Boundary knot method for 2D and 3D Helmholtz and convection-diffusion problems under complicated geometry

The boundary knot method (BKM) of very recent origin is an inherently meshless, integration-free, boundary-type, radial basis function collocation technique for the numerical discretization of general partial differential equation systems. Unlike the method of fundamental solutions, the use of non-singular general solution in the BKM avoids the unnecessary requirement of constructing a controversial artificial boundary outside the physical domain. The purpose of this paper is to extend the BKM to solve 2D Helmholtz and convection-diffusion problems under rather complicated irregular geometry. The method is also first applied to 3D problems. Numerical experiments validate that the BKM can produce highly accurate solutions using a relatively small number of knots. For inhomogeneous cases, some inner knots are found necessary to guarantee accuracy and stability. The stability and convergence of the BKM are numerically illustrated and the completeness issue is also discussed.

A Numerical Study of Indentation Using Indenters of Different Geometry

Finite element simulation of the Berkovich, Vickers, Knoop, and cone indenters was carried out for the indentation of elastic-plastic material. To fix the semiapex angle of the cone, several rules of equivalence were used and examined. Despite the asymmetry and differences in the stress and strain fields, it was established that for the Berkovich and Vickers indenters, the load-displacement relation can closely be simulated by a single cone indenter having a semiapex angle equal to 70.3degrees in accordance with the rule of the volume equivalence. On the other hand, none of the rules is applicable to the Knoop indenter owing to its great asymmetry. The finite element method developed here is also applicable to layered or gradient materials with slight modifications.

Numerical Investigation of Toroidal Shock Wave Focusing in a Cylindrical Chamber

In this paper, focusing of a toroidal shock wave propagating from an annular shock tube into a cylindrical chamber was investigated numerically with the dispersion controlled dissipation (DCD) scheme. The first case for an incident Mach number of 1.5 was conducted and compared with experiments for validation. Then, several cases were calculated for higher incident Mach numbers varying from 2.0 to 5.0, and complicated flow structures were observed. The numerical study was mainly focused on two aspects: focusing process and flow structures. The process, including diffraction, focusing, and reflection, is displayed to reveal the focusing mechanism, and the flow structures at different incident. Mach numbers are used to demonstrate shock reflection styles and focusing characteristics.

A geometry model for tortuosity of flow path in porous media

A simple geometry model for tortuosity of flow path in porous media is proposed based on the assumption that some particles in a porous medium are unrestrictedly overlapped and the others are not. The proposed model is expressed as a function of porosity and there is no empirical constant in this model. The model predictions are compared with those from available correlations obtained numerically and experimentally, both of which are in agreement with each other. The present model can also give the tortuosity with a good approximation near the percolation threshold. The validity of the present tortuosity model is thus verified.

Fractal geometry model for effective thermal conductivity of three-phase porous media

An approximate model, a fractal geometry model, for the effective thermal conductivity of three-phase/unsaturated porous media is proposed based on the thermal-electrical analogy technique and on statistical self-similarity of porous media. The proposed thermal conductivity model is expressed as a function of porosity (related to stage n of Sierpinski carpet), ratio of areas, ratio of component thermal conductivities, and saturation. The recursive algorithm for the thermal conductivity by the proposed model is presented and found to be quite simple. The model predictions are compared with the existing measurements. Good agreement is found between the present model predictions and the existing experimental data. This verifies the validity of the proposed model. (C) 2004 American Institute of Physics.

Resonant mode analysis in toroidal cavities with elliptic cross-sections

Resonant cavity modes in a torus with elliptical cross section are studied by means of a direct variational method. The nonlinear effects of toroidicity and ellipticity on the frequency of the basic mode are analyzed simply and systematically without the restriction of linear theory. It is shown that the toroidicity effect on the m = 0 transverse magnetic mode is less-than-or-equal-to 11%. The frequency of the mode shifts approximately 11-29% when the elongation of the cross section changes from 1 to 2. The effects of toroidicity and ellipticity differ for each resonant mode.

Adiabatic compression of plasma with purely toroidal rotation

A variational method is developed to find approximate solutions to the generalized Grad-Shafranov equations for an adiabatic compression of the plasma with toroidal rotation, via the expansion in Fourier series in poloidal angle of the flux surface coordinates. The numerical results, which are carried out by the present method and by the usual two-dimensional method for a static equilibrium state, agree well.

Variational method for adiabatic compression of plasma with poloidal and toroidal rotation

A variational method is developed for adiabatic compression of plasma with both poloidal and toroidal rotation.

Numerical Investigation of Toroidal Shock Wave Focusing

In this paper,focusing of a toroidal shock wave propagating from a shock tube of an- nular cross-section into a cylindrical chamber was investigated numerically with the dispersion- controlled scheme. For CFD validation, the numerical code was rst applied to calculate both viscous and inviscid ows at a low Mach number of 1.5, which was compared with the experi- ment results and got better consistency. Then the validated code was used to calculate several cases for high Mach numbers. From the result, several major factors that in uent the ow, such as the Mach number and the viscosity, were analyzed detailedly and along with the high Mach number some unusual ow structure was observed and explained theoretically

Topology of toroidal helical fields in non-circular cross-sectional tokamaks

The ordinary differential magnetic field line equations are solved numerically; the tokamak magnetic structure is studied on Hefei Tokamak-7 Upgrade (HT-7U) when the equilibrium field with a monotonic q-profile is perturbed by a helical magnetic field. We find that a single mode (m, n) helical perturbation can cause the formation of islands on rational surfaces with q = m/n and q = (m +/- 1, +/- 2, +/- 3,...)/n due to the toroidicity and plasma shape (i.e. elongation and triangularity), while there are many undestroyed magnetic surfaces called Kolmogorov-Arnold-Moser (KAM) barriers on irrational surfaces. The islands on the same rational surface do not have the same size. When the ratio between the perturbing magnetic field B-r(r) and the toroidal magnetic field amplitude B(phi)0 is large enough, the magnetic island chains on different rational surfaces will overlap and chaotic orbits appear in the overlapping area, and the magnetic field becomes stochastic. It is remarkable that the stochastic layer appears first in the plasma edge region.

Effect of absorption on the diffraction efficiency in Fe : LiNbO3 crystal with 90 degrees recording geometry

In this paper the saturated diffraction efficiency has been optimized by considering the effect of the absorption of the recording light on a crossed-beam grating with 90 degrees recording geometry in Fe:LiNbO3 crystals. The dependence of saturated diffraction efficiency on the doping levels with a known oxidation-reduction state, as well as the dependence of saturated diffraction efficiency on oxidation-reduction state with known doping levels, has been investigated. Two competing effects on the saturated diffraction efficiency were discussed, and the intensity profile of the diffracted beam at the output boundary has also been investigated. The results show that the maximal saturated diffraction efficiency can be obtained in crystals with moderate doping levels and modest oxidation state. An experimental verification is performed and the results are consistent with those of the theoretical calculation.

The multi-weight neuron with geometry algorithm and its application

A novel approach for multi-dimension signals processing, that is multi-weight neural network based on high dimensional geometry theory, is proposed. With this theory, the geometry algorithm for building the multi-weight neuron is mentioned. To illustrate the advantage of the novel approach, a Chinese speech emotion recognition experiment has been done. From this experiment, the human emotions are classified into 6 archetypal classes: fear, anger, happiness, sadness, surprise and disgust. And the amplitude, pitch frequency and formant are used as the feature parameters for speech emotion recognition. Compared with traditional GSVM model, the new method has its superiority. It is noted that this method has significant values for researches and applications henceforth.

Geometrical learning, descriptive geometry, and biomimetic pattern recognition

Studies on learning problems from geometry perspective have attracted an ever increasing attention in machine learning, leaded by achievements on information geometry. This paper proposes a different geometrical learning from the perspective of high-dimensional descriptive geometry. Geometrical properties of high-dimensional structures underlying a set of samples are learned via successive projections from the higher dimension to the lower dimension until two-dimensional Euclidean plane, under guidance of the established properties and theorems in high-dimensional descriptive geometry. Specifically, we introduce a hyper sausage like geometry shape for learning samples and provides a geometrical learning algorithm for specifying the hyper sausage shapes, which is then applied to biomimetic pattern recognition. Experimental results are presented to show that the proposed approach outperforms three types of support vector machines with either a three degree polynomial kernel or a radial basis function kernel, especially in the cases of high-dimensional samples of a finite size. (c) 2005 Elsevier B.V. All rights reserved.