Structures in magnetohydrodynamic turbulence: Detection and scaling
We present a systematic analysis of statistical properties of turbulent current and vorticity structures at a given time using cluster analysis. The data stem from numerical simulations of decaying three-dimensional magnetohydrodynamic turbulence in the absence of an imposed uniform magnetic field;...
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todo:paper_15393755_v82_n5_p_Uritsky2023-10-03T16:22:35Z Structures in magnetohydrodynamic turbulence: Detection and scaling Uritsky, V.M. Pouquet, A. Rosenberg, D. Mininni, P.D. Donovan, E.F. Beltrami Cluster statistics Initial conditions Intermittency Local instability Magnetic Prandtl numbers Magnetohydrodynamic turbulence Numerical simulation Self-organized criticality Statistical properties Systematic analysis Taylor-Reynolds number Three dimensions Turbulence dynamics Vorticity structure X-point Cluster analysis Criticality (nuclear fission) Magnetic fields Reynolds number Three dimensional computer graphics Turbulence Vorticity Magnetohydrodynamics We present a systematic analysis of statistical properties of turbulent current and vorticity structures at a given time using cluster analysis. The data stem from numerical simulations of decaying three-dimensional magnetohydrodynamic turbulence in the absence of an imposed uniform magnetic field; the magnetic Prandtl number is taken equal to unity, and we use a periodic box with grids of up to 15363 points and with Taylor Reynolds numbers up to 1100. The initial conditions are either an X -point configuration embedded in three dimensions, the so-called Orszag-Tang vortex, or an Arn'old-Beltrami-Childress configuration with a fully helical velocity and magnetic field. In each case two snapshots are analyzed, separated by one turn-over time, starting just after the peak of dissipation. We show that the algorithm is able to select a large number of structures (in excess of 8000) for each snapshot and that the statistical properties of these clusters are remarkably similar for the two snapshots as well as for the two flows under study in terms of scaling laws for the cluster characteristics, with the structures in the vorticity and in the current behaving in the same way. We also study the effect of Reynolds number on cluster statistics, and we finally analyze the properties of these clusters in terms of their velocity-magnetic- field correlation. Self-organized criticality features have been identified in the dissipative range of scales. A different scaling arises in the inertial range, which cannot be identified for the moment with a known self-organized criticality class consistent with magnetohydrodynamics. We suggest that this range can be governed by turbulence dynamics as opposed to criticality and propose an interpretation of intermittency in terms of propagation of local instabilities. © 2010 The American Physical Society. Fil:Mininni, P.D. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_15393755_v82_n5_p_Uritsky |
| institution |
Universidad de Buenos Aires |
| institution_str |
I-28 |
| repository_str |
R-134 |
| collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
| topic |
Beltrami Cluster statistics Initial conditions Intermittency Local instability Magnetic Prandtl numbers Magnetohydrodynamic turbulence Numerical simulation Self-organized criticality Statistical properties Systematic analysis Taylor-Reynolds number Three dimensions Turbulence dynamics Vorticity structure X-point Cluster analysis Criticality (nuclear fission) Magnetic fields Reynolds number Three dimensional computer graphics Turbulence Vorticity Magnetohydrodynamics |
| spellingShingle |
Beltrami Cluster statistics Initial conditions Intermittency Local instability Magnetic Prandtl numbers Magnetohydrodynamic turbulence Numerical simulation Self-organized criticality Statistical properties Systematic analysis Taylor-Reynolds number Three dimensions Turbulence dynamics Vorticity structure X-point Cluster analysis Criticality (nuclear fission) Magnetic fields Reynolds number Three dimensional computer graphics Turbulence Vorticity Magnetohydrodynamics Uritsky, V.M. Pouquet, A. Rosenberg, D. Mininni, P.D. Donovan, E.F. Structures in magnetohydrodynamic turbulence: Detection and scaling |
| topic_facet |
Beltrami Cluster statistics Initial conditions Intermittency Local instability Magnetic Prandtl numbers Magnetohydrodynamic turbulence Numerical simulation Self-organized criticality Statistical properties Systematic analysis Taylor-Reynolds number Three dimensions Turbulence dynamics Vorticity structure X-point Cluster analysis Criticality (nuclear fission) Magnetic fields Reynolds number Three dimensional computer graphics Turbulence Vorticity Magnetohydrodynamics |
| description |
We present a systematic analysis of statistical properties of turbulent current and vorticity structures at a given time using cluster analysis. The data stem from numerical simulations of decaying three-dimensional magnetohydrodynamic turbulence in the absence of an imposed uniform magnetic field; the magnetic Prandtl number is taken equal to unity, and we use a periodic box with grids of up to 15363 points and with Taylor Reynolds numbers up to 1100. The initial conditions are either an X -point configuration embedded in three dimensions, the so-called Orszag-Tang vortex, or an Arn'old-Beltrami-Childress configuration with a fully helical velocity and magnetic field. In each case two snapshots are analyzed, separated by one turn-over time, starting just after the peak of dissipation. We show that the algorithm is able to select a large number of structures (in excess of 8000) for each snapshot and that the statistical properties of these clusters are remarkably similar for the two snapshots as well as for the two flows under study in terms of scaling laws for the cluster characteristics, with the structures in the vorticity and in the current behaving in the same way. We also study the effect of Reynolds number on cluster statistics, and we finally analyze the properties of these clusters in terms of their velocity-magnetic- field correlation. Self-organized criticality features have been identified in the dissipative range of scales. A different scaling arises in the inertial range, which cannot be identified for the moment with a known self-organized criticality class consistent with magnetohydrodynamics. We suggest that this range can be governed by turbulence dynamics as opposed to criticality and propose an interpretation of intermittency in terms of propagation of local instabilities. © 2010 The American Physical Society. |
| format |
JOUR |
| author |
Uritsky, V.M. Pouquet, A. Rosenberg, D. Mininni, P.D. Donovan, E.F. |
| author_facet |
Uritsky, V.M. Pouquet, A. Rosenberg, D. Mininni, P.D. Donovan, E.F. |
| author_sort |
Uritsky, V.M. |
| title |
Structures in magnetohydrodynamic turbulence: Detection and scaling |
| title_short |
Structures in magnetohydrodynamic turbulence: Detection and scaling |
| title_full |
Structures in magnetohydrodynamic turbulence: Detection and scaling |
| title_fullStr |
Structures in magnetohydrodynamic turbulence: Detection and scaling |
| title_full_unstemmed |
Structures in magnetohydrodynamic turbulence: Detection and scaling |
| title_sort |
structures in magnetohydrodynamic turbulence: detection and scaling |
| url |
http://hdl.handle.net/20.500.12110/paper_15393755_v82_n5_p_Uritsky |
| work_keys_str_mv |
AT uritskyvm structuresinmagnetohydrodynamicturbulencedetectionandscaling AT pouqueta structuresinmagnetohydrodynamicturbulencedetectionandscaling AT rosenbergd structuresinmagnetohydrodynamicturbulencedetectionandscaling AT mininnipd structuresinmagnetohydrodynamicturbulencedetectionandscaling AT donovanef structuresinmagnetohydrodynamicturbulencedetectionandscaling |
| _version_ |
1807318911200264192 |