Numerical Methods for partial differential equations
Here you can find a list of numerical methods.
Supported
Section titled “Supported”Subdiving a large system into smaller parts called finite elements.
Then over each element, a trial polynomial function is fitted into the PDE, with a residual representing the error.
This process results in :
- a set of algebraic equations for steady-state problems
- a set of ordinary differential equations for transient problems
User Input
Section titled “User Input”- variational problem
- solution space (basis of the finite space)
Advantages
Section titled “Advantages”- sparse matrix
Inputs
Section titled “Inputs”- Spacial Discretization
- Basis function
- Variational Equation
- Function Space
Outputs
Section titled “Outputs”- Function
Dependencies
Section titled “Dependencies”- Sparse Symetric Matrix System Resolution
- Integration
For steady-state problems
- linear solver For transient problems
- ordinary differential equation solver (Euler, Runge-Kutta)
- Spacial Discretization