MeC-Meso-L

Purpose: train/evaluate CNNs for full-field failure-index prediction in tow-based discontinuous composites. Contents: 4000 specimens; 224×224 pixel 2D feature maps [Ex, Ey, Gxy, Vf, c2] and a 224×224 label map Failure index (Denoted FI in dataset). Generation: mesoscale finite-element simulations under uniform remote tension with explicit tow deposition. Use: supervised dense regression; standardize features per channel (training-set stats); report RMSE/SSIM (NRMSE for cross-dataset comparison).