scholarly journals Critical flux Richardson number for Kolmogorov turbulence enabled by TKE transport

2019 ◽  
Vol 145 (721) ◽  
pp. 1551-1558 ◽  
Author(s):  
Livia S. Freire ◽  
Marcelo Chamecki ◽  
Elie Bou‐Zeid ◽  
Nelson L. Dias
Keyword(s):  
Richardson Number ◽  
Critical Flux ◽  
Kolmogorov Turbulence

scholarly journals Estimation of Turbulence Parameters in the Lower Troposphere from ShUREX (2016–2017) UAV Data

Atmosphere ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 384 ◽  
Author(s):  
Hubert Luce ◽  
Lakshmi Kantha ◽  
Hiroyuki Hashiguchi ◽  
Dale Lawrence
Keyword(s):  
Richardson Number ◽  
Layer Structure ◽  
Lower Troposphere ◽  
Energy Dissipation Rate ◽  
Function Parameter ◽  
Mixing Efficiency ◽  
Temperature Structure ◽  
Frequency Spectra ◽  
Kolmogorov Turbulence ◽  
Turbulence Parameters

Turbulence parameters in the lower troposphere (up to ~4.5 km) are estimated from measurements of high-resolution and fast-response cold-wire temperature and Pitot tube velocity from sensors onboard DataHawk Unmanned Aerial Vehicles (UAVs) operated at the Shigaraki Middle and Upper atmosphere (MU) Observatory during two ShUREX (Shigaraki UAV Radar Experiment) campaigns in 2016 and 2017. The practical processing methods used for estimating turbulence kinetic energy dissipation rate ε and temperature structure function parameter C T 2 from one-dimensional wind and temperature frequency spectra are first described in detail. Both are based on the identification of inertial (−5/3) subranges in respective spectra. Using a formulation relating ε and C T 2 valid for Kolmogorov turbulence in steady state, the flux Richardson number R f and the mixing efficiency χ m are then estimated. The statistical analysis confirms the variability of R f and χ m around ~ 0.13 − 0.14 and ~ 0.16 − 0.17 , respectively, values close to the canonical values found from some earlier experimental and theoretical studies of both the atmosphere and the oceans. The relevance of the interpretation of the inertial subranges in terms of Kolmogorov turbulence is confirmed by assessing the consistency of additional parameters, the Ozmidov length scale L O , the buoyancy Reynolds number R e b , and the gradient Richardson number Ri. Finally, a case study is presented showing altitude differences between the peaks of N 2 , C T 2 and ε , suggesting turbulent stirring at the margin of a stable temperature gradient sheet. The possible contribution of this sheet and layer structure on clear air radar backscattering mechanisms is examined.

Effect of Nanofluid on Heat Transfer Enhancement for Mixed Convection Flow Over a Corrugated Surface

2020 ◽  
Vol 45 (4) ◽  
pp. 373-383
Author(s):  
Nepal Chandra Roy ◽  
Sadia Siddiqa
Keyword(s):  
Heat Transfer ◽  
Boundary Layer ◽  
Nusselt Number ◽  
Mixed Convection ◽  
Local Nusselt Number ◽  
Richardson Number ◽  
Thermal Boundary Layer ◽  
Volume Fraction ◽  
Convection Flow ◽  
Mixed Convection Flow

AbstractA mathematical model for mixed convection flow of a nanofluid along a vertical wavy surface has been studied. Numerical results reveal the effects of the volume fraction of nanoparticles, the axial distribution, the Richardson number, and the amplitude/wavelength ratio on the heat transfer of Al2O3-water nanofluid. By increasing the volume fraction of nanoparticles, the local Nusselt number and the thermal boundary layer increases significantly. In case of \mathrm{Ri}=1.0, the inclusion of 2 % and 5 % nanoparticles in the pure fluid augments the local Nusselt number, measured at the axial position 6.0, by 6.6 % and 16.3 % for a flat plate and by 5.9 % and 14.5 %, and 5.4 % and 13.3 % for the wavy surfaces with an amplitude/wavelength ratio of 0.1 and 0.2, respectively. However, when the Richardson number is increased, the local Nusselt number is found to increase but the thermal boundary layer decreases. For small values of the amplitude/wavelength ratio, the two harmonics pattern of the energy field cannot be detected by the local Nusselt number curve, however the isotherms clearly demonstrate this characteristic. The pressure leads to the first harmonic, and the buoyancy, diffusion, and inertia forces produce the second harmonic.

Quantifying the influence of divalent cations mass transport on critical flux and organic fouling mechanism of forward osmosis membrane

Desalination ◽  
2021 ◽  
Vol 512 ◽  
pp. 115146
Author(s):  
Thanh-Tin Nguyen ◽  
Rusnang Syamsul Adha ◽  
Chulmin Lee ◽  
Dong-Ho Kim ◽  
In S. Kim
Keyword(s):  
Mass Transport ◽  
Divalent Cations ◽  
Forward Osmosis ◽  
Critical Flux ◽  
Fouling Mechanism ◽  
Organic Fouling

Development of a new method to evaluate critical flux and system reliability based on particle properties in a membrane bioreactor

Chemosphere ◽  
2021 ◽  
pp. 130763
Author(s):  
Yongsun Jang ◽  
Han-Shin Kim ◽  
Jeong-Hoon Lee ◽  
So-Young Ham ◽  
Jeong-Hoon Park ◽  
...  
Keyword(s):  
System Reliability ◽  
Membrane Bioreactor ◽  
New Method ◽  
Critical Flux ◽  
Particle Properties

High critical flux density gradients near the surface of superconducting niobium

1979 ◽  
Vol 36 (1-2) ◽  
pp. 33-46 ◽  
Author(s):  
A. S. Brito ◽  
G. Zerweck ◽  
O. F. de Lima
Keyword(s):  
Flux Density ◽  
Density Gradients ◽  
Critical Flux

Critical flux determination by the flux-step method in a submerged membrane bioreactor

2003 ◽  
Vol 227 (1-2) ◽  
pp. 81-93 ◽  
Author(s):  
Pierre Le Clech ◽  
Bruce Jefferson ◽  
In Soung Chang ◽  
Simon J. Judd
Keyword(s):  
Membrane Bioreactor ◽  
Step Method ◽  
Critical Flux ◽  
Submerged Membrane Bioreactor ◽  
Flux Determination
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