Probabilistic hygrothermal assessment of various timber frame wall compositions

The market share of timber-based buildings is growing in Europe, due to their advantages concerning CO2 emissions and embodied energy. Regrettably, timber frame constructions are susceptible to moisture damage, and their proper design is thus crucial, with specific emphasis on the ratio of the vapour diffusion resistances of the weather barrier and vapour barrier. While some rules-of-thumb are available, these commonly do not consider climatic aspects nor moisture buffering, and hence do not guarantee optimal solutions. This study targets general guidelines, for various European climates and wall compositions. As this requires numerous simulations, a convolutional neural network is applied, performing over 135,000 simulations, covering 96 wall compositions and 54 European climates. The walls' performance is evaluated via mould index and condensation amount. The results reveal that defining one single criterium to avoid moisture damage is impossible and hence that climate-specific guidelines are needed. It is also noticed that moisture buffering plays an important role in avoiding condensation run-off, much more than the vapour diffusion resistances of weather and vapour barriers. Finally a matrix is defined with the criteria to avoid moisture damage, depending on climatic conditions and wall composition. The key result is that either the insulation material or the weather barrier must provide moisture buffering. Furthermore, each climatic condition and cladding type yields a different criterion for the required vapour diffusion resistances of weather and vapour barriers.

Automated summary

The market share of timber-based buildings is increasing in Europe due to their advantages in CO2 emissions and embodied energy. However, these constructions are prone to moisture damage, making proper design crucial. This study aims to provide general guidelines for different European climates and wall compositions by utilizing a convolutional neural network to simulate and evaluate over 135,000 scenarios. The results highlight the importance of climate-specific guidelines and the role of moisture buffering in preventing condensation.