Abstract

With increasing interest in renewable energy sources, particularly on biomass, and on the technologies to transform them into liquids fuels comes the need to assess its properties. One of the processes that can convert biomass into liquid fuel, bio-oil, is thermochemical liquefaction. However, the experimental determination of many properties can be time and budget consuming. Thus, the numerical models’ development to compute the higher heating value (HHV), with high accuracy, is needed. This work developed a model based on the linear correlation of a dataset composed of 54 samples. The carbon, hydrogen and oxygen content was correlated with HHV to develop a model. The model was compared with other from literature and finally validated with nine samples. Overall, the model exhibited excellent prediction accuracy. The absolute bias error was relatively low, 0.01%. Besides, the model’s good accuracy could be verified by the low absolute average error, 1.48%. The model’s good precision and performance was also demonstrated by the mean absolute error’s low value.

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