Aniekan IKPE, Akanu-ıbiam NDON, Promise ETİM

FUZZY MODELLING AND OPTIMIZATION OF ANAEROBIC CO-DIGESTION PROCESS PARAMETERS FOR EFFECTIVE BIOGAS YIELD FROM BIO-WASTES

In this study, Adaptive Neuro Fuzzy Inference System (ANFIS) was employed in the modelling and optimization of anaerobic process parameters from co-digestion of bio-waste (food waste and Pig slurry) with different masses at constant water content. In six different experimental scenarios, mixture ratios of the bio-waste and water were 0.5:1, 1:1, 2:1, 2.5:1, 3:1 and 3.5:1. The range of parameters measured from the experimental process were used as input variables in the ANFIS model. Five experimentally measured parameters that led to maximum biogas yield as well as ANFIS input parameters and their corresponding output results in terms of maximum biogas yield were selected for validation. Optimum bio-digester temperature of 38oC, pH of 7.1, Hydraulic Retention Time (HRT) of 11 and mixture ratio of 2:1 in the experiment process produced overall maximum biogas yield of 247g while optimum input parameters such as bio-digester temperature of 40oC, pH of 7.1, HRT of 11 and mixture ratio of 2:1 in the ANFIS model produced overall maximum biogas yield of 248g. There was proximity between the experimental and predicted results, indicating that ANFIS model can be used as alternative tool for optimizing anaerobic process parameters from multiple feedstocks for desired biogas yield.

Keywords:

Biogas yield, Bio-wastes Mixture ratio, Water content, Modelling and optimization,

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