Inverse Optimization of Failure Parameters of Carbon Fiber Laminates Under Low‐Velocity Impact

ABSTRACT Accurate simulation of low‐velocity impact (LVI) damage in Carbon Fiber Reinforced Polymer (CFRP) laminates remains challenging due to difficulties in calibrating non‐physical failure parameters. This study develops an efficient inverse optimization framework integrating experimental data and numerical simulation. Drop‐weight impact tests at three energy levels provided benchmark force‐time responses and damage data. The key innovation applies a Global Response Search Methodology (GRSM) with LS‐DYNA simulations to inversely identify the optimal values of the critical failure strain parameters by minimizing the absolute area difference between experimental and simulated force‐time curves. Results confirm that the optimized parameters substantially enhance prediction accuracy: Pearson correlation coefficients exceed 0.97, peak force deviations decrease significantly, and key features including force plateaus and damage progression are captured more realistically. Additionally, the role of the failure parameters in the simulation was analyzed. This GRSM‐based inverse framework provides a reliable and efficient approach for calibrating MAT 54 material models, offering a cost‐effective alternative to traditional trial‐and‐error methods.