What's inside?
This paper presents a design process coupling a 3D inverse design approach with a Multi Objective Genetic Algorithm (MOGA) for axial cooling fan. The aim is to reduce the leakage loss and profile losses to improve performance. The inverse design method parameterizes the 3D shape of the axial fan with a reduced number of design parameters allowing a larger exploration of the design space in the optimization process.
Two designs from the optimization are analyzed in detailed by using 3D Computational Fluid Dynamic (CFD) calculations, which confirm that the design optimized for minimizing leakage losses meets the design specification. Detailed CFD also confirms the reduction in leakage losses in this design.
In this publication, you will:
- Understand the presented methodology multi-objective design of fans in which the blade shape is parameterized in terms of blade loading parameters used as input to a 3D inverse design code.
- Learn how the 3D Inverse Design method is applied, with TURBOdesign1, to parametrically describe the blade geometry.
- See the advantage of using a three-dimensional based approach in this project, it can be used to rapidly and automatically explore a large part of the design space to create impeller that meet contrasting requirements relating to efficiency, flow phenomenon, losses, manufacturing limitations, mechanical constraints or cost.
