EconPapers    
Economics at your fingertips  
 

Numerical Approximation of Model Partial Differential Equations

Ionut Danaila (), Pascal Joly (), Sidi Mahmoud Kaber () and Marie Postel ()
Additional contact information
Ionut Danaila: Laboratoire de Mathématiques Raphaël Salem
Pascal Joly: Laboratoire Jacques-Louis Lions
Sidi Mahmoud Kaber: Laboratoire Jacques-Louis Lions
Marie Postel: Laboratoire Jacques-Louis Lions

Chapter Chapter 1 in An Introduction to Scientific Computing, 2023, pp 1-34 from Springer

Abstract: Abstract A partial differential equation (PDE) is a relation between a function of several variables and its partial derivatives. In this chapter, we first consider the simplest case of ordinary differential equations (ODE), with a solution depending on a single independent variable (time variable here). We present discrete methods for the numerical integration of ODEs. These methods (or numerical schemes) are then used to study three PDEs, depending both on time and space variables, modeling convection, wave and heat propagation.

Date: 2023
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-35032-0_1

Ordering information: This item can be ordered from
http://www.springer.com/9783031350320

DOI: 10.1007/978-3-031-35032-0_1

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2026-07-11
Handle: RePEc:spr:sprchp:978-3-031-35032-0_1