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A Spatial Arrangement Visualisation Strategy for Learning from Large Ensembles of Unsteady Flow-field Data

cam.depositDate2022-01-10
cam.issuedOnline2022-12-29
cam.orpheus.successTue Feb 01 19:02:40 GMT 2022 - Embargo updated
dc.contributor.authorKotnik, A
dc.contributor.authorPullan, G
dc.date.accessioned2022-01-12T14:23:52Z
dc.date.available2022-01-12T14:23:52Z
dc.date.issued2022-01-03
dc.date.updated2022-01-10T09:46:23Z
dc.identifier.doi10.17863/CAM.80095
dc.identifier.isbn9781624106316
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/332651
dc.language.isoeng
dc.publisherAmerican Institute of Aeronautics and Astronautics
dc.publisher.departmentDepartment of Engineering Student
dc.publisher.urlhttp://dx.doi.org/10.2514/6.2022-0810
dc.rightsAll Rights Reserved
dc.rights.urihttp://www.rioxx.net/licenses/all-rights-reserved
dc.subject4012 Fluid Mechanics and Thermal Engineering
dc.subject40 Engineering
dc.titleA Spatial Arrangement Visualisation Strategy for Learning from Large Ensembles of Unsteady Flow-field Data
dc.typeConference Object
prism.publicationDate2022
prism.publicationNameAIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2022
pubs.conference-nameAIAA SCITECH 2022 Forum
pubs.funder-project-idEPSRC (2111124)
pubs.licence-display-nameApollo Repository Deposit Licence Agreement
pubs.licence-identifierapollo-deposit-licence-2-1
rioxxterms.versionAM
rioxxterms.versionofrecord10.2514/6.2022-0810

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