Numerical Partial Differential Equations (Paperback)

Scott MacLachlan

ISBN 10: 1611978270 / ISBN 13: 9781611978278

Published by Society for Industrial & Applied Mathematics,U.S., New York, 2025

About this Item

Paperback. This comprehensive book focuses on numerical methods for approximating solutions to partial differential equations. Intended as a broad survey of methods, the aim is to introduce readers to the central concepts of various families of discretizations and solution algorithm and lay the foundation needed to understand more advanced material, The book is divided into four parts: Part I covers basic background on PDEs and numerical methods,Part II introduces the three main classes of numerical methods for PDEs that are the books focus (finite-difference, finite-element, and finite-volume methods),Part III discusses linear solvers and finite-element and finite-volume methods at a more advanced level, andPart IV presents further high-level topics on discretizations and solvers.The authors include over one hundred well-established definitions, theorems, corollaries, and lemmas, and summaries of and reference to in-depth treatments of more advanced mathematics when needed.Audience This book is intended for advanced undergraduate/first-year graduate and advanced graduate students in applied math, as well as students in science and engineering disciplines. It is also appropriate for researchers in the field of scientific computing.Chapters are designed to be stand-alone, allowing distinct paths through the text, making it appropriate for both single-semester and multisemester courses. It is appropriate for courses on numerical methods for PDEs and numerical linear algebra. Numerical methods for approximating PDE solutions are presented in a rich exploration of discretization techniques such as finite-difference, finite-element, and finite-volume methods. Topics span foundational background, algorithmic strategies, linear solvers, and high-level approaches for advanced students and researchers. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Seller Inventory # 9781611978278

Bibliographic Details

• Title: Numerical Partial Differential Equations (Paperback)
• Publisher: Society for Industrial & Applied Mathematics,U.S., New York
• Publication Date: 2025
• Language: English
• ISBN 10: 1611978270
• ISBN 13: 9781611978278
• Binding: Paperback
• Condition: new

About this title

Synopsis

This comprehensive book focuses on numerical methods for approximating solutions to partial differential equations. Intended as a broad survey of methods, the aim is to introduce readers to the central concepts of various families of discretizations and solution algorithm and lay the foundation needed to understand more advanced material, The book is divided into four parts:

• Part I covers basic background on PDEs and numerical methods,
• Part II introduces the three main classes of numerical methods for PDEs that are the book's focus (finite-difference, finite-element, and finite-volume methods),
• Part III discusses linear solvers and finite-element and finite-volume methods at a more advanced level, and
• Part IV presents further high-level topics on discretizations and solvers.

The authors include over one hundred well-established definitions, theorems, corollaries, and lemmas, and summaries of and reference to in-depth treatments of more advanced mathematics when needed.

Audience

This book is intended for advanced undergraduate/first-year graduate and advanced graduate students in applied math, as well as students in science and engineering disciplines. It is also appropriate for researchers in the field of scientific computing.

Chapters are designed to be stand-alone, allowing distinct paths through the text, making it appropriate for both single-semester and multisemester courses. It is appropriate for courses on numerical methods for PDEs and numerical linear algebra.

About the Author

James Adler is a Professor in the Department of Mathematics at Tufts University.

Hans De Sterck is a Professor in the Department of Applied Mathematics at the University of Waterloo.

Scott MacLachlan is a Professor in the Department of Mathematics and Statistics at Memorial University of Newfoundland and Labrador.

Luke Olson is a Professor of Computer Science at the University of Illinois Urbana-Champaign.