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Fatigue Crack Growth Reliability Analysis by Stochastic Boundary Element Method

Xiyong Huang1, M. H. Aliabadi2, Z. Sharif Khodaei3

Department of Aeronautics, Imperial College London, South Kensington, London SW7 2AZ, U.K.
Department of Aeronautics, Imperial College London, South Kensington, London SW7 2AZ, U.K.E-mail: m.h.aliabadi@imperial.ac.uk
Department of Aeronautics, Imperial College London, South Kensington, London SW7 2AZ, U.K.E-mail: z.sharif-khodaei@imperial.ac.uk

Computer Modeling in Engineering & Sciences 2014, 102(4), 291-330. https://doi.org/10.3970/cmes.2014.102.291

Abstract

In this paper, a stochastic dual boundary element formulation is presented for probabilistic analysis of fatigue crack growth. The method involves a direct differentiation approach for calculating boundary and fracture response derivatives with respect to random parameters. Total derivatives method is used to obtain the derivatives of fatigue parameters with respect to random parameters. First- Order Reliability Method (FORM) is applied to evaluate the most probable point (MPP). Opening mode fatigue crack growth problems are used as benchmarks to demonstrate the performance of the proposed method.

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APA Style
Huang, X., Aliabadi, M.H., Khodaei, Z.S. (2014). Fatigue crack growth reliability analysis by stochastic boundary element method. Computer Modeling in Engineering & Sciences, 102(4), 291-330. https://doi.org/10.3970/cmes.2014.102.291
Vancouver Style
Huang X, Aliabadi MH, Khodaei ZS. Fatigue crack growth reliability analysis by stochastic boundary element method. Comput Model Eng Sci. 2014;102(4):291-330 https://doi.org/10.3970/cmes.2014.102.291
IEEE Style
X. Huang, M.H. Aliabadi, and Z.S. Khodaei, “Fatigue Crack Growth Reliability Analysis by Stochastic Boundary Element Method,” Comput. Model. Eng. Sci., vol. 102, no. 4, pp. 291-330, 2014. https://doi.org/10.3970/cmes.2014.102.291



cc Copyright © 2014 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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