NC SHAPE APPLICATION IN ELECTROMAGNETICS
Shape can handle outputs from EM solvers in order to train Neural Networks models. Once the models are trained, predictions can be made directly from a CAD design from design parameters.
Shape can handle outputs from ANSYS, Maxwell, or CST from Simulia, for training Neural Network models. Once the models are trained, predictions can be made directly from a CAD design, or from design parameters.
DESIGN OF ELECTRONIC COMPONENTS
Electromagnetic simulations are key to the electrification of vehicles and IT hardware simulation.
Shape can become an essential component of your CAE toolchain in these domains for the design of electronic components.
ADVANCED AND REFINED SHAPES
Optimize the electric powertrain with the optimization module.
The optimization module within Shape has the flexibility to produce shapes as advanced and refined as you would obtain with a standard topology optimizer, but does not restrain the application field to fast, simple, linear simulation. We can take into account fatigue or contact issues.