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Forest Products Laboratory
One Gifford Pinchot Drive
Madison, WI 53726-2398
Phone: (608) 231-9200
Fax: (608) 231-9592
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Improving the Accuracy of Automated Instruments for Moisture in Wood

Automated sorption balance. USDA Forest Service
Automated sorption balance. USDA Forest Service
Snapshot: Automated instruments are increasingly used for measuring the equilibrium moisture content of wood. Research finds that common methods have much larger errors than claimed in the literature, so researchers developed a method to improve accuracy.
Summary:

Wood and many other natural materials absorb moisture from the surrounding air or release it depending on the relative humidity and temperature. Most of the performance properties of these materials depend on moisture content. Equilibrium moisture content (EMC) is the moisture content at which the material is neither gaining nor losing moisture when the relative humidity and temperature are constant. The EMC-temperature-relative humidity relationship is fundamental for understanding wood-moisture interactions and is used in a host of technological applications ranging from wood drying to the design of wood structures. Traditionally EMC has been measured manually by repeatedly weighing samples in a constant temperature and humidity environment until no change is detectible. Computer-automated instruments are now commonly used in wood laboratories and allow for continuous measurement with precise temperature and humidity control. These instruments are usually programmed with a series of humidity steps, and each step typically is held until the rate of change in sample mass over time is below an arbitrary threshold. We developed an operational definition of equilibrium for automated measurements and quantified the errors in EMC using different methods for shortening data collection time. Prior claims about accuracy in the literature were unsupported by any data. Wood and other cellulosic materials continue to change moisture content over much longer times than captured by any previous automated measurements. We developed a new method to improve accuracy while keeping data collection time to a minimum.
Princpal Investigator(s):
 Glass, Samuel V.
 Boardman, Charles R
 Zelinka, Samuel L.


Research Location:
  • Madison, WI


External Partners:
  • University of Copenhagen

Fiscal Year: 2018
Highlight ID: 1313
 
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