New correlation of roughness density effect on the turbulent boundary layer

Sigal, Asher; Danberg, James E.

doi:10.2514/3.10427

Cited by 167 publications

(77 citation statements)

References 13 publications

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“…Extensions to the solidity parameter have already appeared in the literature and, for irregular surfaces, van Rij et al [15] redefined the parameter introduced by Sigal and Danberg [14], previously given in Equation (4). A generalisation of this approach is to set…”

Section: Parametrisation Of Topographical Properties For U + and Tkementioning

confidence: 99%

“…The scarcity of data for three-dimensional roughness prevented the authors from developing a completely general model and as such their parameter is known to be better suited for two-dimensional roughness [13,14]. Through a series of channel flow experiments on smooth, patterned rough and completely rough surfaces, van Rij et al [15] proposed a more generalised form of the SigalDanberg parameter which could be applied to three-dimensional irregular roughness.…”

Section: Introductionmentioning

confidence: 99%

“…Sigal and Danberg [13,14] conducted a study to determine a suitable geometric correlation relating to the roughness density effect. Their relation was based on a database of results obtained by Schlichting's experiments [11] and 12 other regular roughness studies (see [13,14] and the references therein). Their new roughness density parameter, s , was given as…”

Section: Introductionmentioning

confidence: 99%

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Surface correlations of hydrodynamic drag for transitionally rough engineering surfaces

Thakkar

Busse

Sandham

2016

Journal of Turbulence

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Rough surfaces are usually characterised by a single equivalent sandgrain roughness height scale that typically needs to be determined from laboratory experiments. Recently, this method has been complemented by a direct numerical simulation approach, whereby representative surfaces can be scanned and the roughness effects computed over a range of Reynolds number. This development raises the prospect over the coming years of having enough data for different types of rough surfaces to be able to relate surface characteristics to roughness effects, such as the roughness function that quantifies the downward displacement of the logarithmic law of the wall. In the present contribution, we use simulation data for 17 irregular surfaces at the same friction Reynolds number, for which they are in the transitionally rough regime. All surfaces are scaled to the same physical roughness height. Mean streamwise velocity profiles show a wide range of roughness function values, while the velocity defect profiles show a good collapse. Profile peaks of the turbulent kinetic energy also vary depending on the surface. We then consider which surface properties are important and how new properties can be incorporated into an empirical model, the accuracy of which can then be tested. Optimised models with several roughness parameters are systematically developed for the roughness function and profile peak turbulent kinetic energy. In determining the roughness function, besides the known parameters of solidity (or frontal area ratio) and skewness, it is shown that the streamwise correlation length and the root-mean-square roughness height are also significant. The peak turbulent kinetic energy is determined by the skewness and rootmean-square roughness height, along with the mean forward-facing surface angle and spanwise effective slope. The results suggest feasibility of relating rough-wall flow properties (throughout the range from hydrodynamically smooth to fully rough) to surface parameters.

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Section: Parametrisation Of Topographical Properties For U + and Tkementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Surface correlations of hydrodynamic drag for transitionally rough engineering surfaces

Thakkar

Busse

Sandham

2016

Journal of Turbulence

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“…Figure 2 shows that this is inconsistent with the experimental data. The correlation of Sigal and Danberg [17] has three regions, where a plateau separates the two legs of the triangle. At this plateau the ratio of k S /k = 8.…”

Section: Discussion Of Results Equivalent Sand Grain Roughnessmentioning

confidence: 99%

“…Several authors have proposed correlations to obtain the equivalent sand grain roughness. Among these are Sigal and Danberg [17], Dvorak [18], Simpson [19], Dirling [20],van Rij et al [21], and Waigh and Kind [22]. Common to all these correlations is the requirement that the roughness image or trace be modeled as a roughness geometry, in order to obtain values for projected and windward areas.…”

Section: Introductionmentioning

confidence: 99%

Simplified Approach to Predicting Rough Surface Transition

Boyle

Stripf

2008

Volume 4: Heat Transfer, Parts a and B

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Turbine vane heat transfer predictions are given for smooth and rough vanes where the experimental data show transition moving forward on the vane as the surface roughness physical height increases. Consistent with smooth vane heat transfer, the transition moves forward for a fixed roughness height as the Reynolds number increases. Comparisons are presented with published experimental data. Some of the data are for a regular roughness geometry with a range of roughness heights, Reynolds numbers, and inlet turbulence intensities. The approach taken in this analysis is to treat the roughness in a statistical sense, consistent with what would be obtained from blades measured after exposure to actual engine environments. An approach is given to determine the equivalent sand grain roughness from the statistics of the regular geometry. This approach is guided by the experimental data. A roughness transition criterion is developed, and comparisons are made with experimental data over the entire range of experimental test conditions. Additional comparisons are made with experimental heat transfer data, where the roughness geometries are both regular as well as statistical. Using the developed analysis, heat transfer calculations are presented for the second stage vane of a high pressure turbine at hypothetical engine conditions.

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An experimental Stommel Retention Zone facility with an application to oil droplet dispersion

Gurung

Smith

Zeidi

et al. 2022

Limnology & Ocean Methods

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Stommel Retention Zones (SRZs) associated with wind-driven Langmuir circulation (LC) facilitate the subsurface retention of particles and thus affect processes such as oil spill dispersion, sediment suspension, oil-particle aggregation, and plankton distribution. Since the effect of SRZs on these processes is difficult to study in the field, we present a novel laboratory facility designed to recreate the counterrotating vortex pair flow pattern associated with small-scale SRZs of various strengths in two dimensions (2D). We then inject an oil jet into this facility to study buoyant oil droplet retention in these SRZs. 2D particle image velocimetry and hybrid Reynolds-averaged Navier-Stokes/large eddy simulation are used to characterize the flow. Large-scale oil droplet trajectories in the SRZs are visualized, and oil droplet statistics in the downwelling region and vortex core are measured using high-magnification brightfield imaging and a droplet detection algorithm. Values of maximum velocity (7.7-32.2 mm s À1 ), turbulent kinetic energy (10 À6 to 10 À4 m 2 s À2 ), and turbulent kinetic energy dissipation rate (10 À7 to 10 À5 m 2 s À3 ) in the downwelling region of the facility fall within the range of values observed in the field. Flow field strength strongly influences oil droplet trajectories, the shape and size of the SRZ, and oil droplet statistics over time, with stronger flows retaining larger oil droplets in the downwelling region over longer periods of time. Indeed, droplets of almost 400 μm diameter are observed in the downwelling region after almost 10 min for the strongest flow. The facility may be used to study the behavior of microplastics, sediments, and zooplankton in LC in the future.

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New correlation of roughness density effect on the turbulent boundary layer

Cited by 167 publications

References 13 publications

Surface correlations of hydrodynamic drag for transitionally rough engineering surfaces

Surface correlations of hydrodynamic drag for transitionally rough engineering surfaces

Simplified Approach to Predicting Rough Surface Transition

An experimental Stommel Retention Zone facility with an application to oil droplet dispersion

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