|April 14, 2014, 12:13||
When will the optimization stop?
Join Date: Mar 2014
Posts: 15Rep Power: 3
According to the documentation Running SU2,"Objective functions (drag, lift, etc.) are determined running a direct flow solution in SU2_CFD and gradients are obtained using the adjoint solution. For each iteration in the design process, the mesh is deformed using SU2_MDC, and the analysis is repeated until a local optimum is reached."
I want to know that when will a local optimum be reached? What the exact meaning of it? It seems that it calls the SU2_CFD many times. How many DESIGNS/DSN_00x will be performed? When will the program terminate?
Hope for your reply!!
|May 15, 2014, 16:08||
Sean R. Copeland
Join Date: Jan 2013
Posts: 40Rep Power: 5
Your question is a good one -- and, in general, not one that has a single answer. The optimization in SU2 uses gradient based optimization techniques to evolve the initial design to the optimal design in the manner that's described in your quote from the website. A local optimum is determined using the KKT conditions (run a google search for this) -- but in principle it's a zero gradient and only small changes in the objective function value from the previous design. The tolerances for these conditions are set in the shape_optimization.py script. Feel free to open this python script and adjust them as you see fit.
The optimizer will call SU2 as many times as it needs until these KKT conditions are met. In general, there's no way to know how many times are required -- it depends on how well-behaved your problem is and how large your design space is.
Hope that helps,
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