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dc.contributor.authorTadeja, Slawomiren
dc.contributor.authorKipouros, Timoleonen
dc.contributor.authorKristensson, Per Olaen
dc.date.accessioned2020-01-10T00:30:14Z
dc.date.available2020-01-10T00:30:14Z
dc.date.issued2020-01-05en
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/300668
dc.description.abstractComputational engineering design methods and tools are common practice in modern industry. Such approaches are integral in enabling designers to efficiently explore larger and more complex design spaces. However, at the same time, computational engineering design methods tend to dramatically increase the number of candidate solutions that decision-makers must interpret in order to make appropriate choices within a set of solutions. Since all candidate solutions can be represented in digital form together with their assessment criteria, evaluated according to some sort of simulation model, a natural way to explore and understand the complexities of the design problem is to visualize their multidimensional nature. The task now involves the discovery of patterns and trends within the multidimensional design space. In this work, we aim to enhance the design decision-making process by embedding visual analytics into an immersive virtual reality environment. To this end, we present a system called IPCP: immersive parallel coordinates plots. IPCP combines the well-established parallel coordinates visualization technique for high-dimensional data with immersive virtual reality. We propose this approach in order to exploit and discover efficient means to use new technology within a conventional decision-making process. The aim is to provide benefits by enhancing visualizations of 3D geometry and other physical quantities with scientific information. We present the design of this system, which allows the representation and exploration of multidimensional scientific datasets. A qualitative evaluation with two surrogate expert users, knowledgeable in multidimensional data analysis, demonstrate that the system can be used successfully to detect both known and previously unknown patterns in a real-world test dataset, producing an early indicative validation of its suitability for decision support in engineering design processes.
dc.description.sponsorshipCambridge European and Trinity Hall; Engineering and Physical Sciences Research Council (EPSRC-1788814)
dc.languageEnglishen
dc.rightsAll rights reserved
dc.rights.uri
dc.titleIPCP: Immersive Parallel Coordinates Plots for Engineering Design Processesen
dc.typeConference Object
prism.publicationDate2020en
dc.identifier.doi10.17863/CAM.47741
dcterms.dateAccepted2019-11-01en
rioxxterms.versionofrecord10.2514/6.2020-0324en
rioxxterms.versionAM
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2020-01-05en
dc.contributor.orcidTadeja, Slawomir [0000-0003-0455-4062]
dc.contributor.orcidKipouros, Timoleon [0000-0003-3392-283X]
rioxxterms.typeConference Paper/Proceeding/Abstracten
pubs.funder-project-idEPSRC (1788814)
cam.issuedOnline2020-01-05en
pubs.conference-nameAIAA Scitech 2020 Forumen
pubs.conference-start-date2020-01-06en


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