A decoupling algorithm with first-order asymptotic integration for reliability-based design optimization

Conventional decoupling approaches usually employ first-order reliability method to deal with probabilistic constraints in a reliability-based design optimization problem. In first-order reliability method, constraint functions are transformed into a standard normal space. Extra non-linearity introd...

Full description

Bibliographic Details
Main Authors: Zhiliang Huang, Tongguang Yang, Fangyi Li
Format: Article
Language:English
Published: SAGE Publishing 2018-09-01
Series:Advances in Mechanical Engineering
Online Access:https://doi.org/10.1177/1687814018793336
Description
Summary:Conventional decoupling approaches usually employ first-order reliability method to deal with probabilistic constraints in a reliability-based design optimization problem. In first-order reliability method, constraint functions are transformed into a standard normal space. Extra non-linearity introduced by the non-normal-to-normal transformation may increase the error in reliability analysis and then result in the reliability-based design optimization analysis with insufficient accuracy. In this article, a decoupling approach is proposed to provide an alternative tool for the reliability-based design optimization problems. To improve accuracy, the reliability analysis is performed by first-order asymptotic integration method without any extra non-linearity transformation. To achieve high efficiency, an approximate technique of reliability analysis is given to avoid calculating time-consuming performance function. Two numerical examples and an application of practical laptop structural design are presented to validate the effectiveness of the proposed approach.
ISSN:1687-8140