Sensitivity analysis of parameters influencing building heating energy consumption using hemp-lime material

Author(s): Andrianandraina, P. Poullain, B. Cazacliu, A. Ventura
Paper category: Proceedings
Book title: Proceedings of the 1st International Conference on Bio-based Building Materials
Editor(s): Sofiane Amziane and Mohammed Sonebi
e-ISBN: 978-2-35158-154-4
Publisher: RILEM Publications SARL
Publication year: 2015
Pages: 687-694
Total Pages: 8
Language : English

Abstract: Heating is the dominant energy load in the french construction sector for both residential and commercial buildings. Many researches were made on hemp based insulation products as hemp-lime is a renewable and bio based resource. Moreover, it exhibits interesting ability in inner air moisture control. However, the physical properties of this material show high variability induced by the manufacturing processes and by surrounding environmental condition such as temperature and humidity. In this work we investigate the effect of these variability and uncertainty sources on the heat and mass transfers through a building wall made of hemp-lime material, in order to identify the determinant factors for energy consumption. We apply the coupled heat and mass transfer model by Künzel to calculate the energy consumption of a simplified building model represented by a floating parallelepiped. The parallelepiped faces are made of hemp lime material and are exposed to various environmental conditions. The Morris sensitivity analysis is applied to the energy consumption model in order to identify parameters which can influence the energy consumption when maintaining comfort conditions in the building volume (temperature 20 to 24°C). These parameters are the hemp-lime material physical properties, the parallelepiped dimension parameters, the variability of external and internal conditions. Morris sensitivity analysis provides a classification according to the parameter influences. This ranking can then be used to determine the parameter(s) or group of parameters whose values can be optimized to lower the heating and cooling energy consumption of the simplified building model.

Online publication : 2015
Publication type : full_text
Public price (Euros) : 0.00