Improving and Demonstrating the Accuracy and Precision of the QUB Method

The performance of building fabric is a critical component in the complex problem of heat decarbonisation. However, a growing body of evidence has shown that there is often a difference between the measured performance of building fabric and its predicted or design performance. This phenomenon is known as the performance gap. Awareness of the performance gap has popularised the concept of measuring fabric performance. This can be characterised by the U-values of individual fabric elements or the HTC (Heat Transfer Coefficient) that describes the whole house fabric performance. HTC measurements are commonly used to evaluate any performance gap. The current standardised method for HTC measurement, coheating, is extremely disruptive as it is required that a home is empty for 15 days or more for steady state conditions to be maintained within the property. As such, coheating can be considered unsuitable for uses outside of research. The QUB method is a dynamic method of HTC and U-value measurement that is completed within a single night. Owing to its short duration the QUB method could potentially be used in mainstream applications such as new build housing and retrofit where a coheating test would not be feasible. This research aims to improve and demonstrate the accuracy (closeness to true value) and precision (dispersion of repeat measurements) of the QUB method. This will identify where the method can be deployed to give informative measurements and its limitations. A method consisting of six field-based case studies was deployed in which repeated QUB measurements were completed and compared to reference HTC and U-value values to determine the accuracy and precision of the measurements. This revealed that variations in test conditions were impacting the dispersion of results and negatively affecting accuracy and precision. These included variability of the temperature ratios in unconditioned spaces, transient thermal mass effects introduced by solar radiation and changes in external temperature, and wind conditions impacting heat transfer. Where observed, this impact is linked to select building characteristics. Consequently, houses with minimal areas of indirect heat loss, insulated building fabric and not of a characteristically high thermal mass often resulted in highest levels of accuracy and precision in QUB measurements. From the results of the case studies, indicative values of accuracy and precision for the QUB HTC measurements were derived based on the building characteristics of the test homes. For homes with characteristics associated with high accuracy and precision the following levels of accuracy and precision are expected: root mean squared error (RMSE) ≤ 15 %, mean bias error (MBE) ≤ |13| %, relative range ≤ 19 % and standard deviation ≤ 7 %. For homes with characteristics associated with low accuracy and precision the equivalent metrics are RMSE ≤ 34 %, MBE ≤ |34| %, relative range ≤ 55 % and standard deviation ≤ 16 %. These values can be used by those conducting QUB HTC measurements to determine the suitability for an application and to provide context on the measurement result. The level of accuracy seen in the QUB U-value measurements was notably lower than that seen in existing work. The reasons for this could not be determined. A novel approach for adjusting HTC measurements for indirect heat loss through unconditioned spaces was proposed. This was done through use of additional temperature and heat flux density measurements and was shown to improve the accuracy and precision of measurements in all applicable instances. However, this practice may, in turn, affect the suitable use cases for the measurement. Future work should consider how these adjustments are communicated in the most understandable way. This study has demonstrated the accuracy and precision of the QUB test in a discrete number of real-world case studies. Whilst limitations of the QUB test are highlighted, its potential to give informative evaluations of building fabric performance are evident. Future work should conduct multiple QUB tests over a duration of close to one year to better understand the impact of changing test conditions. Additionally, the measurements completed in this study could be combined with data from other projects to enable an evaluation of accuracy and precision against a wider range of building characteristics. This will further the understanding gained from this study and give findings that can be generalised across the building stock.<p></p>