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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/9183

Title: Mathematical modeling and optimal control: maximizing yield in submerged alcoholic fermentation
Authors: Neba, Fabrice Abunde
Issue Date: 10-Oct-2016
Abstract: Advances in research into alternative starch sources for industrial production of alcoholic beverages, sorghum, cassava and maize are now being used as cheaper alternatives to imported barley in the brewery industry. In brewing, though involves several unit operations, the fermentation step is regarded as the heart of the entire production where a near optimal environment is desired for microorganisms to grow and produce ethanol. However, the use of fermenters is usually hampered by sub-optimal conditions in terms of yield and productivity, along with the low tolerance of strains to process stresses such as substrate and product toxicity. Attempts to improve the industrial efficacy of fermenters have been in the areas of genetic engineering to improve strain tolerance, but usually involves detailed and unfeasible mechanistic studies. Statistical design of experiments which has also been used often results in local optima due to the relatively small dimensional space covered by the experiments. Mathematical techniques have recorded great successes but proposed solutions however did not consider all degrees of freedom of the problem simultaneously (Inhibiton kinetics, temperature and pH). This thesis presents the modeling of substrate and/or product inhibtion in three different fermentation substrates: sorghum, maize and cassava extracts. At a 99% confidence interval, the pattern of these inhibtions can be described as being a linear or an exponential decrease in ethanol concentration in the case of sorghum, linear and sudden growth stop in the case of maize, linear substrate exponential product, and exponential substrate exponential product in the case of cassava. Optimal control was applied to minimize the effects of such inhibtion in sorghum extracts. Calculus of variation was introduced as a valuable tool to derive and solve the necessary conditions for optimality (optimal temperature and pH profiles). A Simulink model, developed and used for control validation shows an increase in ethanol yield by14.18%, cell growth by 71.96% and a decrease in the residual substrate by 84.77%. Since the model was developed using industrial scale fermentation data, the results obtained in the simulations can satisfactorily represent a real operation unit. From the comparative results presented in the simulations, it is concluded that the proposed strategy can be used in practice to improve the performance of industrial scale alcoholic fermentation.
Description: A thesis submitted to the Department of Agricultural Engineering, Kwame Nkrumah University of Science and Technology, Kumasi in partial fulfillment of the requirements for the degree of Master of Philosophy (Bioengineering), 2016
URI: http://hdl.handle.net/123456789/9183
Appears in Collections:College of Engineering

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