The dynamic gradient adaption executes the gradient adaption automatically. Though all options of gradient adaption are valid for the dynamic gradient adaption, some specific settings are recommended:
In the Gradient Adaption Panel
This value depends on the type of problem solved and the time step used (where applicable). For steady state problems, values of 100 or higher are reasonable and for time dependent problems, values of 10 or lower are often required.
In the Gradient Adaption Controls Panel
The limits for the Min # of Cells and Max # of Cells can affect the Coarsen Threshold and Refine Threshold values. If either the Min # of Cells or the Max # of Cells are violated, the Coarsen Threshold or the Refine Threshold are adjusted to fulfill the limits for the Min # of Cells or the Max # of Cells.
| Even in a 2D problem, the default value of 2 can increase the number of cells by a factor of 16, in the adapted regions. A value of zero leaves this parameter unbounded: in this case you should use a suitable limit for
Min Cell Volume.
Examples of Dynamic Gradient Adaption
Example 1: Steady state problem.
Consider a supersonic flow over the blunt body. To determine the wave drag for such problem, first resolve the shock wave. Start with a coarse mesh and setup dynamic adaption. As you start iterating the solution, the solver will produce a blurred shock, probably in an incorrect location. After the adaptions, the shock will become sharper and move into the correct location.
Example 2: Time dependent problem.
Consider a traveling shock wave. To determine the precise pressure amplitudes and arrival times at a number of locations, you need to resolve the shock wave over the time, so that you can maintain the correct shock strength and its location. Dynamic adaption is efficient in this case, as it refines the mesh near the shock and at the same time it coarsens the mesh wherever needed.
See also Tutorial 4 for an example of applying dynamic gradient adaption to a FLUENT simulation.