| The use of supercritical carbon dioxide (SC CO2) as a solvent to deliver chemicals to porous media has shown promise in various industries. Recently, efforts by the wood treating industry have been made to use SC CO 2 as a replacement to more traditional methods of chemical preservative delivery. Previous studies have shown that the SC CO2 pressure treatment process is capable of impregnating solid wood materials with chemical preservatives, but concentration gradients of preservative often develop during treatment. Widespread application of the treatment process is unlikely unless the treatment inconsistencies can be improved for greater overall treating homogeneity.;The development of a computational flow model to accurately predict the internal pressure of CO2 during treatment is integral to a more consistent treatment process. While similar models that attempt to describe the flow process have been proposed by Ward (1989) and Sahle-Demessie (1994), neither have been evaluated for accuracy. The present study was an evaluation of those models. More specifically, the present study evaluated the performance of a computational flow model, which was based on the viscous flow of compressible CO2 as a single phase through a porous medium at the macroscopic scale. Flow model performance was evaluated through comparisons between predicted pressures that corresponded to internal pressure development measured with inserted sensor probes during treatment of specimens. Pressure measurements were applied through a technique developed by Schneider (2000), which utilizes epoxy-sealed stainless steel tubes that are inserted into the wood as pressure probes. Two different wood species were investigated as treating specimens, Douglas-fir and shortleaf pine.;Evaluations of the computational flow model revealed that it is sensitive to input parameters that relate to both processing conditions and material properties, particularly treating temperature and wood permeability, respectively. This sensitivity requires that the input parameters, principally permeability, be relatively accurate to evaluate the appropriateness of the phenomenological relationships of the computational flow model. Providing this stipulation, it was observed that below the region of transition from CO2 gas to supercritical fluid, the computational flow model has the potential to predict flow accurately. However, above the transition region, the model does not fully account for the physics of the flow process, resulting in prediction inaccuracy.;One potential cause for the loss of prediction accuracy in the supercritical region was attributed to a dynamic change in permeability that is likely caused by an interaction between the flowing SC CO2 and the wood material. Furthermore, a hysteresis was observed between the pressurization and depressurization stages of treatment, which cannot be explained by the current flow model. If greater accuracy in the computational flow model is desired, a more complex approach to the model is necessary, which would include non-constant input parameters of temperature and permeability. Furthermore, the implications of a multi-scale methodology for the flow model were explored from a qualitative standpoint. |
