Parametric analysis of moisture sorption isotherms for wood sheathing using hygrothermal modelling. (March 2020)

• Record Type: Journal Article
• Authors: Zhang, Kevin; Richman, Russell
• Is Part Of: Journal of building engineering. Volume 28(2020)
• Publication Date: 2020-03
• Subjects: Building -- Periodicals; 690.05
• DOI: 10.1016/j.jobe.2019.101047
• Languages: English
• ISSNs: 2352-7102

Abstract

Abstract: A key component of building performance with respect to durability and energy efficiency is at the meso-level, i.e., the wall assembly and components. Performance of these assemblies can be determined through in-situ experimental work (such as building and monitoring a test hut), or by hygrothermal numerical modelling. Modelling is highly dependent on inputs including material data, thermodynamic equations, and weather data; however, numerical modelling, if well executed, can be highly resource efficient compared to experimental work. This study examines material moisture storage through sorption isotherms, which is not well measured in comparison to thermal and vapour resistance. In particular, the study is a parametric assessment of an existing numerical model to determine the effects of modified moisture sorption isotherms compounded with other factors such as wall type, climate, driving rain calculation method, air cavity air change rate, insulation thickness, and presence of an air barrier. Mold index was used as the durability performance indicator. It has been demonstrated that with changes of sorption isotherms up to 25%, the critical threshold for mold index (MI = 3) could be surpassed. This suggests the importance of having accurate sorption isotherm data in hygrothermal modelling. The study forms the first part of a three-phase project to quantify the sensitivity of an existing numerical model to sorption isotherms, to measure isotherms at varying temperature and age, and to calibrate the model to these measured isotherms. Highlights: Hygrothermal modelling can be a powerful predictor of durability. Moisture sorption isotherms are a key input into hygrothermal modelling. Moisture sorption isotherms are not well measured. Inaccurate data can make model results critical with respect to mold risk.