Jangra, Suneina; (2022) Estimating the thermal performance of insulated cold-pitched roofs from in-situ measurements and surveys. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

Loft insulation is one of the most common household energy efficiency upgrades in the UK, yet there is a scarcity of in-situ data evidencing the thermal performance of insulated roofs in real houses. Such data is vital in characterising the thermal performance of the wider housing stock and improving the accuracy of energy-use estimates included in modelling tools which are used to inform government policy aimed at reducing carbon emissions in this sector. Motivated by this gap in knowledge, this research aims to gather insitu data in a sample of case study roofs in order to quantify the potential ‘building fabric thermal performance gap’ associated with residential cold-pitched roofs. The research also aims to investigate the range of issues which may influence a performance gap; including variability in weather conditions, installation issues and the functional complexity of lofts which often house building services and may be accessed by occupants for storage. In-situ data from four case study houses with cold-pitched roofs is therefore used to estimate localised and area weighted in-situ ceiling and roof U-values. In addition to quantitative measurements, visual inspections and thermal imaging surveys were conducted to investigate the installation and condition of the loft insulation in the case studies. The results suggest that the in-situ thermal performance of the case study roofs is better than expected and this positive building fabric thermal performance gap is expected to be a consequence of convective and radiative heat flows in the loft void. If such a performance gap exists in the wider stock, the expected energy and cost savings associated with the installation of additional loft insulation may not be realised, making it harder for the UK to achieve its carbon emissions targets. The second key aim of this thesis is to trial a dynamic probabilistic method combining a lumped parameter model and Bayesian optimisation for estimating in-situ U-values. The dynamic approach which quantifies the thermal mass of the element can incorporate the effects of solar gains and has been shown to reduce the amount of data required to estimate Uvalues for wall elements. For a typical ceiling or roof, the thermal mass of the element is low and there is a functional complexity associated with the presence of a large void in the roof. A collection of lumped parameter models are trialled, including models which incorporate an additional heat input to account for solar gains on the surface of the roof. The results suggest that a simple model with a single effective thermal mass can sufficiently characterise the heat transfer through a roof, producing physically reasonable parameter estimates and sensible in-situ U-value estimates; in some cases, where the conventional steadystate average method failed. The models incorporating solar gains were of limited value in this research; however, this is expected to be due to the low solar gains observed during the data collection period. Further testing of the solar models with additional datasets is therefore recommended as well as refinement of the 1C2R model so that the model is able to identify each of the parameters independently, thereby improving the statistical significance of the results.

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