Accurate thermal parameters of building materials are indispensable in assessing the energy performance and durability of buildings by hygrothermal modeling. The presence of moisture and salt alters the heat and moisture behaviors of the building materials. However, knowledge of their joint influence on the thermal properties of building materials is still limited. This study experimentally investigates the variation in the thermal properties of two types of sintered bricks in the presence of single salts and salt mixtures across the full moisture content range from saturation to dryness. The results confirm that the thermal properties increase with moisture content. The effect of salts on thermal properties is inconsistent in different moisture states. In the dry state, the thermal conductivity and thermal diffusivity of saline bricks increase with increasing salt concentration, while the specific heat capacity decreases. At a moist state, compared to salt-free bricks, the thermal conductivity and specific heat capacity of salted bricks decrease with increasing molarity of salt solutions. Sodium sulfate has a more pronounced influence on the thermal properties than sodium chloride. Finally, the fitting models are proposed to describe the relationships between thermal properties and the moisture and salt content of the bricks. This research is expected to extend the existing dataset and provide precise data for modeling and predicting the energy performance and salt deterioration of the building envelope subjected to salt invasion.

Uncertainty exists in many aspects of building simulation. A deterministic hygrothermal analysis may not sufficiently give a reliable guidance if a number of input variables are subject to uncertainty. In this paper, a probabilistic-based method was developed to evaluate the hygrothermal performance of building components. The approach accounts for the uncertainties from model inputs and propagates them to the outputs through the simulation model, thus it provides a likelihood of performance risk. Latin hypercube sampling technique, incorporated with correlation structure among the inputs, was applied to generate the random samples that follows the intrinsic relations. The performance of an internally insulated masonry wall was evaluated by applying the proposed approach against different criteria. Thermal performance, condensation and mould growth potential of the renovated wall can overall satisfy the requirements stipulated in multifold standards. The most influential inputs were identified by the standardized regression sensitivity analysis and partial correlation technique. Both methods deliver the same key parameters for the single and time-dependent output variables in the case study. The probabilistic method can provide a comprehensive risk analysis and support the decision-maker and engineer in the design and optimization of building components.