Aerodynamic optimisation of civil aero-engine nacelles by dimensionality reduction and multi-fidelity techniques

Date

2022-09-30

Supervisor/s

Journal Title

Journal ISSN

Volume Title

Publisher

Emerald

Department

Type

Article

ISSN

0961-5539

Format

Free to read from

Citation

Tejero F, MacManus DG, Hueso-Rebassa J, et al., (2023) Aerodynamic optimisation of civil aero-engine nacelles by dimensionality reduction and multi-fidelity techniques, International Journal of Numerical Methods for Heat and Fluid Flow, Volume 33, Issue 4, April 2023, pp. 1336-1353

Abstract

Purpose - Aerodynamic shape optimisation is complex due to the high dimensionality of the problem, the associated non-linearity and its large computational cost. These three aspects have an impact on the overall time of the design process. To overcome these challenges, this paper develops a method for transonic aerodynamic design with dimensionality reduction and multi-fidelity techniques.

Design/methodology/approach - The developed methodology is used for the optimisation of an installed civil ultra-high bypass ratio aero-engine nacelle. As such, the effects of airframe-engine integration are considered during the optimisation routine. The active subspace method is applied to reduce the dimensionality of the problem from 32 to 2 design variables with a database compiled with Euler CFD calculations. In the reduced dimensional space, a co-Kriging model is built to combine Euler lower-fidelity and RANS higher-fidelity CFD evaluations.

Findings - Relative to a baseline aero-engine nacelle derived from an isolated optimisation process, the proposed method yielded a non-axisymmetric nacelle configuration with an increment in net vehicle force of 0.65% of the nominal standard net thrust.

Originality - This work investigates the viability of CFD optimisation through a combination of dimensionality reduction and multi-fidelity method, and demonstrates that the developed methodology enables the optimisation of complex aerodynamic problems.

Description

Software Description

Software Language

Github

Keywords

Optimization, dimensionality reduction, multi-fidelity, active subspace, co-kriging

DOI

Rights

Attribution-NonCommercial 4.0 International

Relationships

Relationships

Supplements

Funder/s

European Union funding: 820997