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An improved two-stage framework of evidence-based design optimization

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Abstract

In this paper, an improved two-stage framework is presented to handle the evidence-based design optimization (EBDO) problem under epistemic uncertainty. The improvements include two aspects: (1) in the first stage, the equal areas method is employed to transform evidence variables into random variables, which avoids the assumption that unknown evidence variables and parameters obey the normal distribution. Then, a reliability-based design optimization (RBDO) problem with random variables is defined and solved by the sequential optimization and reliability assessment (SORA) method; (2) in the second stage, an improved algorithm is presented, which can calculate the plausibility of constraint violation more efficiently by continuously recording the minimum and maximum values of limit-state functions. The computational accuracy and efficiency of the improved framework are tested by numerical and engineering examples.

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Abbreviations

RBDO:

Reliability-based design optimization

EBDO:

Evidence-based design optimization

FD:

Frame of discernment

BPA:

Basic probability assignment

Bel :

Belief

Pl :

Plausibility

SORA:

Sequential optimization and reliability assessment

HMV:

Hybrid mean value

MPTP:

Minimum performance target point

PDF:

Probability density function

RBF:

Radial basis functions

ND:

Normal distribution

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Acknowledgements

This research was supported by the National Natural Science Foundation of China [grant numbers 51675196 and 51721092].

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Authors and Affiliations

  1. State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China

    Jinhao Zhang, Mi Xiao, Liang Gao, Haobo Qiu & Zan Yang

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  1. Jinhao Zhang
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  2. Mi Xiao
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  3. Liang Gao
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  4. Haobo Qiu
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  5. Zan Yang
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Corresponding author

Correspondence to Mi Xiao.

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Responsible Editor: Jianbin Du

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Zhang, J., Xiao, M., Gao, L. et al. An improved two-stage framework of evidence-based design optimization. Struct Multidisc Optim 58, 1673–1693 (2018). https://doi.org/10.1007/s00158-018-1991-6

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  • DOI: https://doi.org/10.1007/s00158-018-1991-6

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