López de Vega, Luis
and Dufour, Guillaume and Blanc, Florian and Thollet, William
A Machine Learning Based Body Force Model for Analysis of Fan-Airframe Aerodynamic Interactions.
(2018)
In: Global Power and Propulsion Society Conference 2018, 7 May 2018 - 9 May 2018 (Montréal, Canada).
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(Document in English)
PDF (Author's version) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader 1MB |
Official URL: https://doi.org/10.5281/zenodo.1344526
Abstract
Body force modeling is a numerical strategy that allows an accurate representation of the aerodynamics of turbomachinery blade rows at a reduced computational cost, making it suitable for predicting fan-airframe aerodynamic interactions in boundary layer ingestion (BLI) propulsive architectures. This paper focuses on a new approach for building the body force representation using a machine learning technique, rather than analytically modeling the effects of the blades in the flow. This methodology is developed and assessed in a distorted inflow case representative of a BLI configuration and compared to a full annulus unsteady computation.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Audience (conference): | International conference proceedings |
| Uncontrolled Keywords: | |
| Institution: | Other partners > Airbus (FRANCE) Université de Toulouse > Institut Supérieur de l'Aéronautique et de l'Espace - ISAE-SUPAERO (FRANCE) |
| Laboratory name: | |
| Statistics: | download |
| Deposited On: | 12 Oct 2018 13:21 |
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