Modelagem matemática do processo de secagem de madeira de Pinus taeda

• Autor(a) principal: Titon, Leonardo
• Data de Publicação: 2019
• Tipo de documento: Trabalho de conclusão de curso
• Idioma: por
• Título da fonte: Repositório Institucional da UTFPR (da Universidade Tecnológica Federal do Paraná (RIUT))
• Texto Completo: http://repositorio.utfpr.edu.br/jspui/handle/1/11545
• topic: Madeira serrada - Secagem; Modelos matemáticos; Pinus taeda; Lumber - Drying; Mathematical models; Loblolly pine; CNPQ::ENGENHARIAS::ENGENHARIA QUIMICA

The Pinus taeda is the most cultivated species among the pinus in Brazil, with an estimated area of one million hectares. Native of the United States, in the Brazilian territory this species develops well in regions of cool climate and cold winter, where there is not water deficiency. This condition can be found throughout the plateau of the South and Southeast regions. Its cultivation is destined to produce cellulose, paper, sawn wood, plates and reconstructed wood. Depending on the application of wood, it is necessary to dry the wood in order to achieve desired characteristics such as moisture content and dimensional stability. Among other purposes, the drying process is also widely used for food preservation purposes or even to reduce the mass of the products in order to reduce costs related to transportation. Given the importance of this unity operation, it is convenient to seek information about the processes pertinent to it, such as the variation of humidity as a function of time. Through mathematical modeling, it is possible to establish mathematical relationships between the variables of drying kinetics, and several studies have been developed for this purpose for several products. In this context, the present work aims to model mathematically the drying kinetics of Pinus taeda wood, at temperatures of 70, 80 and 90°C, using the Diffusion, Page and Two-Periods models. The model adjustments to the experimental data were made by the Levenberg Marquardt method, using programming routines elaborated in Scilab® software version 6.0.2. The parameters of the models were correlated with the temperature and the choice of the model that best described the experimental data of the drying was obtained through the comparison of mean square error (MSE), coefficient of determination (R²) and mean relative error (P), being that the Two-Periods model was the one that obtained better performance.