No abstract

The thermal characterisation of a building envelope is usually best performed from on-site measurements with optimised controlled indoor conditions. Conversely, occupant-friendly measurement conditions provide less informative data. Notwithstanding occupancy, the boundary conditions alone contribute to a greater extent to the energy balance, which implies that non-intrusive conditions bring into question the reproducibility and relevance of such measurement. This paper proposes an original numerical methodology to assess the reproducibility and accuracy of the estimation of the overall thermal resistance of an envelope under variable weather conditions. A comprehensive building energy model serves as reference model to produce synthetic data mimicking non-intrusive conditions, each with a different weather dataset. An appropriate model is calibrated from the synthetic data and provides a thermal resistance estimate. The accuracy of the estimates is then assessed in light of the particular weather conditions used for data generation. The originality also lies in the set of weather data that allow for uncertainty and global sensitivity analyses of all estimates with respect to six weather variables. The methodology is applied to a one-storey house reference model, for which thermal resistance is inferred from calibrated RC models. Robust estimations are achieved within 11 days. The outdoor temperature and the wind speed are highly influential because of the large air change rate in the case study.

Verification of the actual thermal performance of a building envelope after renovation is likely to become a useful key for performance contracting in the frame of heavy retrofit operations in buildings. Some existing methods such as the co-heating method, use on-site measurements to estimate the Heat Transfer Coefficient, or its inverse the overall thermal resistance. Although reliable and accurate, they need several days to several weeks of undisturbed measurements which can be rather inconvenient for building occupants and quite expensive in terms of operational costs. This paper investigates perturbation methods to design a 24-h heat input signal that would ensure an accuracy similar to or better than other perturbation methods to estimate an overall thermal resistance of the building envelope. The paper first studies 256 different squared heating signals in a numerical methodology to determine common characteristics of high-scoring 24-h signals. An experimental campaign in a wooden-framed house tested one of the high-scoring signals. The experimental results showed estimation errors higher than expected but consistent with the literature.