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Lactic acid is an important product arising from the anaerobic fermentation of sugars. It is used in the pharmaceutical, cosmetic, chemical, and food industries as well as for biodegradable polymer and green solvent production. In this work, several bacterial strains were isolated from industrial ethanol fermentation, and the most efficient strain for lactic acid production was selected. The fermentation was conducted in a batch system under anaerobic conditions for 50 h at a temperature of 34 degrees C, a pH value of 5.0, and an initial sucrose concentration of 12 g/L using diluted sugarcane molasses. Throughout the process, pulses of molasses were added in order to avoid the cell growth inhibition due to high sugar concentration as well as increased lactic acid concentrations. At the end of the fermentation, about 90% of sucrose was consumed to produce lactic acid and cells. A kinetic model has been developed to simulate the batch lactic acid fermentation results. The data obtained from the fermentation were used for determining the kinetic parameters of the model. The developed model for lactic acid production, growth cell, and sugar consumption simulates the experimental data well.

In this work, mathematical modeling was employed to assess the dynamic behavior of the flash fermentation process for the production of butanol. This process consists of three interconnected units as follows: fermentor, cell retention system (tangential microfiltration), and vacuum flash vessel (responsible for the continuous recovery of butanol from the broth). Based on the study of the dynamics of the process, suitable feedback control strategies [single input/single output (SISO) and multiple input/multiple output (MIMO)] were elaborated to deal with disturbances related to the process. The regulatory control consisted of keeping sugar and/or butanol concentrations in the fermentor constant in the face of disturbances in the feed substrate concentration. Another objective was the maintenance of the proper operation of the flash tank (maintenance of the thermodynamic equilibrium of the liquid and vapor phases) considering that oscillations in the temperature in the tank are expected. The servo control consisted of changes in concentration set points. The performance of an advanced controller, the dynamic matrix control, and the classical proportional-integral controller was evaluated. Both controllers were able to regulate the operating conditions in order to accommodate the perturbations with the lowest possible alterations in the process outputs. However, the performance of the PI controller was superior because it showed quicker responses without oscillations.

In this work, the mathematical optimization of a continuous flash fermentation process for the production of biobutanol was studied. The process consists of three interconnected units, as follows: fermentor, cell-retention system (tangential microfiltration), and vacuum flash vessel (responsible for the continuous recovery of butanol from the broth). The objective of the optimization was to maximize butanol productivity for a desired substrate conversion. Two strategies were compared for the optimization of the process. In one of them, the process was represented by a deterministic model with kinetic parameters determined experimentally and, in the other, by a statistical model obtained using the factorial design technique combined with simulation. For both strategies, the problem was written as a nonlinear programming problem and was solved with the sequential quadratic programming technique. The results showed that despite the very similar solutions obtained with both strategies, the problems found with the strategy using the deterministic model, such as lack of convergence and high computational time, make the use of the optimization strategy with the statistical model, which showed to be robust and fast, more suitable for the flash fermentation process, being recommended for real-time applications coupling optimization and control.

The pretreatment of sugarcane bagasse with lime (calcium hydroxide) is evaluated. The effect of lime pretreatment on digestibility was studied through analyses using central composite design (response surface), considering pretreatment time, temperature, and lime loading as factors. The responses evaluated were the yield of glucose from pretreated bagasse after enzymatic hydrolysis. Experiments were performed using the bagasse as it comes from an alcohol/sugar factory (non-screened bagasse) and bagasse in the size range from 0.248 to 1.397 mm (screened bagasse) (12-60 mesh). It was observed that the particle size presented influence in the release of fermentable sugars after enzymatic hydrolysis using low loading of cellulase and beta-glucosidase (3.5 FPU/g dry pretreated biomass and 1.0 IU/g dry pretreated biomass, respectively).

Pretreatment procedures of sugarcane bagasse with lime (calcium hydroxide) or alkaline hydrogen peroxide were evaluated and compared. Analyses were performed using 2 x 2 x 2 factorial designs, with pretreatment time, temperature, and lime loading and hydrogen peroxide concentration as factors. The responses evaluated were the yield of total reducing sugars (TRS) and glucose released from pretreated bagasse after enzymatic hydrolysis. Experiments were performed using the bagasse as it comes from an alcohol/sugar factory and bagasse in the size range of 0.248 to 1.397 mm (12-60 mesh). The results show that when hexoses and pentoses are of interest, lime should be the pretreatment agent chosen, as high TRS yields are obtained for nonscreened bagasse using 0.40 g lime/g dry biomass at 70 degrees C for 36 h. When the product of interest is glucose, the best results were obtained with lime pretreatment of screened bagasse. However, the results for alkaline peroxide and lime pretreatments of nonscreened bagasse are not very different.

In this work, a systematic method to support the building of bioprocess models through the use of different optimization techniques is presented. The method was applied to a tower bioreactor for bioethanol production with immobilized cells of Saccharomyces cerevisiae. Specifically, a step-by-step procedure to the estimation problem is proposed. As the first step, the potential of global searching of real-coded genetic algorithm (RGA) was applied for simultaneous estimation of the parameters. Subsequently, the most significant parameters were identified using the Placket-Burman (PB) design. Finally, the quasi-Newton algorithm (QN) was used for optimization of the most significant parameters, near the global optimum region, as the initial values were already determined by the RGA global-searching algorithm. The results have shown that the performance of the estimation procedure applied in a deterministic detailed model to describe the experimental data is improved using the proposed method (RGA-PB-QN) in comparison with a model whose parameters were only optimized by RGA.

Soybean oil deodorized distillate is a product derived from the refining process and it is rich in high value-added products. The recovery of these unsaponifiable fractions is of great commercial interest, because of the fact that in many cases, the "valuable products" have vitamin activities such as tocopherols (vitamin E), as well as anticarcinogenic properties such as sterols. Molecular distillation has large potential to be used in order to concentrate tocopherols, as it uses very low temperatures owing to the high vacuum and short operating time for separation, and also, it does not use solvents. Then, it can be used to separate and to purify thermosensitive material such as vitamins. In this work, the molecular distillation process was applied for tocopherol concentration, and the response surface methodology was used to optimize free fatty acids (FFA) elimination and tocopherol concentration in the residue and in the distillate streams, both of which are the products of the molecular distiller. The independent variables studied were feed flow rate (F) and evaporator temperature (T) because they are the very important process variables according to previous experience. The experimental range was 4-12 mL/min for F and 130-200 degrees C for T. It can be noted that feed flow rate and evaporator temperature are important operating variables in the FFA elimination. For decreasing the loss of FFA, in the residue stream, the operating range should be changed, increasing the evaporator temperature and decreasing the feed flow rate; D/F ratio increases, increasing evaporator temperature and decreasing feed flow rate. High concentration of tocopherols was obtained in the residue stream at low values of feed flow rate and high evaporator temperature. These results were obtained through experimental results based on experimental design.

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 degrees 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.

Molecular distillation was studied for the separation of tocopherols from soya sludge, both experimentally and by simulation, under different operating conditions, with good agreement. Evaporator temperatures varied from 100 degrees C to 160 degrees C and feed flow rates ranged from 0.1 to 0.8 kg/h. The process pressure was maintained at 10(-6) bar, the feed temperature at 50 degrees C, the condenser temperature at 60 degrees C, and the stirring at 350 rpm. For each process condition, samples of both streams (distillate and residue) were collected and stored at -18 degrees C before tocopherols analyses. Owing to the differences between molecular weights and vapor pressures of free fatty acids and tocopherols, tocopherols preferentially remained in the residue at evaporator temperatures of 100 degrees C and 120 degrees C, whereas for higher temperatures (140 degrees C and 160 degrees C) and lower feed flow rate, tocopherols tended to migrate to the distillate stream.

In this work, a simulation procedure of a supercritical extraction process was developed through the use of the commercial simulator HYSYS (Hyprotech Ltd.), adapting the existing units to the operating conditions typical of the supercritical extraction process. The objective is to recover provitamin A (beta-carotene) from palm oil (esterified) using carbon dioxide/ethanol as the supercritical mixed solvent. This example characterizes the problem for recovering high added value product from natural sources, as the palm oil, which is desired by the market. Owing to the fact that esterified palm oil is a complex mixture, made by several components, in order to characterize this system in the simulator, it was necessary to create hypothetical components using the UNIFAC (universal function-group activity coefficients model) group contribution, because they are not present in a conventional database and, then, their physical properties must be estimated and/or predicted before the simulation. The optimization was carried out in each simulation for each equipment, in terms of operating conditions (temperature and pressure), in order to obtain the maximum recovery of carotenes. According to the results, it was possible to concentrate carotenes through two cycles of supercritical extraction with high yield. Furthermore, ethyl esters (biodiesel) were also obtained, as a byproduct of the proposed process, which can also be used as an alternative fuel, with the important characteristic that it is renewable.

Monoglycerides (MG) are emulsifiers widely used in food and pharmaceutical industries. Current industrial processes for MG production consist of the interesterification of triglycerides with glycerol (GL), in the presence of inorganic catalysts at high temperatures (> 200 degrees C). This reaction is known as glycerolysis and produces a mixture of approx 50% of MG. This level of concentration is suitable for many applications, although, for some specific uses like margarine, shortening, icing, and cream filling, require distilled MGs, which are purified MG (min. 90%) obtained by the molecular distillation process. Therefore, in this work, a 23 factorial design was employed to evaluate the effects of reaction parameters in the MG content after the interesterification reaction of refined soybean oil with GL in the presence of sodium hydroxide as catalyst. After that, the MG content in the reaction product was enhanced through the molecular distillation process in order to obtain distilled MG.

In this present article, genetic algorithms and multilayer perceptron neural network (MLPNN) have been integrated in order to reduce the complexity of an optimization problem. A data-driven identification method based on MLPNN and optimal design of experiments is described in detail. The nonlinear model of an extractive ethanol process, represented by a MLPNN, is optimized using real-coded and binary-coded genetic algorithms to determine the optimal operational conditions. In order to check the validity of the computational modeling, the results were compared with the optimization of a deterministic model, whose kinetic parameters were experimentally determined as functions of the temperature.

The transesterification of castor oil with ethanol in the presence of sodium ethoxide as catalyst is an exceptional option for the Brazilian biodiesel production, because the castor nut is quite available in the country. Chemically, its oil contains about 90% of ricinoleic acid that gives to the oil some beneficial characteristics such as its alcohol solubility at 30 degrees C. The transesterification variables studied in this work were reaction temperature, catalyst concentration and alcohol oil molar ratio. Through a star configuration experimental design with central points, this study shows that it is possible to achieve the same conversion of esters carrying out the transesterification reaction with a smaller alcohol quantity, and a new methodology was developed to obtain high purity biodiesel.

Soybean oil deodorized distillate (SODD) is a byproduct from refining edible soybean oil; however, the deodorization process removes unsaponifiable materials, such as sterols and tocopherols. Tocopherols are highly added value materials. Molecular distillation has large potential to be used in order to concentrate tocopherols, because it uses very low levels of temperatures because of the high vacuum and short operating time for separation and, also, it does not use solvents. However, nowadays, the conventional way to recover tocopherols is carrying out chemical reactions prior to molecular distillation, making the process not so suitable to deal with natural products. The purpose of this work is to use only molecular distillation in order to recover tocopherols from SODD. Experiments were performed in the range of 140-220 degrees C. The feed flow rate varied from 5 to 15 g/min. The objective of this study was to remove the maximum amount of free fatty acids (FFA) and, so, to increase the tocopherol concentration without add any extra component to the system. The percentage of FFA in the distillate stream of the molecular still is larger at low feed flow rates and low evaporator temperatures, avoiding thermal decomposition effects.

The objective of this work was to develop a model for an extractive ethanol fermentation in a simple and rapid way. This model must be sufficiently reliable to be used for posterior optimization and control studies. A hybrid neural model was developed, combining mass and energy balances with neural networks, which describe the process kinetics. To determine the best model, two structures of neural networks were compared: the functional link networks and the feedforward neural networks. The two structures are shown to describe well the process kinetics, and the advantages of using the functional link networks are discussed.