The University of Southampton
University of Southampton Institutional Repository

Multifidelity surrogate modeling of experimental and computational aerodynamic data sets

Kuya, Yuichi, Takeda, Kenji, Zhang, Xin and Forrester, Alexander (2011) Multifidelity surrogate modeling of experimental and computational aerodynamic data sets AIAA Journal, 49, (2), pp. 289-298. (doi:10.2514/1.J050384).

Record type: Article

Abstract

This study presents a multifidelity surrogate modeling approach, combining experimental and computational aerodynamic data sets. A multifidelity cokriging regression surrogate model is used. This study highlights how lowfidelity data from computations contribute to improving surrogate models built with limited high-fidelity data from experiments. Various types of sampling design for low fidelity data are also examined to study the impact of characteristics of the sampling design on the final surrogate models. Replication, blocking, and randomization techniques originally developed for design of experiments are used to minimize random and systematic errors. Surrogate models representing the performance of an inverted wing with counter-rotating vortex generators in ground effect are constructed, where design variables of the wing ride height and incidence and the response of sectional downforce are examined. A cokriging regression containing 12 experimental and 25 computational data points sampled with a Latin hypercube design shows the best performance here, capturing general characteristics of the target map well.

Full text not available from this repository.

More information

Published date: February 2011
Organisations: Aerodynamics & Flight Mechanics

Identifiers

Local EPrints ID: 177041
URI: http://eprints.soton.ac.uk/id/eprint/177041
ISSN: 0001-1452
PURE UUID: b69bad0f-7718-407c-9b53-78ebd639713e

Catalogue record

Date deposited: 14 Mar 2011 14:10
Last modified: 18 Jul 2017 12:06

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.

×