Artificial neural network based modeling to evaluate methane yield from biogas in a laboratory-scale anaerobic bioreactor
2016
Nair, Vijay V. | Dhar, Hiya | Kumar, Sunil | Thalla, Arun Kumar | Mukherjee, Somnath | Wong, Jonathan W.C.
The performance of a laboratory-scale anaerobic bioreactor was investigated in the present study to determine methane (CH4) content in biogas yield from digestion of organic fraction of municipal solid waste (OFMSW). OFMSW consists of food waste, vegetable waste and yard trimming. An organic loading between 40 and 120kgVS/m3 was applied in different runs of the bioreactor. The study was aimed to focus on the effects of various factors, such as pH, moisture content (MC), total volatile solids (TVS), volatile fatty acids (VFAs), and CH4 fraction on biogas production. OFMSW witnessed high CH4 yield as 346.65LCH4/kgVS added. A target of 60–70% of CH4 fraction in biogas was set as an optimized condition. The experimental results were statistically optimized by application of ANN model using free forward back propagation in MATLAB environment.
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