Krigeage et amélioration attendue à visée industrielle - Prédiction de nouvelles géométrie de système de ventilation améliorant le rendement


  • Agnès Lagnoux UMR5219, Institut de Mathématiques de Toulouse, Université de Toulouse, CNRS
  • Thi Mong Ngoc Nguyen Faculty of Mathematics & Computer Science, University of Science, VNU-HCMC
  • Bruno Demory Valeo
  • Manuel Henner Valeo


This study has been done in cooperation with the automotive supplier Valeo. In automotive industry, client needs evolve quickly in a competitiveness context, particularly, regarding the fan involved in the engine cooling module. The practitioners are asked to propose ``optimal'' new fans in short times. Unfortunately, each evaluation of the underlying computer code may be expensive whence the need of approximated models and specific, parsimonious, and efficient global optimization strategies. In this paper, we propose to use the Kriging interpolation combined with the expected improvement algorithm to provide new fan designs with high performances in terms of efficiency. As far as we know, such a use of Kriging interpolation together with the expected improvement methodology is unique in an industrial context and provide really promising results.