A collocation method based on the Bessel functions of the first kind for singular perturbated differential equations and residual correction

In this paper, a collocation method is given to solve singularly perturbated two‐point boundary value problems. By using the collocation points, matrix operations and the matrix relations of the Bessel functions of the first kind and their derivatives, the boundary value problem is converted to a system of the matrix equations. By solving this system, the approximate solution is obtained. Also, an error problem is constructed by the residual function, and it is solved by the presented method. Thus, the error function is estimated, and the approximate solutions are improved. Finally, numerical examples are given to show the applicability of the method, and also, our results are compared by existing results. Copyright © 2014 JohnWiley & Sons, Ltd.     

Short-cut distillation columns based on orthogonal polynomials of a discrete variable

Increasing competition in the process industries enforces theapplication of mathematical simulation techniques both in thedesign phase and in the operating phase of a plant. A basicapparatus for separation processes is the distillation column.Its rigorous (tray by tray) mathematical modelling results ina system of simultaneous nonlinear equations (algebraic in thesteady-state case, differential-algebraic in the dynamic case).For high (and realistic) numbers of trays and components, thesesystems may become rather large (thousands of equations). Inaddition, realistic plant models often include several distillationcolumns. As a consequence, the numerical solution of these modelsmay become difficult and time-consuming. This has led to attemptsto model the distillation columns less rigorously with the aimof achieving a considerable reduction in the number of equations.The name shortcut distillation columns is common for modelsof this type. The present paper uses a discrete weighted residualmethod for the development of short-cut models. It suggestsa Galerkin method based on orthogonal polynomials in a discretevariable: the tray number. It is a remarkable advantage of thistechnique that even very coarse models satisfy all global balancesexactly.     

A least‐square weighted residual method for level set formulation

In this paper, a least‐square weighted residual method (LSWRM) for level set (LS) formulation is introduced to achieve interface capturing in two‐dimensional (2D) and three‐dimensional (3D) problems. An LSWRM was adopted for two semi‐discretized advection and reinitialization equations of the LS formulation. The present LSWRM provided good mathematical properties such as natural numerical diffusion and the symmetry of the resulting algebraic systems for the advection and reinitialization equations. The proposed method was validated by solving some 2D and 3D benchmark problems such as those involving a rotating slotted disk, the rotation of a slotted sphere, and a time‐reversed single‐vortex flow and a deformation problem of a spherical fluid. The numerical results were compared with those obtained from essentially non‐oscillatory type formulations and particle LS methods. Further, the proposed LSWRM for the LS formulation was coupled with a splitting finite element method code to solve the incompressible Navier–Stokes equations, and then, the collapse of a 3D broken dam flow was well simulated; in the simulation, the entrapping of air and the splashing of the surge front of water were reproduced. The mass conservation of the present method was found to be satisfactory during the entire simulation. Copyright © 2011 John Wiley & Sons, Ltd.     

A total variation based approach to correcting surface coil magnetic resonance images

Magnetic resonance images which are corrupted by noise and by smooth modulations are corrected using a variational formulation incorporating a total variation like penalty for the image and a high order penalty for the modulation. The optimality system is derived and numerically discretized. The cost functional used is non-convex, but it possesses a bilinear structure which allows the ambiguity among solutions to be resolved technically by regularization and practically by normalizing the maximum value of the modulation. Since the cost is convex in each single argument, convex analysis is used to formulate the optimality condition for the image in terms of a primal-dual system. To solve the optimality system, a nonlinear Gauss-Seidel outer iteration is used in which the cost is minimized with respect to one variable after the other using an inner generalized Newton iteration. Favorable computational results are shown for artificial phantoms as well as for realistic magnetic resonance images. Reported computational times demonstrate the feasibility of the approach in practice.     

On expansions of functions of two variables in mixed Fourier-Jacobi series and their application for estimation of errors of cubature formulas

Some problems of expansion of functions of two variables in mixed Fourier-Jacobi series are discussed. In particular, estimates of the convergence rate of these series on classes of functions of two variables characterized by generalized moduli of continuity are given. Applications of these results and estimation of residues of some Chebyshev-type mixed cubature formulas are discussed.     

An acoustoelastic method for measuring residual stresses in slightly orthotropic materials

An acoustoelastic method for residual stress measurement in slightly orthotropic materials by using ultrasonic longitudinal and shear waves is presented. A shear transducer with small vibrator 2 × 2mm² is developed and described, and the measurement of 2-D residual stresses in a seam welded plate was carried out by this method with the shear transducer developed.This project was supported by National Natural Science Fundation of China     

More results on the Ashkin-Teller model

We analyze the low-temperature phase diagram of the Ashkin-Teller model for real values of the quadratic and quartic coupling constants.     

On the use of two QMR algorithms for solving singular systems and applications in Markov chain modeling

Recently, Freund and Nachtigal proposed the quasi-minimal residual algorithm (QMR) for solving general nonsingular non-Hermitian linear systems. The method is based on the Lanczos process, and thus it involves matrix—vector products with both the coefficient matrix of the linear system and its transpose. Freund developed a variant of QMR, the transpose-free QMR algorithm (TFQMR), that only requires products with the coefficient matrix. In this paper, the use of QMR and TFQMR for solving singular systems is explored. First, a convergence result for the general class of Krylov-subspace methods applied to singular systems is presented. Then, it is shown that QMR and TFQMR both converge for consistent singular linear systems with coefficient matrices of index 1. Singular systems of this type arise in Markov chain modeling. For this particular application, numerical experiments are reported.