Author:
López-Pérez P. A.,Puebla H.,Velázquez Sánchez H. I.,Aguilar-López R.
Abstract
Abstract
Living cells, type of substrate, enzymatic hydrolysis play an important role in the efficiency of ethanol production; however, the kinetic parameters of biochemical reactions necessary for modelling these processes are often not accessible directly through experiments. In this context, for the implementation of suitable operational strategies, it is necessary to have kinetic models able to describe the process as realistically as possible. This paper proposes a comparative study of two nonlinear techniques for parametric identification of a kinetic model for ethanol production from recycled paper sludge in order to improve process performance. The parameters of the model are optimized by two methods: using the Levenberg–Marquardt optimization approach and Genetic Algorithms. The performances of both techniques are evaluated using a numerical simulation. The optimal value of these parameters have been obtained based on Genetic Algorithm. Finally, the effect of parametric adjustment and dilution rate on productivity was demonstrated by changing the batch operation to the continuous operating model. The maximum ethanol concentration was about 13.25 g/l in batch process and about 13.9 g/l at Dilution rate: 0.005 1/h corresponding to a productivity of 0.327 in continuous process.
Subject
General Chemical Engineering
Cited by
7 articles.
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