Prediction of biogas production from chemically treated co-digested agricultural waste using artificial neural network

被引:106
作者
Almomani, Fares [1 ]
机构
[1] Qatar Univ, Coll Engn, Dept Chem Engn, POB 2713, Doha, Qatar
关键词
Co-digestion; Kinetic model; Lignin degradation; Biofuel potential; Agricultural biomass; RESPONSE-SURFACE METHODOLOGY; ANAEROBIC-DIGESTION; METHANE PRODUCTION; RICE STRAW; CRUDE GLYCEROL; BUFFALO DUNG; PIG MANURE; FOOD WASTE; SLUDGE; OPTIMIZATION;
D O I
10.1016/j.fuel.2020.118573
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The present study evaluates the effect of co-digestion of agricultural solid wastes (ASWs), cow manure (CM), and the application of chemical pre-treatment with NaHCO3 on the performance of anaerobic digestion (AD) process. An Artificial neural network (ANN) algorithm was developed to model and optimize the cumulative methane production (CMP) from ASWs, CM, and their mixture under mesophilic and thermophilic conditions. The results demonstrated that co-digestion of ASWs with CM with a ratio of 70% to 30% produced the highest CMP of 334 +/- 4 NL/kgVS in comparison with 230 +/- 10 NL/kgVS for mono-digested substrate. The CMP was the highest for the substrate with moisture content (%MC) in the range of 34% to 48%, and it decreased for % MC > 50%. The chemical treatment with NaHCO3 improved the biodegradability of the substrate and increased the CMP by at least 43% with reference to the untreated substrate. An ANN model consists of three layers, 15 neutrons and 260 epochs accurately predict the CMP with 99.1% of data within +/- 10% deviation of the mean experimental value. The developed model can be used to forecast the CMP as a function of operating temperature, the substrate composition, and chemical dose, and can be used for scaling-up and cost analysis purposes.
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页数:13
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