Abstract
The estimation of the thermophysical characteristics of building elements based on in situ monitoring enables their performance to be assessed for quality assurance and successful decision making in policy making, building design, construction and refurbishment. Two physically-informed lumped thermal mass models, together with Bayesian statistical analysis of temperature and heat flow measurements, are presented to derive estimates of the thermophysical properties of a wall. The development of a two thermal mass, three thermal resistance model (2TM) enabled the thermal structure of the wall to be investigated and related to the known physical structure of two heavy-weight walls of different construction: a solid brick wall and an aerated clay, plaster, woodfibre insulation and gypsum fibreboard wall. The 2TM model produced good match to the measured heat flux at both interior and exterior surfaces for both walls, unlike a one thermal mass model (1TM); Bayesian model comparison strongly supported the 2TM over the 1TM model to accurately describe the observed data. Characterisation of the thermal structure and performance of building elements prior to decision making in interventions will support the development of tailored solutions to maximise thermal comfort and minimise energy use through insulation, heating and cooling strategies.
Highlights
The thermophysical properties of the building envelope have been identified as key parameters in the determination and explanation of the energy performance of buildings and are widely used in models to predict the energy demand of the built stock [1,2,3]
This paper presents the development of a dynamic inverse greybox method of estimating effective thermal mass, U-values and R-values, building on that presented in Biddulph et al [13]
The characteristics of the effective thermal mass estimated by the 1TM model using only the internal heat flux measurements are dominated by the material in close proximity to the heat flux plates (HFP) [13] rather than those on the exterior side of the fibreboard insulation
Summary
The thermophysical properties of the building envelope have been identified as key parameters in the determination and explanation of the energy performance of buildings and are widely used in models to predict the energy demand of the built stock [1,2,3]. The method uses lumped thermal mass models to describe the heat transfer across the building element and Bayesian-based optimisation techniques to estimate the best set of model parameters, and includes detailed error analysis. This statistical framework provides the most probable value for the parameters, an estimate of their uncertainties, their probability distribution and correlations [13]. The lumped thermal mass models adopted here enable the estimation of parameters with clear physical interpretation (e.g., R-value and effective thermal mass), which can be subsequently used to gain useful insights into the thermophysical behaviour of the building and how this may be improved. This method does not require that the models tested are nested
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