Abstract:In order to testify the element efficiency and compare the application of different models in anaerobic digestion of the penicillin fermentation residues, the optimized test was designed by Box-Behnken, modeled by the response surface methodology (RSM) and the backpropagation neural network (BP-ANN). Meanwhile, the optimal concentration of single and mixture was determined. The optimal concentrations of single trace elements of Fe2+, Co2+ and Ni2+ were 500mg/L, 30mg/L and 0.3mg/L, which the accumulated biogas production was increased by 102.18%, 45.48% and 60.12% compared with the control. The variation of gas promotion was "weaker-stronger-weaker" with the increasing concentration of different trace elements. The optimal mixture concentration of Fe2+, Co2+ and Ni2+ predicted by the RSM model were 440.94mg/L, 16.22mg/L and 0.39mg/L, R2=0.972, which the prediction of accumulated biogas production was 1314.49mL, and the experimental value was 1256mL with the RE (relative error)=4.65%. Meanwhile, the best-adding concentration of Fe2+, Co2+ and Ni2+ predicted by BP-ANN mode was 495mg/L, 21mg/and 0.5mg/L, R2=0.991, which prediction of accumulated biogas production was 1551.55mL and the experimental value was 1358mL with the RE=0.47%. Compared with the RSM model, the BP-ANN model had a better fit and robust prediction of adding trace elements in anaerobic digestion of the penicillin fermentation residues, which showed that the BP-ANN model had prudential application in the optimization of trace element in anaerobic digestion, and it also provides a new idea to the optimization of anaerobic digestion.
方楠, 赵燕肖, 习彦花, 刘敬, 梁文华, 程辉彩, 张丽萍. 金属离子对青霉素菌渣厌氧发酵产气模型分析[J]. 中国环境科学, 2020, 40(7): 3020-3028.
FANG Nan, ZHAO Yang-Xiao, XI Yang-Hua, WU Jian, LIANG Wen-Hua, CHENG Hui-Cai, ZHANG Li-Ping. Different mathematical models in the analysis of the effect of trace elements on the anaerobic digestion of penicillin fermentation residues. CHINA ENVIRONMENTAL SCIENCECE, 2020, 40(7): 3020-3028.
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