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Yuri Frey Marioni, Enrique Alvarez de Toledo Ortiz, Andrea Cassinelli, Francesco Montomoli, Paolo Adami and Raul Vazquez
In this paper, we investigate the feasibility of using DNS data and machine learning algorithms to assist RANS turbulence model development. High-fidelity DNS data are generated with the incompressible Navier?Stokes solver implemented in the spectral/hp ...
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