Generalized Roughness Effects on Turbulent Boundary Layer Heat Transfer. A Discrete Element Predictive Approach for Turbulent Flow Over Rough Surfaces

Author(s):  
Hugh W. Coleman ◽  
B. K. Hodge ◽  
Robert P. Taylor
1972 ◽  
Vol 56 (4) ◽  
pp. 741-752 ◽  
Author(s):  
G. T. Coleman ◽  
J. L. Stollery

A hypersonic gun tunnel has been used to measure the heat-transfer-rate distribution over a compression corner under turbulent boundary-layer conditions. Attached, incipient and separated flows are considered. The results are compared with other experimental data and with the predictions of a simple theory.


2018 ◽  
Vol 845 ◽  
pp. 417-461 ◽  
Author(s):  
Dong Li ◽  
Kun Luo ◽  
Jianren Fan

Direct numerical simulations of particle-laden flows in a spatially developing turbulent thermal boundary layer over an isothermally heated wall have been performed with realistic fully developed turbulent inflow boundary conditions. To the authors’ best knowledge, this is the first time the effects of inertial solid particles on turbulent flow and heat transfer in a flat-plate turbulent boundary layer have been investigated, using a two-way coupled Eulerian–Lagrangian method. Results indicate that the presence of particles increases the mean streamwise velocity and temperature gradients of the fluid in the near-wall region. As a result, the skin-friction drag and heat transfer are significantly enhanced in the particle-laden flows with respect to the single-phase flow. The near-wall sweep and ejection motions are suppressed by the particles and hence the Reynolds shear stress and wall-normal turbulent heat flux are attenuated, which leads to reductions in the production of the turbulent kinetic energy and temperature fluctuations. In addition, the coherence and spacing of the near-wall velocity and temperature streaky structures are distinctly increased, while the turbulent vortical structures appear to be disorganized under the effect of the particles. Moreover, the intensity of the streamwise vortices decreases monotonically with increasing particle inertia.


2008 ◽  
Vol 130 (2) ◽  
Author(s):  
J. P. Bons ◽  
S. T. McClain ◽  
Z. J. Wang ◽  
X. Chi ◽  
T. I. Shih

Skin friction (cf) and heat transfer (St) predictions were made for a turbulent boundary layer over randomly rough surfaces at Reynolds number of 1×106. The rough surfaces are scaled models of actual gas turbine blade surfaces that have experienced degradation after service. Two different approximations are used to characterize the roughness in the computational model: the discrete element model and full 3D discretization of the surface. The discrete element method considers the total aerodynamic drag on a rough surface to be the sum of shear drag on the flat part of the surface and the form drag on the individual roughness elements. The total heat transfer from a rough surface is the sum of convection on the flat part of the surface and the convection from each of the roughness elements. Correlations are used to model the roughness element drag and heat transfer, thus avoiding the complexity of gridding the irregular rough surface. The discrete element roughness representation was incorporated into a two-dimensional, finite difference boundary layer code with a mixing length turbulence model. The second prediction method employs a viscous adaptive Cartesian grid approach to fully resolve the three-dimensional roughness geometry. This significantly reduces the grid requirement compared to a structured grid. The flow prediction is made using a finite-volume Navier-Stokes solver capable of handling arbitrary grids with the Spalart-Allmaras (S‐A) turbulence model. Comparisons are made to experimentally measured values of cf and St for two unique roughness characterizations. The two methods predict cf to within ±8% and St within ±17%, the RANS code yielding slightly better agreement. In both cases, agreement with the experimental data is less favorable for the surface with larger roughness features. The RANS simulation requires a two to three order of magnitude increase in computational time compared to the DEM method and is not as readily adapted to a wide variety of roughness characterizations. The RANS simulation is capable of analyzing surfaces composed primarily of roughness valleys (rather than peaks), a feature that DEM does not have in its present formulation. Several basic assumptions employed by the discrete element model are evaluated using the 3D RANS flow predictions, namely: establishment of the midheight for application of the smooth wall boundary condition; cD and Nu relations employed for roughness elements; and flow three dimensionality over and around roughness elements.


Author(s):  
J. P. Bons ◽  
S. T. McClain ◽  
Z. J. Wang ◽  
X. Chi ◽  
T. I. Shih

Skin friction (cf) and heat transfer (St) predictions were made for a turbulent boundary layer over randomly rough surfaces at Reynolds number of 1 × 106. The rough surfaces are scaled models of actual gas turbine blade surfaces that have experienced degradation after service. Two different approximations are used to characterize the roughness in the computational model: the discrete element model and full 3-D discretization of the surface. The discrete element method considers the total aerodynamic drag on a rough surface to be the sum of shear drag on the flat part of the surface and the form drag on the individual roughness elements. The total heat transfer from a rough surface is the sum of convection on the flat part of the surface and the convection from each of the roughness elements. Correlations are used to model the roughness element drag and heat transfer thus avoiding the complexity of gridding the irregular rough surface. The discrete element roughness representation was incorporated into a two-dimensional, finite difference boundary layer code with a mixing length turbulence model. The second prediction method employs a viscous adaptive Cartesian grid approach to fully resolve the three-dimensional roughness geometry. This significantly reduces the grid requirement compared to a structured grid. The flow prediction is made using a finite-volume Navier-Stokes solver capable of handling arbitrary grids with the Spalart-Allmaras (S-A) turbulence model. Comparisons are made to experimentally measured values of cf and St for two unique roughness characterizations. The two methods predict cf to within ±8% and St within ±17%, the RANS code yielding slightly better agreement. In both cases, agreement with the experimental data is less favorable for the surface with larger roughness features. The RANS simulation requires a two to three order of magnitude increase in computational time compared to the DEM method and is not as readily adapted to a wide variety of roughness characterizations. The RANS simulation is capable of analyzing surfaces composed primarily of roughness valleys (rather than peaks), a feature that DEM does not have in its present formulation. Several basic assumptions employed by the discrete element model are evaluated using the 3D RANS flow predictions, namely: establishment of the mid-height for application of the smooth wall boundary condition, cD and Nu relations employed for roughness elements, and flow three-dimensionality over and around roughness elements.


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