Predicting fatigue crack growth through the small and long crack regimes for a military transport aircraft loading spectrum using FASTRAN

Predicting fatigue crack growth across the small and long crack regimes in airframe components is a challenging task. Current fracture mechanics methods require, amongst other things, high fidelity small crack growth rate data and a thorough understanding of the different behaviours of small and long cracks. This paper presents a case study where a fatigue crack growth prediction of Aluminium Alloy 7075-T7351 coupons tested to a military transport aircraft loading spectrum, from nucleation to failure, is attempted using the most recent version of the linear-elastic fracture mechanics-based analysis tool FASTRAN v5.76. The military transport aircraft loading spectrum was applied to different coupon configurations to show the effectiveness of FASTRAN for a range of crack growth scenarios. Crack growth rate data for the prediction in the near-threshold region was experimentally obtained from small cracks using quantitative fractography and this data is shown to be a determining factor in the accuracy of the prediction. This paper highlights the challenges faced by engineers in predicting fatigue crack growth under variable amplitude loading from nucleation to failure and demonstrates the ability of FASTRAN to accurately predict load history effects. Areas for continued improvement are identified with the aim of accurate and reliable fatigue crack growth prediction in a range of structures, conditions, and scenarios.

Automated summary

This paper attempts to predict fatigue crack growth of Aluminium Alloy 7075-T7351 from nucleation to failure using the latest version of the linear-elastic fracture mechanics-based analysis tool FASTRAN v5.76. It demonstrates the effectiveness of FASTRAN for different crack growth scenarios and highlights the challenges faced in predicting fatigue crack growth under variable amplitude loading. The paper also identifies areas for improvement in order to achieve accurate and reliable prediction of fatigue crack growth in various structures, conditions, and scenarios.