Uncertainty Quantification for Structural Optimal Design Based on Evidence Theory

doi:10.1007/s12204-015-1633-8

Abstract

Abstract: Uncertainty design can take account of aleatory and epistemic uncertainty in optimal processes. Aleatory uncertainty and epistemic uncertainty can be expressed as evidence theory uniformly, and evidence theory is used to describe the uncertainty. Transferring and response with evidence theory for structural optimal design are introduced. The principle of response evaluation is also set up. Finally, the cantilever beam in a test system is optimized in the introduced optimization process, and the results are estimated by the evaluation principle. The optimal process is validated after the optimization of beam.

Key words: aleatory uncertainty| epistemic uncertainty| optimal design| evidence theory

摘要： Uncertainty design can take account of aleatory and epistemic uncertainty in optimal processes. Aleatory uncertainty and epistemic uncertainty can be expressed as evidence theory uniformly, and evidence theory is used to describe the uncertainty. Transferring and response with evidence theory for structural optimal design are introduced. The principle of response evaluation is also set up. Finally, the cantilever beam in a test system is optimized in the introduced optimization process, and the results are estimated by the evaluation principle. The optimal process is validated after the optimization of beam.

关键词: aleatory uncertainty| epistemic uncertainty| optimal design| evidence theory

CLC Number:

TH 122

HU Sheng-yong* (胡盛勇), LUO Jun (罗军). Uncertainty Quantification for Structural Optimal Design Based on Evidence Theory[J]. Journal of shanghai Jiaotong University (Science), 2015, 20(3): 338-343.

References 10

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