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Characterizing the permeability and dispersion of flows through compressible wood-chip beds

University of British Columbia

During Kraft pulping, cellulose fibres are liberated from a lignin-matrix, found in a wood chip, by reaction at elevated temperature and pressure using an alkaline solution. Poor lignin removal is a deleterious effect that leads to downstream operational difficulties and decreased product quality. A number of research groups speculate that this is caused by the uneven distribution of the alkaline solution through the wood chip bed during reaction. As a result, the goal of this thesis is to characterize the ease by which fluid flows, and disperses, through wood chip beds. One of the open remaining scientific questions is understanding the effect of bed compressibility on the resulting flow patterns. In the first portion of this work we present a methodology to characterize the permeability of a compressible bed of wood chips under mechanical load. We show that under the limiting condition of when the mechanical load is large in comparison to hydraulic pressure the equations of motion can be linearized and solved to produce an expression approximating the variation in porosity along the length of the bed. We show how this may be used, in conjunction with multiple linear regression, to estimate permeability of the bed. The usefulness of these estimates was then tested by predicting the pressure drop versus flow relationship for conditions outside the range of the linearized solution. Good agreement was obtained. In the second portion of this work we present a methodology to characterize the axial dispersion of a solute during steady-flow through a compressible bed of wood chips under mechanical load. We use a non-invasive imaging technique, namely electrical resistance tomography (ERT), to visualize the uniaxial displacement of a salt solution. Here we demonstrate that under two limiting cases the porosity of the porous bed varies slowly in the flow-direction and to the lowest order can be considered a constant. This simplified the optimization routine we used to match the experimental data to the numerical results of the advection-diffusion equation. Using this, a methodology to estimate the axial dispersion is given by a minimization scheme.

Text

2011-07-14

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/35983

Chemical and Biological Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/