Experimental Heat Transfer Coefficients from Ice-Roughened Surfaces for Aircraft Deicing Design

Dukhan, Nihad; Masiulaniec, K. C.; Witt, Kenneth J. De; Fossen, G. James Van

doi:10.2514/2.2556

Cited by 19 publications

(14 citation statements)

References 14 publications

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“…[1,2]. On the aircraft, ice accretion can lead to rough surface states [3][4][5]. In both cases the aerodynamic performance of the airfoil can be altered due to the presence of roughness.…”

Section: Introductionmentioning

confidence: 99%

On the importance of the drag coefficient modelling in the double averaged Navier-Stokes equations for prediction of the roughness effects

Chedevergne

Forooghi

2020

Journal of Turbulence

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The Discrete Element Method (DEM) for modeling of flow over rough walls is revised in the framework of the DANS (Double Averaged Navier-Stokes) equations, with a special focus on the drag term appearing in the mean momentum equation as a key to the robustness of the model. A set of 14 Direct Numerical Simulations (DNS) of channel flows with systematically varying roughness topographies is considered to assess the performances of different drag coefficient closures. While the standard model of Taylor et al. [J. Fluids Eng. 107 (1985), 251257] is found not to be successful in reproducing the distribution of the drag force, a new model is derived. The new model along with the model recently proposed by Kuwata et al. [ Int. J. Heat Fluid Flow 77 (2019), 186201] are employed for the solution of channel flow along with a simple mixing length model. Both models are shown to be successful in prediction of roughness function as long as a constant in the latter model is readjusted. The velocity profiles are also well recovered and in particular the roughness sublayers are accurately reproduced.

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“…[1,2]. On the aircraft, ice accretion can lead to rough surface states [3][4][5]. In both cases the aerodynamic performance of the airfoil can be altered due to the presence of roughness.…”

Section: Introductionmentioning

confidence: 99%

On the importance of the drag coefficient modelling in the double averaged Navier-Stokes equations for prediction of the roughness effects

Chedevergne

Forooghi

2020

Journal of Turbulence

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“…The data [26] demonstrate the benefits of the present AWF formulation in terms of ability to reproduce thermal effects due to roughness in configurations where h + s can be very large.…”

Section: Dukhan Et Al Experimentsmentioning

confidence: 58%

“…In the late 90's, ice shapes obtained in the NASA Icing Research Tunnel were copied and reproduced on flat plates by Dukhan et al [26]. The singularity of these experiments is that some of the rough elements correspond to remarkably large values of the equivalent sand grain height.…”

Section: Dukhan Et Al Experimentsmentioning

confidence: 99%

Analytical wall function including roughness corrections

Chedevergne

2018

International Journal of Heat and Fluid Flow

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Inspired by the work of Aupoix [1, 2] and relying on the analytical wall function of Suga et al. [3], this paper proposes a modified version of the wall model capable of accounting for roughness effects. The thermal correction was enhanced to capture roughness effects due to the increase of the wetted surface of the walls. A derivation of the model adapted to configurations with very large roughness is also proposed. The new model is compared to the former analytical wall function formulation using several rough configurations for which experimental data are available. The validation test cases have been chosen to highlight the improvements brought by the present work.

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“…Although useful for model calibration, these experiments are based on spherical roughness elements that are not necessarily representative of ice accretion roughness. The experimental results of Dukhan et al (1999) are more relevant for icing, and have been used by Radenac et al (2018) for extended rough wall model validation.…”

Section: Thermal Roughness Modelsmentioning

confidence: 99%

Comparison of turbulent Prandtl number correction models for the Stanton evaluation over rough surfaces

Morency

Beaugendre

2020

International Journal of Computational Fluid Dynamics

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In-flight ice accretion code predictions depend on heat loss over rough surfaces. The equivalent sand grain roughness models the friction coefficient, but an additional model is needed for heat transfer predictions. In this paper, a two parameters model based on a turbulent Prandtl number correction is derived from the sublayer Stanton-based model. For flow over rough surfaces, the new model predictions will be compared to a three parameters model from the literature. First, the models are coupled with the Spalart-Allmaras turbulence model to predict heat transfers over rough surfaces. Thereafter, the two models are implemented in the open source software, SU2, and then verified and validated for flow over rough flat plates. Lastly, the predictions of the two models are shown to be similar for ice accretion roughness on flat plates, airfoils and a wing. Model discrepancies are always within the experimental 15% error margin.

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Experimental Heat Transfer Coefficients from Ice-Roughened Surfaces for Aircraft Deicing Design

Cited by 19 publications

References 14 publications

On the importance of the drag coefficient modelling in the double averaged Navier-Stokes equations for prediction of the roughness effects

On the importance of the drag coefficient modelling in the double averaged Navier-Stokes equations for prediction of the roughness effects

Analytical wall function including roughness corrections

Comparison of turbulent Prandtl number correction models for the Stanton evaluation over rough surfaces

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