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Found 4 papers, 1 papers with code
A deep learning energy method for hyperelasticity and viscoelasticity
The potential energy formulation and deep learning are merged to solve partial differential equations governing the deformation in hyperelastic and viscoelastic materials.
Topology optimization of 2D structures with nonlinearities using deep learning
We have considered the case of materials with a linear elastic response with and without stress constraint.
Deep Learning Enabled Strain Mapping of Single-Atom Defects in 2D Transition Metal Dichalcogenides with Sub-picometer Precision
2D materials offer an ideal platform to study the strain fields induced by individual atomic defects, yet challenges associated with radiation damage have so-far limited electron microscopy methods to probe these atomic-scale strain fields.
Materials Science Mesoscale and Nanoscale Physics
Prediction and optimization of mechanical properties of composites using convolutional neural networks
Once the training process is completed, the developed model is validated using data unseen during training.
