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Analysis of moisture risk in internally insulated masonry walls
Abstract Due to the need to preserve the façades of valuable historical buildings, internal thermal insulation is often the only measure for energy retrofitting for such class of buildings. However, internal thermal insulation may lead to moisture damage risks. In this study, the influence of seven parameters, namely water absorption coefficient and diffusion resistance of the exterior render, wind-driven rain load, brick type, masonry structure, thermal insulation type and thermal conductance (U-value), of the internally retrofitted wall on moisture risk is analyzed. Two parameters, water absorption coefficient and wind-driven rain load, have a much larger influence on moisture risk. By comparison, brick type and masonry structure have a very small influence on moisture risk. The influence of U-value on moisture risk is dependent on the insulation system. An artificial neural network (ANN) model is trained based on hygrothermal simulation results. The results predicted by the ANN model are very close to the hygrothermal simulation results. The ANN model enables fast and reliable evaluation of moisture risks. Towards guidelines, the development of an index which would consider jointly render properties and wind-driven rain loads could support a more accurate evaluation of moisture risk in internally insulated masonry walls.
Highlights Hygrothermal modelling is used to assess moisture risk in internally insulated walls. The influence of different parameters on moisture risk is analyzed. An ANN (Artificial neural network) model is trained based on hygrothermal results. The ANN model enables fast and reliable evaluation of moisture risks.
Analysis of moisture risk in internally insulated masonry walls
Abstract Due to the need to preserve the façades of valuable historical buildings, internal thermal insulation is often the only measure for energy retrofitting for such class of buildings. However, internal thermal insulation may lead to moisture damage risks. In this study, the influence of seven parameters, namely water absorption coefficient and diffusion resistance of the exterior render, wind-driven rain load, brick type, masonry structure, thermal insulation type and thermal conductance (U-value), of the internally retrofitted wall on moisture risk is analyzed. Two parameters, water absorption coefficient and wind-driven rain load, have a much larger influence on moisture risk. By comparison, brick type and masonry structure have a very small influence on moisture risk. The influence of U-value on moisture risk is dependent on the insulation system. An artificial neural network (ANN) model is trained based on hygrothermal simulation results. The results predicted by the ANN model are very close to the hygrothermal simulation results. The ANN model enables fast and reliable evaluation of moisture risks. Towards guidelines, the development of an index which would consider jointly render properties and wind-driven rain loads could support a more accurate evaluation of moisture risk in internally insulated masonry walls.
Highlights Hygrothermal modelling is used to assess moisture risk in internally insulated walls. The influence of different parameters on moisture risk is analyzed. An ANN (Artificial neural network) model is trained based on hygrothermal results. The ANN model enables fast and reliable evaluation of moisture risks.
Analysis of moisture risk in internally insulated masonry walls
Zhou, Xiaohai (Autor:in) / Derome, Dominique (Autor:in) / Carmeliet, Jan (Autor:in)
Building and Environment ; 212
26.12.2021
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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|Risk analysis of biodeterioration of wooden beams embedded in internally insulated masonry walls
British Library Online Contents | 2015
|