 Mechanical Engineering  Research Publications
Mechanical Engineering  Research Publications
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ItemNo Preview AvailableModelling the downstream development of a turbulent boundary layer following a step change of roughnessLi, M ; de Silva, CM ; Chung, D ; Pullin, D ; Marusic, I ; Hutchins, N (CAMBRIDGE UNIV PRESS, 20220923)In this study, we develop an analytical model to predict the turbulent boundary layer downstream of a stepchange in the surface roughness where upstream flow conditions are given. We first revisit the classical model of Elliott (Trans. Am. Geophys. Union, vol. 39, 1958, pp. 1048–1054), who modelled the velocity distribution within and above the internal layer with a simple piecewise logarithmic profile, and evolved the velocity profile using the streamwise momentum equation. Elliott's model was originally developed for an atmospheric surface layer, and to make the model applicable to a spatially developing turbulent boundary layer with finite thickness, we propose a number of more physical refinements, including adding a wake function to the velocity profile, considering the growth of the entire boundary layer in the streamwise direction, and using a more realistic shear stress profile in the momentum equation. In particular, we implement the blending model (Li et al., J. Fluid Mech., vol. 923, 2021, p. A18) to account for the deviation of the mean flow within the internal layer from a canonical velocity profile based on the local wall condition. These refinements lead to improved agreement between the prediction and the measurement, especially in the vicinity of the roughtosmooth change.

ItemNo Preview AvailableInvestigation of coldwire spatial and temporal resolution issues in thermal turbulent boundary layersXia, Y ; Rowin, WA ; Jelly, T ; Marusic, I ; Hutchins, N (ELSEVIER SCIENCE INC, 202204)

ItemHeat Transfer Coefficient Estimation for Turbulent Boundary LayersWang, S ; Xia, Y ; Abu Rowin, W ; Marusic, I ; Sandberg, R ; Chung, D ; Hutchins, N ; Tanimoto, K ; Oda, T (The University of Queensland, 20201211)Convective heat transfer in rough wallbounded turbulent flows is prevalent in many engineering applications, such as in gas turbines and heat exchangers. At present, engineers lack the design tools to accurately predict the convective heat transfer in the presence of nonsmooth boundaries. Accordingly, a new turbulent boundary layer facility has been commissioned, where the temperature of an interchangeable test surface can be precisely controlled, and conductive heat losses are minimized. Using this facility, we can estimate the heat transfer coefficient (Stanton number, St), through measurement of the power supplied to the electrical heaters and also from measurements of the thermal and momentum boundary layers evolving over this surface. These methods have been initially investigated over a shorter smooth prototype heated surface and compared with existing St prediction models. Preliminary results suggest that we can accurately estimate St in this facility.

ItemAn investigation of coldwire spatial resolution using a DNS databaseXia, Y ; Rowin, W ; Jelly, T ; Chung, D ; Marusic, I ; Hutchins, N (The University of Queensland, 20201211)The effect of spatial resolution of coldwire anemometry on both the variance and energy spectrum of temperature fluctuations is analyzed through the use of a numerical database. Temperature fluctuation snapshots from a direct numerical simulation (DNS) of a heated smoothwall turbulent channel flow are spatially averaged in the spanwise direction to simulate the wire filtering. The results show that the wire length does not affect the mean temperature while it significantly attenuates the variance of temperature fluctuations, particularly in the vicinity of the wall. As the filter length grows, the peaks of the one and twodimensional energy spectrograms are further attenuated. Limited attenuation is seen when the filter length is smaller than 30 wall units in the vicinity of the wall, whereas a complete suppression of the nearwall energetic peak is observed when the filter length exceeds 100 wall units.

ItemStructure Inclination Angles in the Convective Atmospheric Surface LayerChauhan, K ; Hutchins, N ; Monty, J ; Marusic, I (SPRINGER, 201304)

ItemTowards fullyresolved PIV measurements in high Reynolds number turbulent boundary layers with DSLR camerasde Silva, CM ; Grayson, K ; Scharnowski, S ; Kaehler, CJ ; Hutchins, N ; Marusic, I (SPRINGER, 201806)

ItemTowards Reconciling the LargeScale Structure of Turbulent Boundary Layers in the Atmosphere and LaboratoryHutchins, N ; Chauhan, K ; Marusic, I ; Monty, J ; Klewicki, J (SPRINGER, 201211)

ItemWalldrag measurements of smooth and roughwall turbulent boundary layers using a floating elementBaars, WJ ; Squire, DT ; Talluru, KM ; Abbassi, MR ; Hutchins, N ; Marusic, I (SPRINGER, 2016)The mean wall shear stress, $$øverlineτ _w$$ τ ¯ w , is a fundamental variable for characterizing turbulent boundary layers. Ideally, $$øverlineτ _w$$ τ ¯ w is measured by a direct means and the use of floating elements has long been proposed. However, previous such devices have proven to be problematic due to low signaltonoise ratios. In this paper, we present new direct measurements of $$øverlineτ _w$$ τ ¯ w where high signaltonoise ratios are achieved using a new design of a largescale floating element with a surface area of 3 m (streamwise) × 1 m (spanwise). These dimensions ensure a strong measurement signal, while any error associated with an integral measurement of $$øverlineτ _w$$ τ ¯ w is negligible in Melbourne’s largescale turbulent boundary layer facility. Walldrag induced by both smooth and roughwall zeropressuregradient flows are considered. Results for the smoothwall friction coefficient, $$C_f \equiv øverlineτ _w/q_\infty $$ C f ≡ τ ¯ w / q ∞ , follow a Coles–Fernholz relation $$C_f = \left[ 1/κ \ln \left( Re_θ \right) + C\right] ^2$$ C f = 1 / κ ln R e θ + C  2 to within 3 % ( $$κ = 0.38$$ κ = 0.38 and $$C = 3.7$$ C = 3.7 ) for a momentum thicknessbased Reynolds number, $$Re_θ > 15,000$$ R e θ > 15 , 000 . The agreement improves for higher Reynolds numbers to <1 % deviation for $$Re_θ > 38,000$$ R e θ > 38 , 000 . This smoothwall benchmark verification of the experimental apparatus is critical before attempting any roughwall studies. For a roughwall configuration with P36 grit sandpaper, measurements were performed for $$10,500< Re_θ < 88,500$$ 10 , 500 < R e θ < 88 , 500 , for which the walldrag indicates the anticipated trend from the transitionally to the fully rough regime.

ItemWavelet analysis of wall turbulence to study largescale modulation of small scalesBaars, WJ ; Talluru, KM ; Hutchins, N ; Marusic, I (SPRINGER, 201510)

ItemThe effect of spanwise wavelength of surface heterogeneity on turbulent secondary flowsWangsawijaya, DD ; Baidya, R ; Chung, D ; Marusic, I ; Hutchins, N (Cambridge University Press (CUP), 20200710)We examine the behaviour of turbulent boundary layers over surfaces composed of spanwisealternating smooth and rough strips, where the width of the strips varies such that, where is the boundarylayer thickness averaged over one spanwise wavelength of the heterogeneity. The experiments are configured to examine the influences of spanwise variation in wall shear stress over a large range. Hotwire anemometry and particle image velocimetry (PIV) reveal that the halfwavelength governs the diameter and strength of the resulting mean secondary flows and hence the observed isovels of the mean streamwise velocity. Three possible cases are observed: limiting cases (either or), where the secondary flows are confined near the wall or near the roughness change, and intermediate cases (), where the secondary flows are space filling and at their strongest. These secondary flows, however, exhibit a timedependent behaviour which might be masked by time averaging. Further analysis of the energy spectrogram and fluctuating flow fields obtained from PIV show that the secondary flows meander in a similar manner to that of largescale structures occurring naturally in turbulence over smooth walls. The meandering of the secondary flows is a function of and is most prominent when.