SYMPOSIA PAPER Published: 01 July 2012
STP154520120008

A Systematic Approach to the Study of Accelerated Weathering of Building Joint Sealants

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An accurate service life prediction model is needed for building joint sealants in order to greatly reduce the time to market of a new product and reduce the risk of introducing a poorly performing product into the marketplace. A stepping stone to the success of this effort is the precise control of environmental variables in a laboratory accelerated test apparatus in order to produce reliable weathering data that can be used to generate a predictive model. This contribution reports a systematic study, using a novel laboratory test apparatus, investigating the individual and synergistic impacts of four environmental factors (cyclic movement, temperature, relative humidity, and ultraviolet radiation) on the durability of a sealant system. The apparatus used is unique because it not only allows the precise control of environmental factors but also permits in situ characterization tests so that the specimens need not be removed from the apparatus chamber. Graphical and quantitative statistical approaches have been used to analyze the data. The study shows that the critical role of each individual factor, as well as synergism among the different factors, can be readily quantified, and modes of degradation possibly can be identified.

Author Information

White, Christopher, C.
National Institute of Standards and Technology, Engineering Laboratory, Materials and Structural Systems Division, Gaithersburg, MD, US
Hunston, Donald, L.
National Institute of Standards and Technology, Engineering Laboratory, Materials and Structural Systems Division, Gaithersburg, MD, US
Tan, Kar, Tean
National Institute of Standards and Technology, Engineering Laboratory, Materials and Structural Systems Division, Gaithersburg, MD, US
Filliben, James, J.
National Institute of Standards and Technology, Information Technology Laboratory, Statistical Engineering Division, Gaithersburg, MD, US
Pintar, Adam, L.
National Institute of Standards and Technology, Information Technology Laboratory, Statistical Engineering Division, Gaithersburg, MD, US
Schueneman, Greg
Forest Products Laboratory, Madison, WI, US
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Details
Developed by Committee: C24
Pages: 177–201
DOI: 10.1520/STP154520120008
ISBN-EB: 978-0-8031-7557-0
ISBN-13: 978-0-8031-7531-0