Turbulence Modeling

Turbulence Modeling Resource: The purpose of this site is to provide a central location where Reynolds-averaged Navier-Stokes (RANS) turbulence models are documented. This effort is guided by the Turbulence Model Benchmarking Working Group (TMBWG), a working group of the Fluid Dynamics Technical Committee of the American Institute of Aeronautics and Astronautics (AIAA). The objective is to provide a resource for CFD developers to: obtain accurate and up-to-date information on widely-used RANS turbulence models, and verify that models are implemented correctly. ...


References in zbMATH (referenced in 23 articles )

Showing results 1 to 20 of 23.
Sorted by year (citations)

1 2 next

  1. Bakhvalov, Pavel; Kozubskaya, Tatiana; Rodionov, Pavel: EBR schemes with curvilinear reconstructions for hybrid meshes (2022)
  2. Lodares, Diego; Manzanero, Juan; Ferrer, Esteban; Valero, Eusebio: An entropy-stable discontinuous Galerkin approximation of the Spalart-Allmaras turbulence model for the compressible Reynolds averaged Navier-Stokes equations (2022)
  3. Duben, A. P.; Kozubskaya, T. K.; Rodionov, P. V.; Tsvetkova, V. O.: EBR schemes with curvilinear reconstructions of variables in the near-wall region (2021)
  4. Erb, Aaron; Hosder, Serhat: Analysis and comparison of turbulence model coefficient uncertainty for canonical flow problems (2021)
  5. Harsude, Prakash; Naik, Kethavath Naveen; Chaudhury, Kaustav: Effect of spatially distributed wall concentration on the wall-flux of a passive scalar field in a laminar to turbulent transition boundary layer (2021)
  6. Kozlov, V. E.: Compressibility effectsy in one-equation turbulence models (2021)
  7. Qu, Feng; Sun, Di; Bai, Junqiang: Low-speed modification for the genuinely multidimensional Harten, Lax, van Leer and Einfeldt scheme in curvilinear coordinates (2021)
  8. Malikov, Z.: Mathematical model of turbulence based on the dynamics of two fluids (2020)
  9. Geneva, Nicholas; Zabaras, Nicholas: Quantifying model form uncertainty in Reynolds-averaged turbulence models with Bayesian deep neural networks (2019)
  10. Troshkin, O. V.; Kozlov, S. A.; Fortova, S. V.; Shepelev, V. V.; Eriklintsev, I. V.: Bifurcation model of the laminar-turbulent transition near a flat wall (2019)
  11. Vasconcelos, Artur G. R.; Albuquerque, Duarte M. S.; Pereira, José C. F.: A very high-order finite volume method based on weighted least squares for elliptic operators on polyhedral unstructured grids (2019)
  12. Bermejo, R.; Saavedra, L.: Local projection stabilized Lagrange-Galerkin methods for Navier-Stokes equations at high Reynolds numbers (2018)
  13. Liu, Xiaodong; Xia, Yidong; Luo, Hong: A reconstructed discontinuous Galerkin method for compressible turbulent flows on 3D curved grids (2018)
  14. Majewski, Jerzy; Szałtys, Piotr; Wyrozębski, Marcin: Residual distribution method for high Reynolds number simulations on complex geometries (2018)
  15. Plante, Frédéric; Laurendeau, Éric: Acceleration of Euler and RANS solvers via selective frequency damping (2018)
  16. Jalali, Alireza; Ollivier-Gooch, Carl: Higher-order unstructured finite volume RANS solution of turbulent compressible flows (2017)
  17. Bermejo, Rodolfo; Saavedra, Laura: A second order local projection Lagrange-Galerkin method for Navier-Stokes equations at high Reynolds numbers (2016)
  18. Bermejo, R.; Saavedra, L.: A second order in time local projection stabilized Lagrange-Galerkin method for Navier-Stokes equations at high Reynolds numbers (2016)
  19. Mueller, Jens-Dominik: Essentials of computational fluid dynamics (2016)
  20. De Santis, D.: High-order linear and non-linear residual distribution schemes for turbulent compressible flows (2015)

1 2 next