Mehdi Khojastehpour - Department of Biosystems Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
Amin Nikkhah - Department of Biosystems Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
Alireza Taheri-Rad - Department of Biosystems Engineering, Ferdowsi University of Mashhad, Mashhad, Iran

Several factors can influence the process of biogas production. The type of reactor is one of the key factors that influence biogas production. Therefore, the aim of this study was to construct a portable horizontal polyethylene-based biogas reactor. In addition, the performance of the developed biogas reactor was tested through digestion of cow manure. The experiments were carried out in Mashhad, Iran, during June–July 2016. Biogas production was studied over a span of 58 days’ hydraulic retention time. Artificial neural network (ANN) models were used to predict the production of biogas based on temperature and pH. The Levenberg–Marquardt learning algorithm was employed to develop the best model. The obtained biogas productivity was 0.27 m3 kgVS-1, indicating that the developed biogas reactor was optimum to convert the substrate into biogas. The ANN results highlighted that the best developed model consisted of an input layer with two input variables, one hidden layer with 15 neurons, and one output layer with the correlation coefficient of 0.90. Overall, it was concluded that the ANN models can be employed to prognosticate biogas production using a portable polyethylene biogas reactor.

Artificial neural network, Horizontal Reactor, Modeling