An in situ estimation of the thermal properties of bio-sourced building wall insulation components is of critical importance in improving both the energy efficiency of buildings and the development of construction materials with a smaller environmental footprint. Depending on weather conditions, passive methods are not always feasible; they require time to conduct lengthy testing and may lead to significant uncertainties. This article presents an active method based on power dissipation via flat electrical resistance. The method can be implemented regardless of outdoor weather conditions and is suitable for walls with high overall thermal resistance for which the small average component of the through flow is difficult to estimate. Measurements are conducted of both wall input flows and temperatures. An inverse method, derived from a finite difference model of 1D transfers along with a multi-objective approach, enables the characteristics of a two-material assembly to be identified. A multi-objective method was chosen to solve the problems of high correlation between the thermal parameters of the model. However, the method requires the use of two temperature sensors integrated inside the wall. Following a laboratory validation phase on a PVC/plasterboard assembly, the method is implemented on an actual wall. A coating/hemp concrete assembly is also characterized as part of this work program. The thermal conductivity of the hemp concrete block was estimated at 0.12 W m−1 K−1 and is consistent with values found in the literature.

This article presents an active method of building walls thermal characterization. A thermal stimulation is applied by a heating blanket on one side of the wall. Temperatures and injected heat flux evolutions are recorded by a data logger on the front face and the temperature by an infrared camera on the back face. Those signals are then processed by an inverse method which allows the determination of the thermal conductivity and the specific heat of each wall layers as well as the Newton's coefficient, knowing their thicknesses. Different types of stimulation waveforms are tested and the associated uncertainties are determined.