As usually the trend is a Courant number (CFL no) can only be used for a Transient( Unsteady) flow condition.
Thank you in Advance.
The short answer is Fluent uses the CFL number to compute the time step (even for steady flows). A more detailed explanation follows...
The coupled set of governing equations is discretized in time for both steady and unsteady (transient) calculations. In the steady case, it is assumed that time marching proceeds until a steady-state solution is reached. Temporal discretization of the coupled equations is accomplished by either an implicit or an explicit time-marching algorithm. In the Explicit Formulation the time step is computed from the Courant-Friedrichs-Lewy (CFL) condition. The time step is a function of: the cell volume, the cell face area, and the maximum of local eigenvalues.
Here is some additional information straight from the theory guide (Fluent Version 6) in the section: Steady-State Flow Solution Methods.
For steady-state solutions, convergence acceleration of the explicit formulation can be achieved with the use of local time stepping, residual smoothing, and full-approximation storage multigrid.
Local time stepping is a method by which the solution at each control volume is advanced in time with respect to the cell time step, defined by the local stability limit of the time-stepping scheme.
Residual smoothing, on the other hand, increases the bound of stability limits of the time-stepping scheme and hence allows for the use of a larger CFL value to achieve fast convergence.
The convergence rate of the explicit scheme can be accelerated through use of the full-approximation storage (FAS) multigrid method.
By default, FLUENT uses a 3-stage Runge-Kutta scheme for steady-state flows that use the density-based explicit solver.
Hope this helps!
The short answer is Fluent uses the CFL number to compute the time step (even for steady flows). A more detailed explanation follows...
The coupled set of governing equations is discretized in time for both steady and unsteady (transient) calculations. In the steady case, it is assumed that time marching proceeds until a steady-state solution is reached. Temporal discretization of the coupled equations is accomplished by either an implicit or an explicit time-marching algorithm. In the Explicit Formulation the time step is computed from the Courant-Friedrichs-Lewy (CFL) condition. The time step is a function of: the cell volume, the cell face area, and the maximum of local eigenvalues.
Here is some additional information straight from the theory guide (Fluent Version 6) in the section: Steady-State Flow Solution Methods.
For steady-state solutions, convergence acceleration of the explicit formulation can be achieved with the use of local time stepping, residual smoothing, and full-approximation storage multigrid.
Local time stepping is a method by which the solution at each control volume is advanced in time with respect to the cell time step, defined by the local stability limit of the time-stepping scheme.
Residual smoothing, on the other hand, increases the bound of stability limits of the time-stepping scheme and hence allows for the use of a larger CFL value to achieve fast convergence.
The convergence rate of the explicit scheme can be accelerated through use of the full-approximation storage (FAS) multigrid method.
By default, FLUENT uses a 3-stage Runge-Kutta scheme for steady-state flows that use the density-based explicit solver.
Hope this helps!
You should refer to Fluent Manual for full explanation :
"Steady-State Flow Solution Methods"
https://www.sharcnet.ca/Software/Fluent6/html/ug/node1005.htm
Best regards
@Samuel CFD solvers generally solve steady problems as transient i.e they march in time till the solution becomes unchangeable with time. CFL number is used for getting the time step used for marching in time.
Here also, there are 2 approaches, using explicit or implicit time marching. For explicit. there is a strict criteria for CFL number for stability whereas in implicit approaches, no such criteria / bound is needed. So, you can approach the steady state solution much faster using implicit approach.
Hope this helps.
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