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Investigação Operacional

versão impressa ISSN 0874-5161

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LEAO, Celina P.  e  SOARES, Filomena O.. Heuristic Sensitivity Analysis for Baker's Yeast Model Parameters. Inv. Op. [online]. 2004, vol.24, n.2, pp.247-263. ISSN 0874-5161.

The baker's yeast, essentially composed by living cells of Saccharomyces cerevisiae, used in the bread making and beer industries as a microorganism, has an important industrial role. The simulation procedure represents then a necessary tool to understand clearly the baker's yeast fermentation process. The use of mathematical models based on mass balance equations requires the knowledge of the reaction kinetics, thermodynamics, and transport and physical properties. Models may be more or less complex, however they keep the basic feature of linking observations together into some pattern. A FORTRAN90-based program was developed to simulate the baker's yeast fermentation process in order to predict the dynamic behaviour of a well-mixed reactor. Mass balances written for all the components define a system of ordinary differential equations of initial value problem type (IVP). Considering the kinetics and the gas transfer rates relations as part of the differential system, a differential-algebraic system (DAE) can be defined. The simulation results were compared with the experimental values obtained in a laboratorial five-litre fermenter, operated in fed-batch mode. Prior to the parameter estimation procedure, an identification of the most significant model parameters was carried out. A heuristic sensitivity analysis was performed in order to adjust the model results with the experimental data. The Meyer and Roth method was used to minimise the objective function, defined as the sum of the relative square errors between the calculated and the experimental values (associated to the state variables: biomass, glucose and ethanol). The yield coefficients and the maximum uptake rate for glucose and oxygen were found the most significant parameters.

Palavras-chave : heuristic sensitivity analysis; numerical simulation; parameter estimation.

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