For Heat, Air and Moisture modelling, one of the most crucial hygrothermal properties of porous construction materials is the sorption isotherm. Current techniques for measuring the sorption isotherm rely on the standardized Saturated Salt Solution (SSS) method which is known to be time consuming. Recently, a device called Dynamic Vapor Sorption was applied on building materials allowing faster measurements but limiting the mass and volume of the sample. As this technique is not yet standardized, an experimental procedure was developed and validated on barley straw. Results were also in good agreement with the measurements from the SSS technique.

Nowadays, humidity in buildings has become a major concern because it affects their energy performance, the occupants' comfort and health, and the durability of materials simultaneously. To understand the behavior of buildings towards humidity, numerical models are needed. However, the sensitivity of these models to the indoor sources, especially the ones related to the occupants' presence and activities, has not been thoroughly assessed in the literature. This article proposes to introduce a methodology to investigate the impact of the occupancy profiles of presence on the hygrothermal performance of a room. A hygrothermal model at room scale is developed and coupled with a platform called No-MASS, which provides stochastic occupancy scenarios for office buildings. Four occupancy scenarios representative of the scenarios commonly found in the literature are studied: a stochastic scenario, an average scenario derived from multiple stochastic ones, a constant scenario, and the French regulatory scenario. Comparing the results obtained with the different occupancy scenarios underlined a non-negligible impact of the scenario on indoor heat and moisture balance, mainly due to the consideration of a seasonal effect for the stochastic one.

Due to the environmental impact of building materials, researches on sustainable materials, such as bio-based and earth materials, are now widespread. These materials offer numerous qualities such as their availability, recyclability and their ability to dampen the indoor relative humidity variations due to their hygroscopicity. As these materials can absorb large amount of humidity, numerical and experimental studies of their hygrothermal behaviour are crucial to assess their durability. To validate a hygrothermal model, numerical and experimental data have to be confronted. Such confrontation must take into consideration the uncertainties related to the experimental protocol, but also to the model. Statistical tools such as uncertainty and global sensitivity analysis are essential for this task. The uncertainty analysis estimates the robustness of the model, while the global sensitivity analysis identifies the most influential input(s) responsible for this robustness. However, these methods are not commonly used because of the complexity of hygrothermal models, and therefore the prohibitive simulation cost. This study presents a methodology for comparing the numerical and experimental data of a rammed earth wall subjected to varying temperature and relative humidity conditions. The main objectives are the investigation of the uncertainties impact, the estimation of the model robustness, and finally the identification of the input(s) responsible for the discrepancies between numerical and experimental data. To do so, a recent and low-cost global variance-based sensitivity method, named RBD-FAST, is applied. First, the uncertainty propagation through the model is calculated, then the sensitivity indices are estimated. They represent the part of the output variability related to each input variability. The output of interest is the vapour pressure in the middle of the wall to confront it to the experimental measurement. Good agreement is obtained between the experimental and numerical results. It is also highlighted that the sorption isotherm is the main factor influencing the vapour pressure in the material.