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Prediction of lignocellulosic biomass structural components from ultimate/proximate analysis

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  • Nimmanterdwong, Prathana
  • Chalermsinsuwan, Benjapon
  • Piumsomboon, Pornpote

Abstract

In order to reduce time and resource consumption, the mathematical model was developed to predict lignocellulosic biomass structural components including cellulose, hemicellulose and lignin from ultimate/proximate dataset. Self-organizing maps (SOMs) were integrated with a regression model to obtain more precise results than the procedure without data clustering. In SOMs, the 149-biomass dataset from literatures, expressed by the ratios of VM/C, VM/H, VM/O, FC/C, FC/H, FC/O and ASH/O, were employed for training and clustered into 4 groups. The result indicated that each group had its own characteristics. The regression model with pre-analyzed by SOMs provided better results compared to the model without pre-analyzed by SOMs. The model obtained in this study can be applied to further researches in many fields; e.g. biomass characterization and utilization.

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  • Nimmanterdwong, Prathana & Chalermsinsuwan, Benjapon & Piumsomboon, Pornpote, 2021. "Prediction of lignocellulosic biomass structural components from ultimate/proximate analysis," Energy, Elsevier, vol. 222(C).
    • Handle: RePEc:eee:energy:v:222:y:2021:i:c:s0360544221001948
    DOI: 10.1016/j.energy.2021.119945
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    References listed on IDEAS

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    1. Ullah, Kifayat & Kumar Sharma, Vinod & Dhingra, Sunil & Braccio, Giacobbe & Ahmad, Mushtaq & Sofia, Sofia, 2015. "Assessing the lignocellulosic biomass resources potential in developing countries: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 682-698.
    2. Pablo García Estévez & Antonio Carballo, 2015. "Qualitative judgement in public credit ratings: A proposed supporting approach using Self-Organising Maps (SOMs)," Cuadernos de Economía - Spanish Journal of Economics and Finance, Asociación Cuadernos de Economía, vol. 38(108), pages 181-190, Septiembr.
    3. Naik, Satyanarayan & Goud, Vaibhav V. & Rout, Prasant K. & Jacobson, Kathlene & Dalai, Ajay K., 2010. "Characterization of Canadian biomass for alternative renewable biofuel," Renewable Energy, Elsevier, vol. 35(8), pages 1624-1631.
    4. Liukkonen, M. & Hiltunen, T., 2014. "Adaptive monitoring of emissions in energy boilers using self-organizing maps: An application to a biomass-fired CFB (circulating fluidized bed)," Energy, Elsevier, vol. 73(C), pages 443-452.
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