Dimensionality reduction enhances data-driven reliability-based design optimize

Abstract

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.

Keywords

• reliability-based design optimization
• uncertain input distribution
• reliability with confidence
• dimensionality reduction
• principal component analysis