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    Data from: Climate data processing for the thermal performance analysis of...

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    Updated Jun 13, 2023
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    Giane de Campos Grigoletti; Michelle Gomes Flores; Joaquim Cesar Pizzutti dos Santos (2023). Climate data processing for the thermal performance analysis of buildings in Santa Maria, RS [Dataset]. http://doi.org/10.6084/m9.figshare.20026703.v1
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    jpegAvailable download formats
    Dataset updated
    Jun 13, 2023
    Dataset provided by
    SciELO journals
    Authors
    Giane de Campos Grigoletti; Michelle Gomes Flores; Joaquim Cesar Pizzutti dos Santos
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    State of Rio Grande do Sul, Santa Maria
    Description

    Abstract Processing climatological data and making them available to building designers is of great importance for the thermal performance and energy efficiency of buildings. Test Reference Year, Typical Meteorological Year, bioclimatic chart, EPW and CSV files, wind speed and frequency roses and design day are the most used parameters. Before this study, there was already some systematization of the data available in Santa Maria - RS, however that was for a time range of only eight years. The aim of this study was to process and analyze the climatological data for Santa Maria over a twelve-year period. The method used was based on the scientific literature and followed methods developed and used by Brazilian research groups. The results for Santa Maria show greater discomfort in cold conditions. Direct solar radiation is well distributed throughout the year, indicating the use of passive solar heating in winter and shading in summer. For natural ventilation, the east wind direction should be given preference. The TMY2 file generated in this study is similar to the TRY-INMET (2012), but it presents more significant differences when compared with the SWERA file. The study highlighted the importance of north and northeast orientation for insolation and east direction for natural ventilation. The method presented can be applied in other cities that have available climatological data.

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Click to copy link
Link copied
Close
Cite
Giane de Campos Grigoletti; Michelle Gomes Flores; Joaquim Cesar Pizzutti dos Santos (2023). Climate data processing for the thermal performance analysis of buildings in Santa Maria, RS [Dataset]. http://doi.org/10.6084/m9.figshare.20026703.v1

Data from: Climate data processing for the thermal performance analysis of buildings in Santa Maria, RS

Related Article
Explore at:
jpegAvailable download formats
Dataset updated
Jun 13, 2023
Dataset provided by
SciELO journals
Authors
Giane de Campos Grigoletti; Michelle Gomes Flores; Joaquim Cesar Pizzutti dos Santos
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Area covered
State of Rio Grande do Sul, Santa Maria
Description

Abstract Processing climatological data and making them available to building designers is of great importance for the thermal performance and energy efficiency of buildings. Test Reference Year, Typical Meteorological Year, bioclimatic chart, EPW and CSV files, wind speed and frequency roses and design day are the most used parameters. Before this study, there was already some systematization of the data available in Santa Maria - RS, however that was for a time range of only eight years. The aim of this study was to process and analyze the climatological data for Santa Maria over a twelve-year period. The method used was based on the scientific literature and followed methods developed and used by Brazilian research groups. The results for Santa Maria show greater discomfort in cold conditions. Direct solar radiation is well distributed throughout the year, indicating the use of passive solar heating in winter and shading in summer. For natural ventilation, the east wind direction should be given preference. The TMY2 file generated in this study is similar to the TRY-INMET (2012), but it presents more significant differences when compared with the SWERA file. The study highlighted the importance of north and northeast orientation for insolation and east direction for natural ventilation. The method presented can be applied in other cities that have available climatological data.

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