LiDAR point-cloud mapping of building façades for building energy performance simulation

DC FieldValueLanguage
dc.contributor.authorO'Donnell, James-
dc.contributor.authorTruong-Hong, Linh-
dc.contributor.authorBoyle, Niamh-
dc.contributor.authorCorry, Edward-
dc.contributor.authoret al.-
dc.date.accessioned2019-08-20T07:00:47Z-
dc.date.available2019-08-20T07:00:47Z-
dc.date.copyright2019 Elsevieren_US
dc.date.issued2019-11-
dc.identifier.citationAutomation in Constructionen_US
dc.identifier.issn0926-5805-
dc.identifier.urihttp://hdl.handle.net/10197/10995-
dc.description.abstractCurrent processes that create Building Energy Performance Simulation (BEPS) models are time consuming and costly, primarily due to the extensive manual inputs required for model population. In particular, generation of geometric inputs for existing building models requires significant manual intervention due to the absence, or outdated nature of available data or digital measurements. Additionally, solutions based on Building Information Modelling (BIM) also require high quality and precise geometrically-based models, which are not typically available for existing buildings. As such, this work introduces a semi-automated BEPS input solution for existing building exteriors that can be integrated with other related technologies (such as BIM or CityGML) and deployed across an entire building stock. Within the overarching approach, a novel sub-process automatically transforms a point cloud obtained from a terrestrial laser scanner into a representation of a building's exterior façade geometry as input data for a BEPS engine. Semantic enrichment is performed manually. This novel solution extends two existing approaches: (1) an angle criterion in boundary detection and (2) a voxelisation representation to improve performance. The use of laser scanning data reduces temporal costs and improves input accuracy for BEPS model generation of existing buildings. The approach is tested herein on two example cases. Vertical and horizontal accuracies of 1% and 7% were generated, respectively, when compared against independently produced, measured drawings. The approach showed variation in accuracy of model generation, particularly for upper floors of the test case buildings. However, the energy impacts resulting from these variations represented less than 1% of the energy consumption for both cases.en_US
dc.description.sponsorshipEuropean Commission - Seventh Framework Programme (FP7)en_US
dc.language.isoenen_US
dc.publisherElsevier BVen_US
dc.rightsThis is the author’s version of a work that was accepted for publication in Automation in Construction. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Automation in Construction (107, (2019)) https://doi.org/10.1016/j.autcon.2019.102905en_US
dc.subjectLight Detection And Ranging (LiDAR)en_US
dc.subjectLaser scanningen_US
dc.subjectCity-scale modellingen_US
dc.subjectBuilding Energy Performance Simulation (BEPS)en_US
dc.subjectRetrofiten_US
dc.subjectSemi-automated façades generationen_US
dc.titleLiDAR point-cloud mapping of building façades for building energy performance simulationen_US
dc.typeJournal Articleen_US
dc.internal.authorcontactotherjames.odonnell@ucd.ieen_US
dc.statusPeer revieweden_US
dc.identifier.volume107en_US
dc.check.date2021-08-01-
dc.identifier.doi10.1016/j.autcon.2019.102905-
dc.neeo.contributorO'Donnell|James|aut|-
dc.neeo.contributorTruong-Hong|Linh|aut|-
dc.neeo.contributorBoyle|Niamh|aut|-
dc.neeo.contributorCorry|Edward|aut|-
dc.neeo.contributoret al.||aut|-
dc.date.embargo2021-07-30en_US
dc.description.admin24 month embargo - ACen_US
dc.description.adminUpdate issue date during checkdate report - ACen_US
dc.date.updated2019-08-15T12:49:46Z-
dc.identifier.grantidGA PCIG14-GA-2013-631617-
dc.identifier.grantidERC StG 2012-307836-RETURN-
item.fulltextWith Fulltext-
item.grantfulltextembargo_20210730-
Appears in Collections:Mechanical & Materials Engineering Research Collection
Energy Institute Research Collection
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