scholarly works

Biogas, a form of renewable energy (biofuel) and whose by-products include methane, carbon-dioxide and other gases, depending on substrate type is producible from various substrates, with varying degrees of yield level and quality. However, the climatic and energy requirements in realising the optimum yield remain uncertain and vary with the environment. Therefore, this work was centred towards determining the substrate(s) that would give the optimum yield of methane and carbon-dioxide, under Nigerian climatic conditions. Two different substrates were collected and processed by means of anaerobic digestion for twenty-one days using a continuous flow digester. The synthesized gases were tested for a period of two days at varying atmospheric temperature, and humidity for methane, carbon-dioxide, energy yields, and other gases for each day, using AZ77535 gas analyzer and a gas detector. Economic analysis of the data obtained was also conducted. The substrates collected were cow-dung and pig-dung from University of Ibadan’s teaching and research farm. While pig dung yielded 59% and 53% of methane with 35% and 39% of carbon-dioxide at 33.7°C, 71% and 26°C, 50.1%; cow dung yielded 52% and 44% of methane with 30% and 33% of carbon-dioxide at 32.6°C, 65% and 27°C, 52%, as well as energy contents 18,266KJ/m3; 17,311KJ/m3 and 16,177KJ/m3; 13,817KJ/m3 for days one and two respectively. Pig dung gave a higher yield of methane and carbon-dioxide than cow dung, regardless of the working atmospheric temperature and humidity. Economic analysis of the biogas yield showed a potential saving of $267.24for the first year of production. This information is useful in setting up biogas processing plants in Nigeria.

This paper presents a contribution on the development of a neurofuzzy mathematical model that aids in capturing and analyzing the various parameters in oven design. The oven was designed specifically for domestic and commercial baking operations. The neurofuzzy methodology was used to regulate the oven baking temperatures to acceptable standards. Particular use was made of neurofuzzy model since it is an improvement on the process design. The work was motivated by the need for a more reliable and easily understandable methodology that guides decision makers in making correct decisions in a timely manner. The results obtained demonstrated that it is feasible to apply the model in practice.

scholarly works

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