Prediction of lignocellulosic biomass structural components from ultimate/proximate analysis

被引：29

作者：

Nimmanterdwong, Prathana ^{[1
]}

Chalermsinsuwan, Benjapon ^{[1
]}

Piumsomboon, Pornpote ^{[2
]}

机构：

[1] Chulalongkorn Univ, Dept Chem Technol, Fac Sci, Fuels Res Ctr, 254 Phayathai Rd, Bangkok 10330, Thailand

[2] Chulalongkorn Univ, Ctr Excellence Petrochem & Mat Technol, 254 Phayathai Rd, Bangkok 10330, Thailand

来源：

ENERGY | 2021年 / 222卷

关键词：

Lignocellulosic biomass; Biomass; Structural component; Self-organizing maps;

D O I：

10.1016/j.energy.2021.119945

中图分类号：

O414.1 [热力学];

学科分类号：

摘要：

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. ? 2021 Elsevier Ltd. All rights reserved.

引用

页数：13

共 35 条

[1] Energy consumption analysis of integrated flowsheets for production of fuel ethanol from lignocellulosic biomass [J].