Efficient probabilistic methods for real-time fatigue damage prognosis

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Published Oct 10, 2010
Yibing Xiang Yongming Liu

Abstract

A general probabilistic fatigue crack growth prediction methodology for accurate and efficient damage prognosis is proposed in this paper. This methodology consists two major parts. First, the realistic random loading is transformed to an equivalent constant amplitude loading process based on a recently developed mechanism model. This transformation avoids the cycle-by-cycle calculation of fatigue crack growth under variable amplitude loading. Following this, an inverse first-order reliability method (IFORM) is used to evaluate the fatigue crack growth at an arbitrary reliability level. Inverse FORM method does not require a large number of function evaluations compared to the direct Monte Carlo simulation. Computational cost is significantly reduced and the proposed method is very suitable for real-time damage prognosis. Numerical examples are used to demonstrate the proposed method. Various experimental data under variable amplitude loading are collected and model predictions are compared with experimental data for model validation.

How to Cite

Xiang, Y. ., & Liu, Y. . (2010). Efficient probabilistic methods for real-time fatigue damage prognosis. Annual Conference of the PHM Society, 2(1). https://doi.org/10.36001/phmconf.2010.v2i1.1895
Abstract 351 | PDF Downloads 170

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Keywords

fatigue crack growth, probabilistic, variable amplitude, equivalent stress level

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Xiang, Y., & Liu, Y. (2010 (accepted) ) Inverse first-order reliability method for probabilistic fatigue life prediction of composite laminates under multiaxial loading. ASCE Journal of Aerospace Engineering.
Section
Technical Research Papers

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