Solving PDEs in Python
by Hans Petter Langtangen, Anders Logg
Publisher: Springer 2017
Number of pages: 148
Description:
This book offers a concise and gentle introduction to finite element programming in Python based on the popular FEniCS software library. Using a series of examples, including the Poisson equation, the equations of linear elasticity, the incompressible Navier-Stokes equations, and systems of nonlinear advection-diffusion-reaction equations, it guides readers through the essential steps to quickly solving a PDE in FEniCS, such as how to define a finite variational problem, how to set boundary conditions, how to solve linear and nonlinear systems, and how to visualize solutions and structure finite element Python programs.
Download or read it online for free here:
Download link
(multiple PDF files)
Similar books
Mathematical Computationby Ian Craw - University of Aberdeen
The overall aim of the course is to present modern computer programming techniques in the context of mathematical computation and numerical analysis and to foster the independence needed to use these techniques as appropriate in subsequent work.
(14717 views)
Numerical Methods with Applicationsby Autar K Kaw, Egwu Eric Kalu - Lulu.com
The textbook is written for engineering undergraduates taking a course in numerical methods. It offers a treatise to numerical methods based on a holistic approach and short chapters. The authors included examples of real-life applications.
(20562 views)
The Calculus Of Finite Differencesby L. M. Milne Thomson - Macmillan and co
The object of this book is to provide a simple account of the subject of Finite Differences and to present the theory in a form which can be readily applied -- not only the useful material of Boole, but also the more modern developments.
(15196 views)
Programming for Computations - Pythonby Svein Linge, Hans Petter Langtangen - Springer
This book presents Python programming as a key method for solving mathematical problems. The style is accessible and concise, the emphasis is on generic algorithms, clean design of programs, use of functions, and automatic tests for verification.
(9544 views)