Chunping Dai
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Research Methodology
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Dissertations completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest dissertations.
During the manufacturing of wood composites, mats of resinated fibers, particles or strands are consolidated under heat and pressure to produce panels with the necessary strength and stiffness properties. As the mat consolidates a vertical density profile (VDP) is established and it has a significant impact on panel properties. In order to tailor the VDP of the panel to various end-use applications, a means of describing of the effect of pressing variables on the development of the VDP is needed.This study examined the role of environmental factors, i.e., temperature and moisture content (MC), on the compression and viscoelastic behavior of wood strands. The strand stress-strain relationship during hot pressing was modeled using a modified Hooke’s law, in which the compression modulus as a function of temperature and MC was quantitatively obtained using a regression approach. Similarly, the viscoelastic behavior of strands was investigated for various temperatures and MCs and the results were used to develop a model for predicting the stress relaxation response of the strands. The results showed that the relaxation modulus as a function of time follows a linear relationship on a log-log plot; it is important to note that the response was affected by strain level and environmental conditions.Based on the strand compression properties and mat structure, a comprehensive model was established that simulated the VDP development and was found to be a good description of the experimental results. The effects of mat elastoplasticity and springback on the formation of the VDP were also discussed. In addition, a generalized model based on the beam bending of the wood elements was developed to predict the mat pressure-density relationship of wood composites. This is valuable for improving the fundamental understanding of the relationship between pressing variables and panel properties for process optimization.
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