Grid deformation for computational aeroelastic analysis using RBF interpolation with standard greedy method

Mesh motion and data interpolation using radial basis functions (RBF) in combination with greedy algorithm has proven to be an efficient method in providing both high-quality deformed meshes and speed-up computations. In the present work in-house computational fluid dynamic (CFD) code HUNS3D (Hybrid Unstructured Navier Stokes 3D) has been extended to include dynamic mesh motion and aeroelastic behavior prediction. For large mesh sizes pure form of RBF interpolation becomes unfeasible to implement, therefore greedy algorithm serving as data reduction tool was applied. Computational structural dynamic (CSD) surface mesh usually has small size as compared to CFD mesh; therefore it could serve as RBF sample points and govern the volume mesh deformation. CFD-based aeroelastic simulation involves interpolation of surface loads and surface displacements for one complete loop. Here, RBF interpolation serves as single subroutine and carries out the required data interpolation for both the surface loads and deformations. Provision has been made to keep this subroutine as a standalone mesh motion tool for predefined deformations. Different test cases were simulated to test the robustness and functionality of current implementation. The surface deformation for both structured and unstructured meshes were carried out to access the performance. It was found that RBF interpolation in combination with standard greedy method is an efficient scheme to either conduct a CFD-based aeroelastic analyses or analyze presumed arbitrary deformation. The method is independent of the volume mesh size and performs well for large deformations.