Open AccessDevelopment of moisture reference years for assessing long-term mould growth risk of wood-frame building envelopes
Author(s) -
Wei Lin,
Maurice Defo,
Abhishek Gaur,
Michael A. Lacasse
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2069/1/012015
Subject(s) - moisture , frame (networking) , latin hypercube sampling , index (typography) , set (abstract data type) , term (time) , mathematics , statistics , data set , selection (genetic algorithm) , environmental science , engineering , computer science , meteorology , geography , monte carlo method , mechanical engineering , physics , quantum mechanics , world wide web , programming language , artificial intelligence
A moisture reference year (MRY) is generally used to assess the durability, or long-term performance of building envelopes within a long climatological time period, e.g. a 31 year timeframe. The intent of this paper is to develop a set of moisture reference years that can be used to assess risk to the formation of mould growth in wood-frame buildings over the long-term. The set of moisture reference years have been developed based on 15 realizations of 31-year climate data. Replicated Latin Hypercube Sampling is applied to select 15 sub-realizations with 7 representative years having different levels of moisture index (MI) from each realization. Thereafter, hygrothermal simulations are performed for a brick veneer clad wood-frame wall assembly using the 15 sub-realizations; that sub-realization which produces the highest value of maximum mould growth index over 7-year period is selected as the MRY. The selection process is then implemented for all 15 realizations of the 31-years of data sets, from which 15 sets of 7-year long MRYs are selected to represent the original 15 realizations. It is shown that the 15 sets of 7-year long MRYs can produce the same value of maximum mould growth index as well as the uncertainty as compared to the original 15 realizations having a 31-year climate data set.