The University of Southampton
University of Southampton Institutional Repository

Adjoint quasi-three-dimensional aerodynamic solver for multi-fidelity wing aerodynamic shape optimization

Adjoint quasi-three-dimensional aerodynamic solver for multi-fidelity wing aerodynamic shape optimization
Adjoint quasi-three-dimensional aerodynamic solver for multi-fidelity wing aerodynamic shape optimization
A quasi-three-dimensional method for wing aerodynamic analysis for drag prediction is presented. This method can predict the wing drag with a level of accuracy similar to higher fidelity three-dimensional CFD analysis, with a much lower computational cost. A tool has been developed based on the proposed method and the outputs of the tool have been validated using a higher fidelity CFD tool. Another advantage of the mentioned method (and the tool developed based on that) is to compute the derivatives of any function of interest, such as the wing drag, lift, or pitching moment, with respect to the design variables, mainly the wing geometry, using analytical methods. The tool uses a combination of the Adjoint method, the chain rule for differentiation, and the automatic differentiation to compute the sensitivities. The quasi-three-dimensional aerodynamic solver is used for a multi-fidelity wing aerodynamic shape optimization. A trust region algorithm is used to connect the low fidelity aerodynamic solver to a high fidelity CFD tool for wing drag prediction. The derivatives of the objective function are computed using the low fidelity solver, and the high fidelity solver is used to calibrate the results of the low fidelity one.
1270-9638
241-249
Elham, A.
676043c6-547a-4081-8521-1567885ad41a
Elham, A.
676043c6-547a-4081-8521-1567885ad41a

Elham, A. (2015) Adjoint quasi-three-dimensional aerodynamic solver for multi-fidelity wing aerodynamic shape optimization. Aerospace Science and Technology, 41, 241-249. (doi:10.1016/j.ast.2014.12.024).

Record type: Article

Abstract

A quasi-three-dimensional method for wing aerodynamic analysis for drag prediction is presented. This method can predict the wing drag with a level of accuracy similar to higher fidelity three-dimensional CFD analysis, with a much lower computational cost. A tool has been developed based on the proposed method and the outputs of the tool have been validated using a higher fidelity CFD tool. Another advantage of the mentioned method (and the tool developed based on that) is to compute the derivatives of any function of interest, such as the wing drag, lift, or pitching moment, with respect to the design variables, mainly the wing geometry, using analytical methods. The tool uses a combination of the Adjoint method, the chain rule for differentiation, and the automatic differentiation to compute the sensitivities. The quasi-three-dimensional aerodynamic solver is used for a multi-fidelity wing aerodynamic shape optimization. A trust region algorithm is used to connect the low fidelity aerodynamic solver to a high fidelity CFD tool for wing drag prediction. The derivatives of the objective function are computed using the low fidelity solver, and the high fidelity solver is used to calibrate the results of the low fidelity one.

This record has no associated files available for download.

More information

Published date: 1 February 2015

Identifiers

Local EPrints ID: 471103
URI: http://eprints.soton.ac.uk/id/eprint/471103
ISSN: 1270-9638
PURE UUID: 19309f8d-e27c-498b-8671-160fdaa0350e

Catalogue record

Date deposited: 26 Oct 2022 16:43
Last modified: 16 Mar 2024 21:27

Export record

Altmetrics

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×