Efficient radial basis function mesh deformation methods for aircraft icing

Abstract

This paper presents an approach to update the moving ice boundary resulting from aircraft icing simulations using radial basis function mesh deformation techniques. State-of-the-art surface and volume point reduction schemes are used to reduce the computational cost of the mesh deformation. The data reduction schemes which are utilised include multi-level greedy surface point selection and volume point reduction. The multi-level greedy surface point selection reduces the number of control points to increase the efficiency of the interpolation operation. While the volume point reduction improves the computational cost of the volume mesh update operation which is important for large data sets. The paper assesses the capabilities of radial basis function mesh deformation for both two and three-dimensional problems. Furthermore, the effectiveness of the deformation technique is assessed for both local, non-smooth deformations and global, smooth deformations. The convergence history of the multi-level greedy point selection is assessed in terms of number of control points and computational cost. The location of the selected control points near the ice accretion illustrates the efficacy of the method for localised deformations. The results show that the radial basis function mesh deformation performs well for both the two and three-dimensional problems. The data-reduction schemes utilised in this work represent a significant improvement to standard radial basis function mesh deformation for aircraft icing problems comprising of large data-sets typical of three-dimensional problems.