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

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Abstract

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.

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APA

Huang, Z., Yang, T., & Li, F. (2018). A decoupling algorithm with first-order asymptotic integration for reliability-based design optimization. Advances in Mechanical Engineering, 10(9). https://doi.org/10.1177/1687814018793336

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