scholarly journals Effect of the Reynolds number on turbulence kinetic energy exchanges in flows with highly variable fluid properties

2019 ◽  
Vol 31 (1) ◽  
pp. 015104 ◽  
Author(s):  
D. Dupuy ◽  
A. Toutant ◽  
F. Bataille
Keyword(s):  
Reynolds Number ◽  
Kinetic Energy ◽  
Turbulence Kinetic Energy ◽  
Variable Fluid Properties ◽  
Fluid Properties ◽  
Energy Exchanges

scholarly journals Turbulence kinetic energy exchanges in flows with highly variable fluid properties

2017 ◽  
Vol 834 ◽  
pp. 5-54 ◽  
Author(s):  
Dorian Dupuy ◽  
Adrien Toutant ◽  
Françoise Bataille
Keyword(s):  
Reynolds Number ◽  
Temperature Gradient ◽  
Velocity Fluctuation ◽  
Spectral Studies ◽  
Spectral Energy ◽  
Correlation Tensor ◽  
Variable Fluid Properties ◽  
Fluid Properties ◽  
Energy Exchanges ◽  
The Mean

This paper investigates the energy exchanges associated with the half-trace of the velocity fluctuation correlation tensor in a strongly anisothermal low Mach fully developed turbulent channel flow. The study is based on direct numerical simulations of the channel within the low Mach number hypothesis and without gravity. The overall flow behaviour is governed by the variable fluid properties. The temperature of the two channel walls are imposed at 293 K and 586 K to generate the temperature gradient. The mean friction Reynolds number of the simulation is 180. The analysis is carried out in the spatial and spectral domains. The spatial and spectral studies use the same decomposition of the terms of the evolution equation of the half-trace of the velocity fluctuation correlation tensor. The importance of each term of the decomposition in the energy exchanges is assessed. This lets us identify the terms associated with variations or fluctuations of the fluid properties that are not negligible. Then, the behaviour of the terms is investigated. The spectral energy exchanges are first discussed in the incompressible case since the analysis is not present in the literature with the decomposition used in this study. The modification of the energy exchanges by the temperature gradient is then investigated in the spatial and spectral domains. The temperature gradient generates an asymmetry between the two sides of the channel. The asymmetry can in a large part be explained by the combined effect of the mean local variations of the fluid properties, combined with a Reynolds number effect.

scholarly journals Study on the characteristics of the pressure fluctuations and their contribution to turbulence kinetic energy

2021 ◽  
pp. 105634
Author(s):  
Zhuorui Wei ◽  
Hongsheng Zhang ◽  
Yan Ren ◽  
Qianhui Li ◽  
Xuhui Cai ◽  
...  
Keyword(s):  
Kinetic Energy ◽  
Pressure Fluctuations ◽  
Turbulence Kinetic Energy

Non-Isothermal Peristaltic Flow of Newtonian Fluids in a Circular Tube

2009 ◽  
Author(s):  
M. S. Yun ◽  
B. P. Huynh
Keyword(s):  
Reynolds Number ◽  
Flow Pattern ◽  
Circular Tube ◽  
Pressure Change ◽  
Peristaltic Flow ◽  
Isothermal Flow ◽  
Newtonian Fluids ◽  
Fluid Viscosity ◽  
Fluid Properties ◽  
Isothermal Case

Non-isothermal peristaltic flow of Newtonian fluids in a circular tube is investigated numerically, using a commercial Computational Fluid Dynamics (CFD) software package. Simulation is performed over a range of Reynolds-number values, up to 1000. Temperature affects the flow field via fluid viscosity, which is assumed to decrease exponentially with temperature. Other fluid properties are assumed to be constant, and are similar to those of an oil. Allowing for temperature effects alters significantly the flow pattern and reduces pressure change. In the crest region, recirculation appears in non-isothermal flow at a much smaller Reynolds number Re than in isothermal flow. Influence of the Reynolds number itself is also reduced significantly, such that the flow pattern changes very little with increasing Re, in contrast to the isothermal case. Similarly, in non-isothermal flow, flow pattern is unchanged at different flow rate. This is also in contrast to the isothermal situation.

Composited structure of shallow cumulus clouds

2021 ◽  
Author(s):  
Chris Holloway ◽  
Jian-Feng Gu ◽  
Bob Plant ◽  
Todd Jones
Keyword(s):  
Kinetic Energy ◽  
Vertical Velocity ◽  
Inversion Layer ◽  
Potential Temperature ◽  
Vertical Wind Shear ◽  
Theoretical Models ◽  
Turbulence Kinetic Energy ◽  
Cloud Base ◽  
Asymmetric Structures ◽  
Negatively Buoyant

<div> <div> <div> <div> <p>The normalized distributions of thermodynamic and dynamical variables both within and outside shallow clouds are investigated through a composite algorithm using large eddy simulation of the BOMEX case. The normalized magnitude is maximum near cloud center and decreases outwards. While relative humidity (RH) and cloud liquid water (<em>q<sub>l </sub></em>) decrease smoothly to match the environment, the vertical velocity, virtual potential temperature (<em>θ<sub>v </sub></em>) and potential temperature (<em>θ</em>) perturbations have more complicated behaviour towards the cloud boundary. Below the inversion layer, <em>θ<sub>v</sub></em> becomes <span>negative before the vertical velocity has turned from updraft to subsiding shell outside the cloud, indicating the presence of a transition zone where the updraft is negatively buoyant. Due to the downdraft outside the cloud and the enhanced horizontal turbulent mixing across the edge, the normalized turbulence kinetic energy (TKE) and horizontal turbulence kinetic energy (HTKE) decrease more slowly from the cloud center outwards than the thermodynamic variables. The distributions all present asymmetric structures in response to the vertical wind shear, with more negatively buoyant air, stronger downdrafts and larger TKE on the downshear side. We discuss several implications of the distributions for theoretical models and parameterizations. Positive buoyancy near cloud base is mostly due to </span><span>the virtual effect of water vapor, emphasising the role of moisture in triggering. The mean vertical velocity is found </span><span>to be approximately half the maximum vertical velocity within each cloud, providing a constraint on some models. Finally, products of normalized distributions for different variables are shown to be able to well represent the vertical heat and moisture fluxes, but they underestimate fluxes in the inversion layer because they do not capture cloud top downdrafts.</span></p> </div> </div> </div> </div>

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