Comparison of thermal scaling properties between turbulent pipe and channel flows via DNS

Saha, Sumon; Klewicki, Joseph; Ooi, Andrew; Blackburn, Hugh Maurice

doi:10.1016/j.ijthermalsci.2014.10.010

Cited by 13 publications

(10 citation statements)

References 34 publications

(141 reference statements)

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“…The great advantage of this method is that Θ is periodic in the streamwise direction and Fourier methods can be applied. The equation for Θ becomes ( [11]), Here, the temperature has been adimensionalised by the friction temperature T τ = q w /ρc p u τ . Using this model, the boundary conditions for the modified temperature are simply Θ (y = 0, 2h) = 0.…”

Section: Model Description and Formulationmentioning

confidence: 99%

“…One critical point of DNS is the domain to be simulated. Saha et al in two papers [8,11] investigated the length of the largest turbulent structures in pipes and the comparison between pipes and channels. In fact, in almost all of the papers cited in this introduction and Saha et al's works, the size of the computational box is narrower and shorter than in the classical turbulent channel flow simulations.…”

Section: Introductionmentioning

confidence: 99%

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Influence of the computational domain on DNS of turbulent heat transfer up to Reτ=2000 for Pr<

Lluesma-Rodríguez

Hoyas

Pérez-Quiles

2018

International Journal of Heat and Mass Transfer

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We present a new set of direct numerical simulation data of a passive thermal flow in a turbulent plane Poiseuille flow with constant Prandtl number P r = 0.71, and mixed boundary conditions. Simulations were performed at Re τ = 500, 1000, and 2000 for several computational domains in the range of l x = 2πh to 8πh and l z = πh to 3πh. As a first key result we found that a length of l x = 2πh and a width of l z = π is enough to accurately obtain the one-point statistics and the budgets of the thermal kinetic energy, its dissipation and the thermal fluxes. None of them collapse exactly in wall units. On the other hand, the value of the thermal Kármán constant grows very slightly with the Reynolds number with a value of κ th = 0.44 for Re τ = 2000. The statistics of all simulations can be downloaded from the web page of our group.

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Section: Model Description and Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Influence of the computational domain on DNS of turbulent heat transfer up to Reτ=2000 for Pr<

Lluesma-Rodríguez

Hoyas

Pérez-Quiles

2018

International Journal of Heat and Mass Transfer

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“…The numerical method, including details of its spectral convergence in cylindrical coordinates, is fully described in Blackburn & Sherwin (2004). The solver has been previously employed for DNS of turbulent pipe flow by Chin et al (2010), Saha et al (2011), Saha et al (2014, Saha et al (2015a), Saha et al (2015b), and validated against the Re τ = 314 smooth-wall experimental data of den Toonder & Nieuwstadt (1997) in Blackburn et al (2007). We use a mesh similar to that employed for the straight-pipe case of Saha et al (2015b), also at Re τ = 314.…”

Section: )mentioning

confidence: 99%

Streamwise-varying steady transpiration control in turbulent pipe flow

et al. 2016

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The effect of streamwise-varying steady transpiration on turbulent pipe flow is examined using direct numerical simulation at fixed friction Reynolds number Re τ = 314. The streamwise momentum equation reveals three physical mechanisms caused by transpiration acting in the flow: modification of Reynolds shear stress, steady streaming and generation of non-zero mean streamwise gradients. The influence of these mechanisms has been examined by means of a parameter sweep involving transpiration amplitude and wavelength. The observed trends have permitted identification of wall transpiration configurations able to reduce or increase the overall flow rate −36.1% and 19.3% respectively. Energetics associated with these modifications are presented.A novel resolvent formulation has been developed to investigate the dynamics of pipe flows with a constant cross-section but with time-mean spatial periodicity induced by changes in boundary conditions. This formulation, based on a triple decomposition, paves the way for understanding turbulence in such flows using only the mean velocity profile. Resolvent analysis based on the time-mean flow and dynamic mode decomposition based on simulation data snapshots have both been used to obtain a description of the reorganization of the flow structures caused by the transpiration. We show that the pipe flows dynamics are dominated by a critical-layer mechanism and the waviness induced in the flow structures plays a role on the streamwise momentum balance by generating additional terms.

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“…Few studies are dealing with resolved numerical simulation of pipe flows heat transfer mostly due to the computational complexity associated with the cylindrical coordinate system and the corresponding numerical singularity along the symmetry line. Some examples of Direct Numerical Simulations (DNS) of turbulent pipes flows with homogeneous heating are available [8,9,10,11,12].…”

Section: Introductionmentioning

confidence: 99%

“…Such resolved simulations allowed for the availability of high resolutions statistics and for the development of relations between wall heat flux and flow eddies. When comparing pipe flows with boundary layers flows, Saha et al [12] suggest that, since pipe flow forces the motions near the centerline to interact more vigorously, the wall heat flux promotes stronger temperature fluctuations.…”

Section: Introductionmentioning

confidence: 99%

Extended proper orthogonal decomposition of non-homogeneous thermal fields in a turbulent pipe flow

Antoranz

Ianiro

Flores

et al. 2018

International Journal of Heat and Mass Transfer

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This manuscript analyzes the role of coherent structures in turbulent thermal transport in pipe flows. A Proper Orthogonal Decomposition (POD) analysis is performed on a direct numerical simulation dataset with non-homogeneous boundary conditions, heated on the upper side, representative of solar receivers (Antoranz et al, 2015, Int. J. Heat Fluid Flow, 55). Three flow conditions are analyzed: with friction Reynolds number equal to 180 and Prandtl number equal to 0.7 and 4 and with friction Reynolds number equal to 360 and Prandtl number equal to 0.7. Both POD and extended POD modes are presented and compared. This allows to visualize the main flow modes in terms of both turbulent kinetic energy and temperature fluctuations, analyzing their contribution to the turbulent transport of heat. The POD analysis shows that the temperature fluctuations are described by a more compact modal subspace than the turbulent kinetic energy. The effect of increasing the Reynolds number is to produce a thinner boundary layer, with a slightly less compact representation of both kinetic energy and temperature fluctuations. The increase of the Prandtl number, instead, results in a thinner thermal boundary layer with a greater scale separation between thermal fluctuations and kinetic energy. Temperature POD modes together with velocity extended POD modes are used to analyze and quantify the mode contribution to turbulent thermal transport. Results show that the correlation between velocity and temperature is such that it is possible to describe roughly 100% of the turbulent heat transport and temperature fluctuations with only 40% of the kinetic energy. For the cases with P r = 0.7, the first extended POD mode is a large vertical jet flanked by a pair of counter-rotating vortices near the heated part of the pipe. This single structure accounts for up to 10% of the turbulent heat transport.

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Comparison of thermal scaling properties between turbulent pipe and channel flows via DNS

Cited by 13 publications

References 34 publications

Influence of the computational domain on DNS of turbulent heat transfer up to Reτ=2000 for Pr<

Influence of the computational domain on DNS of turbulent heat transfer up to Reτ=2000 for Pr<

Streamwise-varying steady transpiration control in turbulent pipe flow

Extended proper orthogonal decomposition of non-homogeneous thermal fields in a turbulent pipe flow

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