Characterizing the turbulent drag properties of rough surfaces with a Taylor–Couette set-up

Berghout, Pieter; Bullee, Pim A.; Fuchs, Thomas; Scharnowski, Sven; Kähler, Christian J.; Chung, Daniel; Lohse, Detlef; Huisman, Sander G.

doi:10.1017/jfm.2021.413

Cited by 9 publications

(3 citation statements)

References 42 publications

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“…The first type of rough wall is the irregular rough surface made by adhering particles randomly on the cylindrical wall (Berghout et al. 2019, 2021; Bakhuis et al. 2020).…”

Section: Introductionmentioning

confidence: 99%

Direct numerical simulation of Taylor–Couette flow with vertical asymmetric rough walls

Xu,

Su,

Lan

et al. 2023

J. Fluid Mech.

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Direct numerical simulations are performed to explore the effects of the rotating direction of the vertically asymmetric rough wall on the transport properties of Taylor–Couette (TC) flow, up to a Taylor number of ${Ta} = 2.39\times 10^{7}$ . It is shown that, compared with the smooth wall, the rough wall with vertical asymmetric strips can enhance the dimensionless torque ${Nu}_{\omega }$ . More importantly, at high Ta, clockwise rotation of the inner rough wall (where the fluid is sheared by the steeper slope side of the strips) results in a significantly greater torque enhancement compared to counter-clockwise rotation (where the fluid is sheared by the smaller slope side of the strips), due to the larger convective contribution to the angular velocity flux. However, the rotating direction has a negligible effect on the torque at low Ta. The larger torque enhancement caused by the clockwise rotation of the vertically asymmetric rough wall at high Ta is then explained by the stronger coupling between the rough wall and the bulk, attributed to the larger biased azimuthal velocity towards the rough wall at the mid-gap of the TC system, the increased turbulence intensity manifested by larger Reynolds stress and a thinner boundary layer, and the more significant contribution of the pressure force on the surface of the rough wall to the torque.

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“…The first type of rough wall is the irregular rough surface made by adhering particles randomly on the cylindrical wall (Berghout et al. 2019, 2021; Bakhuis et al. 2020).…”

Section: Introductionmentioning

confidence: 99%

Direct numerical simulation of Taylor–Couette flow with vertical asymmetric rough walls

Xu,

Su,

Lan

et al. 2023

J. Fluid Mech.

View full text Add to dashboard Cite

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“…2021) or industrial grade sandpaper roughness (Berghout et al. 2021). Models that reliably predict (or ) based solely on key topographical parameters are therefore of great value.…”

Section: Introductionmentioning

confidence: 99%

Impact of spanwise effective slope upon rough-wall turbulent channel flow

et al. 2022

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Whereas streamwise effective slope ( $ES_{x}$ ) is accepted as a key topographical parameter in the context of rough-wall turbulent flows, the significance of its spanwise counterpart ( $ES_{y}$ ) remains largely unexplored. Here, the response of turbulent channel flow over irregular, three-dimensional rough walls with systematically varied values of $ES_{y}$ is studied using direct numerical simulation. All simulations were performed at a fixed friction Reynolds number 395, corresponding to a viscous-scaled roughness height $k^{+}\approx 65.8$ (where $k$ is the mean peak-to-valley height). A surface generation algorithm is used to synthesise a set of ten irregular surfaces with specified $ES_{y}$ for three different values of $ES_{x}$ . All surfaces share a common mean peak-to-valley height and are near-Gaussian, which allows this study to focus on the impact of varying $ES_{y}$ , since roughness amplitude, skewness and $ES_{x}$ can be eliminated simultaneously as parameters. Based on an analysis of first- and second-order velocity statistics, as well as turbulence co-spectra and the fractional contribution of pressure and viscous drag, the study shows that $ES_{y}$ can strongly affect the roughness drag penalty – particularly for low- $ES_{x}$ surfaces. A secondary observation is that particular low- $ES_{y}$ surfaces in this study can lead to diminished levels of outer-layer similarity in both mean flow and turbulence statistics, which is attributed to insufficient scale separation between the outer length scale and the in-plane spanwise roughness wavelength.

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“…As previously mentioned, measurements in the near-wall region are challenging due to the strong velocity gradient and small spatial scales. However, using novel optical approaches, high-quality measurements in the nearwall region have been demonstrated in the literature: For instance, single pixel evaluation of PIV recordings (Kähler et al (2012a); Berghout et al (2021)), and by using high magnification PTV (Kähler et al (2012b); Cierpka et al (2013); Bross et al (2019)), to list a few.…”

Section: Introductionmentioning

confidence: 99%

Near-wall turbulence and wall-shear-stress measurements using volumetric μPTV

Fuchs

Bross

Kähler

2022

Preprint

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Accurately determining the wall-shear-stress, τw , experimentally is challenging due to small spatial scales and large velocity gradients present in the near-wall region of turbulent flows. To avoid these resolution requirements, several indirect iterative fitting methods, most notably the Clauser chart method, exist for determining τw by fitting the mean velocity profile further away from the near-wall region in the log-law layer. These methods often require proper selection of fitting constants, assumptions of a canonical flow state, and other empirical based generalizations. To reduce the amount of ambiguity, determining the near-wall velocity gradient by assuming a linear relationship between the mean streamwise velocity and wall normal distance in the viscous sublayer can be used. However, this requires an accurate unbiased measurement of the near wall velocity profile in the region below five viscous spatial units, which can be less than 50 μm for high Reynolds number flows. Therefore, in this study a method for a volumetric defocusing micro particle tracking velocimetry method is presented that is capable of resolving the flow in the viscous sublayer of a turbulent boundary layer up to Ue = 44.7 m/s (Reθ = 27250). This method allows for the measurement of the near-wall flow through a single optical access for illumination and imaging and serves as an excellent complement of larger scale measurements that require near-wall information. The τw values determined from defocusing approach was found to be in good agreement values obtained from a simultaneous parallax PTV measurement. Furthermore, analysis of the diagnostic plot and cumulative distribution of measured fluctuations in the near-wall region, showed that both methods are capable of accurately determining mean velocity and fluctuation profiles in the self-similar viscous sublayer region.

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Characterizing the turbulent drag properties of rough surfaces with a Taylor–Couette set-up

Abstract: Abstract

Cited by 9 publications

References 42 publications

Direct numerical simulation of Taylor–Couette flow with vertical asymmetric rough walls

Direct numerical simulation of Taylor–Couette flow with vertical asymmetric rough walls

Impact of spanwise effective slope upon rough-wall turbulent channel flow

Near-wall turbulence and wall-shear-stress measurements using volumetric μPTV

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