Measurement of low-thermal effusivity of building materials using thermal impedance method

Thermal impedance is a way of defining the characteristics of thermal systems. It is a function that represents the relation between the frequency components of temperature and the flux density in a plane for each frequency. Up to now, its use has been restricted to one-directional conductive systems. From the experimental point of view, it is determined simply by measuring the flux density and temperature simultaneously in a measurement plane. In practice, a fluxmeter in which a thermocouple has been placed is put in contact with the sample. The changes in flux density and temperature measured in this way are different from those in the material access plane. The reasons for this perturbation are the presence of the sensor and the sensor/material contact resistance. In the case of slow changes, due, for example, to micro-climatic variations or day/night stresses of the order of 10-5 or 10-4 Hz, this perturbation is negligible. Studies in these frequency ranges have been exploited in several works. In the present study, we show that it is possible to use thermal impedance as a way of characterizing thermal systems for higher frequencies, taking into account the perturbation created by the measuring instruments. By means of a sensitivity study, we demonstrate several cases linked with the nature of the test material. A frequency range is determined where the perturbation due to the measuring instruments is not too great, allowing the materials to be characterized. Several common construction materials are studied. Particular emphasis was laid in this work on characterizing insulating materials, which are hard to study in variable conditions. The tests discussed in this article were performed in the laboratory in ambient temperature conditions close to 20 °C. The pseudo-random stresses were generated artificially. Series of 100 tests were run for each material. They led to the determination of thermal effusivity with less than 5% error. The method gives results that are reproducible and can be validated by simulation.