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An efficient and robust adaptive Kriging for structural reliability analysis
- Source :
- Structural and Multidisciplinary Optimization. 62:3189-3204
- Publication Year :
- 2020
- Publisher :
- Springer Science and Business Media LLC, 2020.
-
Abstract
- Even though extensive efforts have been made, structural reliability analysis method with both efficiency and robustness is still infrequent in engineering especially when time-consuming numerical models are involved. To address the issue, this paper develops multi-ring-based important sampling (MRIS) and incorporates it into the Kriging-based reliability analysis method authors previously proposed. MRIS can uniformly fill the region of importance with an acceptable number of random points regardless of the number of most probable points and failure sub-domains of investigated structure. As MRIS does not need to evaluate Kriging model during sampling random points, its efficiency does not decrease with increasing the training points of Kriging model, which is a substantial advantage. Therefore, it is used as an optimization method to search for the best next point so as to adaptively increase the accuracy of Kriging model. Additionally, the failure probability predicted by Kriging model and its corresponding accuracy measure are roughly calculated with MRIS. Both of them are essential to judge whether Kriging model meets with a prescribed requirement. Four benchmark examples verify the accuracy, efficiency, and robustness of the proposed reliability analysis method.
- Subjects :
- Measure (data warehouse)
Control and Optimization
Computer science
0211 other engineering and technologies
Sampling (statistics)
02 engineering and technology
computer.software_genre
Computer Graphics and Computer-Aided Design
Computer Science Applications
020303 mechanical engineering & transports
0203 mechanical engineering
Control and Systems Engineering
Robustness (computer science)
Kriging
Benchmark (computing)
Point (geometry)
Data mining
Engineering design process
computer
Software
Reliability (statistics)
021106 design practice & management
Subjects
Details
- ISSN :
- 16151488 and 1615147X
- Volume :
- 62
- Database :
- OpenAIRE
- Journal :
- Structural and Multidisciplinary Optimization
- Accession number :
- edsair.doi...........da60b0095657a9683ef85a62ca64ee31
- Full Text :
- https://doi.org/10.1007/s00158-020-02666-5