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• W2893598089 abstract "The oil palm industry contributes a huge amount of valuable crude palm oil (CPO) as export commodity for Malaysia. It also produces a large quantity of biomass as plantation waste, which can be utilized as potential fuel sources. In order to shed light on the energy output estimation from the biomass, a comprehensive study on the physical properties of the biomass, i.e., bulk density and moisture content is crucial. A Biomass Characteristics Index (BCI) is proposed to represent the relationship between bulk density and moisture content. A numerical framework is developed to determine the BCI. This index is used to estimate the biomass bulk density and moisture content prior to the calorific value calculation. A regression graph is plotted to illustrate the relationship among those values with respect to different appearance or shapes of biomass. The result shows that the biomass of different sizes and shapes has its own specific BCI. The classification of biomass according to its specific BCI can be used to forecast the related bulk density and moisture content. Therefore, it reduces the hassle and time constraint to get those values through the conventional empirical method." @default.
• W2893598089 created "2018-10-05" @default.
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• W2893598089 date "2018-09-26" @default.
• W2893598089 modified "2023-09-25" @default.
• W2893598089 title "Numerical Methods to Estimate Biomass Calorific Values via Biomass Characteristics Index" @default.
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• W2893598089 doi "https://doi.org/10.1007/978-981-13-2236-5_5" @default.
• W2893598089 hasPublicationYear "2018" @default.
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