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Fluid dynamics --- 519.6 --- 519.63 --- 681.3*G18 --- Computational mathematics. Numerical analysis. Computer programming --- Numerical methods for solution of partial differential equations --- Partitial differential equations: domain decomposition methods; elliptic equations; finite difference methods; finite element methods; finite volume methods; hyperbolic equations; inverse problems; iterative solution techniques; methods of lines; multigrid and multilevel methods; parabolic equations; special methods --- 519.63 Numerical methods for solution of partial differential equations --- 519.6 Computational mathematics. Numerical analysis. Computer programming --- Engineering mathematics --- Congresses. --- Calculs numériques
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Fluid dynamics --- 681.3*G18 --- 519.63 --- 519.63 Numerical methods for solution of partial differential equations --- Numerical methods for solution of partial differential equations --- Dynamics --- Fluid mechanics --- Data processing --- Congresses. --- Partitial differential equations: domain decomposition methods; elliptic equations; finite difference methods; finite element methods; finite volume methods; hyperbolic equations; inverse problems; iterative solution techniques; methods of lines; multigrid and multilevel methods; parabolic equations; special methods --- Conferences - Meetings --- Data processing&delete& --- Congresses --- Computational fluid dynamics
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Numerical analysis presents different faces to the world. For mathematicians it is a bona fide mathematical theory with an applicable flavour. For scientists and engineers it is a practical, applied subject, part of the standard repertoire of modelling techniques. For computer scientists it is a theory on the interplay of computer architecture and algorithms for real-number calculations. The tension between these standpoints is the driving force of this book, which presents a rigorous account of the fundamentals of numerical analysis of both ordinary and partial differential equations. The exposition maintains a balance between theoretical, algorithmic and applied aspects. This second edition has been extensively updated, and includes new chapters on emerging subject areas: geometric numerical integration, spectral methods and conjugate gradients. Other topics covered include multistep and Runge-Kutta methods; finite difference and finite elements techniques for the Poisson equation; and a variety of algorithms to solve large, sparse algebraic systems.
517.91 --- 519.62 --- 681.3*G18 --- 519.62 Numerical methods for solution of ordinary differential equations --- Numerical methods for solution of ordinary differential equations --- Numerical solutions&delete& --- Numerical solutions --- Partitial differential equations: domain decomposition methods; elliptic equations; finite difference methods; finite element methods; finite volume methods; hyperbolic equations; inverse problems; iterative solution techniques; methods of lines; multigrid and multilevel methods; parabolic equations; special methods --- Differential equations --- 517.91 Differential equations --- Numerical solutions. --- numerisk analyse --- differensialligninger
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Differential equations, Partial --- Numerical analysis. --- Spectral theory (Mathematics). --- Numerical solutions. --- Numerical analysis --- Spectral theory (Mathematics) --- 517.2 --- 519.63 --- 535.33 --- 681.3*G18 --- 519.63 Numerical methods for solution of partial differential equations --- Numerical methods for solution of partial differential equations --- 535.33 Spectra in general. Emission spectra --- Spectra in general. Emission spectra --- 517.2 Differential calculus. Differentiation --- Differential calculus. Differentiation --- Functional analysis --- Hilbert space --- Measure theory --- Transformations (Mathematics) --- Mathematical analysis --- Numerical solutions --- Partitial differential equations: domain decomposition methods; elliptic equations; finite difference methods; finite element methods; finite volume methods; hyperbolic equations; inverse problems; iterative solution techniques; methods of lines; multigrid and multilevel methods; parabolic equations; special methods
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"This book gives a comprehensive introduction to numerical methods and analysis of stochastic processes, random fields and stochastic differential equations, and offers graduate students and researchers powerful tools for understanding uncertainty quantification for risk analysis. Coverage includes traditional stochastic ODEs with white noise forcing, strong and weak approximation, and the multi-level Monte Carlo method. Later chapters apply the theory of random fields to the numerical solution of elliptic PDEs with correlated random data, discuss the Monte Carlo method, and introduce stochastic Galerkin finite-element methods. Finally, stochastic parabolic PDEs are developed. Assuming little previous exposure to probability and statistics, theory is developed in tandem with state-of the art computational methods through worked examples, exercises, theorems and proofs. The set of MATLAB codes included (and downloadable) allows readers to perform computations themselves and solve the test problems discussed. Practical examples are drawn from finance, mathematical biology, neuroscience, fluid flow modeling and materials science"--
Stochastic partial differential equations. --- 517.95 --- 519.63 --- 681.3*G18 --- Banach spaces, Stochastic differential equations in --- Hilbert spaces, Stochastic differential equations in --- SPDE (Differential equations) --- Stochastic differential equations in Banach spaces --- Stochastic differential equations in Hilbert spaces --- Differential equations, Partial --- Partial differential equations --- Numerical methods for solution of partial differential equations --- Partitial differential equations: domain decomposition methods; elliptic equations; finite difference methods; finite element methods; finite volume methods; hyperbolic equations; inverse problems; iterative solution techniques; methods of lines; multigrid and multilevel methods; parabolic equations; special methods --- Équations aux dérivées partielles stochastiques --- 519.63 Numerical methods for solution of partial differential equations --- 517.95 Partial differential equations --- Équations aux dérivées partielles stochastiques --- Stochastic partial differential equations
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Comprehensive treatment of edge finite element methods Variational theory of Maxwell's equations Error analysis of finite element methods Background material in functional analysis and Sobolev space theory Introduction to inverse problems Since the middle of the last century, computing power has increased sufficiently that the direct numerical approximation of Maxwell's equations is now an increasingly important tool in science and engineering. Parallel to the increasing use of numerical methods in computational electromagnetism there has also been considerable progress in the mathematical understanding of the properties of Maxwell's equations relevant to numerical analysis. The aim of this book is to provide an up to date and sound theoretical foundation for finite element methods in computational electromagnetism. The emphasis is on finite element methods for scattering problems that involve the solution of Maxwell's equations on infinite domains. Suitable variational formulations are developed and justified mathematically. An error analysis of edge finite element methods that are particularly well suited to Maxwell's equations is the main focus of the book. The methods are justified for Lipschitz polyhedral domains that can cause strong singularities in the solution. The book finishes with a short introduction to inverse problems in electromagnetism.
535.13 --- 535.13 Electromagnetic theory (Maxwell) --- Electromagnetic theory (Maxwell) --- finite element method --- computer-aided engineering --- CAE (computer aided engineering) --- Maxwell equations --- Electromagnétisme --- Equations de Maxwell --- Partitial differential equations: domain decomposition methods; elliptic equations; finite difference methods; finite element methods; finite volume methods; hyperbolic equations; inverse problems; iterative solution techniques; methods of lines; multigrid and multilevel methods; parabolic equations; special methods --- Maxwell equations. --- Electromagnétisme --- Electromagnetism --- Finite element method --- Electromagnetics --- Magnetic induction --- Magnetism --- Metamaterials --- Equations, Maxwell --- Differential equations, Partial --- Electromagnetic theory --- FEA (Numerical analysis) --- FEM (Numerical analysis) --- Finite element analysis --- Numerical analysis --- Isogeometric analysis --- Mathematical models --- 519.63 --- 681.3*G18 --- 519.63 Numerical methods for solution of partial differential equations --- Numerical methods for solution of partial differential equations --- Numerical solutions of differential equations --- Functional analysis --- eindige elementen --- Finite element method. --- Mathematical models. --- Méthode des éléments finis --- Modèles mathématiques --- Electromagnetism - Mathematical models --- Equations aux derivees partielles --- Equations de maxwell --- Methodes numeriques --- Elements finis
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532 --- 517.9 --- 517.9 Differential equations. Integral equations. Other functional equations. Finite differences. Calculus of variations. Functional analysis --- Differential equations. Integral equations. Other functional equations. Finite differences. Calculus of variations. Functional analysis --- 532 Fluid mechanics in general. Mechanics of liquids (hydromechanics) --- Fluid mechanics in general. Mechanics of liquids (hydromechanics) --- Partitial differential equations: domain decomposition methods elliptic equations finite difference methods finite element methods finite volume methods hyperbolic equations inverse problems iterative solution techniques methods of lines multigrid and multilevel methods parabolic equations special methods --- Numerical linear algebra: conditioning determinants eigenvalues and eigenvectors error analysis linear systems matrix inversion pseudoinverses singular value decomposition sparse, structured, and very large systems (direct and iterative methods) --- Differential equations, Partial --- Finite element method --- Fluid dynamics --- CFD (Computational fluid dynamics) --- FEA (Numerical analysis) --- FEM (Numerical analysis) --- Finite element analysis --- Numerical analysis --- Isogeometric analysis --- Partial differential equations --- Data processing --- Computer simulation --- 519.6 --- 681.3*G13 --- 681.3*G18 --- 519.6 Computational mathematics. Numerical analysis. Computer programming --- Computational mathematics. Numerical analysis. Computer programming --- Numerical linear algebra: conditioning; determinants; eigenvalues and eigenvectors; error analysis; linear systems; matrix inversion; pseudoinverses; singular value decomposition; sparse, structured, and very large systems (direct and iterative methods) --- Partitial differential equations: domain decomposition methods; elliptic equations; finite difference methods; finite element methods; finite volume methods; hyperbolic equations; inverse problems; iterative solution techniques; methods of lines; multigrid and multilevel methods; parabolic equations; special methods --- Differential equations, Partial. --- Finite element method. --- Data processing. --- Computational fluid dynamics. --- Fluides, Dynamique des --- Equations aux dérivées partielles --- Méthode des éléments finis --- Informatique --- Fluid dynamics - Data processing
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All over the world sport plays a prominent role in society: as a leisure activity for many, as an ingredient of culture, as a business and as a matter of national prestige in such major events as the World Cup in soccer or the Olympic Games. Hence, it is not surprising that science has entered the realm of sports, and, in particular, that computer simulation has become highly relevant in recent years. This is explored in this book by choosing five different sports as examples, demonstrating that computational science and engineering (CSE) can make essential contributions to research on sports topics on both the fundamental level and, eventually, by supporting athletes’ performance.
Mathematics. --- Computational Science and Engineering. --- Computer science. --- Mathématiques --- Informatique --- 519 --- 519.63 --- 681.3*G18 --- Math --- Science --- Numerical methods for solution of partial differential equations --- Partitial differential equations: domain decomposition methods; elliptic equations; finite difference methods; finite element methods; finite volume methods; hyperbolic equations; inverse problems; iterative solution techniques; methods of lines; multigrid and multilevel methods; parabolic equations; special methods --- Computer science --- Mathematics --- Biomechanics. --- Fluid dynamics --Data processing. --- Sports sciences. --- Computational fluid dynamics --- Biomechanics --- Sports sciences --- Engineering & Applied Sciences --- Applied Mathematics --- Mathematics - General --- Physical Sciences & Mathematics --- 519.63 Numerical methods for solution of partial differential equations --- Fluid dynamics --- Data processing. --- Sciences, Sports --- Sport sciences --- Biological mechanics --- Mechanical properties of biological structures --- CFD (Computational fluid dynamics) --- Computer simulation --- Data processing --- Computer mathematics. --- Physics. --- Continuum physics. --- Applied mathematics. --- Engineering mathematics. --- Appl.Mathematics/Computational Methods of Engineering. --- Mathematics of Computing. --- Numerical and Computational Physics. --- Classical Continuum Physics. --- Engineering --- Engineering analysis --- Mathematical analysis --- Classical field theory --- Continuum physics --- Physics --- Continuum mechanics --- Natural philosophy --- Philosophy, Natural --- Physical sciences --- Dynamics --- Computer mathematics --- Discrete mathematics --- Electronic data processing --- Physical education and training --- Biophysics --- Mechanics --- Contractility (Biology) --- Mathematical and Computational Engineering. --- Numerical and Computational Physics, Simulation. --- Classical and Continuum Physics. --- Informatics --- Computer science—Mathematics.
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This book provides a systematic treatment of the mathematical underpinnings of work in data assimilation, covering both theoretical and computational approaches. Specifically the authors develop a unified mathematical framework in which a Bayesian formulation of the problem provides the bedrock for the derivation, development and analysis of algorithms; the many examples used in the text, together with the algorithms which are introduced and discussed, are all illustrated by the MATLAB software detailed in the book and made freely available online. The book is organized into nine chapters: the first contains a brief introduction to the mathematical tools around which the material is organized; the next four are concerned with discrete time dynamical systems and discrete time data; the last four are concerned with continuous time dynamical systems and continuous time data and are organized analogously to the corresponding discrete time chapters. This book is aimed at mathematical researchers interested in a systematic development of this interdisciplinary field, and at researchers from the geosciences, and a variety of other scientific fields, who use tools from data assimilation to combine data with time-dependent models. The numerous examples and illustrations make understanding of the theoretical underpinnings of data assimilation accessible. Furthermore, the examples, exercises and MATLAB software, make the book suitable for students in applied mathema tics, either through a lecture course, or through self-study. .
Calculus --- Mathematics --- Physical Sciences & Mathematics --- Mathematical models. --- Models, Mathematical --- Simulation methods --- 517.95 --- 519.25 --- 519.63 --- 681.3*G18 --- 681.3*G3 --- Partial differential equations --- Statistical data handling --- Numerical methods for solution of partial differential equations --- Partitial differential equations: domain decomposition methods; elliptic equations; finite difference methods; finite element methods; finite volume methods; hyperbolic equations; inverse problems; iterative solution techniques; methods of lines; multigrid and multilevel methods; parabolic equations; special methods --- Probability and statistics: probabilistic algorithms (including Monte Carlo);random number generation; statistical computing; statistical software (Mathematics of computing) --- 519.63 Numerical methods for solution of partial differential equations --- 519.25 Statistical data handling --- 517.95 Partial differential equations --- 681.3*G3 Probability and statistics: probabilistic algorithms (including Monte Carlo);random number generation; statistical computing; statistical software (Mathematics of computing) --- Mathematics. --- Dynamics. --- Ergodic theory. --- Computer mathematics. --- Probabilities. --- Statistics. --- Dynamical Systems and Ergodic Theory. --- Probability Theory and Stochastic Processes. --- Computational Mathematics and Numerical Analysis. --- Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. --- Differentiable dynamical systems. --- Distribution (Probability theory. --- Computer science --- Computer mathematics --- Discrete mathematics --- Electronic data processing --- Distribution functions --- Frequency distribution --- Characteristic functions --- Probabilities --- Differential dynamical systems --- Dynamical systems, Differentiable --- Dynamics, Differentiable --- Differential equations --- Global analysis (Mathematics) --- Topological dynamics --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Econometrics --- Statistics . --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Mathematical statistics --- Risk --- Ergodic transformations --- Continuous groups --- Mathematical physics --- Measure theory --- Transformations (Mathematics) --- Dynamical systems --- Kinetics --- Mechanics, Analytic --- Force and energy --- Mechanics --- Physics --- Statics --- Mathematical models
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This volume addresses some of the research areas in the general field of stability studies for differential equations, with emphasis on issues of concern for numerical studies. Topics considered include: (i) the long time integration of Hamiltonian Ordinary DEs and highly oscillatory systems, (ii) connection between stochastic DEs and geometric integration using the Markov chain Monte Carlo method, (iii) computation of dynamic patterns in evolutionary partial DEs, (iv) decomposition of matrices depending on parameters and localization of singularities, and (v) uniform stability analysis for time dependent linear initial value problems of ODEs. The problems considered in this volume are of interest to people working on numerical as well as qualitative aspects of differential equations, and it will serve both as a reference and as an entry point into further research.
Mathematics. --- Matrix theory. --- Differential Equations. --- Differential equations, partial. --- Computer science --- Algorithms. --- Computational Mathematics and Numerical Analysis. --- Applications of Mathematics. --- Ordinary Differential Equations. --- Partial Differential Equations. --- Linear and Multilinear Algebras, Matrix Theory. --- Mathematics --- Physical Sciences & Mathematics --- Mathematics - General --- Differential equations. --- Markov processes. --- Decomposition (Mathematics) --- 681.3*G17 --- 681.3*G18 --- 519.62 --- 519.63 --- Hamiltonian systems. --- Hamiltonian dynamical systems --- Systems, Hamiltonian --- Differentiable dynamical systems --- Probabilities --- Analysis, Markov --- Chains, Markov --- Markoff processes --- Markov analysis --- Markov chains --- Markov models --- Models, Markov --- Processes, Markov --- Stochastic processes --- Equations, Differential --- Bessel functions --- Calculus --- Ordinary differential equations: boundary value problems; convergence and stability; error analysis; initial value problems; multistep methods; single step methods; stiff equations (Numerical analysis) --- Partitial differential equations: domain decomposition methods; elliptic equations; finite difference methods; finite element methods; finite volume methods; hyperbolic equations; inverse problems; iterative solution techniques; methods of lines; multigrid and multilevel methods; parabolic equations; special methods --- Numerical methods for solution of ordinary differential equations --- Numerical methods for solution of partial differential equations --- 519.63 Numerical methods for solution of partial differential equations --- 519.62 Numerical methods for solution of ordinary differential equations --- 681.3*G17 Ordinary differential equations: boundary value problems; convergence and stability; error analysis; initial value problems; multistep methods; single step methods; stiff equations (Numerical analysis) --- 517.91 Differential equations --- Differential equations --- Algorism --- Computer mathematics --- Discrete mathematics --- Electronic data processing --- Partial differential equations --- Math --- Algebra. --- Partial differential equations. --- Applied mathematics. --- Engineering mathematics. --- Computer mathematics. --- Asymptotic theory. --- 517.91 --- Numerical solutions --- Algebra --- Arithmetic --- Science --- Foundations --- Mathematical analysis --- Engineering --- Engineering analysis --- Markov processes --- Hamiltonian systems
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