SUMMARY
Finite Difference Method (FDM) and Finite Element Method (FEM) are both numerical techniques for solving Partial Differential Equations (PDEs). While FDM is suitable for rectangular domains and can handle various types of PDEs, it lacks the versatility of FEM, which is better suited for irregular integration domains. Specific implementations of FDM and FEM are limited to certain types of equations, and there is no universal FDM scheme applicable to all PDEs. Resources such as Langtangen's online works provide valuable guidance for implementing these methods in Python.
PREREQUISITES
- Understanding of Partial Differential Equations (PDEs)
- Familiarity with Finite Difference Method (FDM)
- Knowledge of Finite Element Method (FEM)
- Basic programming skills in Python
NEXT STEPS
- Study the implementation of FDM for solving elliptic, parabolic, and hyperbolic PDEs.
- Explore Langtangen's resources on numerical methods for PDEs.
- Learn about coordinate transformations for mapping grids in FDM.
- Investigate the advantages of using FEM for complex geometries compared to FDM.
USEFUL FOR
Researchers, engineers, and students in computational mathematics, particularly those focusing on numerical methods for solving Partial Differential Equations.