Airtightness evaluation of Canadian dwellings and influencing factors based on measured data and predictive models

Abstract

The airtightness of buildings has a significant impact on buildings’ energy efficiency, maintenance and occupant comfort. The main goal of this study is to provide an evaluation of the air leakage characteristics of dwellings in different regions in Canada. This study evaluated the key influencing factors on airtightness performance based on a large set of measured data (73,450 dwellings located in Canada with 11 measurement parameters for each). Machine learning models based on multivariate regression (MVR) and Random Forest Ensemble (RFE) were developed to predict the air leakage value. The RFE model, which shows better results than MVR, was used to evaluate the effect of the ageing of buildings. Results showed that the maximum increase in air leakage occurs during the first year after construction – approximately 25%, and then 3.7% in the second year, after which the increase rate becomes insignificant and relatively constant – approximately 0.3% per year. The findings from this study can provide significant information for building designs, building performance simulations and strengthening standards and guidelines policies on indoor environmental quality.

Thermal Loads Map and Overall Energy Analysis Depending on Low-Effort Parameters Change: A Commercial Building Case Study

“…The same outcome occurred for the non-residential building studied in [9], where the larger thickness of the insulating material entailed a larger reduction in the energy demand. The air infiltration also had a considerable effect on energy consumption and internal comfort, as demonstrated for several Canadian dwellings, and a model based on the machine learning approach has been proposed to support new building designs [10]. The same findings were discussed in [11], where the energy load for the heating season decreased with the increase in the airtightness, regardless of the wall composition.…”