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Dirty climate data and mould growth in Australian residential buildings

Citation

Su, F and Dewsbury, M and Burnham, R and Fay, R, Dirty climate data and mould growth in Australian residential buildings, The Australian and New Zealand Architectural Science Association Symposium 2 December 2021, 02 December 2021, online (2021) [Conference Extract]


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Official URL: https://anzasca.net/paper/dirty-climate-data-and-m...

Abstract

Introduction

Australia’s current climate datasets were developed for thermal (heating and cooling) building performance simulations during a period where government policy pushed for a reduction of greenhouse gases. These datasets do not include rain as they were not required for thermal simulations. Wind Driven Rain (WDR) is critical in hygrothermal analysis (Salonvaara and Karagiozis 1998), the practitioner is left with a choice; to cobble together a dataset by adding precipitation to the existing climate data or to use one of an assortment of climate datasets available online or through private corporations. Predictably, with this muddy climate data situation, simulation outcomes vary from practitioner to practitioner.

Methods

WUFI Pro 6.5 is an internationally recognised hygrothermal simulation application and will be used to simulate hygrothermal behaviour and moisture content in interstitial spaces.

Melbourne Tullamarine was chosen for its rich precipitation data owing to its proximity to an international airport. The wall assembly is precast concrete. A typical Class 2 apartment building construction.

Using RMY, simulate hygrothermal behaviour and mould growth with two datasets:

    • RMY with no alterations
    • RMY with added rain data

Results

The results show a similarity in moisture content that was not expected.

Conclusion

Climate data is concatenated from a period of historical weather observations. The current Representative Meteorological Year (RMY) is produced following the procedure for the generation of the Typical Meteorological Year (TMY2) using the Finkelstein–Schafer statistic on weighting factor on data fields (Lee n.d.) from a period of record between 1970 – 2005. The weighting factors for RMY were chosen for thermal simulations, and as such, the dataset is thermally selected with an emphasis on temperature and solar radiation and do not include rain data.

Are these thermally selected climate datasets producing realistic hygrothermal simulation outcomes?

Future research will scrutinise how other jurisdictions constructed their climate files for hygrothermal analysis and formulate experiments to test their methodology using Australian climate and weather data

Item Details

Item Type:Conference Extract
Keywords:clmate change, climate data, hygrothermal, simulation, building physics
Research Division:Built Environment and Design
Research Group:Architecture
Research Field:Architectural science and technology
Objective Division:Construction
Objective Group:Construction design
Objective Field:Residential construction design
UTAS Author:Su, F ( Freya Su)
UTAS Author:Dewsbury, M (Dr Mark Dewsbury)
UTAS Author:Burnham, R (Dr Richard Burnham)
UTAS Author:Fay, R (Professor Roger Fay)
ID Code:148106
Year Published:2021
Deposited By:Architecture and Design
Deposited On:2021-12-03
Last Modified:2021-12-08
Downloads:0

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