Establishing material hygrothermal characteristics via long-term monitoring and best-fit numerical models

Abstract

Numerical models of heat and moisture transfer for performance forecast of lightweight insulating assemblies require many inputs. These include exterior climate data (i.e. temperature, relative humidity, solar radiation), interior climate data or standard models, transfer coefficients, correct initial conditions, etc. Most importantly, one needs reliable material models. A material model includes porosity, density, heat capacity, but also non-constant properties, such as thermal conductivity, vapor/liquid water diffusivity, sorption curves. These are, in general, difficult to determine, and material database entries often are incomplete, or simply non-existent. However, if one performs long-term monitoring of temperature and relative humidity dynamics within building envelopes, there is a way to determine hygrothermal curves and properties of the underlying materials. This can be done by performing simulations and finding the set of optimal hygrothermal curves and coefficients such that the experimental data is matched sufficiently well. Despite the appeal, this best-fit model approach is fraught with perils due to many unknowns and must be used carefully. In this article, we demonstrate the application of this method to insulating assemblies for which 6+ years' worth of experimental data is available, and showcase our results obtained using WUFI Pro 6.3 and the derived and verified material models.