Issue |
E3S Web Conf.
Volume 172, 2020
12th Nordic Symposium on Building Physics (NSB 2020)
|
|
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Article Number | 17004 | |
Number of page(s) | 7 | |
Section | Moisture measurements | |
DOI | https://doi.org/10.1051/e3sconf/202017217004 | |
Published online | 30 June 2020 |
Uncertainty and sensitivity analysis applied to a rammed earth wall: evaluation of the discrepancies between experimental and numerical data
1 LGCB-LTDS, UMR 5513 CNRS, ENTPE, Université de Lyon, 69100 Vaulx-en-Velin, France
2 Univ. Savoie Mont-Blanc, CNRS, LOCIE, 73000 Chambéry, France
* Corresponding author: rudy.bui@entpe.fr
Due to the environmental impact of building materials, researches on sustainable materials, such as bio-based and earth materials, are now widespread. These materials offer numerous qualities such as their availability, recyclability and their ability to dampen the indoor relative humidity variations due to their hygroscopicity. As these materials can absorb large amount of humidity, numerical and experimental studies of their hygrothermal behaviour are crucial to assess their durability.
To validate a hygrothermal model, numerical and experimental data have to be confronted. Such confrontation must take into consideration the uncertainties related to the experimental protocol, but also to the model. Statistical tools such as uncertainty and global sensitivity analysis are essential for this task. The uncertainty analysis estimates the robustness of the model, while the global sensitivity analysis identifies the most influential input(s) responsible for this robustness. However, these methods are not commonly used because of the complexity of hygrothermal models, and therefore the prohibitive simulation cost.
This study presents a methodology for comparing the numerical and experimental data of a rammed earth wall subjected to varying temperature and relative humidity conditions. The main objectives are the investigation of the uncertainties impact, the estimation of the model robustness, and finally the identification of the input(s) responsible for the discrepancies between numerical and experimental data. To do so, a recent and low-cost global variance-based sensitivity method, named RBD-FAST, is applied. First, the uncertainty propagation through the model is calculated, then the sensitivity indices are estimated. They represent the part of the output variability related to each input variability. The output of interest is the vapour pressure in the middle of the wall to confront it to the experimental measurement. Good agreement is obtained between the experimental and numerical results. It is also highlighted that the sorption isotherm is the main factor influencing the vapour pressure in the material.
© 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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