Details
| Original language | English |
|---|---|
| Article number | 101936 |
| Journal | Structural Safety |
| Volume | 84 |
| Early online date | 5 Feb 2020 |
| Publication status | Published - May 2020 |
Abstract
The non-intrusive imprecise stochastic simulation (NISS) is a general framework for the propagation of imprecise probability models and analysis of reliability. The most appealing character of this methodology framework is that, being a pure simulation method, only one precise stochastic simulation is needed for implementing the method, and the requirement of performing optimization analysis on the response functions can be elegantly avoided. However, for rare failure events, the current NISS methods are still computationally expensive. In this paper, the classical line sampling developed for precise stochastic simulation is injected into the NISS framework, and two different imprecise line sampling (ILS) methods are developed based on two different interpretations of the classical line sampling procedure. The first strategy is devised based on the set of hyperplanes introduced by the line sampling analysis, while the second strategy is developed based on an integral along each individual line. The truncation errors of both methods are measured by sensitivity indices, and the variances of all estimators are derived for indicating the statistical errors. A test example and three engineering problems of different types are introduced for comparing and demonstrating the effectiveness of the two ILS methods.
Keywords
- Aleatory uncertainty, Epistemic uncertainty, Imprecise probability models, Line sampling, Sensitivity analysis, Uncertainty quantification
ASJC Scopus subject areas
- Engineering(all)
- Civil and Structural Engineering
- Engineering(all)
- Building and Construction
- Engineering(all)
- Safety, Risk, Reliability and Quality
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In: Structural Safety, Vol. 84, 101936, 05.2020.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Non-intrusive imprecise stochastic simulation by line sampling
AU - Song, Jingwen
AU - Valdebenito, Marcos
AU - Wei, Pengfei
AU - Beer, Michael
AU - Lu, Zhenzhou
N1 - Funding Information: This work is supported by National Natural Science Foundation of China (NSFC) under grant number 51905430 . The first author is supported by the program of China Scholarship Council (CSC). The second and third authors are both supported by the Alexander von Humboldt Foundation of Germany. The second author also acknowledges the support by CONICYT ( National Commission for Scientific and Technological Research ) under grant number 1180271 .
PY - 2020/5
Y1 - 2020/5
N2 - The non-intrusive imprecise stochastic simulation (NISS) is a general framework for the propagation of imprecise probability models and analysis of reliability. The most appealing character of this methodology framework is that, being a pure simulation method, only one precise stochastic simulation is needed for implementing the method, and the requirement of performing optimization analysis on the response functions can be elegantly avoided. However, for rare failure events, the current NISS methods are still computationally expensive. In this paper, the classical line sampling developed for precise stochastic simulation is injected into the NISS framework, and two different imprecise line sampling (ILS) methods are developed based on two different interpretations of the classical line sampling procedure. The first strategy is devised based on the set of hyperplanes introduced by the line sampling analysis, while the second strategy is developed based on an integral along each individual line. The truncation errors of both methods are measured by sensitivity indices, and the variances of all estimators are derived for indicating the statistical errors. A test example and three engineering problems of different types are introduced for comparing and demonstrating the effectiveness of the two ILS methods.
AB - The non-intrusive imprecise stochastic simulation (NISS) is a general framework for the propagation of imprecise probability models and analysis of reliability. The most appealing character of this methodology framework is that, being a pure simulation method, only one precise stochastic simulation is needed for implementing the method, and the requirement of performing optimization analysis on the response functions can be elegantly avoided. However, for rare failure events, the current NISS methods are still computationally expensive. In this paper, the classical line sampling developed for precise stochastic simulation is injected into the NISS framework, and two different imprecise line sampling (ILS) methods are developed based on two different interpretations of the classical line sampling procedure. The first strategy is devised based on the set of hyperplanes introduced by the line sampling analysis, while the second strategy is developed based on an integral along each individual line. The truncation errors of both methods are measured by sensitivity indices, and the variances of all estimators are derived for indicating the statistical errors. A test example and three engineering problems of different types are introduced for comparing and demonstrating the effectiveness of the two ILS methods.
KW - Aleatory uncertainty
KW - Epistemic uncertainty
KW - Imprecise probability models
KW - Line sampling
KW - Sensitivity analysis
KW - Uncertainty quantification
UR - http://www.scopus.com/inward/record.url?scp=85078907328&partnerID=8YFLogxK
U2 - 10.1016/j.strusafe.2020.101936
DO - 10.1016/j.strusafe.2020.101936
M3 - Article
AN - SCOPUS:85078907328
VL - 84
JO - Structural Safety
JF - Structural Safety
SN - 0167-4730
M1 - 101936
ER -