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207mm apart. 171. The cone surfaces were also created based on the randomly-rough surfaces. The cone surfaces were created with equivalent centerline averaged roughness, Ra = 1 N N ∑y i , values as their respective i =1 randomly-rough surfaces. Cone Surface Results The method presented concerning the reference surface and flow characteristics below the datum was made concerning a randomly-rough surface, but if the method presented can be used for randomly- rough surfaces, the method should also hold for surfaces with cone roughness-elements.
The layered representation of the Erosion 2 surface, the Erosion 2 Layered surface is shown in Figure 7. -12- Figure 6. Bitmap Image of the Deposit Layered Surface -13- Figure 7. Bitmap Image of the Erosion 2 Layered Surface Two cone surfaces, the Deposit Cone surface and the Erosion Cone surface, were also studied. These surfaces were used to validate the model developed by Taylor for non-sparse cone surfaces. 969 mm. 065- mm apart. 730. 445 mm. 207mm apart. 171. The cone surfaces were also created based on the randomly-rough surfaces.
The Erosion 2 Layered surface is also in agreement with the raw experimental data, and would not be changed much by considering temperature drop along the blockages. The Erosion 2 Layered surface is sparse and has very small diameter roughness elements that look like pin fins. While the blockage elements may have a moderately low “pin fin” efficiencies, the surface would have a high surface efficiency because it is sparse. Thus, considering temperature loss along the Erosion 2 Layered surface would not significantly change its average Stanton number prediction.