Previous studies show that climate change has an impact on the damage risks in solid masonry facades. To conserve these valuable buildings, it is important to determine the projected change in damages for the original and internally insulated cases. Since historical masonry covers a wide range of properties, it is unknown how sensitive the climate change impact is to variations in different parameters, such as wall thickness, brick type, etc. A factorial study is performed to determine the climate change impact on freeze-thaw risk, mould growth and wood decay in solid masonry in Brussels, Belgium. It is found that the critical orientation equals the critical wind-driven rain orientation and does not change over time. Further, the freeze-thaw risk is generally decreasing, whereas the change in mould growth and wood decay depends on the climate scenario. Knowing the brick type and rain exposure coefficient is most important when assessing the climate change impact. For freeze-thaw risk and wood decay, it is found that simulating one wall thickness for the uninsulated and one insulated case is sufficient to represent the climate change impact. Finally, the effects of climate change generally do not compensate for the increase in damage after the application of internal insulation.

Historical masonry constructions are difficult to mimic in hygrothermal models. The material properties of the walls are often highly uncertain due to the natural origin of the aggregates and the various, manual production processes used through time. Therefore, sensitivity analyses based on probabilistic simulations are powerful tools to indicate the risks on damage in masonry constructions. Damage criteria for relevant pathologies such as frost damage, potential decay of wooden beam heads and mould growth at the interior surface are used. The assessment methods (Scatter plots, Classification trees and Sobol indices) are based on 1D Heat, Air and Moisture simulations, including realistic variations on climate parameters and wall properties. These methodologies are applied to probabilistic simulations in which a potential damage risk is expected in historic masonries. The application of interior insulation, the use of hydrophobic treatments, and the impact of potential water infiltrations through cracks are discussed. In most of these situations a high dependency of each of the damage criteria on the rain intensity, the trend of the moisture retention/liquid conductivity curve and the absorption coefficient is evident, but also additional insights are found. For example, the thermal impact of interior insulation is negligible compared to its reduction of the first phase drying potential towards the interior. For hydrophobic treatments, the risk for damage typically decreases, but in combination with a rain water infiltration rate above approximately 5% of the wind driven rain the risk on mould growth at the interior surface significantly increases.

Historic masonry has a rich and colorful history making it a treasured part in our society. To preserve and protect this heritage, adequate moisture control, retrofit, and restauration strategies are required. However, due to the large range of material properties inherent to historic brickwork, a single uniform renovation strategy appears impossible. To describe similarity in brickwork, the existing clustering approach developed by Zhao was evaluated. The idea is that different types of bricks with similar properties can be represented by a single representative brick for that cluster, for example, when conducting hygrothermal simulations. It could help improve existing retrofit practice by reducing characterization processes and minimizing time-consuming laboratory measuring tests. However, in this paper the approach presented by Zhao is questioned since the clustering is solely based on an equal impact of the material properties and the response behavior and associated degradation risks are neglected. The aim of this paper was twofold. Firstly, similarity in brickwork obtained by clustering according to Zhao was evaluated by means of hygrothermal simulations to see whether bricks in the same cluster show similar degradation risks. Zhao’s clustering provides homogenous clusters regarding physical material properties, but significant variation was found in degradation risks for different bricks within the same cluster. Secondly, a methodology is presented to translate similarities in degradation profiles toward similarities in material properties. Sensitivity analyses were used to study the response behavior based on three degradations risks: mold growth, wood rot, and frost damage. Finally, an overall clustering scheme was generated for brickwork, based on classification trees for different degradation phenomena.