Interval Analysis Method of Fault Tree Based on Convex Model

2011 ◽  
Vol 314-316 ◽  
pp. 2569-2573
Author(s):  
Yan Ming Xiong ◽  
Jun Li ◽  
Shi Ling Li ◽  
Zhan Ping Yang
Keyword(s):  
Interval Analysis ◽  
Fault Tree ◽  
Evidence Theory ◽  
Simulation Method ◽  
Analysis Method ◽  
Convex Model ◽  
Interval Probability ◽  
Practical Applications ◽  
Interval Analysis Method ◽  
Interval Operators

A novel interval analysis method of fault tree is proposed. Evidence theory is applied to calculate the interval probability of basic events. Convex model is applied to structure the interval operators for interval analysis, and Monte-Carlo simulation method is used to calculate conditional extreme. Simulation result demonstrates that the proposed method is coinciding with the practical applications very well, and can be applied when statistical data are incomplete.

Structure Buckling Load Interval Analysis of Ventilated Supercavitating Vehicles

2010 ◽  
Vol 452-453 ◽  
pp. 85-88
Author(s):  
Wei Dong Chen ◽  
Ling Zhou ◽  
Wei Guang An
Keyword(s):  
Interval Analysis ◽  
Analysis Method ◽  
Lower And Upper Bounds ◽  
Convex Model ◽  
Thin Cylindrical Shell ◽  
Buckling Loads ◽  
Supercavitating Vehicles ◽  
Interval Analysis Method ◽  
Model Method ◽  
Interval Width

Axial and circumferential critical buckling loads of thin cylindrical shell with stiffened rings are obtained by semi-analytical FEM. Then the interval widths of critical buckling loads which are obtained by interval analysis method are compared to those obtained by convex model method. The lower and upper bounds of axial and circumferential critical buckling loads increase with the increase of number of ring and are larger when the ring is placed on the inside of the shell than that is placed on the outside of the shell. The influence of variety of interval width of each basic variable on the variety of interval widths of critical buckling loads is obtained in this paper.

scholarly journals A novel interval analysis method to identify and reduce pure electric vehicle structure-borne noise

2020 ◽  
Vol 475 ◽  
pp. 115258 ◽  
Author(s):  
Hai B. Huang ◽  
Jiu H. Wu ◽  
Xiao R. Huang ◽  
Wei P. Ding ◽  
Ming L. Yang
Keyword(s):  
Electric Vehicle ◽  
Interval Analysis ◽  
Analysis Method ◽  
Interval Analysis Method ◽  
Vehicle Structure

Evidence-Based Structural Uncertainty Quantification by Dimension Reduction Decomposition and Marginal Interval Analysis

2019 ◽  
Vol 142 (5) ◽  
Author(s):  
Lixiong Cao ◽  
Jie Liu ◽  
Chao Jiang ◽  
Zhantao Wu ◽  
Zheng Zhang
Keyword(s):  
Dimension Reduction ◽  
Uncertainty Quantification ◽  
Interval Analysis ◽  
Evidence Theory ◽  
Evidence Based ◽  
Original Performance ◽  
Engineering Applications ◽  
Performance Function ◽  
One Dimensional ◽  
Interval Analysis Method

Abstract Evidence theory has the powerful feature to quantify epistemic uncertainty. However, the huge computational cost has become the main obstacle of evidence theory on engineering applications. In this paper, an efficient uncertainty quantification (UQ) method based on dimension reduction decomposition is proposed to improve the applicability of evidence theory. In evidence-based UQ, the extremum analysis is required for each joint focal element, which generally can be achieved by collocating a large number of nodes. Through dimension reduction decomposition, the response of any point can be predicted by the responses of corresponding marginal collocation nodes. Thus, a marginal collocation node method is proposed to avoid the call of original performance function at all joint collocation nodes in extremum analysis. Based on this, a marginal interval analysis method is further developed to decompose the multidimensional extremum searches for all joint focal elements into the combination of a few one-dimensional extremum searches. Because it overcomes the combinatorial explosion of computation caused by dimension, this proposed method can significantly improve the computational efficiency for evidence-based UQ, especially for the high-dimensional uncertainty problems. In each one-dimensional extremum search, as the response at each marginal collocation node is actually calculated by using the original performance function, the proposed method can provide a relatively precise result by collocating marginal nodes even for some nonlinear functions. The accuracy and efficiency of the proposed method are demonstrated by three numerical examples and two engineering applications.

Reliability Model of Series and Parallel Systems under Imperfect Information

2012 ◽  
Vol 204-208 ◽  
pp. 4932-4935
Author(s):  
Bin Suo ◽  
Chao Zeng ◽  
Yong Sheng Cheng ◽  
Jun Li
Keyword(s):  
Failure Probability ◽  
Imperfect Information ◽  
Evidence Theory ◽  
Parallel Systems ◽  
Probability Method ◽  
Analysis Method ◽  
Interval Method ◽  
Additional Information ◽  
Interval Analysis Method ◽  
Reliability Calculation

In the situation that unit failure probability is imprecise when calculation the failure probability of system, classical probability method is not applicable, and the analysis result of interval method is coarse. To calculate the reliability of series and parallel systems in above situation, D-S evidence theory was used to represent the unit failure probability. Multi-sources information was fused, and belief and plausibility function were used to calculate the reliability of series and parallel systems by evidential reasoning. By this mean, lower and upper bounds of probability distribution of system failure probability were obtained. Simulation result shows that the proposed method is preferable to deal with the imprecise probability in reliability calculation, and can get additional information when compare with interval analysis method.

INTERVAL AND SUBINTERVAL ANALYSIS METHODS OF THE STRUCTURAL ANALYSIS AND THEIR ERROR ESTIMATIONS

2006 ◽  
Vol 03 (02) ◽  
pp. 229-244 ◽  
Author(s):  
Y. T. ZHOU ◽  
C. JIANG ◽  
X. HAN
Keyword(s):  
Interval Analysis ◽  
Taylor Expansion ◽  
Truncation Error ◽  
Estimation Methods ◽  
Uncertain Parameters ◽  
Analysis Method ◽  
Interval Analysis Method ◽  
Analysis Methods ◽  
Second Derivatives ◽  
Error Estimations

In this paper, the interval analysis method is introduced to calculate the bounds of the structural displacement responses with small uncertain levels' parameters. This method is based on the first-order Taylor expansion and finite element method. The uncertain parameters are treated as the intervals, not necessary to know their probabilistic distributions. Through dividing the intervals of the uncertain parameters into several subintervals and applying the interval analysis to each subinterval combination, a subinterval analysis method is then suggested to deal with the structures with large uncertain levels' parameters. However, the second-order truncation error of the Taylor expansion and the linear approximation of the second derivatives with respect to the uncertain parameters, two error estimation methods are given to calculate the maximum errors of the interval analysis and subinterval analysis methods, respectively. A plane truss structure is investigated to demonstrate the efficiency of the presented method.

Sign in / Sign up

Export Citation Format

Share Document