Air leakage in Catalan dwellings: Developing an airtightness model and leakage airflow predictions

In this study we estimate the air leakage distribution of single-family dwellings in Catalonia and use a statistical analysis of an airtightness database for single-family dwellings in France to identify the building characteristics that have the greatest influence on airtightness. The most signific...

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Detalles Bibliográficos
Autores: Montoya Rodríguez, María Isabel, Pastor Ferrer, Elsa|||0000-0002-2985-3635, Carrié Rémi, F., Guyot, Gaelle, Planas Cuchi, Eulàlia|||0000-0002-7053-3959
Tipo de recurso: artículo
Fecha de publicación:2009
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/7179
Acceso en línea:https://hdl.handle.net/2117/7179
https://dx.doi.org/10.1016/j.buildenv.2009.12.009
Access Level:acceso abierto
Palabra clave:Aire -- Mesurament
Aire -- Contaminació
Cases unifamiliars
Edificis -- Estructures
Àrees temàtiques de la UPC::Enginyeria química::Impacte ambiental
Descripción
Sumario:In this study we estimate the air leakage distribution of single-family dwellings in Catalonia and use a statistical analysis of an airtightness database for single-family dwellings in France to identify the building characteristics that have the greatest influence on airtightness. The most significant variables are found to be the structure type, the floor area, the age of the building, the number of stories and the insulation type. A multiple linear regression technique is then applied to establish a predictive model for deriving an estimated value of airtightness from these characteristics. To estimate the infiltration airflow, a stochastic simulation of the building characteristics was performed per census tract using real data on the distributions of building variables taken from the census information. The model is then applied to determine the power law coefficient and the airtightness distribution. The predicted flow coefficients are combined with the AIM-2 model and given meteorological conditions to determine the infiltration airflow. Two sets of meteorological conditions are considered: average conditions and extreme conditions for each season.