The non-destructive thermal characterization of building envelopes relies significantly on various factors such as climate conditions, monitoring devices used, indoor environment, and conditioning systems. In the case of both the temperature-based method (TBM) and heat flux meter (HFM) approaches, U-value is determined considering the ideal condition of steady state. However, it is challenging to accurately define the true thermal condition of buildings when monitoring is affected by inherent uncertainties of the chosen approach and inadequate instrumentation of building envelopes. This paper presents the outcomes of an experimental campaign, that aimed to evaluate the impact of incorrectly positioned exterior sensors, on the precision of U-value measurements. This study simultaneously employed the TBM and HFM approaches. To enhance the accuracy of the results, rigorous outlier detection and statistical analysis were employed on the data collected from three autonomous monitoring systems. The findings of this study revealed that the applied data analysis yielded more satisfactory results for the TBM approach compared to HFM. However, regardless of the approach used, the effectiveness of outlier detection relied heavily on the accuracy of the monitoring systems. When removing an individual outlier, the monitoring systems characterized with higher accuracies provided U-values that were closer to the theoretical values, than less accurate ones.

In this paper, we define the hygrothermal properties of a rammed earth wall through experimental analysis, relating thermal parameters to moisture content. These tests were conducted in Campo de Criptana (Ciudad Real, Spain), and the wall examined in this study is a 70-cm-thick north-facing rammed earth wall that is part of an occupied traditional dwelling Ambient and surface temperature and humidity values were monitored, along with the temperature and humidity at several points inside the wall and the heat flux on both sides of the wall. We recorded the wall’s behaviour regarding ambient comfort conditions for one year and obtained transmittance and conductivity values. Results show that it is quite difficult to analyse the hygrothermal behaviour of a rammed earth wall throughout the year, since the properties of the wall vary enormously. We found that, to evaluate the thermal behaviour of the wall, it was not appropriate to consider the same conductivity value for whole sections of the wall, as this value varies according to moisture content (generally between 0.39 and 0.55 Wm⁻¹ K⁻¹): we propose seasonal values for conductivity. Finally, the hygrothermal stability that these structures provide to the spaces they enclose has been shown, especially during hot and dry periods.

This paper describes the influence of thermal parameters—conductivity, transmittance, and thermal mass—in the estimation of comfort and energy demand of a building with rammed earth walls, and consequently, the compliance with standards. It is known that nominal design data does not match in situ measured values, especially in traditionally constructed buildings. We have therefore monitored a room in a building with rammed earth walls, designed a computerised model, and compared four different alternatives where we have changed the value for the thermal conductivity (in situ vs. estimated) and the consideration of thermal mass. When we then analyse the compliance with the Spanish energy saving code, using measured values would result in lower differences with the standards’ limits and even comply with the global thermal transmittance (K-value) requirement. This would mean a more realistic approach to the restoration of traditional buildings leading to the use of thinner and more suitable insulation and retrofitting systems, encouraging the use of rammed earth in new buildings, and therefore reducing the carbon footprint due to materials used in construction. Results show that the building model that uses in situ values and considers thermal mass (S1) is closer to reality when assessing thermal comfort. Finally, using nominal data would result in requiring 43% more energy in the selected winter period and 102% more energy in the selected summer period to keep the same comfort conditions as in the alternative where measured values are used.