Maintaining Thermal Comfort of a Naturally Ventilated Residential House by Intelligently Actuating Windows

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aut.relation.conference24th International Conference on Computer-Aided Architectural Design Research in Asia (CAADRIA 2019)en_NZ
aut.relation.endpage714
aut.relation.startpage705
aut.relation.volume1en_NZ
aut.researcherAnderson, Timothy
dc.contributor.authorPokhrel, Men_NZ
dc.contributor.authorAnderson, Ten_NZ
dc.contributor.authorLie, Ten_NZ
dc.date.accessioned2019-06-20T02:40:06Z
dc.date.available2019-06-20T02:40:06Z
dc.date.copyright2019-04-15en_NZ
dc.date.issued2019-04-15en_NZ
dc.description.abstractIn New Zealand’s (NZ) mild climatic conditions, most residential houses are ventilated naturally, mainly by opening windows. However, maintaining the indoor thermal comfort characteristics of a house by modulating natural ventilation is particularly challenging, as the solution is not explicit. Determining a solution requires a technique that adjusts openable window area while encapsulating the complexity, dynamics, and nonlinearity associated with the natural ventilation driving forces and building thermal behavior. By verifying that there exists a significant potential of regulating indoor thermal comfort of a relatively airtight and insulated house by adjusting window openable area; this work additionally confirmed an excellent capability of Artificial Neural Network (ANN) technique in predicting air temperature time-series of the naturally ventilated house. On the basis of these examinations, this work particularly developed a co-simulation strategy between building thermal-airflow model and the ANN model and demonstrated that windows could be regulated intelligently to modulate the natural ventilation and maintain indoor thermal comfort level during the summer period by applying Artificial Neural Network (ANN) based predictive controller technique.en_NZ
dc.identifier.citationIntelligent & Informed, Proceedings of the 24th International Conference of the Association for Computer-Aided Architectural Design Research in Asia (CAADRIA) 2019, Volume 1, 705-714. © 2019 and published by the Association for Computer-Aided Architectural Design Research in Asia (CAADRIA), Hong Kong.
dc.identifier.isbn978-988-78917-1-0en_NZ
dc.identifier.urihttps://hdl.handle.net/10292/12576
dc.publisherThe Association for Computer-Aided Architectural Design Research in Asia (CAADRIA), Hong Kongen_NZ
dc.relation.urihttp://papers.cumincad.org/data/works/att/caadria2019_330.pdf
dc.rightsNOTICE: this is the author’s version of a work that was accepted for publication. 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 (see Citation). The original publication is available at (see Publisher's Version).
dc.rights.accessrightsOpenAccessen_NZ
dc.subjectNatural Ventilationen_NZ
dc.subjectThermal Comforten_NZ
dc.subjectArtificial Neural Network (ANN)en_NZ
dc.subjectResidential Houseen_NZ
dc.subjectIntelligent Windowsen_NZ
dc.titleMaintaining Thermal Comfort of a Naturally Ventilated Residential House by Intelligently Actuating Windowsen_NZ
dc.typeConference Contribution
pubs.elements-id359367
pubs.organisational-data/AUT
pubs.organisational-data/AUT/Design & Creative Technologies
pubs.organisational-data/AUT/Design & Creative Technologies/Engineering, Computer & Mathematical Sciences
pubs.organisational-data/AUT/PBRF
pubs.organisational-data/AUT/PBRF/PBRF Design and Creative Technologies
pubs.organisational-data/AUT/PBRF/PBRF Design and Creative Technologies/PBRF ECMS
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