Pure physics modeling is not enough for particularly complex applications. Once the physics-based VTS is tested, an additional component can be added to the architecture if the required accuracy is not achieved: the discrepancy model.

Our proprietary neural network has several benefits, designed to guarantee stability:

1. The user defines 4 simple hyperparameters, and the network can be trained with a single mouse click.

2. It ensures high accuracy under real-time operating variability, due to nonlinear effects, time-varying boundary conditions, or unmodelled effects. 

3. Captures unmodelled dynamics and disturbances not configured in the FEM problem definition.