Solving PDEs in Python
by Hans Petter Langtangen, Anders Logg
Publisher: Springer 2017
Number of pages: 148
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.
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by Daniele Venturi - arXiv
The purpose of this manuscript is to provide a new perspective on the problem of numerical approximation of nonlinear functionals and functional differential equations. The proposed methods will be described and demonstrated in various examples.
by M.N. Spijker - Leiden University
Stability estimates and resolvent conditions in the numerical solution of initial value problems. Contents: Partial differential equations and numerical methods; Linear algebra; Stability in the numerical solution of differential equations; etc.
by 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.
by Adrian Sandu - Virginia Tech
Contents: a quick tour of fortran 95; the building blocks of a fortran application; flow control; computer arithmetic; applications; intrinsic functions; input and output; arrays; more on procedures; parametrized intrinsic types; derived types; etc.