Where non linear aerodynamics sets a precedent in the governing flow, to which the
transonic Mach regime is concerned, producing aeroelastic models under such conditions
have taken its toll on the balance between computational cost and accuracy. This
thesis investigates the utilization of the Support Vector Machine algorithm to produce
a surrogate model/response surface based on estimations of the damping coefficients of
aeroelastic models in order to predict the flutter boundary for a binary flutter system
based on a NACA 64A010 airfoil. A single fidelity aeroelastic model, in which the
aerodynamics is governed by the Euler equations and the aeroelastic equations of motion
solved in the time domain, is studied across a parameter space. Whereby, the proposed
space is bounded and varied in the Mach range of 0.7-0.9 and the Flutter Speed Index
of a range 0.4-2.0, wherein, the transonic dip is successfully demonstrated. The Prony
series based Matrix Pencil, as a system identification method, is used to estimate the
damping coefficients, in which the inputs are the Pitch and Plunge responses of the
aeroelastic system. With the damping estimates, a single Support Vector Classification
along with two Support Vector Regression models, Epsilon-SVR and Least Squares-SVR
(LS-SVR), were used to generate the response surfaces. With the regression models
indicating promising results, two new sampling plans based on an Augemented Latin
Hypercube of 75 samples was proposed with the aim to further reduce the computational
cost. Results indicate that the Epsilon-SVR model with its satisfactory generalization
capabilities produced the best predicitions for the flutter boundary, however, the results
also suggests the difficulty posed when dealing with training and test distributions in
the samples.