Investigation of the relationship between moisture content and density of selected Malaysian biomass
Suspended moisture in raw biomass materials is undesired in biomass fuel applications. In commercial and industrial practices, the moisture content in biomass fuel is normally in between 10-20 by weight in order to maximize the heating value of the fuel. Determining the moisture content in biomass m...
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Format: | Article |
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Universiti Malaysia Pahang
2016
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Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85008640771&doi=10.15282%2fjmes.10.2.2016.15.0199&partnerID=40&md5=79d13a22f8e85ec932e081babcfe49b4 http://eprints.utp.edu.my/25861/ |
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Institution: | Universiti Teknologi Petronas |
Summary: | Suspended moisture in raw biomass materials is undesired in biomass fuel applications. In commercial and industrial practices, the moisture content in biomass fuel is normally in between 10-20 by weight in order to maximize the heating value of the fuel. Determining the moisture content in biomass materials using the conventional oven-drying method is time consuming. This paper studied the linear relationship between the density and moisture content in several Malaysian lignocellulosic biomass residues from palm oil (oil palm frond, oil palm trunk, oil palm leaf, empty fruit bunch, palm mesocarp fiber and palm kernel shell), rice (rice husk), coconut (coconut frond and shell) and sugar (sugarcane bagasse) industries and their potential function as a tool for moisture determination with reference to their density. The biomass moisture content and density were determined through the oven drying method at 105°C and constant volume weighing at every 1-hour drying interval. All samples showed a linear relationship between moisture content and density, and a linear model for each biomass was constructed. The linear models were cross-validated using a set of measured observations to determine the prediction reliability and accuracy at 95 confidence interval. The cross validation regressions revealed the R2 and adjusted R2 values of above 0.9, while the standard error of regressions was found to be less than 3.1 wt. of moisture content for all linear models except for that of rice husk, indicating that the linear models are statistically reliable and accurate for moisture content determination using density. The average time of moisture determination using the density-moisture content models was found to be only between 45-60 minutes compared to the conventional drying method that took 24 hours to complete. © Universiti Malaysia Pahang. |
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