Improving the Vector Basis Neural Network for RANS Equations Using Separate Trainings
<|reference_start|>Improving the Vector Basis Neural Network for RANS Equations Using Separate Trainings: We present a new data-driven turbulence model for Reynolds-averaged Navier-Stokes equations called $\nu_t$-Vector Basis Neural Network. This new model, grounded on the already existing Vector Basis Neural Network, predicts separately the turbulent viscosity $\nu_t$ and the contribution of the Reynolds force vector that is not already accounted in $\nu_t$. Numerical experiments on the flow in a Square Duct show the better accuracy of the new model compared to the reference one.<|reference_end|>
@article{oberto2024improving,
    title={Improving the Vector Basis Neural Network for RANS Equations Using
  Separate Trainings},
    author={Davide Oberto},
    journal={arXiv preprint arXiv:2409.17721},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.17721},
    primaryClass={physics.flu-dyn cs.NA math.NA}
}