Modeling and Multiresponse Optimization for Anaerobic Codigestion of Oil Refinery Wastewater and Chicken Manure by Using Artificial Neural Network and the Taguchi Method

文献类型： 外文期刊

第一作者： Mehryar, Esmaeil

作者： Mehryar, Esmaeil;Ding, Weimin;Talha, Zahir;Mehryar, Esmaeil;Hemmat, Abbas;Hassan, Muhammad;Kafashan, Jalal;Kafashan, Jalal;Huang, Hongying

作者机构：

期刊名称：BIOMED RESEARCH INTERNATIONAL （ 影响因子：3.411； 五年影响因子：3.62 ）

ISSN： 2314-6133

年卷期： 2017 年

页码：

收录情况： SCI

摘要： To study the optimum process conditions for pretreatments and anaerobic codigestion of oil refinery wastewater (ORWW) with chicken manure, L-9 (3(4)) Taguchi's orthogonal array was applied. The biogas production (BGP), biomethane content (BMP), and chemical oxygen demand solubilization (CODS) in stabilization rate were evaluated as the process outputs. The optimum conditions were obtained by using Design Expert software (Version 7.0.0). The results indicated that the optimum conditions could be achieved with 44% ORWW, 36 degrees C temperature, 30 min sonication, and 6% TS in the digester. The optimum BGP, BMP, and CODS removal rates by using the optimum conditions were 294.76 mL/gVS, 151.95 mL/gVS, and 70.22%, respectively, as concluded by the experimental results. In addition, the artificial neural network (ANN) technique was implemented to develop an ANN model for predicting BGP yield and BMP content. The Levenberg-Marquardt algorithm was utilized to train ANN, and the architecture of 9-19-2 for the ANN model was obtained.

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