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Design space optimisation of an unmanned aerial vehicle submerged inlet through the formulation of a data-fusion-based hybrid model

Published online by Cambridge University Press:  12 May 2021

F. Akram ,
H. A. Khan Open the ORCID record for H. A. Khan [Opens in a new window] ,
T. A. Shams Open the ORCID record for T. A. Shams [Opens in a new window]  and
D. Mavris Open the ORCID record for D. Mavris [Opens in a new window]
F. Akram
Affiliation:
Aerospace Engineering Department National University of Sciences and Technology (NUST) H-12, Islamabad, 44000Pakistan
H. A. Khan*
Affiliation:
Aerospace Engineering Department National University of Sciences and Technology (NUST) H-12, Islamabad, 44000Pakistan
T. A. Shams
Affiliation:
Aerospace Engineering Department National University of Sciences and Technology (NUST) H-12, Islamabad, 44000Pakistan
D. Mavris
Affiliation:
Aerospace Engineering Department Georgia Institute of TechnologyAtlantaGA, 30332USA
*
[email protected]
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Abstract

The research focuses on the design space optimisation of National Advisory Committee for Aeronautics (NACA) submerged inlets through the formulation of a hybrid data fusion methodology. Submerged inlets have drawn considerable attention owing to their potential for good on-design performance, for example during cruise flight conditions. However, complexities due to the geometrical topology and interactions among various design variables remain a challenge. This research enhances the current design knowledge of submerged inlets through the utilisation of data mining and Computational Fluid Dynamics (CFD) methodologies, focusing on design space optimisation. A two-pronged approach is employed where the first step encompasses a low-fidelity model through data mining and surrogate modelling to predict and optimise the design parameters, while the second step uses the Design of Experiments (DOE) approach based on the CFD results for the candidate design geometry to construct a surrogate model with high fidelity for design refinement. The feasibility of the proposed methodology is demonstrated for the optimisation of the total pressure recovery of a NACA submerged inlet for the subsonic flight regime. The proposed methodology is found to provide good agreement between the surrogate and CFD-based model and reduce the optimisation processing time by half in comparison with conventional (global-based) CFD optimisation approaches.

Keywords

Data fusionSurrogate modellingMDONACA submerged inlet designCFD
Type
Research Article
Information
The Aeronautical Journal , Volume 125 , Issue 1292 , October 2021 , pp. 1815 - 1832
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Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of Royal Aeronautical Society

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Footnotes

This work is an extension of research that was presented at the 28th AIAA Applied Aerodynamics Conference, 2010 in Chicago, IL, USA.

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