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In this chapter, we extend the treatment we gave to power series in the preceding chapter to Fourier series and their generalizations, whether convergent or divergent. In particular, we are concerned with Fourier cosine and sine series, orthogonal polynomial expansions, series that arise from Sturm—Liouville problems, such as Fourier—Bessel series, and other general special function series.
Several convergence acceleration methods have been used on such series, with limited success. An immediate problem many of these methods face is that they do not produce any acceleration when applied to Fourier and generalized Fourier series. The transformations of Euler and of Shanks discussed in the following chapters and the d-transformation are exceptions. See the review paper by Smith and Ford [318] and the paper by Levin and Sidi [165]. With those methods that do produce acceleration, another problem one faces in working with such series is the lack of stability and acceleration near points of singularity of the functions that serve as limits or antilimits of these series. Recall that the same problem occurs in dealing with power series.
In this chapter, we show how the d-transformation can be used effectively to accelerate the convergence of these series. The approach we are about to propose has two main ingredients that can be applied also with some of the other sequence transformations.
An important problem that arises in many scientific and engineering applications is that of finding or approximating limits of infinite sequences {Am}. The elements Am of such sequences can show up in the form of partial sums of infinite series, approximations from fixed-point iterations of linear and nonlinear systems of equations, numerical quadrature approximations to finite- or infinite-range integrals, whether simple or multiple, etc. In most applications, these sequences converge very slowly, and this makes their direct use to approximate limits an expensive proposition. There are important applications in which they may even diverge. In such cases, the direct use of the Am to approximate their so-called “antilimits” would be impossible. (Antilimits can be interpreted in appropriate ways depending on the nature of {Am}. In some cases they correspond to analytic continuation in some parameter, for example.)
An effective remedy for these problems is via application of extrapolation methods (or convergence acceleration methods) to the given sequences. (In the context of infinite sequences, extrapolation methods are also referred to as sequence transformations.) Loosely speaking, an extrapolation method takes a finite and hopefully small number of the Am and processes them in some way. A good method is generally nonlinear in the Am and takes into account, either explicitly or implicitly, their asymptotic behavior as m → ∞ in a clever fashion.
In this paper, we study the exterior boundary value problems of the Darwinmodel to the Maxwell's equations. The variational formulation is establishedand the existence and uniqueness is proved. We use the infinite element methodto solve the problem, only a small amount of computational work is needed.Numerical examples are given as well as a proof of convergence.
Degenerate parabolic variational inequalities with convection are solved bymeans of a combined relaxation method and method of characteristics. Themathematical problem is motivated by Richard's equation, modelling theunsaturated – saturated flow in porous media. By means of the relaxationmethod we control the degeneracy. The dominance of the convection iscontrolled by the method of characteristics.
In this paper, the main purpose is to reveal what kind of qualitative dynamicalchanges a continuous age-structured model may undergo as continuous reproduction is replaced withan annual birth pulse. Using the discrete dynamical system determined by the stroboscopic map we obtain an exact periodic solution of system with density-dependent fertility and obtain the threshold conditions for its stability. We also present formal proofs of the supercritical flip bifurcation at the bifurcation as well as extensive analysis of dynamics in unstableparameter regions. Above this threshold, there is a characteristic sequence of bifurcations, leading to chaotic dynamics, which implies that the dynamical behavior of the single species model with birth pulses are very complex, including small-amplitude annual oscillations, large-amplitude multi-annual cycles, and chaos. This suggests that birth pulse, in effect, provides a natural period or cyclicity that allowsfor a period-doubling route to chaos. Finally, we discuss the effects of generation delay on stability of positiveequilibrium (or positive periodic solution), and show that generation delay is found to act both as a destabilizing and a stabilizing effect.
The paper deals with the numerical resolution of the convection-diffusion system which arises when modeling combustion for turbulent flow. The considered model is of compressible turbulent reacting type where the turbulence-chemistry interactions are governed by additional balance equations. The system of PDE's, that governs such a model, turns out to be in non-conservation form and usual numerical approaches grossly fail in the capture of viscous shock layers. Put in other words, classical finite volume methods induce large errors when approximated the convection-diffusion extracted system. To solve this difficulty, recent works propose a nonlinear projection scheme based on cancellation phenomenon of relevant dissipation rates of entropy. Unfortunately, such a property never holds in the present framework. The nonlinear projection procedures are thus extended.
We study in this paper some numerical schemes for hyperbolic systemswith unilateral constraint. In particular, we deal with the scalar case, the isentropicgas dynamics system and the full-gas dynamics system.We prove the convergence of the scheme to an entropy solutionof the isentropicgas dynamics with unilateral constraint on the density and mass loss.We also study the non-trivial steady states of the system.
In this paper we propose a finite element method for the approximation ofsecond order elliptic problems on composite grids. The method isbased on continuous piecewise polynomial approximation on eachgrid and weak enforcement of the proper continuity at anartificial interface defined by edges (or faces) of one the grids.We prove optimal order a priori and energy type a posteriori error estimates in 2 and 3 space dimensions,and present some numerical examples.
We study the gradient flow for the total variation functional, which arises in image processing and geometric applications. We propose a variational inequality weak formulation for the gradient flow,and establish well-posedness of the problem by the energy method. The main idea of our approach is to exploit the relationship betweenthe regularized gradient flow (characterized by a small positive parameterε, see (1.7)) and the minimal surface flow [21]and the prescribed mean curvature flow [16].Since our approach is constructive and variational, finite element methods can be naturally applied to approximate weak solutions of the limiting gradient flow problem. We propose a fully discrete finite element method and establish convergence tothe regularized gradient flow problem as h,k → 0, and to the total variation gradient flow problem as h,k,ε → 0in general cases.Provided that the regularized gradient flow problem possessesstrong solutions, which is proved possible if the datum functionsare regular enough, we establish practical a priori error estimates for the fully discrete finite element solution, in particular, by focusing on the dependence of the error bounds on the regularization parameter ε. Optimal order error bounds are derived for the numerical solution under the meshrelation k = O(h2). In particular, it is shown thatall error bounds depend on $\frac{1}{\varepsilon}$ onlyin some lower polynomial order for small ε.
By itself, a system of ordinary differential equations has many solutions. Commonly a solution of interest is determined by specifying the values of all its components at a single point x = a. This point and a direction of integration define an initial value problem. In many applications the solution of interest is determined in a more complicated way. A boundary value problem specifies values or equations for solution components at more than one point in the range of the independent variable x. Generally IVPs have a unique solution, but this is not true of BVPs. Like a system of linear algebraic equations, a BVP may not have a solution at all, or may have a unique solution, or may have more than one solution. Because there might be more than one solution, BVP solvers require an estimate (guess) for the solution of interest. Often there are parameters that must be determined in order for the BVP to have a solution. Associated with a solution there might be just one set of parameters, a finite number of possible sets, or an infinite number of possible sets. As with the solution itself, BVP solvers require an estimate for the set of parameters of interest. Examples of the possibilities were given in Chapter 1, and in this chapter others are used to penetrate further into the matter.