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In order to learn shape optimization with the discrete adjoint method, I am trying to optimize the 3D hemisphere cylinder with the aim of reducing CD. The model can be seen below. Deformation is only allowed for the sphere. There is no constraint for optimization.
First of all, this is my configuration file for shape_optimization.py. config.txt
The below figure shows the initial box with FFD_DEGREE= (6, 4, 4). The control point at the red dots are held fixed to ensure continuity between the sphere and cylinder. Other control points are free to move in all directions (i,j,k)
Optimization starts without a problem. For baseline geometry pressure coefficients on the sphere match with the experimental result. Residuals go down for both direct and adjoint simulations. The figure below shows optimization history until it diverges at DSN_32.
Below, you can see various designs. The optimization tries to make the shape more slender :)
When it diverged, I tried different CFL numbers but it did not solve the issue. The quality does not change until DNS_027 but then CV Sub-Volume Ratio starts to increase. I believe it diverges at DNS_32 due to mesh quality.
How to deal with this diverging problem at DSN_32? I believe that my initial mesh has good quality.
How to ensure continuity at the intersection between sphere and cylinder. I try both FFD_CONTINUITY= USER_INPUT and 2ND_DERIVATIVE but I could not get rid of the issue in the below figure.
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Hey everybody,
In order to learn shape optimization with the discrete adjoint method, I am trying to optimize the 3D hemisphere cylinder with the aim of reducing CD. The model can be seen below. Deformation is only allowed for the sphere. There is no constraint for optimization.
First of all, this is my configuration file for shape_optimization.py. config.txt
The below figure shows the initial box with FFD_DEGREE= (6, 4, 4). The control point at the red dots are held fixed to ensure continuity between the sphere and cylinder. Other control points are free to move in all directions (i,j,k)
Optimization starts without a problem. For baseline geometry pressure coefficients on the sphere match with the experimental result. Residuals go down for both direct and adjoint simulations. The figure below shows optimization history until it diverges at DSN_32.
Below, you can see various designs. The optimization tries to make the shape more slender :)
When it diverged, I tried different CFL numbers but it did not solve the issue. The quality does not change until DNS_027 but then CV Sub-Volume Ratio starts to increase. I believe it diverges at DNS_32 due to mesh quality.
NEED HELP
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