Dimensionality reduction enhances data-driven reliability-based design optimize

Autor: Yoshihiro KANNO
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Journal of Advanced Mechanical Design, Systems, and Manufacturing, Vol 14, Iss 1, Pp JAMDSM0008-JAMDSM0008 (2020)
Druh dokumentu: article
ISSN: 1881-3054
DOI: 10.1299/jamdsm.2020jamdsm0008
Popis: A recently proposed data-driven approach to reliability-based design optimization of structures constructs a sufficient condition that the target reliability is guaranteed with the specified confidence level, without relying on any assumptions on statistical information of random variables. In general, there exists a gap between this sufficient condition and the original confidence-level constraint. This paper presents a simple dimensionality reduction technique that can possibly mitigate this gap. This technique is applied to the compliance constraint with the uncertain external load. Numerical experiments on truss and continuum examples demonstrate that the proposed method can drastically reduce the over-conservativeness of the original method.
Databáze: Directory of Open Access Journals