E3S Web Conf.
Volume 172, 202012th Nordic Symposium on Building Physics (NSB 2020)
|Number of page(s)||6|
|Section||Moisture performance of structures|
|Published online||30 June 2020|
Sensitivity of the hygrothermal behaviour of homogeneous masonry constructions: from Sobol indices to decision trees
Ghent University, Building Physics group, 9000 Ghent, Belgium
* Corresponding author: Klaas.Calle@UGent.be
Historic masonry constructions are difficult to mimic in hygrothermal models. Next to the usual uncertainties on the input of hygrothermal models as the outdoor/indoor climate also the properties of the wall themselves are often highly uncertain due to the natural origin of the aggregates and the various, manual production processes used through time. Therefore, this paper presents a probabilistic analysis that indicates the sensitivity of several damage criteria which are often encountered in practice such as mould growth at the interior surface, frost damage, and potential decay of wooden beam heads. The analysis is based on 1D simulations, including realistic variations on climate parameters as wall properties. With Kriging based surrogate modelling the output of the probabilistic simulations is translated into sensitivity indices, Total Sobol indices. These indices summarize the dependency of the damage criteria for each of the input parameters including multi order effects. The Total Sobol indices indicate a generally 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. Based on the probabilistic output binary flowcharts are generated to indicate for which combinations of input parameters high risks are to be expected. These binary flowcharts can be adopted by e.g. engineering firms to define whether, a more detailed assessment is required, and which input are necessary. This indicates when basic in situ assessments of the hygrothermal properties of the facade can suffice.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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