Publication:
A novel maximum volume sampling model for reliability analysis

Placeholder

Organizational Units

Authors

Meng, Zeng
Pang, Yongsheng
Wu, Zhigen
Ren, Shanhong
Yıldız, Ali Rıza

Advisor

Language

Publisher:

Elsevier Science

Journal Title

Journal ISSN

Volume Title

Abstract

In this study, a maximum volume sampling model is proposed to improve the accuracy and efficiency of reliability computation. An ellipsoid is constructed with the maximum volume approach in a safe domain, and a new maximum volume optimization method is proposed. The sampling model only computes the samples outside the ellipsoid, which considerably enhances computational efficiency. Furthermore, the uniform sampling strategy and Givens transformation are adopted to efficiently solve the maximum volume optimization model. A series system example, a three-dimensional rock slope example, and an arch bridge example are tested to verify the validity of the proposed maximum volume sampling model. The results indicate that the maximum volume sampling model displays high accuracy and efficiency.

Description

Source:

Keywords:

Keywords

Subset simulation, Probability, Approximate, Efficiency, Stability, Accuracy, Moments, Reliability, Optimization, Sampling strategy, Givens transformation, Maximum volume sampling model, Engineering, Mathematics, Mechanics

Citation

Endorsement

Review

Supplemented By

Referenced By

2

Views

0

Downloads

View PlumX Details