Atoms (Sep 2024)

Data-Based Kinematic Viscosity and Rayleigh–Taylor Mixing Attributes in High-Energy Density Plasmas

  • Snezhana I. Abarzhi,
  • Kurt C. Williams

DOI
https://doi.org/10.3390/atoms12100047
Journal volume & issue
Vol. 12, no. 10
p. 47

Abstract

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We explore properties of matter and characteristics of Rayleigh–Taylor mixing by analyzing data gathered in the state-of-the-art fine-resolution experiments in high-energy density plasmas. The eminent quality data represent fluctuations spectra of the X-ray imagery intensity versus spatial frequency. We find, by using the rigorous statistical method, that the fluctuations spectra are accurately captured by a compound function, being a product of a power law and an exponential and describing, respectively, self-similar and scale-dependent spectral parts. From the self-similar part, we find that Rayleigh–Taylor mixing has steep spectra and strong correlations. From the scale-dependent part, we derive the first data-based value of the kinematic viscosity in high-energy density plasmas. Our results explain the experiments, agree with the group theory and other experiments, and carve the path for better understanding Rayleigh–Taylor mixing in nature and technology.

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