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Numerical methods for partial differential equations : finite difference and finite volume methods / Sandip Mazumder.

By: Material type: TextTextPublication details: London : Academic Press / Elsevier, 2016.Description: xix, 461 p. : ill. ; 24 cmISBN:
  • 0128498943
Subject(s): DDC classification:
  • 22 515.353 MAZ
Online resources:
Contents:
Introduction to Numerical Methods for Solving Differential Equations -- The Finite Difference Method (FDM) -- Solution to System of Linear Algebraic Equations -- Stability and Convergence of Iterative Solvers -- Treatment of Time Derivative (Parabolic and Hyperbolic PDEs) -- The Finite Volume Method (FVM) -- Unstructured Finite Volume Method -- Miscellaneous Topics -- Appendix A: Useful Relationships in Matrix Algebra -- Appendix B: Useful Relationships in Vector Calculus -- Appendix C: Tensor Notations and Useful Relationships
Summary: Numerical Methods for Partial Differential Equations: Finite Difference and Finite Volume Methods focuses on two popular deterministic methods for solving partial differential equations (PDEs), namely finite difference and finite volume methods. The solution of PDEs can be very challenging, depending on the type of equation, the number of independent variables, the boundary, and initial conditions, and other factors. These two methods have been traditionally used to solve problems involving fluid flow. For practical reasons, the finite element method, used more often for solving problems in solid mechanics, and covered extensively in various other texts, has been excluded. The book is intended for beginning graduate students and early career professionals, although advanced undergraduate students may find it equally useful. The material is meant to serve as a prerequisite for students who might go on to take additional courses in computational mechanics, computational fluid dynamics, or computational electromagnetics. The notations, language, and technical jargon used in the book can be easily understood by scientists and engineers who may not have had graduate-level applied mathematics or computer science courses.
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Holdings
Item type Current library Collection Call number Vol info Status Date due Barcode Item holds
Book - Borrowing Book - Borrowing Central Library First floor Baccah 515.353 MAZ (Browse shelf(Opens below)) 25845 Checked out 10/06/2023 000034482
Total holds: 0

Index : p. 455-461.

Includes bibliographical references.

Introduction to Numerical Methods for Solving Differential Equations -- The Finite Difference Method (FDM) -- Solution to System of Linear Algebraic Equations -- Stability and Convergence of Iterative Solvers -- Treatment of Time Derivative (Parabolic and Hyperbolic PDEs) -- The Finite Volume Method (FVM) -- Unstructured Finite Volume Method -- Miscellaneous Topics -- Appendix A: Useful Relationships in Matrix Algebra -- Appendix B: Useful Relationships in Vector Calculus -- Appendix C: Tensor Notations and Useful Relationships

Numerical Methods for Partial Differential Equations: Finite Difference and Finite Volume Methods focuses on two popular deterministic methods for solving partial differential equations (PDEs), namely finite difference and finite volume methods. The solution of PDEs can be very challenging, depending on the type of equation, the number of independent variables, the boundary, and initial conditions, and other factors. These two methods have been traditionally used to solve problems involving fluid flow. For practical reasons, the finite element method, used more often for solving problems in solid mechanics, and covered extensively in various other texts, has been excluded. The book is intended for beginning graduate students and early career professionals, although advanced undergraduate students may find it equally useful. The material is meant to serve as a prerequisite for students who might go on to take additional courses in computational mechanics, computational fluid dynamics, or computational electromagnetics. The notations, language, and technical jargon used in the book can be easily understood by scientists and engineers who may not have had graduate-level applied mathematics or computer science courses.

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