Study of Heat Transport Across a Quasi-Stochastic Magnetic Field in Magnetic Confined Plasma Physics

Heat diffusion across a non-local quasi-stochastic magnetic field in tokamak plasma is numerically studied. The perturbed magnetic field is found to be a key factor in influencing effective radial heat conductivity whether the magnetic field is stochastic or not. Being different from previous work, a non-local perturbed magnetic field is used. Analytical results and numerical simulation results are compared between the conditions with a full and a quasi-perturbed stochastic field. The analytical results are found to be still consistent with numerical simulation results when the perturbed field is quasi-stochastic.

Cosmological Constant and Energy Density of Random Electromagnetic Field

It is shown that the non-equilibrium electrically neutral and relativistically invariant vacuum-like state with the negative energy density and positive pressure may exist at the non-zero temperature in the system of spinor particles, antiparticles, and random electromagnetic field generated by particle-particle, particle-antiparticle, and antiparticle-antiparticle transitions. At the temperature of the order of 10 -5 K, the energy density of its state corresponds to the dark energy density in absolute magnitude. The cosmological constant for such material medium turns out to be negative.

RANDOM TERRAIN MODEL

In order to slove a realistic test problem of TF/TA algorithm, it is necessary to make a discrete terrain model. The model has adjustable roughness parameters so as to test the optimization procedure for different types of terrain. In this paper, an algorithm to generate random terrain data is given.

Simulation of stochastic wind field for large complex structures based on modified Fourier spectrum

Simulation for stochastic wind field is very important in analyzing dynamic responses of large complex structures due to strong wind.The typical simulation method is the spectrum representation method (SRM),but the SRM has drawbacks of inferior precision in lower frequency and slow calculating speed.In view of this,the modified Fourier spectrum method (MFSM) is introduced into the simulation of stochastic wind field in this paper.In this method,phase information of wind velocity time history is determined by cross power spectral density (CPSD) between adjacent points,and the wind velocity time history with time and space correlation is generated by iterative modification for CPSD considering auto power spectral density (APSD).Simulation of the wind field for a long-span bridge is undertaken to verify the effectiveness of the MFSM.Simulation results of the SRM and the MFSM are compared.It can be concluded that the MFSM is more accurate and has higher calculation speed than the SRM.

Study of the approximate approaches to the POD based spectral representation method

The spectral representation method (SRM) is most widely used in simulating the stochastic field.The proper orthogonal decomposition (POD) based SRM is an important form.This paper investigates the approximate approaches to the POD-based SRM in simulating two typical problems,i.e.,the seismic ground motion and wind velocity fields simulations.Then,the accuracy resulting from the power spectral density matrix-based POD method (PSRM) is compared to that of the coherency matrix-based POD method (CPSRM).It is concluded that the CPSRM maintains a much higher accuracy than the PSRM.In the CPSRM,the linear interpolation of eigenvectors and third-order polynomial interpolation of eigenvalues can be accepted to attain high accuracy;the linearly distributed interpolation nodes are effective in the ground motions simulation;however,the exponentially distributed interpolation nodes are effective in the wind velocity simulation.