Abstract
Due to the uncertainties originating from the underlying physical model, material properties and the measurement data in fatigue crack growth (FCG) processing, the prediction of fatigue crack growth lifetime is still challenging. The objective of this paper was to investigate a methodology for uncertainty quantification in FCG analysis and probabilistic remaining useful life prediction. A small-timescale growth model for the fracture mechanics-based analysis and predicting crack-growth lifetime is studied. A stochastic collocation method is used to alleviate the computational difficulties in the uncertainty quantification in the small-timescale model-based FCG analysis, which is derived from tensor products based on the solution of deterministic FCG problems on sparse grids of collocation point sets in random space. The proposed method is applied to the prediction of fatigue crack growth lifetime of Al7075-T6 alloy plates and verified by fatigue crack-growth experiments. The results show that the proposed method has the advantage of computational efficiency in uncertainty quantification of remaining life prediction of FCG.
Highlights
Fatigue damage is among the most common failure modes in structural safety
This paper focuses on the remaining useful life prognosis taking into account the uncertainties in fatigue crack growth (FCG) analysis
A stochastic collocation approach is developed for uncertainty quantification of remaining useful life prediction in small-timescale FCG model
Summary
Fatigue damage is among the most common failure modes in structural safety. It refers to the performance degradation process of structural materials due to cyclic loading. The fatigue damage process accumulates from small crack initiation, propagates to macro cracks and leads to structural failure under certain conditions. The prognosis of fatigue damage plays a critical role in estimating an engineering system’s remaining useful life based on the damage evolution model [1]. Sources of uncertainties widely exist in the process of fatigue propagation analysis, including the variability in material properties, experimental errors, variation in loading conditions and model inaccuracy [2]. This paper focuses on the remaining useful life prognosis taking into account the uncertainties in fatigue crack growth (FCG) analysis
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