A surrogate model for vortex generator flows has been created. This was done by developing a framework to generate a reduced order approximation of a discrete optimized source-term on a uniform grid. The discrete optimized source term uses the flow field of a vortex generator simulation with a body-fitted mesh (BFM) as objective. The reduced order approximation yields very similar results to the optimized solution and shows that it can be used to train the surrogate model.
The surrogate model was trained by varying the inflow angle and Reynolds number in 24 training simulations. The shape factor, velocity profile and circulation downstream of the vortex generator are better in the proposed surrogate model than in the jBAY model, showing that the surrogate model is more accurate. Additionally, unlike the jBAY model, this new surrogate model is independent of the mesh refinement.