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Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
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Sensors and Materials, Volume 33, Number 11(1) (2021)
Copyright(C) MYU K.K.
pp. 3873-3884
S&M2730 Research Paper of Special Issue
https://doi.org/10.18494/SAM.2021.3608
Published: November 17, 2021

Prediction of Moisture Content Changes during Natural Drying of Forest Residues Using Load-cell-mounted Drying Platforms [PDF]

Yun-Sung Choi, In-Seon Jeong, Min-Jae Cho, Ho-Seong Mun, Jae-Heun Oh, and Sang-Kyun Han

(Received August 30, 2021; Accepted October 25, 2021)

Keywords: forest biomass, woody fuel, comminution, prediction model, biomass energy

The use of renewable energy has increased markedly with growing global efforts to reduce fossil carbon emissions. Among various renewable energy sources, forest residues produced from timber harvesting are considered effective energy production sources. The combustion effectiveness of forest residues is highly affected by their quality, particularly their moisture content. However, determining when forest residues reach the target moisture content (< 30%) during natural drying is a challenge to forest managers. Therefore, in this study, we investigated the changes in moisture content during the natural drying of forest residues and developed a prediction model for estimating the changes in moisture content using meteorological factors. The changes in moisture content had similar patterns to the changes in precipitation during the natural drying of forest residues, and the minimum natural drying time required to reach the target moisture content was approximately 26 days in summer. A prediction model for estimating the changes in moisture content was developed using meteorological factors including precipitation, wind speed, effective humidity, and solar radiation quantity; the average absolute difference between the measured and predicted moisture contents was 22.7% in the model validation. Although the developed prediction model has limited accuracy in estimating the precise moisture content of forest residues during natural drying, it could aid forest managers to roughly determine the appropriate production and transportation times of forest residues for energy production.

Corresponding author: Sang-Kyun Han


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This work is licensed under a Creative Commons Attribution 4.0 International License.

Cite this article
Yun-Sung Choi, In-Seon Jeong, Min-Jae Cho, Ho-Seong Mun, Jae-Heun Oh, and Sang-Kyun Han, Prediction of Moisture Content Changes during Natural Drying of Forest Residues Using Load-cell-mounted Drying Platforms, Sens. Mater., Vol. 33, No. 11, 2021, p. 3873-3884.



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