Characterization and application of maximum entropy fatigue damage model based on digital image correlation and inverse analysis

In this study, a progress damage model that integrates the Maximum Entropy Fracture Model (MEFM) with the A -F kinematic hardening model is proposed to characterize the low -cycle fatigue damage behavior of metals. The MEFM establishes a correlation between the damage value and cumulative dissipation at the integration point through a damage accumulation parameter. Concurrently, the constitutive relationship of the material is delineated by the A -F kinematic hardening model. To shift enhance both efficiency and accuracy of obtaining model parameters, this study employs the inverse analysis techniques to derive damage accumulation parameter and material properties, departing from the conventional approach of experimental data fitting. Uniaxial tensile fatigue experiments were conducted on copper to validate the efficacy of the progressive damage model, which is also a key step in the process of inverse analysis. Digital Image Correlation (DIC) was employed to rectify the post-test displacement field, with the corrected displacement serving as a boundary condition in simulations. Comparisons between simulation results and experimental data highlight the capability of the developed progressive damage model. This model demonstrates effectiveness in predicting the formation and propagation of low -cycle fatigue damage in ductile metal materials, leading to ultimate failure.