Mechanics & Industry
Volume 16, Number 1, 2015
|Number of page(s)||8|
|Published online||16 September 2014|
Meta-model based optimization of a large diameter semi-radial conical hub engine cooling fan
1 Universitéde Lyon, UMR CNRS 5509,
Laboratoire de Mécanique des Fluides et d’Acoustique, École Centrale de
2 Valeo Systèmes Thermiques, 8 rue Louis Lormand, 78321 La Verriere, France
3 Université de Lyon, UMR CNRS 5513, Laboratoire de Tribologie et Dynamique des Systèmes, École Centrale de Lyon, 69130 Ecully, France
a Corresponding author:
Accepted: 25 June 2014
Turbomachinery design is an iterative process that can be time-consuming and expensive, especially when an extensive knowledge of the performance envelope is required. The approach described in the present paper can significantly cut the turnaround times down without jeopardizing the accuracy of the final result. A parameterization technique based on radial basis functions (RBF) is used and Reynolds Averaged Navier-Stokes (RANS) simulations are subsequently performed on a set of selected morphed meshes, the goal of which is to produce an aerodynamic database containing first-order, second-order and second-order cross derivatives of objectives with respect to parameters. New solutions, corresponding to any variations of the selected parameters, can thus be extrapolated thanks to the information included in the aforementioned database. In this way, a meta-model is built and can be easily explored by a genetic algorithm. This approach has been experimented on a new concept of engine cooling fan featuring low torque and high efficiency. A reference fan design has been adapted for the particular surrounding of the vehicle underhood, where the downstream flow is radially deviated from its axis by the engine. The optimization process has resulted in an efficiency improvement of three points for one of the obtained optima.
Key words: Turbomachinery design / computational fluid dynamics (CFD) / parameterization / mesh morphing / meta-model / optimization / engine cooling fan
© AFM, EDP Sciences 2014
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.