Performance of the <i>k</i>-<i>kL</i> model for aerodynamics applications

Kalkote, Nikhil Narayan; Kumar, Ashutosh; Assam, Ashwani; Eswaran, V.

doi:10.1108/hff-07-2019-0570

Cited by 6 publications

(8 citation statements)

References 36 publications

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“…The implementations of the three fully turbulent RANS models in the PRAVAHA solver have been validated in previous work (Joshi et al , 2019; Sharma et al , 2020; Kalkote et al , 2019). The validation of the SA-BCM transition model implementation in the solver is presented below prior to the results of the airfoil stall simulations.…”

Section: Resultsmentioning

confidence: 99%

“…They also predict the separation point in flows involving mild adverse pressure gradient to a reasonable extent at a much lower computational expense than LES and hybrid RANS-LES. This can be seen from the work of Kalkote et al (2019), where a recently proposed two-equation k -kL model is shown to predict flows over high lift configurations of multi-element airfoils reasonably well. Nevertheless, the performance of RANS models deteriorates in the case of massively separated flows like the post-stall flow over airfoils (Shur et al, 1999;Strelets, 2001).…”

Section: Introductionmentioning

confidence: 85%

“…Unlike other two-equation models, the k -kL model solves an exact transport equation for the turbulent integral length scale (L) to better capture the effects of turbulence. This model is observed to perform better than the SA model in near-stall flow conditions of multi-element airfoils (Kalkote et al, 2019). Although the effects of transition are not significant at Re = 6 Â 10 6 , the recently proposed oneequation SA-BCM transition model (Çakmakçıo glu et al, 2020) is also included in the analysis to see its performance in flows where transition effects are negligible.…”

Section: Hff 324mentioning

confidence: 98%

“…All the RANS simulations shown in this study are performed on the Pravaha solver, which is an in-house unstructured grid finite-volume compressible flow solver developed by the authors’ research group at IIT Hyderabad (Joshi et al , 2019; Kalkote et al , 2019; Assam, 2019). The implicit solver has been equipped with an all-speed algorithm with low Mach preconditioning (Weiss et al , 1999) that allows the simulation of flows in the incompressible regime using the compressible form of the Navier–Stokes (NS) equations.…”

Section: Base Solver and Governing Equationsmentioning

confidence: 99%

“…The initial conditions are taken as the same as the far-field conditions in the entire domain. The model implementation in the solver has been thoroughly validated and tested for various aerodynamic flows (Kalkote et al , 2019).…”

Section: Reynolds-averaged Navier–stokes Turbulence Modelsmentioning

confidence: 99%

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On the performance of RANS turbulence models in predicting static stall over airfoils at high Reynolds numbers

Nived

Mukesh

Athkuri

et al. 2021

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Purpose This paper aims to conduct, a detailed investigation of various Reynolds averaged Navier–Stokes (RANS) models to study their performance in attached and separated flows. The turbulent flow over two airfoils, namely, National Advisory Committee for Aeronautics (NACA)-0012 and National Aeronautics and Space Administration (NASA) MS(1)-0317 with a static stall setup at a Reynolds number of 6 million, is chosen to investigate these models. The pre-stall and post-stall regions, which are in the range of angles of attack 0°–20°, are simulated. Design/methodology/approach RANS turbulence models with the Boussinesq approximation are the most commonly used cost-effective models for engineering flows. Four RANS models are considered to predict the static stall of two airfoils: Spalart–Allmaras (SA), Menter’s k – ω shear stress transport (SST), k – kL and SA-Bas Cakmakcioglu modified (BCM) transition model. All the simulations are performed on an in-house unstructured-grid compressible flow solver. Findings All the turbulence models considered predicted the lift and drag coefficients in good agreement with experimental data for both airfoils in the attached pre-stall region. For the NACA-0012 airfoil, all models except the SA-BCM over-predicted the stall angle by 2°, whereas SA-BCM failed to predict stall. For the NASA MS(1)-0317 airfoil, all models predicted the lift and drag coefficients accurately for attached flow. But the first three models showed even further delayed stall, whereas SA-BCM again did not predict stall. Originality/value The numerical results at high Re obtained from this work, especially that of the NASA MS(1)-0317, are new to the literature in the knowledge of the authors. This paper highlights the inability of RANS models to predict the stall phenomenon and suggests a need for improvement in modeling flow physics in near- and post-stall flows.

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Section: Resultsmentioning

confidence: 99%