Determination of Oriented Strandboard Properties from a 3D Density Distribution using the Finite Element Method
Date of Award
Doctor of Philosophy
Richard M. Bennett
Edwin G. Burdette, Eric C. Drumm, Siqun Wang
Computer modeling of Oriented Strand Board (OSB) properties has gained widespread attention with numerous models created to better understand OBS behavior. Recent models allow researchers to observe multiple variables such as changes in moisture content, density and resin effects on panel performance. Thickness-swell variation influences panel durability and often has adverse effects on a structural panel’s bending stiffness. The prediction of out-of-plane swell under changing moisture conditions was, therefore, the essence for developing a model in this research.
The finite element model accounted for both vertical and horizontal density variations, the three-dimensional (3D) density variation of the board. The density variation, resulting from manufacturing processes, affects the uniformity of thickness-swell in OSB and is often exacerbated by continuous sorption of moisture that leads to potentially damaging internal stresses in the panel. The overall thickness-swell (the cumulative swell from non- uniform horizontal density profile, panel swell from free water, and spring-back from panel compression) was addressed through the finite element model in this research.
The pursued goals in this study were, first and foremost, the development of a robust and comprehensive finite element model which integrated several component studies to investigate the effects of moisture variation on the out-of-plane thickness-swell of OSB panels, and second, the extension of the developed model to predict panel stiffness. It is hoped that this paper will encourage researchers to adopt the 3D density distribution approach as a viable approach to analyzing the physical and mechanical properties of OSB.
Takie, Alan Derek Nii, "Determination of Oriented Strandboard Properties from a 3D Density Distribution using the Finite Element Method. " PhD diss., University of Tennessee, 2006.