Rafael Ramos de Andrade

Kinetics of ethanol production from sugarcane bagasse enzymatic hydrolysate concentrated with molasses under cell recycle

In this work, a kinetic model for ethanol fermentation from sugarcane bagasse enzymatic hydrolysate concentrated with molasses was developed. A model previously developed for fermentation of pure molasses was modified by the inclusion of a new term for acetic acid inhibition on microorganism growth rate and the kinetic parameters were estimated as functions of temperature. The influence of the hydrolysate on the kinetic parameters is analyzed by comparing with the parameters from fermentation of pure molasses. The impact of cells recycling in the kinetic parameters is also evaluated, as well as on the ethanol yield and productivity. The model developed described accurately most of the fermentations performed in several successive batches for temperatures from 30 to 38°C.

Estimation of Temperature Dependent Parameters of a Batch Alcoholic Fermentation Process

In this work, a procedure was established to develop a mathematical model considering the effect of temperature on reaction kinetics. Experiments were performed in batch mode in temperatures from 30 to 38°C. The microorganism used was Saccharomyces cerevisiae and the culture media, sugarcane molasses. The objective is to assess the difficulty in updating the kinetic parameters when there are changes in fermentation conditions. We conclude that, although the re-estimation is a time-consuming task, it is possible to accurately describe the process when there are changes in raw material composition if a re-estimation of parameters is performed.

Study of kinetic parameters in a mechanistic model for bioethanol production through a screening technique and optimization

The accurate description of the kinetics and robust modeling of biotechnological processes can only be achieved by incorporating reliable methodologies to easily update the model when there are changes in operational conditions. The purpose of this work is to provide a systematic approach with which to perform model parameters screening and updating in biotechnological processes. Batch experiments are performed to develop a mechanistic model, considering the effect of temperature on the kinetics, and further experiments (batch fermentations using sugar cane molasses from a different harvest) are used to validate the effectiveness of screening before parameters updating. The reduction in the number of kinetic parameters to be re-estimated enabled by the screening procedure reduces significantly the complexity of the optimization, which makes the updating procedure to be significantly quicker, while resulting in accurate performance of the updated model.

A LabVIEW-based intelligent system for monitoring of bioprocesses

Abstract The application presented in this study illustrates the usefulness of an automated monitoring system carried out in LabVIEW environment. The results obtained have show that it is possible to infer into a real-time basis the key variables in bioethanol fermentation using pH, turbidity, CO 2 flow rate and temperature on line measurements and a MLP-based Software Sensor. On-line monitoring system provided accurate online predictions of the concentrations during the fermentation process even when the secondary variables measurements were noisy. This study also will illustrate the usefulness of an automated monitoring system carried out in graphical programming environment.