An interesting paper involving the use of RBF Morph has been presented at 10th International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control with Applications to Industrial and Societal Problems – EUROGEN 2013 (Las Palmas de Gran Canaria, Spain, October 7 – 9, 2013).

The paper “Optimization under Uncertainty using Adjoint Solver and RBF Morph” is available in the download area of this site or using a direct link.


This paper presents an industrial approach to optimization under uncertainty where the design variables and the uncertainties are handled by two different optimization modules of ANSYS Fluent, respectively the Adjoint Solver and the RBF morph.

The approach shown here is based on the use of the Adjoint solver to drive the shape modification of the considered geometry: the adjoint sensitivities are used to guide intelligent design modifications and improve the product perfomance.

The presence of geometrical uncertainties is handled using the RBF morph that combines a very accurate control of the geometrical parameters with an extremely fast mesh deformation: a system of radial functions is used to produce a solution for the mesh movement/morphing, from a list of source points and their displacements.

An industrial application is presented to show that the Adjoint solver can be used for optimization of a Formula 1 front wing, taking into account the geometrical uncertainties associated with the rotating rubber tire and vehicle steering.