A mesh-free KAN-PINN method for solving nonlinear strain-limiting partial differential equations, featuring exact hard boundary ansatz and pseudo-Huber residual loss for enhanced training stability.
See LICENSE filePhysics-Informed Neural NetworksQuasi-linear PDEStrain-limiting
DeepFEAv2 applies deep learning surrogate models to transient finite element analysis on unstructured meshes, enabling joint prediction of node-based and element-based outputs to reduce computational cost in structural mechanics.
See LICENSE fileFinite Element AnalysisDeep LearningTransient Simulation
A conditional diffusion approach to structural topology optimization from MIT that uses surrogate-model guidance to optimise both mechanical compliance and manufacturability, outperforming conditional GANs by a wide margin.
arXiv preprint (code and data publicly available)Topology OptimizationDiffusion ModelGenerative Design
