Current sheets with multi-component plasma in planetary magnetospheres

2020 ◽  
Author(s):  
Victor Popov ◽  
Vladimir Domrin ◽  
Helmi Malova ◽  
Elena Grigorenko ◽  
Anatoly Petrukovich
Keyword(s):  
Current Sheet ◽  
Space Plasma ◽  
The Self ◽  
Oxygen Ions ◽  
Sheet Structure ◽  
Self Consistent ◽  
Thin Current Sheet ◽  
Component Plasma ◽  
Current Densities ◽  
Simulation Results

<p>The self-consistent hybrid model of a thin current sheet with a thickness about several proton gyroradii in a space plasma is proposed, taking into account multicomponent collisionless space plasma. Several plasma components are often presented in planetary magnetotails (Hermean, Martian, Terrestrial and other ones). Influence of heavy oxygen ions with different properties on current sheet structure is analyzed. It is shown that high relative concentrations of oxygen ions, as well as their relatively high temperatures and flow drift speeds lead to a significant thickening of the sheet and a formation of an additional embedding scale. For some real parameters the profiles of self-consistent current densities and magnetic field have symmetrical jumps of derivatives, i.e. sharp changes of gradients. The comparison is made with observations in the Martian magnetosphere. The qualitative agreement of simulation results with observational data is shown.</p>

scholarly journals Quantum Transport Simulation of the DOS function, Self-Consistent Fields and Mobility in MOS Inversion Layers

VLSI Design ◽  
1998 ◽  
Vol 6 (1-4) ◽  
pp. 21-25 ◽  
Author(s):  
Dragica Vasileska ◽  
Terry Eldridge ◽  
Paolo Bordone ◽  
David K. Ferry
Keyword(s):  
Quantum Transport ◽  
Born Approximation ◽  
Inversion Layer ◽  
The Self ◽  
Charge Densities ◽  
Self Energy ◽  
Self Consistent ◽  
Inversion Charge ◽  
Simulation Results ◽  
Subband Structure

We describe a simulation of the self-consistent fields and mobility in (100) Si-inversion layers for arbitrary inversion charge densities and temperatures. A nonequilibrium Green's functions formalism is employed for the state broadening and conductivity. The subband structure of the inversion layer electrons is calculated self-consistently by simultaneously solving the Schrödinger, Poisson and Dyson equations. The self-energy contributions from the various scattering mechanisms are calculated within the self-consistent Born approximation. Screening is treated within RPA. Simulation results suggest that the proposed theoretical model gives mobilities which are in excellent agreement with the experimental data.

scholarly journals Thin current sheet embedded within a thicker plasma sheet: Self-consistent kinetic theory

2000 ◽  
Vol 105 (A6) ◽  
pp. 13029-13043 ◽  
Author(s):  
M. I. Sitnov ◽  
L. M. Zelenyi ◽  
H. V. Malova ◽  
A. S. Sharma
Keyword(s):  
Kinetic Theory ◽  
Current Sheet ◽  
Plasma Sheet ◽  
Self Consistent ◽  
Thin Current Sheet

Influence of Oxygen Ions on the Structure of the Thin Current Sheet in the Earth’s Magnetotail

2020 ◽  
Vol 60 (2) ◽  
pp. 171-183
Author(s):  
V. I. Domrin ◽  
Kh. V. Malova ◽  
V. Yu. Popov ◽  
E. E. Grigorenko ◽  
A. A. Petrukovich
Keyword(s):  
Current Sheet ◽  
Oxygen Ions ◽  
Thin Current Sheet

scholarly journals An Intelligent Evaluation Method to Analyze the Competitiveness of Airlines

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Jun Zhao ◽  
Xumei Chen
Keyword(s):  
Neural Network ◽  
Prior Knowledge ◽  
Evaluation Method ◽  
Standard Sample ◽  
Reference Value ◽  
The Self ◽  
Index Data ◽  
Som Neural Network ◽  
Simulation Results ◽  
Self Organizing

An intelligent evaluation method is presented to analyze the competitiveness of airlines. From the perspective of safety, service, and normality, we establish the competitiveness indexes of traffic rights and the standard sample base. The self-organizing mapping (SOM) neural network is utilized to self-organize and self-learn the samples in the state of no supervision and prior knowledge. The training steps of high convergence speed and high clustering accuracy are determined based on the multistep setting. The typical airlines index data are utilized to verify the effect of the self-organizing mapping neural network on the airline competitiveness analysis. The simulation results show that the self-organizing mapping neural network can accurately and effectively classify and evaluate the competitiveness of airlines, and the results have important reference value for the allocation of traffic rights resources.

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