Extracting a mixing parameter from 2D radiographic imaging of variable-density turbulent flow

被引:5
作者
Kurien, S. [1 ]
Doss, F. W. [2 ]
Livescu, D. [3 ]
Flippo, K. [4 ]
机构
[1] Los Alamos Natl Lab, Theoret Div, T-3, Los Alamos, NM 87545 USA
[2] Los Alamos Natl Lab, Theoret Design Div, XTD IDA, Los Alamos, NM 87545 USA
[3] Los Alamos Natl Lab, Comp & Computat Sci Div, CCS 2, Los Alamos, NM 87545 USA
[4] Los Alamos Natl Lab, Phys Div, P-24, Los Alamos, NM 87545 USA
关键词
Turbulence models; Variable-density turbulence; Radiographic imaging;
D O I
10.1016/j.physd.2020.132354
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
We extract a suitably averaged fluctuating density from the two-dimensional radiographic image of a flow. The X-ray attenuation is given by the Beer-Lambert law which exponentially damps the incident beam intensity by a factor proportional to the density, opacity and thickness of the target. By making reasonable assumptions for the mean density, opacity and effective thickness of the target flow, we estimate the density fluctuation contribution to the attenuation. The extracted density fluctuations averaged across the thickness of the flow in the direction of the beam may be used to form the density-specific-volume correlation b. In a statistical description of variable-density turbulence, b quantifies the degree of mixedness. The ability to extract a measure of mixedness from experimental data would be a powerful tool that could be used in the validation of mix models. The scheme proposed is tested for DNS data computed for variable density buoyancy-driven mixing. We quantify the deficits in the extracted value of b due to target thickness, Atwood number and modeled signal noise. This analysis justifies using the proposed scheme to infer the mix parameter from thin targets at moderate to low Atwood numbers. To illustrate how the scheme might be used in a practical problem, we demonstrate its application to a radiographic image of counter-shear flow obtained from experiments at the National Ignition Facility. Published by Elsevier B.V.
引用
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页数:10
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