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The problem is related to the Airfoil optimization MACH Aero framework of MDO Lab. While running the airfoil_opt.py code, it gives an error indicating that there is an error in the SLSQP.py
Steps to reproduce issue
Run Bash in windows. Enter the docker through bash and run the following,
Run genMesh.py
Run genFFD.py
Run airfoil_opt.py
Current behavior
When I run "mpirun -np 4 python airfoil_opt.py | tee output.txt" in bash, the program runs properly till the following:
+-------------------------------------------------------------------------------+
| Sparsity structure of constraint Jacobian | |
+-------------------------------------------------------------------------------+
Then it displays the following error:
ValueError: failed to initialize intent(inout) array -- expected elsize=8 but got 16 -- input 'D' not compatible to 'd'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/home/mdolabuser/mount/mach-aero/SA7038/airfoil_opt.py", line 270, in <module>
sol = opt(optProb, MP.sens, storeHistory=os.path.join(args.output, "opt.hst"))
File "/home/mdolabuser/.pyenv/versions/3.9.16/lib/python3.9/site-packages/pyoptsparse/pySLSQP/pySLSQP.py", line 218, in __call__
slsqp.slsqp(m, meq, la, n, xs, blx, bux, ff, gg, df, dg, acc, maxit,
ValueError: failed in converting 5th argument `x' of slsqp.slsqp to C/Fortran array
Description
The problem is related to the Airfoil optimization MACH Aero framework of MDO Lab. While running the airfoil_opt.py code, it gives an error indicating that there is an error in the SLSQP.py
Steps to reproduce issue
Run Bash in windows. Enter the docker through bash and run the following,
Current behavior
When I run "mpirun -np 4 python airfoil_opt.py | tee output.txt" in bash, the program runs properly till the following:
Then it displays the following error:
Expected behavior
it should produce results similar to the results provided in the following:
https://mdolab-mach-aero.readthedocs-hosted.com/en/latest/machAeroTutorials/airfoilopt_singlepoint.html
Note:
You can excess the pySLSQP.py at:
https://github.com/mdolab/pyoptsparse/tree/main/pyoptsparse/pySLSQP
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