A deep energy method simulates fourth-order phase-field fracture in piezoresistive materials via one-way coupled electrical sensing after solving the mechanics-fracture problem.
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A Kolosov-Muskhelishvili informed neural network satisfies plane elasticity equations by construction, achieves sub-1% errors on benchmarks, and uses transfer learning to predict crack paths under multiple criteria with over 70% less training time.
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A multiphysics deep energy method for fourth-order phase-field fracture with piezoresistive self-sensing
A deep energy method simulates fourth-order phase-field fracture in piezoresistive materials via one-way coupled electrical sensing after solving the mechanics-fracture problem.
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Transfer-learned Kolosov-Muskhelishvili Informed Neural Networks for Fracture Mechanics
A Kolosov-Muskhelishvili informed neural network satisfies plane elasticity equations by construction, achieves sub-1% errors on benchmarks, and uses transfer learning to predict crack paths under multiple criteria with over 70% less training time.