A neural network surrogate predicts minimum peel force for a 90-degree skin-adhesive peel test from material and fracture parameters, matching FEM simulation outputs with R^2 of 0.94 on a held-out test set.
and Ma, Y ., Multifunctional Adhesive Hydrogels: From Design to Biomedical Applications
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Neural networks for the prediction of peel force for skin adhesive interface using FEM simulation
A neural network surrogate predicts minimum peel force for a 90-degree skin-adhesive peel test from material and fracture parameters, matching FEM simulation outputs with R^2 of 0.94 on a held-out test set.