Characterization and Prediction of Epoxy Resin Curing Behavior Using a Data-Driven Kinetic Model Based on Dual Kriging

A data-driven kinetic framework based on Dual Kriging is developed to represent epoxy curing behavior and supply a local cure-rate function for finite element (FE) analysis. Error-controlled compression reduces 7200 isothermal observations to 187 points, with maximum and mean normalized reconstruction errors of 0.45% and 0.069%, respectively. The compressed interpolant reproduces the E-51 conversion histories measured by differential scanning calorimetry (DSC), including their late-stage plateaus. A separable 245-node rate representation is implemented in a sequential thermo-chemo-mechanical analysis, combining E-51 experimental data at 55–70 °C with auxiliary Kamal–Sourour data at 30–50 °C. The two kinetics models produce similar temperature and strain histories during staged curing; both underestimate the measured temperature peak and late-stage contraction. Temperature interpolation is evaluated separately using independent DSC measurements for another epoxy system, with the rate model constructed entirely from experimental data. With the complete 70 °C curve withheld and six temperatures used for training, the peak-normalized rate root mean square error (RMSE) is 1.11%, and the apparent-conversion RMSE is 0.00271. Withholding each of the five interior temperatures in turn gives rate errors of 1.11–5.58%. Within this dataset, expanding the training-temperature set improves prediction more than increasing the node count along existing curves.