UCL Energy Institute


Research Methods and Analysis

The PCB group research addresses the in-situ thermal performance of buildings, their components and systems. We use a variety of methods and analysis techniques, key examples of which are outlined below. The group is also able to provide consultancy services on a range of topics, including but not limited to those outlined below. Please contact us <link to contacts section, below> to discuss your needs.


Heat loss and energy use:

  • Co-heating test: A coheating test is a method to measure the quasi-steady state whole house heat loss coefficient of a building (in W/K) using electrical resistance heating. Members of the PCB group have extensive experience in the measurement and analysis of building heat loss using the co-heating methodology.
  • In-situ U-value measurement: U-values are a measure of the heat transfer coefficient (in W/m2K) of a building element such as a wall, roof or floor, and are normally measured using a combination of heat flux and temperature sensors. The PCB group has a range of capabilities with respect to in-situ U-value measurement using Hukselfux HFP01 heat flux sensors, and has developed novel methodologies using Bayesian analysis that reduce measurement error, cut the length of measurement times from several weeks to just a few days, and extend the monitoring to non-winter periods.

Monitoring of energy use, controls and environmental conditions in buildings: Members of the PCB group have extensive experience of the monitoring of energy use in buildings, the measurement of important environmental variables such as internal and external

Analysis techniques

The analysis methods we apply are generally characterised by a physically informed approach, seeking to derive insights into the physical performance of buildings and relate this to construction methods and quality, the performance of the system and its usage patterns, and potential interventions to improve either the performance of the system as built or the construction process.

We pay particular attention to the robustness of the data analysis we undertake and the methods we apply. We use statistical techniques to quantify the error and uncertainties associated to our analyses. We apply a range of statistical methods to estimate the performance of the system under investigation, for example using Bayesian methods for inverse modelling.