Lagrangian Statistics for Dispersion in Magnetohydrodynamic Turbulence

Pratt, J.; Busse, Angela; Mueller, Wolf-Chrisian

doi:10.1002/essoar.10503192.1

Cited by 1 publication

(7 citation statements)

References 39 publications

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“…2007 b ; Busse & Müller 2008; Pratt et al. 2020 b ), and are larger than those used in Yeung et al. (2006) and Sawford et al.…”

Section: Simulationsmentioning

confidence: 78%

“…Deterministic forcing has the advantage that no stochastic source of fluctuations is introduced on large scales. We call the deterministic forcing method that we use homogeneous forcing; it is distinct from forcing methods used in several earlier works on Lagrangian MHD turbulence (Busse et al 2007;Homann et al 2007b;Busse & Müller 2008;Busse et al 2010) but identical to the forcing method used in Pratt et al (2020b). Homogeneous forcing establishes a constant injection of energy at large scales.…”

Section: Simulationsmentioning

confidence: 99%

“…as discussed in Cho & Vishniac 2000;Schekochihin, Cowley & Yousef 2008;Verdini et al 2015). We explored the corresponding time-scale dependence of this anisotropy from the Lagrangian point of view in Pratt et al (2020b). Due to the elongation of eddies in the direction aligned with the magnetic field, the smallest length scales relevant for the study of turbulence are different from those in the perpendicular direction.…”

Section: Resolution Of Anisotropic Mhd Turbulencementioning

confidence: 99%

“…2010) but identical to the forcing method used in Pratt et al. (2020 b ). Homogeneous forcing establishes a constant injection of energy at large scales.…”

Section: Simulationsmentioning

confidence: 99%

“…2013; Pratt et al. 2017; Pratt, Busse & Muller 2020 a ; Pratt, Busse & Müller 2020 b ). In contrast, the study of neutral-fluid turbulence from a Lagrangian viewpoint has a long history (e.g.…”

Section: Introductionmentioning

confidence: 99%

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Reynolds number dependence of Lagrangian dispersion in direct numerical simulations of anisotropic magnetohydrodynamic turbulence

2022

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Large-scale magnetic fields thread through the electrically conducting matter of the interplanetary and interstellar medium, stellar interiors and other astrophysical plasmas, producing anisotropic flows with regions of high-Reynolds-number turbulence. It is common to encounter turbulent flows structured by a magnetic field with a strength approximately equal to the root-mean-square magnetic fluctuations. In this work, direct numerical simulations of anisotropic magnetohydrodynamic (MHD) turbulence influenced by such a magnetic field are conducted for a series of cases that have identical resolution, and increasing grid sizes up to $2048^3$ . The result is a series of closely comparable simulations at Reynolds numbers ranging from 1400 up to 21 000. We investigate the influence of the Reynolds number from the Lagrangian viewpoint by tracking fluid particles and calculating single-particle and two-particle statistics. The influence of Alfvénic fluctuations and the fundamental anisotropy on the MHD turbulence in these statistics is discussed. Single-particle diffusion curves exhibit mildly superdiffusive behaviours that differ in the direction aligned with the magnetic field and the direction perpendicular to it. Competing alignment processes affect the dispersion of particle pairs, in particular at the beginning of the inertial subrange of time scales. Scalings for relative dispersion, which become clearer in the inertial subrange for a larger Reynolds number, can be observed that are steeper than indicated by the Richardson prediction.

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“…2007 b ; Busse & Müller 2008; Pratt et al. 2020 b ), and are larger than those used in Yeung et al. (2006) and Sawford et al.…”

Section: Simulationsmentioning

confidence: 78%

Section: Simulationsmentioning

confidence: 99%

Section: Resolution Of Anisotropic Mhd Turbulencementioning

confidence: 99%

“…2010) but identical to the forcing method used in Pratt et al. (2020 b ). Homogeneous forcing establishes a constant injection of energy at large scales.…”

Section: Simulationsmentioning

confidence: 99%