Fatigue life prediction of aero engine blade tenons based on the second-order HDMR-SCN method

Aero-engine blade tenons are prone to fatigue fracture, and accurately assessing their fatigue life is difficult. This study proposes a second-order high-dimensional model representation (HDMR) and stochastic configured network (SCN) method for predicting fatigue crack propagation life under different parameter transformations. The effectiveness of the finite element analysis method is verified through experimental and numerical analyses of the crack-propagation behavior of DD6 material. Four key characteristic parameters affecting the crack life of the tenon are identified, and a surrogate model for the crack propagation life of the tenon is established. The results show that the constructed surrogate model achieves high prediction accuracy and computational efficiency, with the relative error between predicted and actual values controlled at 5%. This method provides a useful approach for assessing the fatigue crack propagation life of critical components in aero-engines.