Showing papers on "Partial differential equation published in 1996"

A fast marching level set method for monotonically advancing fronts

Abstract: A fast marching level set method is presented for monotonically advancing fronts, which leads to an extremely fast scheme for solving the Eikonal equation. Level set methods are numerical techniques for computing the position of propagating fronts. They rely on an initial value partial differential equation for a propagating level set function and use techniques borrowed from hyperbolic conservation laws. Topological changes, corner and cusp development, and accurate determination of geometric properties such as curvature and normal direction are naturally obtained in this setting. This paper describes a particular case of such methods for interfaces whose speed depends only on local position. The technique works by coupling work on entropy conditions for interface motion, the theory of viscosity solutions for Hamilton-Jacobi equations, and fast adaptive narrow band level set methods. The technique is applicable to a variety of problems, including shape-from-shading problems, lithographic development calculations in microchip manufacturing, and arrival time problems in control theory.

Monotone operators in Banach space and nonlinear partial differential equations

Abstract: PDE examples by type Linear problems...An introduction Nonlinear stationary problems Nonlinear evolution problems Accretive operators and nonlinear Cauchy problems Appendix Bibliography Index.

A convergent adaptive algorithm for Poisson's equation

Abstract: We construct a converging adaptive algorithm for linear elements applied to Poisson’s equation in two space dimensions. Starting from a macro triangulation, we describe how to construct an initial triangulation from a priori information. Then we use a posteriors error estimators to get a sequence of refined triangulation and approximate solutions. It is proved that the error, measured in the energy norm, decreases at a constant rate in each step until a prescribed error bound is reached. Extension to higher-order elements in two space dimension and numerical results are included.

Ergodicity for infinite dimensional systems

Abstract: This book is devoted to the asymptotic properties of solutions of stochastic evolution equations in infinite dimensional spaces. It is divided into three parts: Markovian dynamical systems; invariant measures for stochastic evolution equations; invariant measures for specific models. The focus is on models of dynamical processes affected by white noise, which are described by partial differential equations such as the reaction-diffusion equations or Navier–Stokes equations. Besides existence and uniqueness questions, special attention is paid to the asymptotic behaviour of the solutions, to invariant measures and ergodicity. Some of the results found here are presented for the first time. For all whose research interests involve stochastic modelling, dynamical systems, or ergodic theory, this book will be an essential purchase.

Multiple Scale and Singular Perturbation Methods

Abstract: 1. Introduction.- 1.1. Order Symbols, Uniformity.- 1.2. Asymptotic Expansion of a Given Function.- 1.3. Regular Expansions for Ordinary and Partial Differential Equations.- References.- 2. Limit Process Expansions for Ordinary Differential Equations.- 2.1. The Linear Oscillator.- 2.2. Linear Singular Perturbation Problems with Variable Coefficients.- 2.3. Model Nonlinear Example for Singular Perturbations.- 2.4. Singular Boundary Problems.- 2.5. Higher-Order Example: Beam String.- References.- 3. Limit Process Expansions for Partial Differential Equations.- 3.1. Limit Process Expansions for Second-Order Partial Differential Equations.- 3.2. Boundary-Layer Theory in Viscous, Incompressible Flow.- 3.3. Singular Boundary Problems.- References.- 4. The Method of Multiple Scales for Ordinary Differential Equations.- 4.1. Method of Strained Coordinates for Periodic Solutions.- 4.2. Two Scale Expansions for the Weakly Nonlinear Autonomous Oscillator.- 4.3. Multiple-Scale Expansions for General Weakly Nonlinear Oscillators.- 4.4. Two-Scale Expansions for Strictly Nonlinear Oscillators.- 4.5. Multiple-Scale Expansions for Systems of First-Order Equations in Standard Form.- References.- 5. Near-Identity Averaging Transformations: Transient and Sustained Resonance.- 5.1. General Systems in Standard Form: Nonresonant Solutions.- 5.2. Hamiltonian System in Standard Form Nonresonant Solutions.- 5.3. Order Reduction and Global Adiabatic Invariants for Solutions in Resonance.- 5.4. Prescribed Frequency Variations, Transient Resonance.- 5.5. Frequencies that Depend on the Actions, Transient or Sustained Resonance.- References.- 6. Multiple-Scale Expansions for Partial Differential Equations.- 6.1. Nearly Periodic Waves.- 6.2. Weakly Nonlinear Conservation Laws.- 6.3. Multiple-Scale Homogenization.- References.

Partial Differential Equations I: Basic Theory

Abstract: Basic Theory of ODE and Vector Fields.- 1 The derivative.- 2 Fundamental local existence theorem for ODE.- 3 Inverse function and implicit function theorems.- 4 Constant-coefficient linear systems exponentiation of matrices.- 5 Variable-coefficient linear systems of ODE: Duhamel's principle.- 6 Dependence of solutions on initial data and on other parameters.- 7 Flows and vector fields.- 8 Lie brackets.- 9 Commuting flows Frobenius's theorem.- 10 Hamiltonian systems.- 11 Geodesies.- 12 Variational problems and the stationary action principle.- 13 Differential forms.- 14 The symplectic form and canonical transformations.- 15 First-order, scalar, nonlinear PDE.- 16 Completely integrable Hamiltonian systems.- 17 Examples of integrable systems central force problems.- 18 Relativistic motion.- 19 Topological applications of differential forms.- 20 Critical points and index of a vector field.- A Nonsmooth vector fields.- References.- 2 The Laplace Equation and Wave Equation.- 1 Vibrating strings and membranes.- 2 The divergence of a vector field.- 3 The covariant derivative and divergence of tensor fields.- 4 The Laplace operator on a Riemannian manifold.- 5 The wave equation on a product manifold and energy conservation.- 6 Uniqueness and finite propagation speed.- 7 Lorentz manifolds and stress-energy tensors.- 8 More general hyperbolic equations energy estimates.- 9 The symbol of a differential operator and a general Green-Stokes formula.- 10 The Hodge Laplacian on k-forms.- 11 Maxwell's equations.- References.- 3 Fourier Analysis, Distributions, and Constant-Coefficient Linear PDE.- 1 Fourier series.- 2 Harmonic functions and holomorphic functions in the plane.- 3 The Fourier transform.- 4 Distributions and tempered distributions.- 5 The classical evolution equations.- 6 Radial distributions, polar coordinates, and Bessel functions.- 7 The method of images and Poisson's summation formula.- 8 Homogeneous distributions and principal value distributions.- 9 Elliptic operators.- 10 Local solvability of constant-coefficient PDE.- 11 The discrete Fourier transform.- 12 The fast Fourier transform.- The mighty Gaussian and the sublime gamma function.- References.- 4 Sobolev Spaces.- 1 Sobolev spaces on ?n.- 2 The complex interpolation method.- 3 Sobolev spaces on compact manifolds.- 4 Sobolev spaces on bounded domains.- 5 The Sobolev spaces Hs0(?).- 6 The Schwartz kernel theorem.- References.- 5 Linear Elliptic Equations.- 1 Existence and regularity of solutions to the Dirichlet problem.- 2 The weak and strong maximum principles.- 3 The Dirichlet problem on the ball in ?n.- 4 The Riemann mapping theorem (smooth boundary).- 5 The Dirichlet problem on a domain with a rough boundary.- 6 The Riemann mapping theorem (rough boundary).- 7 The Neumann boundary problem.- 8 The Hodge decomposition and harmonic forms.- 9 Natural boundary problems for the Hodge Laplacian.- 10 Isothermal coordinates and conformal structures on surfaces.- 11 General elliptic boundary problems.- 12 Operator properties of regular boundary problems.- Spaces of generalized functions on manifolds with boundary.- The Mayer-Vietoris sequence in deRham cohomology.- References.- 6 Linear Evolution Equations.- 1 The heat equation and the wave equation on bounded domains.- 2 The heat equation and wave equation on unbounded domains.- 3 Maxwell's equations.- 4 The Cauchy-Kowalewsky theorem.- 5 Hyperbolic systems.- 6 Geometrical optics.- 7 The formation of caustics.- Some Banach spaces of harmonic functions.- The stationary phase method.- References.- A Outline of Functional Analysis.- 1 Banach spaces.- 2 Hilbert spaces.- 3 Frechet spaces locally convex spaces.- 4 Duality.- 5 Linear operators.- 6 Compact operators.- 7 Fredholm operators.- 8 Unbounded operators.- 9 Semigroups.- References.- B Manifolds, Vector Bundles, and Lie Groups.- 1 Metric spaces and topological spaces.- 2 Manifolds.- 3 Vector bundles.- 4 Sard's theorem.- 5 Lie groups.- 6 The Campbell-Hausdorff formula.- 7 Representations of Lie groups and Lie algebras.- 8 Representations of compact Lie groups.- 9 Representations of SU(2) and related groups.- References.

A finite point method in computational mechanics. applications to convective transport and fluid flow

Abstract: The paper presents a fully meshless procedure fo solving partial differential equations. The approach termed generically the ‘finite point method’ is based on a weighted least square interpolation of point data and point collocation for evaluating the approximation integrals. Some examples showing the accuracy of the method for solution of adjoint and non-self adjoint equations typical of convective-diffusive transport and also to the analysis of compressible fluid mechanics problem are presented.

Weak and Measure-Valued Solutions to Evolutionary PDEs

Abstract: This book provides a concise treatment of the theory of nonlinear evolutionary partial differential equations. It provides a rigorous analysis of non-Newtonian fluids, and outlines its results for applications in physics, biology, and mechanical engineering

Scientific Computing

Abstract: Heath 2/e, presents a broad overview of numerical methods for solving all the major problems in scientific computing, including linear and nonlinear equations, least squares, eigenvalues, optimization, interpolation, integration, ordinary and partial differential equations, fast Fourier transforms, and random number generators. The treatment is comprehensive yet concise, software-oriented yet compatible with a variety of software packages and programming languages. The book features more than 160 examples, 500 review questions, 240 exercises, and 200 computer problems. Changes for the second edition include: expanded motivational discussions and examples; formal statements of all major algorithms; expanded discussions of existence, uniqueness, and conditioning for each type of problem so that students can recognize "good" and "bad" problem formulations and understand the corresponding quality of results produced; and expanded coverage of several topics, particularly eigenvalues and constrained optimization. The book contains a wealth of material and can be used in a variety of one- or two-term courses in computer science, mathematics, or engineering. Its comprehensiveness and modern perspective, as well as the software pointers provided, also make it a highly useful reference for practicing professionals who need to solve computational problems. Table of contents 1 Scientific Computing 2 Systems of Linear Equations 3 Linear Least Squares 4 Eigenvalues Problems 5 Nonlinear Equations 6 Optimization 7 Interpolation 8 Numerical Integration and Differentiation 9 Initial Value Problems for ODEs 10 Boundary Value Problems for ODEs 11 Partial Differential Equations 12 Fast Fourier Transform 13 Random Numbers and Simulation

Two-grid Discretization Techniques for Linear and Nonlinear PDEs

Abstract: A number of finite element discretization techniques based on two (or more) subspaces for nonlinear elliptic partial differential equations (PDEs) is presented. Convergence estimates are derived to justify the efficiency of these algorithms. With the new proposed techniques, solving a large class of nonlinear elliptic boundary value problems will not be much more difficult than the solution of one linearized equation. Similar techniques are also used to solve nonsymmetric and/or indefinite linear systems by solving symmetric positive definite (SPD) systems. For the analysis of these two-grid or multigrid methods, optimal ${\cal L}^p$ error estimates are also obtained for the classic finite element discretizations.

Fast Fluid Registration of Medical Images

Abstract: This paper offers a new fast algorithm for non-rigid Viscous Fluid Registration of medical images that is at least an order of magnitude faster than the previous method by Christensen et al. [4]. The core algorithm in the fluid registration method is based on a linear elastic deformation of the velocity field of the fluid. Using the linearity of this deformation we derive a convolution filter which we use in a scalespace framework. We also demonstrate that the ’demon’-based registration method of Thirion [13] can be seen as an approximation to the fluid registration method and point to possible problems.

Fitted Numerical Methods for Singular Perturbation Problems: Error Estimates in the Maximum Norm for Linear Problems in One and Two Dimensions

Abstract: Since the first edition of this book, the literature on fitted mesh methods for singularly perturbed problems has expanded significantly. Over the intervening years, fitted meshes have been shown to be effective for an extensive set of singularly perturbed partial differential equations. In the revised version of this book, the reader will find an introduction to the basic theory associated with fitted numerical methods for singularly perturbed differential equations. Fitted mesh methods focus on the appropriate distribution of the mesh points for singularly perturbed problems. The global errors in the numerical approximations are measured in the pointwise maximum norm. The fitted mesh algorithm is particularly simple to implement in practice, but the theory of why these numerical methods work is far from simple. This book can be used as an introductory text to the theory underpinning fitted mesh methods.

Numerical recipes in Fortran 77 : the art of scientific computing : volume 1 of fortran numerical recipes

Abstract: Legal matters List of computer programs 1. Preliminaries 2. Solution of linear algebraic equations 3. Interpolation and extrapolation 4. Integration of functions 5. Evaluation of functions 6. Special functions 7. Random numbers 8. Sorting 9. Root finding and nonlinear sets of equations 10. Minimization or maximization of functions 11. Eigensystems 12. Fast Fourier transform 13. Fourier and spectral applications 14. Statistical description of data 15. Modeling of data 16. Integration of ordinary differential equations 17. Two point boundary value problems 18. Integral equations and inverse theory 19. Partial differential equations 20. Less-numerical algorithms References Index of programs and dependencies General index.

Particle hopping models and traffic flow theory

Abstract: This paper shows how particle hopping models fit into the context of traffic flow theory, that is, it shows connections between fluid-dynamical traffic flow models, which derive from the Navier-Stokes equations, and particle hopping models. In some cases, these connections are exact and have long been established, but have never been viewed in the context of traffic theory. In other cases, critical behavior of traffic jam clusters can be compared to instabilities in the partial differential equations. Finally, it is shown how all this leads to a consistent picture of traffic jam dynamics. In consequence, this paper starts building a foundation of a comprehensive dynamic traffic theory, where strengths and weaknesses of different models (fluid-dynamical, car-following, particle hopping) can be compared, and thus allowing to systematically chose the appropriate model for a given question.

Stochastic Calculus: A Practical Introduction

Abstract: CHAPTER 1. BROWNIAN MOTION Definition and Construction Markov Property, Blumenthal's 0-1 Law Stopping Times, Strong Markov Property First Formulas CHAPTER 2. STOCHASTIC INTEGRATION Integrands: Predictable Processes Integrators: Continuous Local Martingales Variance and Covariance Processes Integration w.r.t. Bounded Martingales The Kunita-Watanabe Inequality Integration w.r.t. Local Martingales Change of Variables, Ito's Formula Integration w.r.t. Semimartingales Associative Law Functions of Several Semimartingales Chapter Summary Meyer-Tanaka Formula, Local Time Girsanov's Formula CHAPTER 3. BROWNIAN MOTION, II Recurrence and Transience Occupation Times Exit Times Change of Time, Levy's Theorem Burkholder Davis Gundy Inequalities Martingales Adapted to Brownian Filtrations CHAPTER 4. PARTIAL DIFFERENTIAL EQUATIONS A. Parabolic Equations The Heat Equation The Inhomogeneous Equation The Feynman-Kac Formula B. Elliptic Equations The Dirichlet Problem Poisson's Equation The Schroedinger Equation C. Applications to Brownian Motion Exit Distributions for the Ball Occupation Times for the Ball Laplace Transforms, Arcsine Law CHAPTER 5. STOCHASTIC DIFFERENTIAL EQUATIONS Examples Ito's Approach Extension Weak Solutions Change of Measure Change of Time CHAPTER 6. ONE DIMENSIONAL DIFFUSIONS Construction Feller's Test Recurrence and Transience Green's Functions Boundary Behavior Applications to Higher Dimensions CHAPTER 7. DIFFUSIONS AS MARKOV PROCESSES Semigroups and Generators Examples Transition Probabilities Harris Chains Convergence Theorems CHAPTER 8. WEAK CONVERGENCE In Metric Spaces Prokhorov's Theorems The Space C Skorohod's Existence Theorem for SDE Donsker's Theorem The Space D Convergence to Diffusions Examples Solutions to Exercises References Index

Renormalization group and singular perturbations: Multiple scales, boundary layers, and reductive perturbation theory

Abstract: Perturbative renormalization group theory is developed as a unified tool for global asymptotic analysis. With numerous examples, we illustrate its application to ordinary differential equation problems involving multiple scales, boundary layers with technically difficult asymptotic matching, and WKB analysis. In contrast to conventional methods, the renormalization group approach requires neither ad hoc assumptions about the structure of perturbation series nor the use of asymptotic matching. Our renormalization group approach provides approximate solutions which are practically superior to those obtained conventionally, although the latter can be reproduced, if desired, by appropriate expansion of the renormalization group approximant. We show that the renormalization group equation may be interpreted as an amplitude equation, and from this point of view develop reductive perturbation theory for partial differential equations describing spatially extended systems near bifurcation points, deriving both amplitude equations and the center manifold. @S1063651X~96!00506-5#

Improved multiquadric approximation for partial differential equations

Abstract: Based on the idea of the DRM, a numerical method has been devised to interpolate the forcing term of partial differential equations by using multiquadric approximations, a special class of radial basis functions, and then use them to approximate particular solutions. To obtain a good shape parameter of the multiquadrics, we use the technique of cross validation. After we find a particular solution, we then use the method of fundamental solutions to solve the homogeneous PDEs. To demonstrate the effectiveness of our method, four numerical results, including a 3D case, are given.

Integral Representations for Spatial Models of Mathematical Physics

Abstract: Introduction and some remarks on generalisations of complex analysis a-holomorphic function theory Electrodynamical models Massive spinor fields Hypercomplex factorization, systems of non-linear partial differential equations generated by Futer-type operators.

Multiscale convergence and reiterated homogenisation

Abstract: This paper generalises the notion of two-scale convergence to the case of multiple separated scales of periodic oscillations. It allows us to introduce a multi-scale convergence method for the reiterated homogenisation of partial differential equations with oscillating coefficients. This new method is applied to a model problem with a finite or infinite number of microscopic scales, namely the homogenisation of the heat equation in a composite material. Finally, it is generalised to handle the homogenisation of the Neumann problem in a perforated domain.

Global attractors for the three-dimensional Navier-Stokes equations

Abstract: In this paper we show that the weak solutions of the Navier-Stokes equations on any bounded, smooth three-dimensional domain have a global attractor for any positive value of the viscosity. The proof of this result, which bypasses the two issues of the possible nonuniqueness of the weak solutions and the possible lack of global regularity of the strong solutions, is based on a new point of view for the construction of the semiflow generated by these equations. We also show that, under added assumptions, this global attractor consists entirely of strong solutions.

Notes on the eigensystem of magnetohydrodynamics

Abstract: The eigenstructure of the equations governing one-dimensional ideal magnetohy-drodynamics is examined, motivated by the wish to exploit it for construction of high-resolution computational algorithms. The results are given in simple forms that avoid indeterminacy or degeneracy whenever possible. The unavoidable indeterminacy near the magnetosonic (or triple umbilic) state is analysed and shown to cause no difficulty in evaluating a numerical flux function. The structure of wave paths close to this singularity is obtained, and simple expressions are presented for the structure coefficients that govern wave steepening.