A study of energetic large-scale structures in turbulent boundary layer

Wu, Yanhua

doi:10.1063/1.4873199

Cited by 45 publications

(43 citation statements)

References 21 publications

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“…In particular, the mode energy distribution is in good agreement with the ZPG data presented in Ref. [ 66 ] at R e 𝜃 = 8200, suggesting that in the considered range the energy share between large-scale and small-scale features is independent of both R e and β . About 20% of the energy contribution is ascribed to the first mode, 10% is ascribed to the second mode and barely 5% to the third and the fourth modes.…”

Section: Pod and Modal Contribution To Turbulence Statisticssupporting

confidence: 86%

Adverse-Pressure-Gradient Effects on Turbulent Boundary Layers: Statistics and Flow-Field Organization

Vila

Örlü

Vinuesa

et al. 2017

Flow Turbulence Combust

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This manuscripts presents a study on adverse-pressure-gradient turbulent boundary layers under different Reynolds-number and pressure-gradient conditions. In this work we performed Particle Image Velocimetry (PIV) measurements supplemented with Large-Eddy Simulations in order to have a dataset covering a range of displacement-thickness-based Reynolds-number 2300 34000 and values of the Clauser pressure-gradient parameter β up to 2.4. The spatial resolution limits of PIV for the estimation of turbulence statistics have been overcome via ensemble-based approaches. A comparison between ensemble-correlation and ensemble Particle Tracking Velocimetry was carried out to assess the uncertainty of the two methods. The effects of β, R e and of the pressure-gradient history on turbulence statistics were assessed. A modal analysis via Proper Orthogonal Decomposition was carried out on the flow fields and showed that about 20% of the energy contribution corresponds to the first mode, while 40% of the turbulent kinetic energy corresponds to the first four modes with no appreciable dependence on β and R e within the investigated range. The topology of the spatial modes shows a dependence on the Reynolds number and on the pressure-gradient strength, in line with the results obtained from the analysis of the turbulence statistics. The contribution of the modes to the Reynolds stresses and the turbulence production was assessed using a truncated low-order reconstruction with progressively larger number of modes. It is shown that the outer peaks in the Reynolds-stress profiles are mostly due to large-scale structures in the outer part of the boundary layer.

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Section: Pod and Modal Contribution To Turbulence Statisticssupporting

confidence: 86%

Adverse-Pressure-Gradient Effects on Turbulent Boundary Layers: Statistics and Flow-Field Organization

Vila

Örlü

Vinuesa

et al. 2017

Flow Turbulence Combust

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“…To address those particularly sized structures responsible for the lack of outer-layer similarity, POD modes can be used to bandpass filter the velocity fields to obtain a spatially-filtered representation of the original field (Wu and Christensen 2010 ; Wu 2014 ). Bandpass-filtered velocities are generated after reconstructing each individual fluctuating velocity field by projecting it onto the most energetic modes containing of the total turbulent kinetic energy (Wu and Christensen 2010 ), which is denoted 0.5 E .…”

Section: Resultsmentioning

confidence: 99%

Turbulent Flow Over Large Roughness Elements: Effect of Frontal and Plan Solidity on Turbulence Statistics and Structure

Placidi

Ganapathisubramani

2017

Boundary-Layer Meteorol

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Wind-tunnel experiments were carried out on fully-rough boundary layers with large roughness (δ/ h ≈ 10, where h is the height of the roughness elements and δ is the boundary-layer thickness). Twelve different surface conditions were created by using LEGO™ bricks of uniform height. Six cases are tested for a fixed plan solidity (λ P ) with variations in frontal density (λ F ), while the other six cases have varying λ P for fixed λ F . Particle image velocimetry and floating-element drag-balance measurements were performed. The current results complement those contained in Placidi and Ganapathisubramani (J Fluid Mech 782:541-566, 2015), extending the previous analysis to the turbulence statistics and spatial structure. Results indicate that mean velocity profiles in defect form agree with Townsend's similarity hypothesis with varying λ F , however, the agreement is worse for cases with varying λ P . The streamwise and wall-normal turbulent stresses, as well as the Reynolds shear stresses, show a lack of similarity across most examined cases. This suggests that the critical height of the roughness for which outer-layer similarity holds depends not only on the height of the roughness, but also on the local wall morphology. A new criterion based on shelter solidity, defined as the sheltered plan area per unit wall-parallel area, which is similar to the 'effective shelter area' in Raupach and Shaw (Boundary-Layer Meteorol 22:79-90, 1982), is found to capture the departure of the turbulence statistics from outer-layer similarity. Despite this lack of similarity reported in the turbulence statistics, proper orthogonal decomposition analysis, as well as two-point spatial correlations, show that some form of universal flow structure is present, as all cases exhibit virtually identical proper orthogonal decomposition mode shapes and correlation fields. Finally, reduced models based on proper orthogonal decomposition reveal that the small scales of the turbulence play a significant role in assessing outer-layer similarity.

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“…As described above and in Wu (2014), the POD coefficients a 1 and a 2 can be used to identify the dominant instantaneous turbulence structures which are the major contributors to form the first two POD modes. The histograms of a 1 and a 2 , normalized by their own root-mean-square (RMS) values, are presented in Fig.…”

Section: Resultsmentioning

confidence: 99%

“…Since the second POD modes accounts for a much lower energy than the first mode, the dominant contributors to this mode impact much less on the statistics (Wu, 2014), and therefore their effects will not be discussed here.…”

Section: Contribution To Turbulence Statistics From Dominant Structurmentioning

confidence: 97%

“…It is now widely accepted that coherent turbulence structures exist in various turbulent flows (e.g Robinson, 1991;Adrian, 2007) and they are dynamically important for transporting momentum and energy. In addition, very recently, Wu (2014) used the coefficients of the proper orthogonal decomposition (POD) to establish the relationship between the POD modes and the instantaneous energetic turbulence structures and studied the effects of these structures on the turbulence characteristics of a zero-pressure-gradient turbulent boundary layer. This work is particularly motivated by this study of Wu (2014) and the objective of this work is to apply this new method to investigate the turbulence structures within the turbulent flows at the inboard section of the suction surface of a rotating blade when stall delay occurs.…”

Section: Introductionmentioning

confidence: 99%

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