Self–regularization by projection for noisy pseudodifferential equations of negative order

It is well known, that pseudodifferential equations of negative order considered in Sobolev spaces with small smoothness indices are ill–posed. On the other hand, it is known that efficient discretization schemes with properly chosen discretization parameters allow to obtain a regularization effect for such equations. The main accomplishment of the present paper is the principle for the adaptive choice of the discretization parameters directly from noisy discrete data. We argue that the combination of this principle with wavelet–based matrix compression techniques leads to algorithms which are order–optimal in the sense of complexity.     

Regularized numerical integration of multibody dynamics with the generalized method

This paper discusses the consistent regularization property of the generalized α method when applied as an integrator to an initial value high index and singular differential-algebraic equation model of a multibody system. The regularization comes from within the discretization itself and the discretization remains consistent over the range of values the regularization parameter may take. The regularization involves increase of the smallest singular values of the ill-conditioned Jacobian of the discretization and is different from Baumgarte and similar techniques which tend to be inconsistent for poor choice of regularization parameter. This regularization also helps where pre-conditioning the Jacobian by scaling is of limited effect, for example, when the scleronomic constraints contain multiple closed loops or singular configuration or when high index path constraints are present. The feed-forward control in Kane’s equation models is additionally considered in the numerical examples to illustrate the effect of regularization. The discretization presented in this work is adopted to the first order DAE system (unlike the original method which is intended for second order systems) for its A-stability and same order of accuracy for positions and velocities.     

New Optimization Approach to Multiphase Flow

A new optimization formulation for simulating multiphase flow in porous media is introduced. A locally mass-conservative, mixed finite-element method is employed for the spatial discretization. An unconditionally stable, fully-implicit time discretization is used and leads to a coupled system of nonlinear equations that must be solved at each time step. We reformulate this system as a least squares problem with simple bounds involving only one of the phase saturations. Both a Gauss–Newton method and a quasi-Newton secant method are considered as potential solvers for the optimization problem. Each evaluation of the least squares objective function and gradient requires solving two single-phase self-adjoint, linear, uniformly-elliptic partial differential equations for which very efficient solution techniques have been developed.     

Applied topics of control theory,mathematical statistics,and mathematical cybernetics

A stochastic discrepancy method is proposed for the construction of a solving system of equations of the projective grid method in Bubnov-Galerkin form. The interpolation polynomial on a finite element is viewed as the result of weighted averaging of the nodal parameters of the element. A simple posterior bound on discretization error is considered.Translated from Vychislitel'naya i Prikladnaya Matematika, No. 65, pp. 100–103, 1988.     

Semidiscretization and error estimates for distributed control of the instationary Navier-Stokes equations

Summary. Optimal control problems governed by the two-dimensional instationary Navier–Stokes equations and their spatial discretizations with finite elements are investigated. A concept of semi–discrete solutions to the control problem is introduced which is utilized to prove existence and uniqueness of discrete controls in neighborhoods of regular continuous solutions. Furthermore, an optimal error estimate in terms of the spatial discretization parameter is given.Correspondence to: M. Hinze     

Calculating unsteady seepage in a pressure gradient in the presence of thin weakly permeable inclusions

A new mathematical model is developed for unsteady seepage in a pressure gradient through a compressible foundation of a gravity dam with an antiseepage curtain. High-accuracy discretization algorithms are developed for the corresponding initial boundary-value problem with a discontinuous solution.Institute of Cybernetics of the Ukrainian Academy of Sciences and Kiev University. Translated from Vychislitel'naya i Prikladnaya Matematika, No. 74, pp. 32–38, 1992;     

Consistent approximations in Newton-type decomposition methods

Summary A class of Newton-type decomposition methods for the solution of large systems of nonlinear equations recently introduced by the first two authors is extended in such a way that consistent approximations to the derivatives by appropriate difference quotients are permitted. Concrete realizations with essential merits for practical computation and a rigorous convergence analysis are given. For special choices of the discretization parameterR-orders greater than one are derived.Dedicated to Prof. Dr. Dr. h.c. Lothar Collatz on the occasion of his 75th birthday     

A numerical method for the Cahn–Hilliard equation with a variable mobility

We consider a conservative nonlinear multigrid method for the Cahn–Hilliard equation with a variable mobility of a model for phase separation in a binary mixture. The method uses the standard finite difference approximation in spatial discretization and the Crank–Nicholson semi-implicit scheme in temporal discretization. And the resulting discretized equations are solved by an efficient nonlinear multigrid method. The continuous problem has the conservation of mass and the decrease of the total energy. It is proved that these properties hold for the discrete problem. Also, we show the proposed scheme has a second-order convergence in space and time numerically. For numerical experiments, we investigate the effects of a variable mobility.     

Numerical construction of an optimal control in the mayer problem with constraints for a nonlinear mechanical system

A methodology is proposed for the numerical construction of an optimal control for a nonlinear system in the presence of nonclassical constraints. The sequential linearization and reduction of all the constraints of the problem to a single integral form allow one on the different stages of solution of the problem to use their discretization step and thereby to preserve the dimension of the resulting nonlinear programming problem.Translated from Dinamicheskie Sistemy, No. 5, pp. 74–79, 1986.     

Chebyshev pseudospectral method for computing numerical solution of convection–diffusion equation

A method for computing highly accurate numerical solutions of 1D convection–diffusion equations is proposed. In this method, the equation is first discretized with respect to the spatial variable, transforming the original problem into a set of ordinary differential equations, and then the resulting system is integrated in time by the fourth-order Runge–Kutta method. Spatial discretization is done by using the Chebyshev pseudospectral collocation method. Before describing the method, we review a finite difference-based method by Salkuyeh [D. Khojasteh Salkuyeh, On the finite difference approximation to the convection–diffusion equation, Appl. Math. Comput. 179 (2006) 79–86], and, contrary to the proposal of the author, we show that this method is not suitable for problems involving time dependent boundary conditions, which calls for revision. Stability analysis based on pseudoeigenvalues to determine the maximum time step for the proposed method is also carried out. Superiority of the proposed method over a revised version of Salkuyeh’s method is verified by numerical examples.     

ERROR ESTIMATES FOR TWO-SCALE COMPOSITE FINITE ELEMENT APPROXIMATIONS OF NONLINEAR PARABOLIC EQUATIONS

We study spatially semidiscrete and fully discrete two-scale composite finite element method for approximations of the nonlinear parabolic equations with homogeneous Dirich-let boundary conditions in a convex polygonal domain in the plane.This new class of finite elements,which is called composite finite elements,was first introduced by Hackbusch and Sauter[Numer.Math.,75(1997),pp.447-472]for the approximation of partial differential equations on domains with complicated geometry.The aim of this paper is to introduce an efficient numerical method which gives a lower dimensional approach for solving par-tial differential equations by domain discretization method.The composite finite element method introduces two-scale grid for discretization of the domain,the coarse-scale and the fine-scale grid with the degrees of freedom lies on the coarse-scale grid only.While the fine-scale grid is used to resolve the Dirichlet boundary condition,the dimension of the finite element space depends only on the coarse-scale grid.As a consequence,the resulting linear system will have a fewer number of unknowns.A continuous,piecewise linear composite finite element space is employed for the space discretization whereas the time discretization is based on both the backward Euler and the Crank-Nicolson methods.We have derived the error estimates in the L∞(L2)-norm for both semidiscrete and fully discrete schemes.Moreover,numerical simulations show that the proposed method is an efficient method to provide a good approximate solution.     

Contraction behaviour of iteration–discretization based on gradient type projections

There is a wide range of iterative methods in infinite dimensional spaces to treat variational equations or variational inequalities. As a rule, computational handling of problems in infinite dimensional spaces requires some discretization. Any useful discretization of the original problem leads to families of problems over finite dimensional spaces. Thus, two infinite techniques, namely discretization and iteration are embedded into each other. In the present paper, the behaviour of truncated iterative methods is studied, where at each discretization level only a finite number of steps is performed. In our study no accuracy dependent a posteriori stopping criterion is used. From an algorithmic point of view, the considered methods are of iteration–discretization type. The major aim here is to provide the convergence analysis for the introduced abstract iteration–discretization methods. A special emphasis is given on algorithms for the treatment of variational inequalities with strongly monotone operators over fixed point sets of quasi-nonexpansive mappings.     

Error estimation and adaptive discretization for the discrete stochastic Hamilton–Jacobi–Bellman equation

Summary. Generalizing an idea from deterministic optimal control, we construct a posteriori error estimates for the spatial discretization error of the stochastic dynamic programming method based on a discrete Hamilton–Jacobi–Bellman equation. These error estimates are shown to be efficient and reliable, furthermore, a priori bounds on the estimates depending on the regularity of the approximate solution are derived. Based on these error estimates we propose an adaptive space discretization scheme whose performance is illustrated by two numerical examples.Mathematics Subject Classification (2000): 93E20, 65N50, 49L20, 49M25, 65N15Acknowledgments. This research was supported by the Center for Empirical Macroeconomics, University of Bielefeld. The support is gratefully acknowledged. I would also like to thank an anonymous referee who suggested several improvements for the paper.     

BDDC methods for discontinuous Galerkin discretization of elliptic problems

A discontinuous Galerkin (DG) discretization of Dirichlet problem for second-order elliptic equations with discontinuous coefficients in 2-D is considered. For this discretization, balancing domain decomposition with constraints (BDDC) algorithms are designed and analyzed as an additive Schwarz method (ASM). The coarse and local problems are defined using special partitions of unity and edge constraints. Under certain assumptions on the coefficients and the mesh sizes across ∂Ω_i, where the Ω_i are disjoint subregions of the original region Ω, a condition number estimate C(1+max_ilog(H_i/h_i))² is established with C independent of h_i, H_i and the jumps of the coefficients. The algorithms are well suited for parallel computations and can be straightforwardly extended to the 3-D problems. Results of numerical tests are included which confirm the theoretical results and the necessity of the imposed assumptions.     

Increasing the accuracy of solutions to a discrete spectral problem

Two methods for increasing the accuracy of discrete Sturm — Liouville problems are examined. In one of these the principal term of the expansion for the error of the eigenvalues by small parameter steps is used. The other method is based on a minimized functional, which corresponds to a discrete scheme of fourth-order accuracy relative to the discretization parameter.Translated fromVychislitel'naya i Prikladnaya Matematika, No. 69, pp. 56–63, 1989.     

Nyström discretization of parabolic boundary integral equations

A Nyström method for the discretization of thermal layer potentials is proposed and analyzed. The method is based on considering the potentials as generalized Abel integral operators in time, where the kernel is a time dependent surface integral operator. The time discretization is the trapezoidal rule with a corrected weight at the endpoint to compensate for singularities of the integrand. The spatial discretization is a standard quadrature rule for surface integrals of smooth functions. We will discuss stability and convergence results of this discretization scheme for second-kind boundary integral equations of the heat equation. The method is explicit, does not require the computation of influence coefficients, and can be combined easily with recently developed fast heat solvers.     

Uniformly Convergent Multigrid Methods for Convection–Diffusion Problems without Any Constraint on Coarse Grids

We construct a class of multigrid methods for convection–diffusion problems. The proposed algorithms use first order stable monotone schemes to precondition the second order standard Galerkin finite element discretization. To speed up the solution process of the lower order schemes, cross-wind-block reordering of the unknowns is applied. A V-cycle iteration, based on these algorithms, is then used as a preconditioner in GMRES. The numerical examples show that this method is convergent without imposing any constraint on the coarsest grid and the convergence of the preconditioned method is uniform.     

Numerical method for solving a boundary-value problem of thermoelasticity

We consider the problem of determining the stress-strain state of an elastoplastic layer under impulse heating. The theory of small elastoplastic strains with linear hardening is used. A boundary-value problem is obtained for the equations of thermoelasticity whose coefficients at any time are functionals of strain history. A method is developed for solving this problem, based on discretization by space and time variables and application of an appropriate difference scheme. This scheme constructs a recursive evolution process for the state column at the nodes of the space grid. Numerical implementation of the method has demonstrated its reliability and efficiency.Translated from Vychislitel'naya i Prikladnaya Matematika, No. 58, pp. 66–71, 1986.