On the ion-inertial range density power spectra in solar wind turbulence

Abstract. De-magnetised ions in the ion inertial range of quasi-neutral plasmas respond to Kolmogorov inertial range velocity turbulence power spectra via the spectrum of the velocity turbulence related random mean square induction electric field. Maintenance of electrical quasi-neutrality in this field causes deformation in the power spectral density of the density turbulence. Experimentally confirmed Kolmogorov inertial range spectra in solar wind velocity turbulence and observations of density power spectra suggest that the observed unexplained scale-limited occasional bumps in the density power spectrum may be caused by this electric ion response. Magnetic power spectra react passively to the density spectrum by warranting pressure balance. This effect still neglects contribution of Hall currents and is restricted to the ion inertial range scale. It occurs under certain conditions only. While both density and magnetic turbulence spectra in the range of ion inertial scales deviate from Kolmogorov, the velocity turbulence preserves its Kolmogorov inertial range shape in this process to which spectral advection turns out to be secondary.

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On the ion-inertial-range density-power spectra in solar wind turbulence

Annales Geophysicae ◽

10.5194/angeo-37-183-2019 ◽

2019 ◽

Vol 37 (2) ◽

pp. 183-199 ◽

Cited By ~ 2

Author(s):

Rudolf A. Treumann ◽

Wolfgang Baumjohann ◽

Yasuhito Narita

Keyword(s):

Solar Wind ◽

Source Region ◽

Power Spectra ◽

Density Fluctuations ◽

Inertial Range ◽

Wave Number ◽

Mean Flow ◽

Pressure Balance ◽

Density Spectrum ◽

Velocity Turbulence

Abstract. A model-independent first-principle first-order investigation of the shape of turbulent density-power spectra in the ion-inertial range of the solar wind at 1 AU is presented. Demagnetised ions in the ion-inertial range of quasi-neutral plasmas respond to Kolmogorov (K) or Iroshnikov–Kraichnan (IK) inertial-range velocity–turbulence power spectra via the spectrum of the velocity–turbulence-related random-mean-square induction–electric field. Maintenance of electrical quasi-neutrality by the ions causes deformations in the power spectral density of the turbulent density fluctuations. Assuming inertial-range K (IK) spectra in solar wind velocity turbulence and referring to observations of density-power spectra suggest that the occasionally observed scale-limited bumps in the density-power spectrum may be traced back to the electric ion response. Magnetic power spectra react passively to the density spectrum by warranting pressure balance. This approach still neglects contribution of Hall currents and is restricted to the ion-inertial-range scale. While both density and magnetic turbulence spectra in the affected range of ion-inertial scales deviate from K or IK power law shapes, the velocity turbulence preserves its inertial-range shape in the process to which spectral advection turns out to be secondary but may become observable under special external conditions. One such case observed by WIND is analysed. We discuss various aspects of this effect, including the affected wave-number scale range, dependence on the angle between mean flow velocity and wave numbers, and, for a radially expanding solar wind flow, assuming adiabatic expansion at fast solar wind speeds and a Parker dependence of the solar wind magnetic field on radius, also the presumable limitations on the radial location of the turbulent source region.

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Reflection-driven magnetohydrodynamic turbulence in the solar atmosphere and solar wind

Journal of Plasma Physics ◽

10.1017/s0022377819000540 ◽

2019 ◽

Vol 85 (4) ◽

Cited By ~ 13

Author(s):

Benjamin D. G. Chandran ◽

Jean C. Perez

Keyword(s):

Solar Wind ◽

Heating Rate ◽

Three Dimensional ◽

Power Spectra ◽

Inertial Range ◽

Magnetic Flux Tube ◽

Analytic Model ◽

Mhd Turbulence ◽

Background Magnetic Field ◽

Turbulent Heating

We present three-dimensional direct numerical simulations and an analytic model of reflection-driven magnetohydrodynamic (MHD) turbulence in the solar wind. Our simulations describe transverse, non-compressive MHD fluctuations within a narrow magnetic flux tube that extends from the photosphere, through the chromosphere and corona and out to a heliocentric distance $r$ of 21 solar radii $(R_{\odot })$ . We launch outward-propagating ‘ $\boldsymbol{z}^{+}$ fluctuations’ into the simulation domain by imposing a randomly evolving photospheric velocity field. As these fluctuations propagate away from the Sun, they undergo partial reflection, producing inward-propagating ‘ $\boldsymbol{z}^{-}$ fluctuations’. Counter-propagating fluctuations subsequently interact, causing fluctuation energy to cascade to small scales and dissipate. Our analytic model incorporates dynamic alignment, allows for strongly or weakly turbulent nonlinear interactions and divides the $\boldsymbol{z}^{+}$ fluctuations into two populations with different characteristic radial correlation lengths. The inertial-range power spectra of $\boldsymbol{z}^{+}$ and $\boldsymbol{z}^{-}$ fluctuations in our simulations evolve toward a $k_{\bot }^{-3/2}$ scaling at $r>10R_{\odot }$ , where $k_{\bot }$ is the wave-vector component perpendicular to the background magnetic field. In two of our simulations, the $\boldsymbol{z}^{+}$ power spectra are much flatter between the coronal base and $r\simeq 4R_{\odot }$ . We argue that these spectral scalings are caused by: (i) high-pass filtering in the upper chromosphere; (ii) the anomalous coherence of inertial-range $\boldsymbol{z}^{-}$ fluctuations in a reference frame propagating outwards with the $\boldsymbol{z}^{+}$ fluctuations; and (iii) the change in the sign of the radial derivative of the Alfvén speed at $r=r_{\text{m}}\simeq 1.7R_{\odot }$ , which disrupts this anomalous coherence between $r=r_{\text{m}}$ and $r\simeq 2r_{\text{m}}$ . At $r>1.3R_{\odot }$ , the turbulent heating rate in our simulations is comparable to the turbulent heating rate in a previously developed solar-wind model that agreed with a number of observational constraints, consistent with the hypothesis that MHD turbulence accounts for much of the heating of the fast solar wind.

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The usefulness of Poynting's theorem in magnetic turbulence

Annales Geophysicae ◽

10.5194/angeo-35-1353-2017 ◽

2017 ◽

Vol 35 (6) ◽

pp. 1353-1360 ◽

Cited By ~ 2

Author(s):

Rudolf A. Treumann ◽

Wolfgang Baumjohann

Keyword(s):

Solar Wind ◽

Self Organization ◽

Conductivity Spectrum ◽

Velocity Fluctuations ◽

Magnetic Turbulence ◽

Relativistic Transformation ◽

Solar Wind Turbulence ◽

Power Spectral ◽

Power Spectral Densities ◽

Wind Turbulence

Abstract. We rewrite Poynting's theorem, already used in a previous publication Treumann and Baumjohann (2017a) to derive relations between the turbulent magnetic and electric power spectral densities, to make explicit where the mechanical contributions enter. We then make explicit use of the relativistic transformation of the turbulent electric fluctuations to obtain expressions which depend only on the magnetic and velocity fluctuations. Any electric fluctuations play just an intermediate role. Equations are constructed for the turbulent conductivity spectrum in Alfvénic and non-Alfvénic turbulence in extension of the results in the above citation. An observation-based discussion of their use in application to solar wind turbulence is given. The inertial range solar wind turbulence exhibits signs of chaos and self-organization.

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Power Spectra Density Replication Control Strategy for 2-Axis Hydraulic Shaker Based on HV Estimator

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.596.610 ◽

2014 ◽

Vol 596 ◽

pp. 610-615

Author(s):

Yu Chen ◽

Qiang Li Luan ◽

Zhang Wei Chen ◽

Hui Nong He

Keyword(s):

Response Function ◽

Control Algorithm ◽

Power Spectra ◽

Time History ◽

Good Effect ◽

System Response ◽

Power Spectral ◽

Iterative Correction ◽

Replication Control ◽

The Given

Hydraulic shaker, equipment of simulating laboratory vibration environment, can accurately replicate the given power spectral density (PSD) and time history with an appropriate control algorithm. By studying method Hv estimator of frequency response function (FRF) estimation, a FRF identification strategy based on the Hv estimator is designed to increase the convergence rapidity and improve the system response function specialty. The system amplitude-frequency characteristics in some frequency points or frequency bands have large fluctuation. To solve this issue, a step-varying and frequency-sectioning iterative correction control algorithm is proposed for the control of 2-axial exciter PSD replication tests and the results show that the algorithm has a good effect on the control of hydraulic shaker, and can achieve reliable and high-precision PSD replication.

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