\(S\)-frame discrepancy correction models for data-informed Reynolds stress closure
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Publication:2134488
DOI10.1016/j.jcp.2021.110717OpenAlexW3201508484MaRDI QIDQ2134488
Alireza Doostan, Riccardo Balin, Eric L. Peters, Kenneth E. Jansen, John A. Evans
Publication date: 3 May 2022
Published in: Journal of Computational Physics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2004.08865
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Invariant data-driven subgrid stress modeling in the strain-rate eigenframe for large eddy simulation, Invariant data-driven subgrid stress modeling on anisotropic grids for large eddy simulation
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- Quantifying and reducing model-form uncertainties in Reynolds-averaged Navier-Stokes simulations: a data-driven, physics-informed Bayesian approach
- RANS turbulence model development using CFD-driven machine learning
- Semidefinite programming versus the reformulation-linearization technique for nonconvex quadratically constrained quadratic programming
- The numerical computation of turbulent flows
- Analysis of variance designs for model output
- A novel evolutionary algorithm applied to algebraic modifications of the RANS stress-strain relationship
- Representation of stress tensor perturbations with application in machine-learning-assisted turbulence modeling
- Data-driven modelling of the Reynolds stress tensor using random forests with invariance
- A paradigm for data-driven predictive modeling using field inversion and machine learning
- Industrial application of RANS modelling: capabilities and needs
- Detached-Eddy Simulation
- On nonlinear K-l and K-ε models of turbulence
- Reassessment of the scale-determining equation for advanced turbulence models
- Computational Modeling of Turbulent Flows
- Predictions of Channel and Boundary-Layer Flows with a Low-Reynolds-Number Turbulence Model
- Progress in the development of a Reynolds-stress turbulence closure
- A more general effective-viscosity hypothesis
- On explicit algebraic stress models for complex turbulent flows
- Direct numerical simulation of backward-facing step flow at and expansion ratio 2
- DIRECT NUMERICAL SIMULATION: A Tool in Turbulence Research
- Sensitivity Analysis in Practice
- Reynolds-averaged Navier–Stokes equations with explicit data-driven Reynolds stress closure can be ill-conditioned
- Deep Learning: An Introduction for Applied Mathematicians
- Reynolds averaged turbulence modelling using deep neural networks with embedded invariance
- Numerical study of turbulent separation bubbles with varying pressure gradient and Reynolds number