Critical properties of the self-consistent Ornstein–Zernike approximation for three-dimensional lattice gases with varying range of interaction

1998 ◽  
Vol 108 (11) ◽  
pp. 4516-4524 ◽  
Author(s):  
A. Borge ◽  
J. S. Ho/ye
Keyword(s):  
Three Dimensional ◽  
The Self ◽  
Lattice Gases ◽  
Critical Properties ◽  
Dimensional Lattice ◽  
Self Consistent

scholarly journals Three-dimensional modelling of accretion columns: spatial asymmetry and self-consistent simulations

2020 ◽  
Vol 501 (1) ◽  
pp. 564-575
Author(s):  
M I Gornostaev
Keyword(s):  
Radiation Flux ◽  
Three Dimensional ◽  
3D Models ◽  
3D Modelling ◽  
The Self ◽  
Physical Parameters ◽  
Hydrodynamic Simulations ◽  
X Ray ◽  
Self Consistent ◽  
Column Base

ABSTRACT The paper presents the results of three-dimensional (3D) modelling of the structure and the emission of accretion columns formed above the surface of accreting strongly magnetized neutron stars under the circumstances when a pressure of the photons generated in the column base is enough to determine the dynamics of the plasma flow. On the foundation of numerical radiation hydrodynamic simulations, several 3D models of accretion column are constructed. The first group of the models contains spatially 3D columns. The corresponding calculations lead to the distributions of the radiation flux over the sidewalls of the columns which are not characterized by axial symmetry. The second group includes the self-consistent modelling of spectral radiative transfer and two-dimensional spatial structure of the column, with both thermal and bulk Comptonization taken into account. The changes in the structure of the column and the shape of X-ray continuum are investigated depending on physical parameters of the model.

Parallel 3-D particle-in-cell modelling of charged ultrarelativistic beam dynamics

2015 ◽  
Vol 81 (6) ◽  
Author(s):  
Marina A. Boronina ◽  
Vitaly A. Vshivkov
Keyword(s):  
Distribution Function ◽  
Electromagnetic Fields ◽  
High Efficiency ◽  
Three Dimensional ◽  
The Self ◽  
Beam Dynamics ◽  
Particle In Cell ◽  
Self Consistent ◽  
Longitudinal Effects ◽  
Parallel Code

We present a three-dimensional (3-D) particle-in-cell (PIC) model and parallel code for the self-consistent motion of charged ultrarelativistic beams (${\it\gamma}\sim 10^{3}{-}10^{5}$) in supercolliders. We use the 3-D set of Maxwell’s equations for the electromagnetic fields, and the Vlasov equation for the distribution function of the beam particles. The model incorporates automatically the longitudinal effects, which can play a significant role in the cases of super-high densities. We present numerical results for the dynamics of two focused ultrarelativistic beams with a size ratio 10:1:100. The results demonstrate high efficiency of the proposed computational methods and algorithms, which are applicable to a variety of problems in relativistic plasma physics.

scholarly journals Three-Dimensional MHD Modeling of Interplanetary Solar Wind Using Self-Consistent Boundary Condition Obtained from Multiple Observations and Machine Learning

Universe ◽  
2021 ◽  
Vol 7 (10) ◽  
pp. 371
Author(s):  
Yi Yang ◽  
Fang Shen
Keyword(s):  
Magnetic Field ◽  
Machine Learning ◽  
Boundary Condition ◽  
Solar Wind ◽  
Three Dimensional ◽  
The Self ◽  
Multiple Observations ◽  
Self Consistent ◽  
Mhd Modeling ◽  
The Magnetic Field

Three-dimensional (3-d) magnetohydrodynamics (MHD) modeling is a key method for studying the interplanetary solar wind. In this paper, we introduce a new 3-d MHD solar wind model driven by the self-consistent boundary condition obtained from multiple observations and the Artificial Neural Network (ANN) machine learning technique. At the inner boundary, the magnetic field is derived using the magnetogram and potential field source surface extrapolation; the electron density is derived from the polarized brightness (pB) observations, the velocity can be deduced by an ANN using both the magnetogram and pB observations, and the temperature is derived from the magnetic field and electron density by a self-consistent method. Then, the 3-d interplanetary solar wind from CR2057 to CR2062 is modeled by the new model with the self-consistent boundary conditions. The modeling results present various observational characteristics at different latitudes, and are in better agreement with both the OMNI and Ulysses observations compared to our previous MHD model based only on photospheric magnetic field observations.

scholarly journals Influence of the Self-Consistent Regional Ensemble Background Error Covariance on Hurricane Inner-Core Data Assimilation with the GSI-Based Hybrid System for HWRF

2016 ◽  
Vol 73 (12) ◽  
pp. 4911-4925 ◽  
Author(s):  
Zhaoxia Pu ◽  
Shixuan Zhang ◽  
Mingjing Tong ◽  
Vijay Tallapragada
Keyword(s):  
Data Assimilation ◽  
Inner Core ◽  
Doppler Radar ◽  
Three Dimensional ◽  
The Self ◽  
Background Error ◽  
Core Data ◽  
Background Error Covariance ◽  
Error Covariance ◽  
Self Consistent

Abstract An initial vortex spindown, or strong adjustment to the structure and intensity of a hurricane’s initial vortex, presents a significant problem in hurricane forecasting, as with the NCEP Hurricane Weather Research and Forecasting Model (HWRF), because it can cause significantly degraded intensity forecasts. In this study, the influence of the self-consistent regional ensemble background error covariance on assimilating hurricane inner-core tail Doppler radar (TDR) observations in HWRF is examined with the NCEP gridpoint statistical interpolation (GSI)-based ensemble–three-dimensional variational (3DVAR) hybrid data assimilation system. It is found that the resolution of the background error covariance term, coming from the ensemble forecasts, has notable influence on the assimilation of hurricane inner-core observations and subsequent forecasting results. Specifically, the use of ensemble forecasting at high-resolution native grids results in significant reduction of the vortex spindown problem and thus leads to improved hurricane intensity forecasting. Further diagnoses are conducted to examine the spindown problem with a gradient wind balance. It is found that artificial vortex initialization, performed before data assimilation, can cause strong supergradient winds or imbalance in the vortex inner-core region. Assimilation of hurricane inner-core TDR data can significantly mitigate this imbalance by reducing the supergradient effects. Compared with the use of a global ensemble background error term, application of the self-consistent regional ensemble background covariance to inner-core data assimilation leads to better representation of the mesoscale hurricane inner-core structures. It can also result in more realistic vortex structures in data assimilation even when the observational data are unevenly distributed.

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