Inferring the thermal resistance and effective thermal mass of a wall using frequent temperature and heat flux measurements

• Published in: Energy and buildings 2014-08, Vol.78, p.10-16
• Main Authors: Biddulph, Phillip, Gori, Virginia, Elwell, Clifford A., Scott, Cameron, Rye, Caroline, Lowe, Robert, Oreszczyn, Tadj
• Format: Article
• Language: English
• Subjects: Applied sciences; Bayesian Statistics; Buildings; Buildings. Public works; Computation methods. Tables. Charts; Exact sciences and technology; External envelopes; External wall; Heat Transfer; In-situ Measurements; Measurements. Technique of testing; R-value; Structural analysis. Stresses; Thermal Mass; U-Value; Wall. Partition
• ISSN: 0378-7788
• DOI: 10.1016/j.enbuild.2014.04.004

•We analysed in-situ thermal measurements of a wall to derive its U-value.•A new analysis technique is quicker by a factor of 3 over traditional methods.•U-values calculated using the new technique match those from conventional methods.•U-values are smaller than expected from direct calculations using assumptions.•Wind and moisture are important contributions to the variance in the results. Evaluating how much heat is lost through external walls is a key requirement for building energy simulators and is necessary for quality assurance and successful decision making in policy making and building design, construction and refurbishment. Heat loss can be estimated using the temperature differences between the inside and outside air and an estimate of the thermal transmittance (U-value) of the wall. Unfortunately the actual U-value may be different from those values obtained using assumptions about the materials, their properties and the structure of the wall after a cursory visual inspection. In-situ monitoring using thermometers and heat flux plates enables more accurate characterisation of the thermal properties of walls in their context. However, standard practices require that the measurements are carried out in winter over a two-week period to significantly reduce the dynamic effects of the wall's thermal mass from the data. A novel combination of a lumped thermal mass model, together with Bayesian statistical analysis is presented to derive estimates of the U-value and effective thermal mass. The method needs only a few days of measurements, provides an estimate of the effective thermal mass and could potentially be used in summer.