Such treatment also promoted color changes. The thermal modification improved the physical properties but reduced the mechanical strength of the wood, from 150 ✬ and above. The purpose of this research was to evaluate the physical, mechanical, and colorimetric properties of the ANN-assisted thermally modified woods of Eucalyptus urophylla and Pinus oocarpa, in order to predict their structural and esthetic properties. Therefore, the use of artificial intelligence, as an artificial neural network (ANN), to conduct the thermal process, can be an alternative to overcome the laborious and detailed work needed to perform the treatment. However, such heat treatment needs precise process control tools, since it improves the physical properties of wood but reduces its mechanical resistance. In addition, the wood’s appearance is also enhanced, as its color is made darker, thus more similar to those of tropical woods, which increases its commercial value. Forest wood can be enhanced by thermal modifications, which improve the wood’s natural durability and dimensional stability. Fracture toughness was dominated by the dimensional parameters of the specimen contributing (42%) followed by anisotropy and physical properties.įast-growing wood plantations have been widely used as an alternative to the suppression of native vegetation. For predicting the crack extension, density had the greatest contribution (20%) followed by previous crack length and force contributing 16% equally. This was followed by volume and physical properties. A sensitivity analysis of the networks revealed that the crack length was the most influential with 21% contribution followed by grain angle with 14% contribu - tion for predicting the applied force. Each was successful, producing respective R2 of 0.870, 0.865, and 0.621 on validation data. Three artificial neural networks were developed to predict the: 1) force required to propagate a crack, 2) crack extension, and 3) fracture toughness of an individual specimen. The Average fracture toughness was calculated from GIc and it was 215 kPa.m0.5. No significant differences in GIc, between initial and subsequent crack lengths were found for the smaller specimens by paired sample t-tests, but differences were significant for the largest specimen size. Since cracks extended in stages, full compliance-crack length relationship was developed for each specimen based on their initial and subsequent crack lengths. Video imaging, was used to measure crack length during propagation. For each specimen, grain and ring angles, density and moisture content were measured. A total of 123 specimens consisting of four sizes of specimen with each size having four different crack lengths were tested. Strain energy release rate (GIc) of Pinus radiata in the TL opening mode was determined using the compliance crack length relationship.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |