. A reliability interval composed of the belief measure and the plausibility measure is finally obtained for the structure. Two numerical examples are investigated to demonstrate the effectiveness of the proposed method.

Hybrid reliability analysis for energy-absorbing composite structures based on evidence theory

2014 ◽  
Vol 33 (22) ◽  
pp. 2095-2105 ◽  
Author(s):  
Shuyong Duan ◽  
Xujing Yang ◽  
Yourui Tao ◽  
Zhangping Hu ◽  
Yunbiao Chen
Keyword(s):  
Reliability Analysis ◽  
Composite Structures ◽  
Epistemic Uncertainty ◽  
Evidence Theory ◽  
Analysis Model ◽  
Element Analysis ◽  
Explicit Finite Element ◽  
Hybrid Reliability ◽  
Energy Absorbing ◽  
Composite Energy

It is important to investigate the uncertain modeling and reliability analysis for the crashworthiness capacity of composite energy-absorbing structures (CEAS) in which there are random and epistemic uncertainty. A probability-evidence theory hybrid uncertainty model and a corresponding efficient reliability analysis method for the crashworthiness capacity of CEAS are presented in this paper. In this method, evidence theory is introduced to address the difficulties in the epistemic uncertain modeling due to the lack of experimental samples, which expand greatly the applicability of reliability analysis technology in the crashworthiness capacity of CEAS research. Moreover, the probability theory is applied to address the random uncertainty. Based on the traditional equivalence normalization method, a probability-evidence theory hybrid reliability analysis model for the crashworthiness capacity of CEAS is developed. An explicit finite element analysis is used to calculate the peak crushing force and the specific energy absorption of CEAS which are presented by the quadratic response surface. Two numerical examples of CEAS are presented for verification of the validity of the proposed method.

Evidence Theory-Based Reliability Analysis and Optimization in Engineering Design

2007 ◽  
Author(s):  
Li Du ◽  
Liping He ◽  
Hong-Zhong Huang
Keyword(s):  
Reliability Analysis ◽  
Engineering Design ◽  
Epistemic Uncertainty ◽  
Evidence Theory ◽  
Theoretical Research ◽  
Future Research ◽  
Sufficient Information ◽  
Computationally Efficient ◽  
Input Uncertainty ◽  
Analysis And Design

Engineering design under uncertainty has gained considerable attention in recent years. There exist two different types of uncertainties in practical engineering applications: aleatory uncertainty that is classified as objective and irreducible uncertainty with sufficient information on input uncertainty data and epistemic uncertainty that is a subjective and reducible uncertainty that is caused by the lack of knowledge on input uncertainty data. Among several alternative tools to handle uncertainty, evidence theory has proved to be computationally efficient and stable tool for reliability analysis and design optimization under aleatory and/or epistemic uncertainty involved in engineering systems. This paper attempts to give a better understanding of uncertainty in engineering design with a general overview. The overview includes theoretical research, computational development, and performable ability consideration of evidence theory during recent years. At last, perspectives on future research are stated.

A Reliability-Based Multidisciplinary Design Optimization Method with Evidence Theory and Probability Theory

2018 ◽  
Vol 25 (01) ◽  
pp. 1850003 ◽  
Author(s):  
Chen Guoqiang ◽  
Tan Jianping ◽  
Tao Yourui
Keyword(s):  
Probability Theory ◽  
Design Optimization ◽  
Reliability Analysis ◽  
Computational Efficiency ◽  
Multidisciplinary Design Optimization ◽  
Epistemic Uncertainty ◽  
Evidence Theory ◽  
Optimization Method ◽  
Multidisciplinary Design ◽  
Multidisciplinary System

Uncertainties, including aleatory and epistemic uncertainties, always exist in multidisciplinary system. Due to the discontinuous nature of epistemic uncertainty and the complex coupled relation among subsystems, the computational efficiency of reliability-based multidisciplinary design optimization (RBMDO) with mixed aleatory and epistemic uncertainties is extremely low. A novel RBMDO procedure is presented in this paper based on combined probability theory and evidence theory (ET) to deal with hybrid-uncertainties and improve the computational efficiency. Firstly, based on Bayes method, a novel method to define the probability density function of the aleatory variables is proposed. Secondly, the conventional equivalent normal method (J-C method) is modified to reliability analysis with hybrid-uncertainties. Finally, a novel RBMDO procedure is suggested by integrating the modified J-C method into the frame of sequence optimization and reliability analysis (SORA). Numerical examples and engineering example are applied to demonstrate the performance of the proposed method. The examples show the excellence of the RBMDO method both in computational efficiency and accuracy. The proposed method provides a practical and effective reliability design method for multidisciplinary system.

An efficient epistemic uncertainty analysis method for structural-acoustic problem based on evidence theory

2018 ◽  
Vol 66 (2) ◽  
pp. 117-130
Author(s):  
Ning Chen ◽  
Shengwen Yin ◽  
Dejie Yu ◽  
Zuojun Liu ◽  
Baizhan Xia
Keyword(s):  
Uncertainty Analysis ◽  
Epistemic Uncertainty ◽  
Evidence Theory ◽  
Analysis Method ◽  
Acoustic Problem
Sign in / Sign up

Export Citation Format

Share Document