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Main Authors: Lagnoux, Agnès, Nguyen, T. M. Ngoc, Demory, Bruno, Henner, Manuel
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2410.21830
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author Lagnoux, Agnès
Nguyen, T. M. Ngoc
Demory, Bruno
Henner, Manuel
author_facet Lagnoux, Agnès
Nguyen, T. M. Ngoc
Demory, Bruno
Henner, Manuel
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2410_21830
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Expected Improvement applied to an industrialcontext -- Prediction of new geometries increasing theefficiency of fans
Lagnoux, Agnès
Nguyen, T. M. Ngoc
Demory, Bruno
Henner, Manuel
Applications
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.
title Expected Improvement applied to an industrialcontext -- Prediction of new geometries increasing theefficiency of fans
topic Applications
url https://arxiv.org/abs/2410.21830