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Convective heat transfer in green façade system

handle: 11586/248058
Green facades are passive living technologies applied to buildings. They produce many advantages for human wellbeing, building performance, and city environments. Knowledge of the energy behaviour of green facade systems is needed to inform their best design and application, and to define their energy performances. Heat and mass exchanges between the system and the surrounding environment must be determined. In this paper, the schematisation of the green facade system into layers and the energy balance approach are proposed. This study focuses on the analysis of the convective heat transfer occurring between the plant layer and the external air. It is difficult to realistically describe this mechanism and many approaches in the literature were considered. Six different formulae were evaluated. Mathematical modelling and empirical data were both used. Once it was discovered that forced convection was the prevailing convective type, selected formulae were applied to the data, which were collected from an experimental green facade at the University of Bari. Based on the energy balance of the plant layer, a comparison between the calculated and measured values was carried out. Qualitative and quantitative statistical methods were used to assess the goodness-of-fit of the considered convective models. These analyses suggest the least and the most suitable approaches for convective heat transfer evaluation. The empirical equation of Morrison and Barfield and an adaptation to green facades of Deardorff model showed the best agreement. This study could be extended in order to write codes for building energy simulation software.
690, Passive system, Green infrastructure, Energy balance, Modelling, Convective coefficient, Green layer
690, Passive system, Green infrastructure, Energy balance, Modelling, Convective coefficient, Green layer
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).25 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
