Expected Improvement applied to an industrial context-Prediction of new geometries increasing the eciency of fans

B. Demory , M. Henner (1) , Agnès Lagnoux (2) , T.M.N. Nguyen

1 Valeo Engine Cooling
2 IMT - Institut de Mathématiques de Toulouse UMR5219

In automotive industry, client needs evolve quickly in a competitiveness context, particularly, regarding the fan involved in the engine cooling module. This study has been done in cooperation with the automotive supplier Valeo. Here, we propose to use the Kriging interpolation and the Expected Improvement algorithm to provide new fan designs with high performances in terms of eciency. As far as we know, such a use of Kriging and Expected Improvement methodologies are innovative and provide really promising results.

Mots clés: Kriging; Expected improvement; Optimization

Domaines: Mathématiques [math]; Statistiques [stat]; Applications [stat.AP]

B. Demory, M. Henner, Agnès Lagnoux, T.M.N. Nguyen. Expected Improvement applied to an industrial context-Prediction of new geometries increasing the eciency of fans. 2019. ⟨hal-02044258v1⟩