期刊
ENERGY
卷 232, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2021.121010
关键词
Hydrothermal carbonization; Sewage sludge; Hydrochar; Nitrogen content; Machine learning
资金
- National Natural Science Foundation of China [21776063, U1704127]
- Scientific and Technological Innovation Team of the University of Henan Province [18IRTSTHN010]
- Scientific and Technological Research Projects of Henan Province [182102311077]
A neural network model was successfully used to predict the nitrogen content of hydrochar, with sewage sludge-N identified as the main contributor, predicting a conversion rate of 40-70%.
In this work, 138 datapoints, including elemental composition and ultimate analysis of various types of sewage sludge, and the hydrothermal carbonization reaction conditions, are used to develop a prediction model for the nitrogen content of the hydrochar. The results suggested that a two-layer feedforward neural network with five (05) neurons in the hidden layer can accurately predict the nitrogen content of the hydrochar based on the reaction temperature and the contents of nitrogen, carbon, volatiles and fixed carbon in the feedstock. Over 100 runs, the R-2 and RMSE are in [87.547-99.097%] and [0.243-1.431] wt.% (db), respectively. Moreover, a statistical and regression analysis revealed that the sewage sludge-N is the main contributor to the hydrochar-N. Mostly, 40-70% of sewage sludge-N goes to hydrochar-N. The results are consistent with previous experimental reports, and this model can be used to predict the sewage sludge-derived hydrochar-N. (C) 2021 Elsevier Ltd. All rights reserved.
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