Hasna Fadhila
A new non-linear RANS model with enhanced near-wall treatment of turbulence anisotropy
Fadhila, Hasna; Medina, Humberto; Aleksandrova, Svetlana; Benjamin, Stephen
Authors
HUMBERTO MEDINA HUMBERTO.MEDINA@NOTTINGHAM.AC.UK
Associate Professor
Svetlana Aleksandrova
Stephen Benjamin
Abstract
A new ω-based non-linear eddy-viscosity model is proposed. It was developed based on the original k−ω model and formulated using a quadratic stress-strain relation for the Reynolds stress tensor, with an added realisability condition. For enhanced treatment of near-wall turbulence anisotropy, a formulation that scales only with the turbulent Reynolds number is proposed for the first time. The new model has been implemented in the open-source Computational Fluid Dynamics (CFD) package OpenFOAM and validated against plane channel flow, a zero-pressure-gradient flat plate, and a U-bend curved channel configuration. To further assess the performance of the model for more complex geometries, it has been tested on configurations relevant to automotive applications. Overall, the new model outperforms the standard k−ω model. For example, on a curved channel, improved predictions for the minimum pressure and maximum skin friction of approximately 50% are obtained. Improved predictions are also obtained for quantities of practical engineering relevance, such as the pressure distribution along the wall of a sudden expansion diffuser, a configuration used to inform the design of automotive exhaust systems. This demonstrates that the proposed model has important practical applications for internal flows where anisotropic turbulence effects dominate.
Journal Article Type | Article |
---|---|
Acceptance Date | Jan 22, 2020 |
Online Publication Date | Jan 28, 2020 |
Publication Date | Jun 1, 2020 |
Deposit Date | Oct 6, 2023 |
Publicly Available Date | Nov 24, 2023 |
Journal | Applied Mathematical Modelling |
Print ISSN | 0307-904X |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 82 |
Pages | 293-313 |
DOI | https://doi.org/10.1016/j.apm.2020.01.056 |
Public URL | https://nottingham-repository.worktribe.com/output/25683569 |
Publisher URL | https://www.sciencedirect.com/science/article/abs/pii/S0307904X20300561?via%3Dihub |
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