The most common method of drying wood for the furniture industry is in kilns at temperatures below 180(DEGREES)F. The procedures currently in use involve more or less empirically determined drying schedules which require a week or more residence time in the kiln.; With rapidly increasing energy costs and the demand for shorter processing times for green wood, interest has developed in perfecting faster and more efficient ways of drying lumber. High temperature drying is being considered as an alternative; however, if care is not taken, the severe conditions required by high temperature drying may lead to degradation of the wood. Successful high speed drying will require a more thorough understanding of the drying process and the measurement of variables such as surface temperature, interior temperatures, and heat transfer coefficients.; In this work, techniques were developed for accurately measuring the surface and interior temperatures of the drying wood. Yellow poplar lumber was dried at dryer temperatures from 215(DEGREES)F to 300(DEGREES)F with wet bulb temperatures ranging from 130(DEGREES)F to 180(DEGREES)F in order to generate surface and interior temperature profiles and wood moisture content profiles. Detailed temperature and moisture profiles for these runs are presented.; A mathematical model, based on Luikov's equations, was developed for use in predicting surface and interior temperature profiles and moisture profiles during the drying of lumber. A fixed network procedure developed by Crank was used to solve the model equations.; Using the model and the experimental data for yellow poplar, empirical correlations were developed for predicting the evaporation rate at the surface of the wood during the constant rate period and the overall diffusion coefficient.; The results from the model were compared with the experimental data obtained during this study, with the results of a model described in the literature, and with experimental data from the literature. The model developed in this work was found to predict drying curves from the literature better than the model described in the literature.
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