A hybrid approach for global sensitivity analysis
Creators
Description
Distribution based sensitivity analysis (DSA) computes sensitivity of the input random variables with respect to the change in distribution of output response. Although DSA is widely appreciated as the best tool for sensitivity analysis, the computational issue associated with this method prohibits its use for complex structures involving costly finite element analysis. For addressing this issue, this paper presents a method that couples polynomial correlated function expansion (PCFE) with DSA. PCFE is a fully equivalent operational model which integrates the concepts of analysis of variance decomposition, extended bases and homotopy algorithm. By integrating PCFE into DSA, it is possible to considerably alleviate the computational burden. Three examples are presented to demonstrate the performance of the proposed approach for sensitivity analysis. For all the problems, proposed approach yields excellent results with significantly reduced computational effort. The results obtained, to some extent, indicate that proposed approach can be utilized for sensitivity analysis of large scale structures. - Highlights: • A hybrid approach for global sensitivity analysis is proposed. • Proposed approach integrates PCFE within distribution based sensitivity analysis. • Proposed approach is highly efficient.
Availability note (English)
Available from http://dx.doi.org/10.1016/j.ress.2016.10.013Additional details
Identifiers
- DOI
- 10.1016/j.ress.2016.10.013;
- PII
- S0951-8320(16)30664-0;
Publishing Information
- Journal Title
- Reliability Engineering and System Safety
- Journal Volume
- 158
- Journal Page Range
- p. 50-57
- ISSN
- 0951-8320
- CODEN
- RESSEP
INIS
- Country of Publication
- United Kingdom
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 48063231
- Subject category
- S42: ENGINEERING;
- Descriptors DEI
- ALGORITHMS; CORRELATION FUNCTIONS; DISTRIBUTION; FINITE ELEMENT METHOD; MECHANICS; PERFORMANCE; POLYNOMIALS; RANDOMNESS; SENSITIVITY ANALYSIS
- Descriptors DEC
- CALCULATION METHODS; FUNCTIONS; MATHEMATICAL LOGIC; MATHEMATICAL SOLUTIONS; NUMERICAL SOLUTION
Optional Information
- Copyright
- Copyright (c) 2016 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.