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October 2, 2016, 08:56 |
Sensetivities
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#1 |
Member
Tom
Join Date: Oct 2015
Posts: 67
Rep Power: 11 |
Hello my friends
I’ve been involved with this problem for about a week and I’m still struggling to find a way around it I have a wing which is look like the attached picture. I want to do some optimization on that based on let’s say drag objective function. I solved the RANS eq. on the geometry and the convergence went well. The residuals are: Iter Time(s) Res[Rho] Res[nu] CLift(Total) CDrag(Total) 20000 2.646225 -7.977799 -10.375939 0.414779 0.296870 After that I solve the continuous adjoint equations (drag OF), which the residuals are: Iter Time(s) Res[Psi_Rho] Res[Psi_E] Sens_Geo Sens_Mach 20000 4.535583 -3.265719 -9.096933 -3.0207e+03 -2.9336e-01 I investigate a lot of effort on the meshing part. The grid was generated using pointwise software. In this geometry there are not any noticeable sharp edges but I try to resolve any feature on the geometry (added pictures). As it is shown in the residuals the surface sensitivities are really high which lead to high gradients and high surface deformation. can any body give a hint on that? ** in the countour the values are mostly around 30000 |
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March 11, 2017, 04:36 |
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#2 | |
Senior Member
Heather Kline
Join Date: Jun 2013
Posts: 309
Rep Power: 14 |
Quote:
CFL_REDUCTION_ADJFLOW = (something less than 1 to use a smaller CFL than the direct problem) LIMIT_ADJFLOW= (default 1E6, can test out other values) MG_ADJFLOW = YES by default, however NO can be useful when convergence is difficult RELAXATION_FACTOR_ADJFLOW = something slightly less than one if there is an issue with the mesh SPATIAL_ORDER_ADJFLOW = 1ST_ORDER often has an easier time converging. Although it is recommended to use the same numerical method setting for direct and adjoint, you can also play around with that if your problem is not converging well. |
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