Time-Variant Reliability-Based Optimization with Double-Loop Kriging Surrogates

Author(s):  
Hongbo Zhang ◽  
Younes Aoues ◽  
Didier Lemosse ◽  
Hao Bai ◽  
Eduardo Souza De Cursi
Author(s):  
Ondřej Slowik ◽  
Drahomír Novák

Abstract The paper presents newly developed university software FNPO designed for reliability-based optimization. The program works with a newly proposed optimization method called Aimed Multilevel Sampling (AMS) in the optimization cycle of reliability-based optimization. For simulation at different levels of the algorithm AMS and reliability calculations program uses cyclic calls of program FReET - so called double-loop approach. The developed software enables to optimize model of general complexity with consideration of deterministic and/or reliability constraints.


2019 ◽  
Vol 78 (13) ◽  
pp. 1167-1177
Author(s):  
S. K. Pidchenko ◽  
A. A. Taranchuk ◽  
A. Totsky ◽  
V. B. Sharonov

2019 ◽  
Vol 55 (23) ◽  
pp. 1254-1255 ◽  
Author(s):  
Xiaojun Jin ◽  
Wei Zhang ◽  
Shiming Mo ◽  
Zhaobin Xu ◽  
Chaojie Zhang ◽  
...  

Author(s):  
S. Leventis ◽  
G. Papadopoulos ◽  
S. Koubias ◽  
J. Constantinides
Keyword(s):  

Symmetry ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 90
Author(s):  
Shufang Song ◽  
Lu Wang

Global sensitivity analysis (GSA) is a useful tool to evaluate the influence of input variables in the whole distribution range. Variance-based methods and moment-independent methods are widely studied and popular GSA techniques despite their several shortcomings. Since probability weighted moments (PWMs) include more information than classical moments and can be accurately estimated from small samples, a novel global sensitivity measure based on PWMs is proposed. Then, two methods are introduced to estimate the proposed measure, i.e., double-loop-repeated-set numerical estimation and double-loop-single-set numerical estimation. Several numerical and engineering examples are used to show its advantages.


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