260 citations · 327 across the 5 of their papers we have counts for
5 papers
CFD-driven Symbolic Identification of Algebraic Reynolds-Stress Models
I. Ben Hassan SaÏdi, M. Schmelzer, P. Cinnella +1
A CFD-driven deterministic symbolic identification algorithm for learning explicit algebraic Reynolds-stress models (EARSM) from high-fidelity data is developed building on the fro…
Data-driven RANS closures for three-dimensional flows around bluff bodies
Jasper P. Huijing, Richard P. Dwight, Martin Schmelzer
In this short note we apply the recently proposed data-driven RANS closure modelling framework of Schmelzer et al. (2020) to fully three-dimensional, high Reynolds number flows: na…
Customized data-driven RANS closures for bi-fidelity LES-RANS optimization
Yu Zhang, Richard P. Dwight, Martin Schmelzer +3
Multi-fidelity optimization methods promise a high-fidelity optimum at a cost only slightly greater than a low-fidelity optimization. This promise is seldom achieved in practice, d…
Discovery of Algebraic Reynolds-Stress Models Using Sparse Symbolic Regression
Martin Schmelzer, Richard P. Dwight, Paola Cinnella
** This article is published (open-access). ** A novel deterministic symbolic regression method SpaRTA (Sparse Regression of Turbulent Stress Anisotropy) is introduced to infer alg…
Stochastic turbulence modeling in RANS simulations via Multilevel Monte Carlo
Prashant Kumar, Martin Schmelzer, Richard P. Dwight
A multilevel Monte Carlo (MLMC) method for quantifying model-form uncertainties associated with the Reynolds-Averaged Navier-Stokes (RANS) simulations is presented. Two, high-dimen…