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245	1	0	_aLocal and global sensitivity analysis of a coupled heat and moisture transfers model: effect of the variability of cob material properties
490	0		_vHeat and Mass Transfer, 60, p.67-87, 2024
520	3		_aAmong earthen construction techniques, cob might be an interesting solution to mitigate greenhouse gases emissions and energy consumption of the building industry. One main issue encountered is that the cob material shows large variability of hygrothermal properties, which could consequently have an impact on the reliability of the estimation of the energy consumption of cob buildings. At the wall scale, the hygrothermal properties significantly influence the kinetics of moisture and heat transfers through the building shell, both being coupled. In order to measure the relative contribution of the variation of the hygrothermal properties, a sensitivity analysis of a coupled heat and moisture transfer model has been carried out on a cob wall. More specifically, a local sensitivity analysis has been performed (one model input wobbles around a reference value)and compared with a global sensitivity analysis, which may provide the potential interaction between model inputs. For the latter approach, the Morris method was used and allows to find the influence level of material properties and the relationships with model outputs. Two study cases have been performed: a static loading case, to find temperature and water vapour pressure profiles across the cob wall until the steady state and a dynamic loading case under a 2.5 years external dynamic loading (St-Nazaire meteorological data, France). As main results, the global approach showed in general a higher variability of properties, the sorption isotherms and the water vapour permeability were the most influential input parameters on humidity profiles while on temperature ones, the variability of both properties led up to 0.25 °C variation range. The influence of thermal properties was very sensitive to the daily-loading variation while that of the hygric properties was very sensitive to the seasonal-loading variation.
700	1	2	_aTchiotsop, J.
700	1	2	_aBonnet, S.
700	1	2	_aKiessé, T. S.
700	1	2	_aIssaadi, N.
700	1	2	_aPoullain, P.
856	4	0	_uhttps://drive.google.com/file/d/1Eas2mEqtCagABg8SOTofiKOKHyFBIzWX/view?usp=drivesdk _zPara ver el documento ingresa a Google con tu cuenta: @cicy.edu.mx
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