
Deep Neural Network Hyperelasticity
Deep Neural Networks is a powerful Machine Learning method. In this article I will show how to create a hyperelastic model using ML.
We create essential tools for your finite element (FE) analysis! MCalibration® can quickly calibrate almost any material model. The PolyUMod® library is a plugin to your FE solver that contains the most accurate material models available!
Experimentally measure the mechanical response of your material using basic mechanical tests.
Read in all experimental data files into MCalibration. Select a suitable PolyUMod or native material model. Click Optimize. MCalibration will do the rest.
Import the MCalibration material model into your FE solver. Then run your FE simulation as usual.
In many important applications the material response is sufficiently non-linear that simple hyperelasticity or metal plasticity is not good enough. In these cases the PolyUMod library can be very useful since it contains a selection of the most advanced and accurate material models that are currently available. The PolyUMod library is easy to use and can give you a significant competitive advantage!
Selecting and calibrating a suitable material model can be very challenging. The MCalibration software makes that task easy! It can calibrate all PolyUMod material models, and most built-in models in FE solvers.
Deep Neural Networks is a powerful Machine Learning method. In this article I will show how to create a hyperelastic model using ML.
This article is part 2 in my series on continuum mechanics. The focus is on invariants, vectors, and tensors.
This article is part 1 of my series on continuum mechanics. The focus is on kinematics and the deformation gradient.