Affiliation:
1. School of Biological Sciences, GuiZhou Education University, Guiyang, Asian, China
Abstract
Background
When the moisture content of a fuel bed is higher than the fiber saturation moisture content (0.35 g g−1), the drying process is controlled by evaporation (>0.35 g g−1) and diffusion (>0.35 g g−1). Packing ratio has a significant effect on the drying process. Ignoring the impacts of packing ratio or the separate phases of the drying process is one main reason for inaccurate moisture content predictions.
Method
This study simulated the drying process in five Masson pine (Pinus massoniana Lamb.) needle beds with different packing ratios. Using the fiber saturation moisture content as the cut-off point, we divided the drying process into two phases. The drying mechanism of each phase was different and had its own drying equation. Using a model that does not distinguish the two phases of the drying process as a comparison, the prediction effect of the two-phase model was analyzed. The influence of the fuel bed packing ratio on the drying process was also analyzed.
Results
We found that, regardless of any changes in packing ratio, the two-phase model could better simulate the drying process, with a mean absolute error (MAE) and mean relative error (MRE) of the two-phase model 18.4% and 25.6% less than the one-phase model, respectively. The time-lag prediction model was established with the packing ratio, and the errors were all within the allowable range, but the prediction effect of the time-lag prediction model based on the two-phase model was larger.
Conclusion
It was further demonstrated that considering the packing ratio of the fuel bed and distinguishing the two separate phases of the drying process could both effectively improve the prediction accuracy of the moisture content of fuel beds based on the semi-physical method.
Funder
Science and Technology Support Program of Guizhou Province
Natural Science Foundation of Guizhou Province
Youth Science and Technology Talent Development Project of Education Department in Guizhou Province
China National Natural Science Foundation
Subject
General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience
Cited by
3 articles.
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