TCC - Bacharelado em Engenharia de Alimentos (UAG)
URI permanente para esta coleçãohttps://arandu.ufrpe.br/handle/123456789/2954
Navegar
1 resultados
Resultados da Pesquisa
Item Modelagem e simulação do processo de fermentação alcoólica na indústria sucroalcooleira(2019-01-30) Costa, Emerson Rodrigues; Rosal, Andréa Galindo Carneiro; Camelo, Marteson Cristiano dos Santos; http://lattes.cnpq.br/1815470140889772; http://lattes.cnpq.br/5799738310371979; http://lattes.cnpq.br/1735669985702468Ethanol is an easily obtainable biofuel, originating from the alcoholic fermentation process of the sugarcane juice, which consists of the transformation of the organic matter through a biological and anaerobic process. The yeasts responsible for alcoholic fermentation are Saccharomyces cerevisae, where several studies are constantly carried out to better understand this process. One of these studies of great importance for engineering is the application of mathematical modeling, in which are evaluated how much the concentrations of substrates and cells influence the generated products. Thus, in this work the objective was to develop a mathematical model and computational simulation for the alcoholic fermentation of a large sugar-alcohol plant. The tests and analyzes were carried out during the month of november of the recurring year to the development of this study, where the samples collected were of the treated yeast, the feed wort and the fermented wort of each fermentation dorn, which were submitted to the determination analyzes concentration of biomass for the treated ferment and for the fermented must; total reducing sugars for the feed must and for the fermented must; and determination of ethanol concentration for the treated ferment and for the fermented wort. The kinetic models used were obtained from the literature, being the six models most used for other similar studies. The kinetic model capable of better matching was the GHOSE & TYAGI (1979) model that describes the conditions as a limiting substrate, inhibition by the substrate and linear inhibition by the product, obtaining a mathematical model capable of predicting substrate and product concentrations, with average margin of error between the stages of 38.32% and 4.79%, respectively. Since none of the kinetic models used in the study takes into account the variation of cell concentration, the kinetic models were not able to adapt and predict the process as a function of yeast concentration throughout the fermentation stages.