A stochastic fatigue damage model for composite single lap shear joints based on Markov chains and thermoelastic stress analysis

摘要

Quantitative damage detection in composite single lap joints during fatigue is difficult and not practical with many traditional experimental methods. The objective of this study is to combine a new experimental analysis method with existing stochastic models that is capable of taking the scatter inherent in composite fatigue data into account for better representation of damage evolution in single-lap joints. This study presents a new quantitative approach where thermoelastic stress analysis (TSA), a remote sensing and non-destructive evaluation technique, is used for in situ continuous monitoring for fatigue damage detection of Fibre Reinfoced Polymeric (FRP) S2-glass/E733FR single-lap joints. Image analysis algorithms are developed to capture the debonding fronts, and Markov Chain models (MCMs) are developed to capture the fatigue damage evolution in composite lap-joints based on the experimental analysis. The TSA damage index at the last fatigue cycle is used to calibrate the MCMs, and damage predictions using the MCMs are then examined at different fatigue cycles. Methods to construct a predictive stochastic S-N curve utilizing the MCMs are discussed. The proposed IR-TSA with MCMs is shown to be very effective in predicting the damage evolution and allowed constructing S-N curves that take the variability into account for damage in composite single-lap joints.