Selection of Existing Sail Designs for Multi-Fidelity Surrogate Models

Show simple item record

dc.contributor.author Peart, Tanya
dc.contributor.author Aubin, Nicolas
dc.contributor.author Nava, Stefano
dc.contributor.author Cater, John
dc.contributor.author Norris, Stuart
dc.date.accessioned 2022-02-01T23:07:08Z
dc.date.available 2022-02-01T23:07:08Z
dc.date.issued 2022-1-5
dc.identifier.uri https://hdl.handle.net/2292/58076
dc.description.abstract <jats:p>Velocity Prediction Programs (VPPs) are commonly used to help predict and compare the performance of different sail designs. A VPP requires an aerodynamic input force matrix which can be computationally expensive to calculate, limiting its application in industrial sail design projects. The use of multi-fidelity kriging surrogate models has previously been presented by the authors to reduce this cost, with high-fidelity data for a new sail being modelled and the low-fidelity data provided by data from existing, but different, sail designs. The difference in fidelity is not due to the simulation method used to obtain the data, but instead how similar the sail’s geometry is to the new sail design. An important consideration for the construction of these models is the choice of low-fidelity data points, which provide information about the trend of the model curve between the high-fidelity data. A method is required to select the best existing sail design to use for the low-fidelity data when constructing a multi-fidelity model. The suitability of an existing sail design as a low fidelity model could be evaluated based on the similarity of its geometric parameters with the new sail. It is shown here that for upwind jib sails, the similarity of the broadseam between the two sails best indicates the ability of a design to be used as low-fidelity data for a lift coefficient surrogate model. The lift coefficient surrogate model error predicted by the regression is shown to be close to 1% of the lift coefficient surrogate error for most points. Larger discrepancies are observed for a drag coefficient surrogate error regression.</jats:p>
dc.language en
dc.publisher The Society of Naval Architects and Marine Engineers
dc.relation.ispartofseries Journal of Sailing Technology
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher.
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm
dc.title Selection of Existing Sail Designs for Multi-Fidelity Surrogate Models
dc.type Journal Article
dc.identifier.doi 10.5957/jst/2022.7.2.31
pubs.issue 01
pubs.begin-page 31
pubs.volume 7
dc.date.updated 2022-01-05T19:47:22Z
dc.rights.holder Copyright: The author en
pubs.end-page 51
pubs.publication-status Published
dc.rights.accessrights http://purl.org/eprint/accessRights/RetrictedAccess en
pubs.subtype Article
pubs.elements-id 874841
dc.identifier.eissn 2475-370X
pubs.online-publication-date 2022-1-5


Files in this item

Find Full text

This item appears in the following Collection(s)

Show simple item record

Share

Search ResearchSpace


Browse

Statistics