The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Correlation-Based Transition Modeling for Unstructured Parallelized Computational Fluid Dynamics Codes
Abstract
A new correlation-based transition model has been developed, which is built strictly on local variables. As a result, the transition model is compatible with modern computational fluid dynamics techniques such as unstructured grids and massively parallel execution. The model is based on two transport equations, one for intermittency and one for a transition onset criterion in terms of momentum-thickness Reynolds number. A number of validation papers have been published on the basic formulation of the model. However, until now the full model correlations have not been published. The main goal of the present paper is to publish the full model and release it to the research community so that it can continue to be further validated and possibly extended or improved. Included in this paper are a number of test cases that can be used to validate the implementation of the model in a given computational fluid dynamics code. The authors believe that the current formulation is a significant step forward in engineering transition modeling, as it allows the combination of transition correlations with general-purpose computational fluid dynamics codes. There is a strong potential that the model will allow the first-order effects of transition to be included in everyday industrial computational fluid dynamics simulations.
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Citations
Cites
Two-equation eddy-viscosity turbulence models for engineering applications
Menter, F. R. (1994) · AIAA Journal · doi:10.2514/3.12149 · Cited by 21,593
Self-citationA Correlation-Based Transition Model Using Local Variables—Part I: Model Formulation
Menter, F. R., Langtry, R. B., Likki, S. R., Suzen, Y. B., Huang, P. G., & Völker, S. (2006) · Journal of Turbomachinery · doi:10.1115/1.2184352 · Cited by 1,485
Self-citationViscous-inviscid analysis of transonic and low Reynolds number airfoils
Drela, M., & Giles, M. B. (1987) · AIAA Journal · doi:10.2514/3.9789 · Cited by 1,097
The calculation of low-Reynolds-number phenomena with a two-equation model of turbulence
Jones, W. P., & Launder, B. E. (1973) · International Journal of Heat and Mass Transfer · doi:10.1016/0017-9310(73)90125-7 · Cited by 1,000
Transition Modelling for General Purpose CFD Codes
Menter, F. R., Langtry, R., & Völker, S. (2006) · Flow, Turbulence and Combustion · doi:10.1007/s10494-006-9047-1 · Cited by 692
Self-citationLangtry, R. B., Menter, F. R., Likki, S. R., Suzen, Y. B., Huang, P. G., & Völker, S. (2006) · Journal of Turbomachinery · doi:10.1115/1.2184353 · Cited by 529
Self-citationDesign and experimental results for the S809 airfoil
Somers, D. M. (1997) · doi:10.2172/437668 · Cited by 458
TRANSITION MODELLING BASED ON LOCAL VARIABLES
Menter, F. R., Esch, T., & Kubacki, S. (2002) · Engineering Turbulence Modelling and Experiments 5 · doi:10.1016/b978-008044114-6/50053-3 · Cited by 168
Self-citationSuzen, Y. B., Huang, P. G., Hultgren, L. S., & Ashpis, D. E. (2003) · Journal of Turbomachinery · doi:10.1115/1.1580159 · Cited by 124
Langtry, R., Gola, J., & Menter, F. R. (2006) · AIAA Aerospace Sciences Meeting and Exhibit · doi:10.2514/6.2006-395 · Cited by 115
Self-citation
Cited by
RANS turbulence model development using CFD-driven machine learning
Zhao, Y., Akolekar, H. D., Weatheritt, J., Michelassi, V., & Sandberg, R. D. (2020) · Journal of Computational Physics · doi:10.1016/j.jcp.2020.109413 · Cited by 303
Metadata
- Authors
- Langtry, R. B., & Menter, F. R.
- Venue
- AIAA Journal
- Published
- 2009-12
- Volume
- 47
- Issue
- 12
- Pages
- 2894-2906
- ISSN
- 0001-1452 (ISSN-L)
- 1533-385X
- OpenAlex
- W1983457630
- Cited by
- 1,527
- References
- 11
- FWCI
- 15.85
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.