«
»

Latent-space Dynamics for Reduced Deformable Simulation

Lawson Fulton, Vismay Modi, David Duvenaud, David I. W. Levin, Alec Jacobson

We propose the first reduced model simulation framework for deformable solid dynamics using autoencoder neural networks.We provide a data-driven approach to generating nonlinear reduced spaces for deformation dynamics. In contrast to previous methods using machine learning which accelerate simulation by approximating the time-stepping function, we solve the true equations of motion in the latent-space using a variational formulation of implicit integration. Our approach produces drastically smaller reduced spaces than conventional linear model reduction, improving performance and robustness. Furthermore,our method works well with existing force-approximation cubature methods.

Latent-space Dynamics for Reduced Deformable Simulation

Posted by christopherbatty on May 8th, 2019 Posted in Uncategorized
(Comments are closed)