Implementation, Realization and an Effective Solver of Two-Equation Turbulence Models
-
Published:2023-11-22
Issue:1
Volume:98
Page:
-
ISSN:0885-7474
-
Container-title:Journal of Scientific Computing
-
language:en
-
Short-container-title:J Sci Comput
Author:
Langer S.,Swanson R. C.
Abstract
AbstractCurrently, when the Reynolds-Averaged Navier–Stokes (RANS) equations are solved using turbulence modelling, most often the one-equation model of Spalart and Allmaras is used. Then, it is only necessary to solve the RANS equations in conjunction with a single transport equation for modeling turbulence. For this model, considerable assessment and analysis has been performed, allowing the possibility of a reliable solution method for an eddy viscosity required to compute the Reynolds stresses in the RANS equations. Such evaluation along with analysis has not been performed for similar performance with two-equation models of the $$k$$
k
-$$\omega $$
ω
type. The primary objective of this paper is to present and discuss the components of an effective numerical algorithm for solving the RANS equations and the two transport equations of $$k$$
k
-$$\omega $$
ω
type turbulence models. All the important details of the turbulence model as actually implemented are given, which is sometimes not done in various papers considering such modeling. The viability and effectiveness of this solution algorithm are demonstrated by solving both two-dimensional and three-dimensional aerodynamic flows. In all applications, a linear rate of convergence without oscillations or other evidence of unstable behavior is observed. This behavior is also particularly true when the proposed algorithm is applied to systematically refined mesh sequences, which is generally not observed with algorithms solving more than one transport equation. Thus numerical integration errors are systematically reduced, allowing for a significantly more reliable assessment of the effectiveness of the model itself. Additionally, in this paper analysis of the solution algorithm, including linear stability, is also performed for a particular flow problem.
Funder
Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)
Publisher
Springer Science and Business Media LLC
Subject
Computational Theory and Mathematics,General Engineering,Theoretical Computer Science,Software,Applied Mathematics,Computational Mathematics,Numerical Analysis
Reference51 articles.
1. Levy, D.W., Zickuhr, T., Vassburg, J., Agrawal, S., Wahls, R.A., Pirzadeh, S., Hemsch, M.J.: Summary of Data from the First AIAA CFD Drag Prediction Workshop. AIAA Paper 2002-0841 (2002) 2. Levy, D.W., Laflin, K.R., Tinoco, E.N., Vassberg, J.C., Mani, M., Rider, B., Rumsey, C.L., Wahls, R.A., Morrison, J.H., Brodersen, O.P., Crippa, S., Mavriplis, D.J., Murayama, M.: Summary of Data from the Fifth AIAA CFD Drag Prediction Workshop. In Proc. 51st AIAA Aerospace Sciences Meeting, Gravepine (Dallas/Ft. Worth Region), Texas, January 2013, Number 2013-0046 in Conference Proceeding Series. AIAA (2013) 3. Tinoco, E.N., Brodersen, O.P., Keye, S., Laflin, K.R., Feltrop, E., Vassberg, J.C., Mani, M., Rider, B., Wahls, R.A., Morrison, J.H., Hue, D., Roy, C.J., Mavriplis, D.J., Murayama, M.: Summary data from the 6th AIAA CFD drag prediction workshop: CRM cases. J. Aircr. 55(4), 1352–1379 (2018) 4. Derlaga, J.M., Morrison, J.H.: Statistical analysis of solutions from the sixth AIAA computational fluid dynamics drag prediction workshop. J. Aircr. 55(4), 1388–1400 (2019) 5. Rumsey, C.L., Slotnick, J.P., Long, M., Stuever, A.R., Wayman, T.R.: Summary of the first AIAA CFD high-lift prediction workshop. J. Aircr. 48(6), 2068–2079 (2011)
|
|