Limit states of structures and global sensitivity analysis based on Cramér-von Mises distance

Limit states of structures and global sensitivity analysis based on Cramér-von Mises distance

Článek Scopus

This article presents a stochastic computational model for the analysis of the reliability of a drawn steel bar. The whole distribution of the limit state function is studied using global sensitivity analysis based on Cramér-von Mises distance. The algorithm for estimating the sensitivity indices is based on one loop of the Latin Hypercube Sampling method in combination with numerical integration. The algorithm is effective due to the approximation of resistance using a three-parameter lognormal distribution. Goodness-of-fit tests and other comparative studies demonstrate the significant accuracy and suitability of the three-parameter lognormal distribution, which provides better results and faster response than sampling-based methods. Global sensitivity analysis is evaluated for two load cases with proven dominant effect of the long-term variation load action, which is introduced using Gumbel probability density function. The Cramér-von Mises indices are discussed in the context of other types of probability oriented sensitivity indices whose performance has been studied earlier.

This article presents a stochastic computational model for the analysis of the reliability of a drawn steel bar. The whole distribution of the limit state function is studied using global sensitivity analysis based on Cramér-von Mises distance. The algorithm for estimating the sensitivity indices is based on one loop of the Latin Hypercube Sampling method in combination with numerical integration. The algorithm is effective due to the approximation of resistance using a three-parameter lognormal distribution. Goodness-of-fit tests and other comparative studies demonstrate the significant accuracy and suitability of the three-parameter lognormal distribution, which provides better results and faster response than sampling-based methods. Global sensitivity analysis is evaluated for two load cases with proven dominant effect of the long-term variation load action, which is introduced using Gumbel probability density function. The Cramér-von Mises indices are discussed in the context of other types of probability oriented sensitivity indices whose performance has been studied earlier.

Global sensitivity analysis, steel, probability, failure, reliability, random sampling

Global sensitivity analysis, steel, probability, failure, reliability, random sampling

KALA, Z.

2021

07.07.2020

NAUN

1998-4448

International Journal of Mechanics

14

1

Spojené státy americké

107

118

12

https://www.naun.org/main/NAUN/mechanics/2020/a282003-caw.pdf

http://hdl.handle.net/11012/196686

a282003-caw