Discrete adjoint benchmarks

This data set contains meshes for three discrete adjoint benchmarks along with ADflow configuration scripts to reproduce the results in the paper. If you are interested in running your adjoint solver for comparison, it is recommended to use the provided meshes (either structured or unstructured format) and the same flow conditions and CPU cores as described in the paper. If you would like to generate your own meshes, we suggest using a similar cell number for each benchmark. When comparing the performance, please report the runtime (in Taubench work unit), peak memory usage (resident set size in GB), number of CPU cores and mesh cells, as well as a description of your adjoint solver and the computing platform (including the Tau reference runtime). ADODG3: A low-speed rectangular wing. ADODG4: The common research model (CRM) wing. ADODG5: The CRM wing-body-tail configuration. *_Multiblock_Structured_Mesh.cgns: Multiblock structured mesh files for ADflow. *_Overset_Structured_Mesh.cgns: Multiblock overset mesh files for ADflow. *_Singleblock_Unstructured_Mesh.cgns: These meshes are identical to *_Multiblock_Structured_Mesh.cgns except that they are in single block unstructured mesh format. The far field, symmetry, and wall boundary names are FARFIELD, SYMMETRY, and WING, respectively. *_FFD.xyz: Free-form deformation (FFD) files for defining design variables. *_ADflow_Run_Script.py: Python scripts for reproducing the ADflow adjoint results in the paper. See detailed instructions in the scripts. Code_Version.txt: The required codes to produce the results and their links and versions. Reference: Gaetan K.W. Kenway, Charles A. Mader, Ping He, and Joaquim R. R. A. Martins. Effective adjoint approaches in Computational Fluid Dynamics, Progress in Aerospace Sciences, 2019.