/AeroelasticAirfoil-SU2

A simple framework that automatically generates SU2 configuration (.cfg) files and make calls to SU2 to perform aeroelastic simulations all within Python. The Matrix Pencil method is then used to compute the damping coefficient.

Primary LanguagePythonMIT LicenseMIT

AeroelasticAirfoil-SU2

A simple framework that automatically generates SU2 configuration (.cfg) files and make calls to SU2 to perform aeroelastic simulations all within Python. The Matrix Pencil [4] method is then used to compute the damping coefficient. The code is based on SU2 v7.2.1 Blackbird (any version >= 7 should work). I wrote this code for my undergraduate thesis "On a Support Vector Machine Approach To Surrogate Modelling: Predicting the Aeroelastic Flutter Boundary Within the Transonic Regime" alongside a conference paper [2].

Notes:

Required packages: numpy, scipy

References:

[1] Economon, T. D., Palacios, F., Copeland, S. R., Lukaczyk, T. W., and Alonso, J.J., SU2: An Open-Source Suite for Multiphysics Simulation and Design, AIAA Journal, Vol. 54, No. 3, 2016, pp. 828–846. (https://github.com/su2code/SU2)

[2] Palar, P.S., Izzaturahman, F., Zuhal, L.R. and Shimoyama, K., Prediction of the Flutter Boundary in Aeroelasticity via a Support Vector Machine.

[3] Palar, P.S., Parussini, L., Bregant, L., Shimoyama, K., Izzaturrahman, M.F., Baehaqi, F.A. and Zuhal, L., 2022. Composite Kernel Functions for Surrogate Modeling using Recursive Multi-Fidelity Kriging. In AIAA SCITECH 2022 Forum (p. 0506).

[4] Jacobson, K.E., Kiviaho, J.F., Kennedy, G.J. and Smith, M.J., 2019. Evaluation of time-domain damping identification methods for flutter-constrained optimization. Journal of Fluids and Structures, 87, pp.174-188.