Iterative techniques for 3-D boundary element method systems of equations

A key issue in the boundary element method (BEM) is the solution of the associated system of algebraic equations whose matrices are dense, nonsymmetric and sometimes ill conditioned. For large scale tridimensional problems, direct methods like Gauss elimination become too expensive and iterative methods may be preferable. This paper presents a comparison of the performances of some iterative techniques based on conjugate gradient solvers as conjugate gradient squared (CGS) and bi-conjugate gradient (Bi-CG) that seem to have the potential to be efficient and competitive for BEM algebraic systems of equations, specially when used with an appropriate preconditioner. A comparison with the direct application of the conjugate gradient method to the normalized systems of equations (CGNE and CGNR) is also presented.     

Explicit solutions of certain multidimensional inverse problems for systems of parabolic-type equations

Explicit solutions have been found for inverse problems of determining the system coefficients of parabolic equations, where the unknown coefficients are functions of time and space variables. The results of numerical calculations are given.Translated from Inzhenerno-Fizicheskii Zhurnal, Vol. 56, No. 2, pp. 319–327, February, 1989.     

Periodic solutions in systems of piecewise- linear differential equations

Motivated by the periodic behaviour of regulatory networks within cell biology and neurology, we have studied the periodic solutions of piecewise-linear, first- order differential equations with identical relative decay rates. The flow of the solution trajectories can be represented qualitatively by a directed graph. By examining the cycles in this graph and solving the eigenvalue problem for corresponding mapping matrices, all closed, period-1 orbits can be found by analytical means. Theorems about their exist- ence, stabiiiiy and uniqueness are derived. For three-dimensional systems, the basins of attraction of the limit cycles can be explicitly determined and it is shown that higher periodic and chaotic solutions do not exist.     

Smoothing techniques for certain primitive variable solutions of the Navier–Stokes equations

Several types of smoothing technique are considered which generate continuous approximation (i.e. nodal values) for vorticity and pressure from finite element solutions of the Navier–Stokes equations using quadrilateral elements. The simpler schemes are based on combinations of linear extrapolation and/or averaging algorithms which convert elementwise. Gauss point values to nodal point values. More complicated schemes, based on a global smoothing technique which employ the mass matrix (consistent or lumped), are also presented. An initial assessment of the accuracy of the several schemes is obtained by comparing the approximate vorticities with an analytical function. Next, qualitative vorticity comparisons are made from numerical solutions of the steady-state driven cavity problem. Finally, applications of smoothing techniques to discontinuous pressure fields are demonstrated.     

On decomposing systems of polynomial equations with finitely many solutions

This paper deals with systems ofm polynomial equations inn unknown, which have only finitely many solutions. A method is presented which decomposes the solution set into finitely many subsets, each of them given by a system of type $$f_1 \left( {x_1 } \right) = 0,f_2 \left( {x_1 ,x_2 } \right) = 0, \ldots ,f_n \left( {x_1 , \ldots ,x_n } \right) = 0$$ . The main tools for the decomposition are from ideal theory and use symbolical manipulations. For the ideal generated by the polynomials which describe the solution set, a lexicographical Gröbner basis is required. A particular element of this basis allows the decomposition of the solution set. By a recursive application of these decomposition techniques the triangular subsystems are finally obtained. The algorithm gives even for non-finite solution sets often also usable decompositions.     

New integral relations for analytical solutions of parabolic-type equations in noncylindrical domains

The theory of the method of Green’s functions in solving boundary-value problems of nonstationary heat conduction in domains with moving boundaries has been developed. A modification of the thermal-potential method for a uniform law of motion of the boundary has been proposed, which leads to integral relations of a new (simplest) form compared to the existing results; this makes it possible to consider numerous particular cases that are of practical interest for many applications. A number of special features of model representations of nonstationary heat transfer in domains with moving boundaries have been revealed.     

New reliability modeling methods for structural systems with hybrid uncertainty

The present study investigates the hybrid reliability modeling of structures in which the inputs contain both random variables and interval variables. Hybrid uncertainty is divided into three categories, including random variables mixed with random variables, interval variables mixed with interval variable, and random variables mixed with interval variables. In order to perform the reliability analysis of structural systems, first, the Bayes method is proposed in the present study to obtain distribution parameters of random variables. Moreover, the self-sample method is introduced to obtain the interval boundaries based on the least available measuring data. Then, the reliability models are established for three situations and the reliability indices are defined and derived accordingly. The abovementioned three types of reliability indices outline the general situation of structural systems. Finally, the specific calculation process is described in details through different examples. Furthermore, the accuracy and efficiency of the proposed method is discussed by comparing the results obtained from the Monte Carlo simulation and those of other methods. The obtained results indicate that the performance of the proposed model in solving reliability modeling problems is better.     

Parallel multisplitting,block Jacobi type solutions of linear systems of equations

Three parallel iterative schemes to solve banded systems of equations are presented in this study. The techniques are special implementations of the theory of matrix multisplitting. The resulting algorithms are implemented on a Multiple Instruction Multiple Data (MIMD) grid architecture using 16 Transputer processors. Parametric analyses are performed to develop convergence criteria and examine the speed-up of solution. It is concluded that the algorithms make very efficient use of the parallel computer architecture, especially if this consists of a large number of nodes.     

Bounded solutions for non-autonomous parabolic equations

The existence of bounded solutions (including in particular homoclinic and heteroclinic solutions) is studied for non-autonomous perturbed parabolic partial differential equations, without the restriction that the linear variational equation has a unique non-trivial bounded solution. Specifically, an idea applied to ordinary differential equations by Hale (1984) and by Battelli and Laari (1990) is realised in an infinite-dimensional setting. Like other work on related problems, the main technique is Lyapunov?Schmidt reduction; we use that technique here in the context of bounded solutions, rather than the more usual setting of periodic or homoclinic solutions. Moreover, several technical obstacles are circumvented in the infinite-dimensional setting?in particular in the proof of the existence of a solution to the reduced bifurcation equation. Non-uniqueness is shown to occur for the Kuramoto-Sivashinsky equation, demonstrating the need to remove the uniqueness restriction     

A new hybrid method for solving linear–non‐linear systems of equations

This paper presents a new method for solving any combination of linear–non‐linear equations. The method is based on the separation of linear equations in terms of some selected variables from the non‐linear ones. The linear group is solved by means of any method suitable for the linear system. This operation needs no iteration. The non‐linear group, however, is solved by an iteration technique based on a new formula using the Taylor series expansion. The method has been described and demonstrated in several examples of analytical systems with very good results. The new method needs the initial approximations for non‐linear variables only. This requires far less computation than the Newton–Raphson method. The method also has a very good convergence rate. The proposed method is most beneficial for engineering systems that very often involve a large number of linear equations with limited number of non‐linear equations. Copyright © 2005 John Wiley & Sons, Ltd.     

A comparison of direct and preconditioned iterative techniques for sparse,unsymmetric systems of linear equations

In this paper we compare direct and preconditioned iterative methods for the solution of nonsymmetric, sparse systems of linear algebraic equations. These problems occur in finite difference and finite element simulations of semiconductor devices, and fluid flow problems. We consider five iterative methods that appear to be the most promising for this class of problems: the biconjugate gradient method, the conjugate gradient squared method, the generalized minimal residual method, the generalized conjugate residual method and the method of orthogonal minimization. Each of these methods was tested using similar preconditioning (incomplete LU factorization) on a set of large, sparse matrices arising from finite element simulation of semiconductor devices. Results are shown where we compare the computation time and memory requirements for each of these methods against one another, as well as against a direct method that uses LU factorization to solve these problems. The results of our numerical experiments show that preconditioned iterative methods are a practical alternative to direct methods in the solution of large, sparse systems of equations, and can offer significant savings in storage and CPU time.     

(2+1)维非线性演化方程的形式新解

主要从两个方面讨论(1)将非线性演化方程的形式级数解进行对称延拓;(2)利用"秩"的概念,对非线性演化方程进行分类.即如果方程各项中"秩"的取值全为奇数或偶数,则可借助椭圆方程的方法解之;若方程各项中"秩"的取值奇偶性不一致,则给出一形式幂级数解.并以两个(2+1)维非线性演化方程为例,说明改进的方法能较好地求得非线性演化方程的更多形式新解.     

On asymptotic behavior of oscillatory solutions of operator differential equations perturbed by a fast Markov process

We study the asymptotic behavior of the distributions of the solution of the differential equation of the form

in a separable Hilbert space H where y(t) is an ergodic homogenous Markov process in a measurable space (Y, C) satisfying some mixing conditions and A(y), y Y is a family of commuting closed linear operators with the same dense domain. Using the spectral representation of the solution we construct an H-valued process û_ε(t) which is expressed in terms of the solution of the averaged equation

where = ƒ A(y)(dy) and is the ergodic distribution of Y(t), and some Gaussian random fields with independent increments. We show that the distributions of u_ε(t/ε) and û_ε(t) asymptotically coincide.     

An analytical-numerical method for fast evaluation of probability densities for transient solutions of nonlinear Itô’s stochastic differential equations

Probability densities for solutions of nonlinear Itô’s stochastic differential equations are described by the corresponding Kolmogorov-forward/Fokker-Planck equations. The densities provide the most complete information on the related probability distributions. This is an advantage crucial in many applications such as modelling floating structures under the stochastic-load due to wind or sea waves. Practical methods for numerical solution of the probability density equations are combined, analytical-numerical techniques. The present work develops a new analytical-numerical approach, the successive-transition (ST) method, which is a version of the path-integration (PI) method. The ST technique is based on an analytical approximation for the transition probability density. It enables the PI approach to explicitly allow for the damping matrix in the approximation. This is achieved by extending another method, introduced earlier for bistable nonlinear reaction-diffusion equations, to the probability density equations. The ST method also includes a control for the size of the time-step. The overall accuracy of the ST method can be tested on various nonlinear examples. One such example is proposed. It is one-dimensional nonlinear Itô’s equation describing the velocity of a ship maneuvering along a straight line under the action of the stochastic drag due to wind or sea waves. Another problem in marine engineering, the rolling of a ship up to its possible capsizing is also discussed in connection with the complicated damping matrix picture. The work suggests a few directions for future research.     

Reduced-basis techniques for rapid reliable optimization of systems described by affinely parametrized coercive elliptic partial differential equations

We present a technique for the rapid and reliable optimization of systems characterized by linear-functional outputs of coercive elliptic partial differential equations with affine (input) parameter dependence. The critical ingredients are: reduced-basis approximation to effect significant reduction in state-space dimensionality; a posteriori error bounds to provide rigorous error estimation and control; “offline/online” computational decompositions to permit rapid evaluation of output bounds, output bound gradients, and output bound Hessians in the limit of many queries; and reformulation of the approximate optimization statement to ensure (true) feasibility and control of suboptimality. To illustrate the method we consider the design of a three-dimensional thermal fin: Given volume and power objective-function weights, and root temperature “not-to-exceed” limits, the optimal geometry and heat transfer coefficient can be determined—with guaranteed feasibility—in only 2.3 seconds on a 500 MHz Pentium machine; note the latter includes only the online component of the calculations. Our method permits not only interactive optimal design at conception and manufacturing, but also real-time reliable adaptive optimal design in operation.     

Analytical solutions of coupled-mode equations for multiwaveguide systems, obtained by use of Chebyshev and generalized Chebyshev polynomials

A novel approach is proposed for obtaining the analytical solutions of the coupled-mode equations (CMEs); the method is applicable for an arbitrary number of coupled waveguides. The mathematical aspects of the CMEs and their solution by use of Chebyshev polynomials are discussed. When mode coupling between only adjacent waveguides is considered (denoted weak coupling), the first and second kinds of the usual Chebyshev polynomials are appropriate for evaluating the CMEs for linearly distributed and circularly distributed multiwaveguide systems, respectively. However, when one is considering the coupling effects between nonadjacent waveguides also (denoted strong coupling), it is necessary to use redefined generalized Chebyshev polynomials to express general solutions in a form similar to those for the weak-coupling case. As concrete examples, analytical solutions for 2 x 2, 3 x 3, and 4 x 4 linearly distributed directional couplers are obtained by the proposed approach, which treats the calculation as a nondegenerate eigenvalue problem. In addition, for the 3 x 3 circularly distributed directional coupler, which gives rise to a degenerate eigenvalue problem, an analytical solution is obtained in an improved way. Also, for comparison and without loss of generality, to clarify the difference between the two coupling cases, analytical solutions for a 5 x 5 circularly distributed directional coupler are obtained by use of the usual and the redefined generalized Chebyshev polynomials.     

Reliability analysis techniques for mechanical systems

This paper discusses the application of known system reliability analysis techniques and identifies problems encountered in the practical implementation of these methods, revealing that no single technique is sufficient or even feasible in the case of complex mechanical systems. A new functional analysis method as well as a (new) criticality quantitative approach and failure mechanism analysis are presented and used to analyse an aircraft fuel system. A rigorous and detailed FMECA is still required. Besides its main function it will supply much of the valuable information for many other techniques.     

Advanced modeling techniques for micromagnetic systems

We present a review of micromagnetic and magnetotransport modeling methods which go beyond the standard model. We first give a brief overview of the standard micromagnetic model, which for (i) the steady-state (equilibrium) solution is based on the minimization of the free energy functional, and for (ii) the dynamical solution, relies on the numerical solution of the Landau-Lifshitz-Gilbert (LLG) equation. We present three complements to the standard model, i.e., (i) magnetotransport calculations based on ohmic conduction in the presence of the anisotropic magnetoresistance (AMR) effect, (ii) magnetotransport calculations based on spin-dependent tunneling in the presence of single charge tunneling (Coulomb blockade) effect, and (iii) stochastic micromagnetics, which incorporates the effects of thermal fluctuations via a white-noise thermal field in the LLG equation. All three complements are of practical importance: (i) magnetotransport model either in the ohmic or tunneling transport regimes, enables the conversion of the micromagnetic results to the measurable quantity of magnetoresistance ratio, while (ii) stochastic modeling is essential as the dimensions of the micromagnetic system reduces to the deep submicron regime and approaches the superparamagnetic limit.