Mesh deformation based on artificial neural networks |
| |
Authors: | Domen Stadler Franc Kosel Damjan Čelič Andrej Lipej |
| |
Affiliation: | 1. Turboinstitut , Ljubljana, Slovenia domen.stadler@turboinstitut.si;3. Faculty for Mechanical Engineering , University of Ljubljana , Ljubljana, Slovenia;4. Turboinstitut , Ljubljana, Slovenia |
| |
Abstract: | In the article a new mesh deformation algorithm based on artificial neural networks is introduced. This method is a point-to-point method, meaning that it does not use connectivity information for calculation of the mesh deformation. Two already known point-to-point methods, based on interpolation techniques, are also presented. In contrast to the two known interpolation methods, the new method does not require a summation over all boundary nodes for one displacement calculation. The consequence of this fact is a shorter computational time of mesh deformation, which is proven by different deformation tests. The quality of the deformed meshes with all three deformation methods was also compared. Finally, the generated and the deformed three-dimensional meshes were used in the computational fluid dynamics numerical analysis of a Francis water turbine. A comparison of the analysis results was made to prove the applicability of the new method in every day computation. |
| |
Keywords: | mesh deformation artificial neural networks back-propagation learning algorithm Francis water turbine mesh quality criteria |
|
|