Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.buildenv.2021.108101
Title: Model development of Roof Thermal Transfer Value (RTTV) for green roof in tropical area: A case study in Singapore
Authors: He, Yang 
Lin, Ervine Shengwei 
Tan, Chun Liang 
Yu, Zhongqi 
Tan, Puay Yok 
Wong, Nyuk Hien 
Keywords: Science & Technology
Technology
Construction & Building Technology
Engineering, Environmental
Engineering, Civil
Engineering
Thermal performance
Roof thermal transfer value
Green roof
Equivalent thermal resistance
Tropical area
ARTIFICIAL NEURAL-NETWORKS
ENERGY-CONSUMPTION
PERFORMANCE EVALUATION
RANDOM FOREST
BUILDINGS
IRRIGATION
SYSTEMS
GARDEN
Issue Date: 1-Oct-2021
Publisher: PERGAMON-ELSEVIER SCIENCE LTD
Citation: He, 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
Abstract: Green 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.
Source Title: BUILDING AND ENVIRONMENT
URI: https://scholarbank.nus.edu.sg/handle/10635/228047
ISSN: 03601323
1873684X
DOI: 10.1016/j.buildenv.2021.108101
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