A probabilistic approach to moisture risk assessment for internal wall insulation
EngD research conducted by Valentina Marinicioni
The UK has pledged to reduce its carbon emissions by 80% by 2050. This translates into reducing the energy consumption of the existing building stock, one of the least efficient in Europe and responsible for nearly a quarter of UK’s carbon emissions. Improving the energy efficiency of solid wall buildings requires the use of challenging measures such as internal wall insulation, which – if incorrectly designed and installed – can lead to moisture accumulation and mould growth at the interface between the insulation and the existing wall. Consequently, a thorough moisture risk assessment is a key part of the design and specification process for internal wall insulation. This project aims at developing a framework for the probabilistic moisture risk assessment of internal wall insulation.
The framework includes (i) the selection of suitable mould growth risk criteria, (ii) the use of space-filling sampling schemes for probabilistic risk assessment, and (iii) the evaluation of metamodeling techniques for the development of faster surrogate models, considering their accuracy and influence on the user experience. This framework will constitute the foundation of a risk-based decision-making tool, which could inform designers and architects during the developed and technical design stages of retrofit projects.