Some Turbulence and Diffusion Parameter Estimates within Cooling Tower Plumes Derived from Sodar Data

1980 ◽  
Vol 19 (12) ◽  
pp. 1395-1404 ◽  
Author(s):  
R. L. Coulter ◽  
K. H. Underwood
Keyword(s):  
Cooling Tower ◽  
Diffusion Parameter ◽  
Parameter Estimates ◽  
Sodar Data ◽  
And Diffusion ◽  
Turbulence And Diffusion

Meridional Circulation, Turbulence, and Diffusion Processes in Stars

1976 ◽  
Vol 32 ◽  
pp. 109-116 ◽  
Author(s):  
S. Vauclair
Keyword(s):  
Convection Zone ◽  
Diffusion Processes ◽  
Meridional Circulation ◽  
Diffusion Time ◽  
Work In Progress ◽  
First Results ◽  
Stellar Envelopes ◽  
And Diffusion ◽  
Turbulence And Diffusion ◽  
Hr Diagram

This paper gives the first results of a work in progress, in collaboration with G. Michaud and G. Vauclair. It is a first attempt to compute the effects of meridional circulation and turbulence on diffusion processes in stellar envelopes. Computations have been made for a 2 Mʘstar, which lies in the Am - δ Scuti region of the HR diagram.Let us recall that in Am stars diffusion cannot occur between the two outer convection zones, contrary to what was assumed by Watson (1970, 1971) and Smith (1971), since they are linked by overshooting (Latour, 1972; Toomre et al., 1975). But diffusion may occur at the bottom of the second convection zone. According to Vauclair et al. (1974), the second convection zone, due to He II ionization, disappears after a time equal to the helium diffusion time, and then diffusion may happen at the bottom of the first convection zone, so that the arguments by Watson and Smith are preserved.

scholarly journals Turbulence and diffusion in the lower atmosphere

1946 ◽  
Vol 186 (1004) ◽  
pp. 20-35 ◽  
Keyword(s):  
Water Vapour ◽  
Atmospheric Turbulence ◽  
Classical Theory ◽  
Quantitative Approach ◽  
Lower Atmosphere ◽  
Mixing Length ◽  
Self Consistent ◽  
Consistent Treatment ◽  
And Diffusion ◽  
Turbulence And Diffusion

The only existing theory of atmospheric turbulence which is capable of giving a quantitative approach to the complex problems of diffusion in the lower atmosphere is the classical theory in which it is generally assumed that the effect of eddies in the atmosphere is completely analogous to that of molecules in a gas apart from a difference of scale. This assumption, which later evidence has shown to be incorrect, is not essential to the theory, and in the present paper is replaced by the assumption that the mixing length of an eddy increases with both height above and nature of the earth’s surface . With this assumption a self-consistent treatment of diffusion is developed which is able to account quantitatively for such meteorological phenomena as the distribution of water vapour over land and sea (including evaporation from the oceans) and the diffusion of smoke near the ground. The treatment is mainly confined to diffusion in an adiabatic atmosphere.

scholarly journals Quantitative Measurement of Diffusion-weighted Imaging Signal Using Expression-controlled Aquaporin-4 Cells: Comparative Study of 2-compartment and Diffusion Kurtosis Imaging Models

2021 ◽  
Author(s):  
Akiko Imaizumi ◽  
Takayuki Obata ◽  
Jeff Kershaw ◽  
Yasuhiko Tachibana ◽  
Yoichiro Abe ◽  
...  
Keyword(s):  
Cell Membrane ◽  
Water Permeability ◽  
Diffusion Weighted Imaging ◽  
Aquaporin 4 ◽  
Diffusion Kurtosis Imaging ◽  
Parameter Estimates ◽  
Aqp4 Expression ◽  
Diffusion Weighted ◽  
Diffusion Kurtosis ◽  
And Diffusion

Purpose: The purpose of this study was to compare parameter estimates for the 2-compartment (2Comp) and diffusion kurtosis imaging (DKm) models obtained from diffusion-weighted imaging (DWI) of aquaporin-4 (AQP4) expression-controlled cells, and to look for biomarkers that indicate differences in the cell membrane water permeability. Methods: DWI was performed on AQP4-expressing and non-expressing cells and the signal was analyzed with the 2Comp and DKm models. For the 2Comp model, the diffusion coefficients (Df, Ds) and volume fractions (Ff, Fs, Ff=1-Fs) of the fast and slow compartments were estimated. For the DKm model, estimates of the diffusion kurtosis (K) and corrected diffusion coefficient (D) were obtained. Results: For the 2Comp model, Ds and Fs showed clear differences between AQP4-expressing and non-expressing cells. Fs was also sensitive to cell density. There was no clear relationship with the cell type for the DKm parameters. Conclusions: Changes to cell membrane water permeability due to AQP4 expression affected DWI of cell suspensions. For the 2Comp and DKm models, Ds was the parameter most sensitive to differences in AQP4 expression.

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