Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.buildenv.2021.108101
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dc.titleModel development of Roof Thermal Transfer Value (RTTV) for green roof in tropical area: A case study in Singapore
dc.contributor.authorHe, Yang
dc.contributor.authorLin, Ervine Shengwei
dc.contributor.authorTan, Chun Liang
dc.contributor.authorYu, Zhongqi
dc.contributor.authorTan, Puay Yok
dc.contributor.authorWong, Nyuk Hien
dc.date.accessioned2022-07-06T09:41:56Z
dc.date.available2022-07-06T09:41:56Z
dc.date.issued2021-10-01
dc.identifier.citationHe, Yang, Lin, Ervine Shengwei, Tan, Chun Liang, Yu, Zhongqi, Tan, Puay Yok, Wong, Nyuk Hien (2021-10-01). Model development of Roof Thermal Transfer Value (RTTV) for green roof in tropical area: A case study in Singapore. BUILDING AND ENVIRONMENT 203. ScholarBank@NUS Repository. https://doi.org/10.1016/j.buildenv.2021.108101
dc.identifier.issn03601323
dc.identifier.issn1873684X
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/228047
dc.description.abstractGreen roofs have been used widely in tropical countries due to their energy-saving and passive cooling effect. However, the model to calculate a thermal performance evaluation metric has yet to be established, which has hindered the inclusion of green roof in the envelope thermal performance standards in building regulations. This paper aims to develop a model to predict Roof Thermal Transfer Value (RTTV) of green roofs under a tropical climate. Firstly, the efficiency and accuracy of hygrothermal transfer model of green roof was validated against field data, and annual heat gain through four types of green roofs was simulated. Subsequently, the RTTV of four green roofs was calculated based on linear interpolation between RTTV of a common bare roof and corresponding annual heat gain, which ranged from 2.29 to 2.49 W/m2. Given the complexity and time-consuming of RTTV calculation by the hygrothermal transfer model, three types of regression models were developed based on the dataset of four significant design factors and corresponding values of RTTV. And it was found that multilayer perceptron (MLP) regression method had a better performance than multiple regression (MR) and random forest (RF) method. Finally, the equivalent thermal resistance of plant layer was calculated based on the RTTV model and other five simplified calculation methods, and the implicit reason that differences exist among them were discussed. The conclusions drawn in this paper can provide a methodology for a quick evaluation of thermal performance of green roof during the early stages of design.
dc.language.isoen
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD
dc.sourceElements
dc.subjectScience & Technology
dc.subjectTechnology
dc.subjectConstruction & Building Technology
dc.subjectEngineering, Environmental
dc.subjectEngineering, Civil
dc.subjectEngineering
dc.subjectThermal performance
dc.subjectRoof thermal transfer value
dc.subjectGreen roof
dc.subjectEquivalent thermal resistance
dc.subjectTropical area
dc.subjectARTIFICIAL NEURAL-NETWORKS
dc.subjectENERGY-CONSUMPTION
dc.subjectPERFORMANCE EVALUATION
dc.subjectRANDOM FOREST
dc.subjectBUILDINGS
dc.subjectIRRIGATION
dc.subjectSYSTEMS
dc.subjectGARDEN
dc.typeArticle
dc.date.updated2022-07-06T05:10:27Z
dc.contributor.departmentDEAN'S OFFICE (COLLEGE OF DESIGN & ENG)
dc.contributor.departmentARCHITECTURE
dc.contributor.departmentBUILDING
dc.description.doi10.1016/j.buildenv.2021.108101
dc.description.sourcetitleBUILDING AND ENVIRONMENT
dc.description.volume203
dc.published.statePublished
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