FDTD 101: Time step size and CFL condition in FDTD
Lecture 7: Time step size and CFL condition in FDTD
The choice of time step size can have a strong impact on the behavior of FDTD algorithms. In this lecture, we provide a simple and intuitive argument on deriving an important condition on choosing time step size, known as the Courant–Friedrichs–Lewy (CFL) condition.
- Graphically illustrate how information propagates over 1D and 2D Yee grids, which aids an easy derivation of the speed of numerical dependency and the CFL condition.
- Introduce Courant number, and explain that CFL condition imposes an upper bound of time step size decided by the smallest grid size in the computational domain.
- Show that computational cost increases rapidly with spatial resolution under two considerations: spatially more grid points, and temporally finer time step size required by CFL condition.
