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Open Access

Hybrid Structure Reliability Analysis Based on the Damped Newton Method

Hongwei Zheng, Guangwei Meng, Feng Li( ), Tonghui Wei, Wei Luo, Yaming Guo
School of Mechanical and Aerospace Engineeering, Jilin University, Changchun 130012, China.
School of Materials Science and Engineering, Jilin University, Changchun 130012, China.
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Abstract

This paper presents a hybrid model reliability analysis method based on the damped Newton method with both random and interval variables to solve the hybrid structure reliability problem. The method combines an outer iterative solution and inner layer numerical calculation. In the outer iteration, the method seeks an optimized solution to the interval variable iterative by adding the boundary constraint condition based on the damped Newton optimization theory. In the inner layer solution, the method first reduces the dimension of the random variable through the dimension reduction method, then obtains the first four-order central moment of the function through the application of the Taylor expansion method, and finally calculates the reliability index of the structure according to the fourth-order moment calculation structure of the function. The results of a numerical example and an engineering ten-rod truss structure show that the proposed method can effectively solve the random-interval hybrid reliability problem and has better calculation accuracy than that of the two-layer iterative method.

Keywords

random-interval variable hybrid modelreliability analysisdamped Newton optimizationsingle-layer iterationfourth-order moment method

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Tsinghua Science and Technology
Volume 25 Issue 5,
October 2020
Pages 668-677
DOI: 10.26599/TST.2019.9010073
Cite this article:
Zheng H, Meng G, Li F, et al. Hybrid Structure Reliability Analysis Based on the Damped Newton Method. Tsinghua Science and Technology, 2020, 25(5): 668-677. https://doi.org/10.26599/TST.2019.9010073

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Received: 15 September 2019
Revised: 09 November 2019
Accepted: 03 December 2019
Published: 16 March 2020
© The author(s) 2020

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
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