Order Approximation Schemes Research Articles

Numerical simulation of contaminant biodegradation by higher order methods and adaptive time stepping

In this work we present and analyze a reliable and robust approximation scheme for biochemically reacting transport in the subsurface following Monod type kinetics. Water flow is modeled by the Richards equation. The proposed scheme is based on higher order finite element methods for the spatial discretization and the two step backward differentiation formula for the temporal one. The resulting nonlinear algebraic systems of equations are solved by a damped version of Newton's method. For the linear problems of the Newton iteration Krylov space methods are used. In computational experiments conducted for realistic subsurface (groundwater) contamination scenarios we show that the higher order approximation scheme significantly reduces the amount of inherent numerical diffusion compared to lower order ones. Thereby an artificial transverse mixing of the species leading to a strong overestimation of the biodegradation process is avoided. Finally, we present a robust adaptive time stepping technique for the coupled flow and transport problem which allows efficient long-term predictions of biodegradation processes.

NONLINEAR MONOTONIZATION OF THE BABENKO SCHEME

The goal of the paper is to present and test the nonlinear monotonization of the Babenko scheme for solving 2D linear advection equation with alternating‐sign velocities. The numerical method of monotonization is based on the idea of limited artificial diffusion. There are some approaches for constructing quasi‐monotonic second order approximation schemes for solving hyperbolic systems and equations of gas dynamics: flux correction methods, the Godunov method, TVD methods and others. In particular, many authors developed the idea of TVD method. We try to use this idea to get a new quasi‐monotonic high order accuracy scheme based on the well‐known non‐monotonic Babenko scheme. The algorithm is presented for 1D problem. For testing 2D problem we use the splitting algorithm. The proposed monotonized scheme has shown the best results among all considered in the paper schemes especially for non-smooth initial profile.

Nonlinear monotonization of the Babenko scheme 1

Abstract The goal of the paper is to present and test the nonlinear monotonization of the Babenko scheme for solving 2D linear advection equation with alternating‐sign velocities. The numerical method of monotonization is based on the idea of limited artificial diffusion. There are some approaches for constructing quasi‐monotonic second order approximation schemes for solving hyperbolic systems and equations of gas dynamics: flux correction methods, the Godunov method, TVD methods and others. In particular, many authors developed the idea of TVD method. We try to use this idea to get a new quasi‐monotonic high order accuracy scheme based on the well‐known non‐monotonic Babenko scheme. The algorithm is presented for 1D problem. For testing 2D problem we use the splitting algorithm. The proposed monotonized scheme has shown the best results among all considered in the paper schemes especially for non‐smooth initial profile.

A fast forward solution with a boundary element method for eddy current nondestructive testing

Eddy current non-destructive testing is used to determine position and size of cracks or other defects in conducting materials. The presence of a crack normal to the excited eddy currents distorts the magnetic field; so for the identification of defects a very accurate and fast 3D-computation of the magnetic field is necessary. A computation scheme for 3D quasistatic electromagnetic fields by means of the Boundary Element Method is presented. Although the use of constant field approximations on boundary elements is the easiest way, it often provides an insufficient accuracy. This can be overcome by higher order approximation schemes. The numerical results are compared against some analytically solvable arrangements.

Analysis of the Wilsonian effective potentials in dynamical chiral symmetry breaking

The nonperturbative renormalization group equation for the Wilsonian effective potential is given in a certain simple approximation scheme in order to study chiral symmetry breaking phenomena dynamically induced by strong gauge interactions. The evolving effective potential is found to be nonanalytic in the infrared, which indicates spontaneous generation of the fermion mass. It is also shown that the renormalization group equation gives the identical effective fermion mass with that obtained by solving the Schwinger-Dyson equation in the (improved) ladder approximation. Moreover, the introduction of the collective field corresponding to the fermion composite into the theory space is found to offer an efficient method to evaluate the order parameters: the dynamical mass and the chiral condensate. The relation between the renormalization group equation incorporating the collective field and the Schwinger-Dyson equation is also clarified.

On Application of Nonlinear Monotone High order Approximation Schemes in the Atmosphere Pollution Modeling Problem

On Application of Nonlinear Monotone High order Approximation Schemes in the Atmosphere Pollution Modeling Problem

Sigmoid generators for neural computing using piecewise approximations

A piecewise second order approximation scheme is proposed for computing the sigmoid function. The scheme provides high performance with low implementation cost; thus, it is suitable for hardwired cost effective neural emulators. It is shown that an implementation of the sigmoid generator outperforms, in both precision and speed, existing schemes using a bit serial pipelined implementation. The proposed generator requires one multiplication, no look-up table and no addition. It has been estimated that the sigmoid output is generated with a maximum computation delay of 21 bit serial machine cycles representing a speedup of 1.57 to 2.23 over other proposals.

A general scheme for first order approximations in optimization

In this paper we present a general approach for treating first order approximation schemes constrained extremum problems. We underline that, roughly speaking, these schemes present two geometric one and an analytical one. We will show that separation theorems and tangent fundamental role for deriving a scheme from the geometrical viewpoint; from the other derivative is the key concept for the analytical viewpoint. The purpose of the paper is scheme for first order approximations in optimization and to put in evidence the connections geometrical and analytical properties of the problem. The main interest is devoted to those which are useful for deriving necessary optimality conditions and for the construction of Solution methods.