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    Study of moisture conditions in a multi-story mass timber building through the use of sensors and WUFI hygrothermal modeling

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    Author
    Kordziel, Steven
    Advisor
    Pei, Shiling
    Date issued
    2018
    Keywords
    cross laminated timber
    hygrothermal
    WUFI
    glulam
    CLT
    mass timber
    
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    URI
    https://hdl.handle.net/11124/172342
    Abstract
    Mass timber products have shown promise as an innovative alternative to conventional framing systems for use in tall wood buildings, but this new trend in design and construction poses concerns for the long-term durability of the products. A major challenge that classically faces timber products is the threat of moisture-induced mold and decay fungi, which are a heightened concern in mass timber buildings exposed to the environment for extended duration during construction. Consequently, it is important to understand the hygric and thermal (hygrothermal) conditions that mass timber products can experience in multi-story constructions and to be able to quantify the behavior of the products for their suitable design and implementation. An eight-story mass timber building located in Portland, Oregon was chosen for this study and was instrumented for moisture content monitoring through its production, construction, and in-situ use. Record breaking precipitation levels occurred during the building’s construction and while dimension lumber and glulam products subsequently dried to acceptable levels, cross laminated timber products (CLT) dried more slowly. These measurements have an observed bias and the decay risk for the products is inconclusive. Samples of CLT used in the building were characterized for hygrothermal properties and integrated into WUFI, a simulation software, for analysis of the building. The software showed limitations for correctly simulating the behavior of CLT in isolated lab experiments and therefore a re-calibration was performed for accurate simulation. Preliminary on-site simulation results provide a decent approximation of observed data despite its high variance, but drying rate predicted by the program is lower than what was measured.
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