Improving the economic performances of the beet-sugar industry

General trend of free trade at the regional level as well as in the direction of European Union has motivated sugar factories located in Serbia to invest into technologies that are more efficient in order to make their products more competitive in the markets of Europe. Until 2005, the project of energy efficiency improvement in Serbian sugar factories was conducted in Crvenka and Žabalj. Now, they have energy consumption around 1 MJ/kg beet, in contrast to the previous consumption of 1.2 up to 1.5 MJ/kg beet. Further improvements are possible but investments would be high. A result of measurements taken during 2006, after the sugar factory "Donji Srem" - Pećinci was reconstructed showed that a considerable saving has been achieved. The first set of measurements showed that the energy consumption was 1.01 MJ/kg beet, which was 20% higher than intended, but at the same time energy savings were about 30% lower with respect to the values before the reconstruction

Microfiltration of distillery stillage: Influence of membrane pore size

Stillage is one of the most polluted waste products of the food industry. Beside large volume, the stillage contains high amount of suspended solids, high values of chemical oxygen demand and biological oxygen demand, so it should not be discharged in the nature before previous purification. In this work, three ceramic membranes for microfiltration with different pore sizes were tested for stillage purification in order to find the most suitable membrane for the filtration process. Ceramic membranes with a nominal pore size of 200 nm, 450 nm and 800 nm were used for filtration. The influence of pore size on permeate flux and removal efficiency was investigated. A membrane with the pore size of 200 nm showed the best filtration performance so it was chosen for the microfiltration process

Optimization of cultivation medium for the production of antibacterial agents

Optimization of the cultivation medium for production of antibiotic effective against pathogenic bacteria Staphylococcus aureus using strain of Streptomyces spp. isolated from the environment represents the aim of this study. After the biosynthesis, the medium was analyzed by determining residual sugar and nitrogen, and the antibiotic activity was determined using diffusion-disc method. Experiments were carried out in accordance with the Box-Behnken design, with three factors varied on three levels (glucose: 10.0, 30.0 and 50.0 g/L; soybean meal: 5.0, 15.0 and 25.0 g/L; phosphates: 0.5, 1.0 and 1.5 g/L) and for the optimization of selected parameters Response Surface Methodology was used. The obtained model with the desirability function of 0.985 estimates that the lowest amounts of residual sugar (0.89 g/L) and nitrogen (0.24 g/L) and the largest possible inhibition zone diameter (21.88 mm) that with its antibiotic activity against S. aureus creates the medium containing 10.0 g/L glucose, 5.0 g/L soybean meal and 1.04 g/L phosphates

2D simulation and analysis of fluid flow between two sinusoidal parallel plates using lattice Bolzmann method

In order to obtain a better heat transfer, it is important to enhance fluid mixing in heat exchangers. Since there are negative effects when heat exchangers are operating in turbulent regime (like significant pressure drop, increased size of the pump) it is necessary to apply the techniques which would provide better fluid mixing when heat exchangers are operating in laminar regime. Investigations have shown that use of sinusoidal instead of flat plates results in this effect. This study is a result of two dimensional simulation of fluid flow between two parallel sinusoidal plates. Simulation was done with the use of modified Openlb code, based on lattice Boltzmann method. Reynolds number was varied from 200 to 1000, and space between the plates was varied from 3cm to 5 cm. Results showed that sinusoidal plates enhance fluid mixing, especially with greater values of Re and smaller space between the plates, which is in agreement with previous investigations

Influence of the geometry on the riser gas holdup in an external-loop airlift reactor: empirical and neural network modelling

Experimental studies on the effect of geometrical characteristics (restriction orifice free area and sparger configuration) on the riser gas holdup of an external-loop airlift reactor have been conducted in this paper. The impact of the addition of non-coalescing media, such as n-butanol, was also investigated. In general, the decrease in the restriction orifice free area led to a substantial increase (up to 90%) in the riser gas holdup. The addition of n-butanol effected gas holdup to a lesser extent, as it increased the gas holdup in the range of 4-15%, depending on the restriction orifice free area. On the other hand, the impact of the sparger type was observed only at lower gas velocities, for which the sinter plate increased the gas holdup up to 20% in comparison to the single orifice. The paper also presents an empirical correlation for the estimation of the riser gas holdup with an average relative error of 7%. Finally, a neural network model with an average relative error of 2.4% was proposed. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. 172025

Performance of falling film plate evaporators in reconstructed multiple-effect evaporation station in sugar factory

General trend of free trade in regional level as well as in the direction of European Union has motivated sugar factories located in Serbia to invest into technologies that are more efficient in order to make their products more competitive at the markets in Europe. The aim of this work was to evaluate effects of falling film plate evaporators on the energy consumption of evaporation plant, as well as to validate performance of this type of evaporators. It was found that this type of evaporator decreased energy requirements and in the same time evaporation process was more effective due to high values of heat transfer coefficients.

Multi-objective optimization of microfiltration of baker’s yeast using genetic algorithm

This paper presents a multi-objective optimization model by applying genetic algorithm in order to search for optimal operating parameters of microfiltration of baker’s yeast in the presence of static mixer as a turbulence promoter. The operating variables were the suspension concentration, transmembrane pressure, and feed flow rate. Two conflicting objective functions, maximizing the permeate flux and maximizing the reduction of energy consumption, were considered. This multi-objective optimization problem was solved by using the elitist non-dominated sorting genetic algorithm in the Matlab R2015b software. The Pareto fronts along with the process decision variables correspondding to the optimal solutions were obtained. It was found that lower suspension concentrations (2-4.5 g/L), feed flow rate in the range 109-127 L/h, and transmembrane pressure of 1 bar were the optimal process parameters which yielded maximum permeate flux (177-191 L/(m2h)) and maximum reduction of energy consumption (44-50%). Finally, the results were compared with the previously published results obtained by applying desirability function approach. Given that genetic algorithms have generated multiple solutions in a single optimization run, the study proved that genetic algorithms are preferable to classical optimization methods. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. TR-31002

Optimization of the flux values in multichannel ceramic membrane microfiltration of Baker`s yeast suspension

The objective of this work was to estimate the effects of the operating parameters on the baker's yeast microfiltration through multichannel ceramic membrane. The selected parameters were transmembrane pressure, suspension feed flow, and initial suspension concentration. In order to investigate the influence and interaction effects of these parameters on the microfiltration operation, two responses have been chosen: average permeate flux and flux decline. The Box-Behnken experimental design and response surface methodology was used for result processing and process optimization. According to the obtained results, the most important parameter influencing permeate flux during microfiltration is the initial suspension concentration. The maximum average flux value was achieved at an initial concentration of 0.1 g/L, pressure around 1.25 bars and a flow rate at 16 L/h. [Projekat Ministarstva nauke Republike Srbije, br. TR 31002

Flux intensification during microfiltration of distillery stillage using a kenics static mixer

The present work studies the effect of operating parameters (pH, feed flow rate, and transmembrane pressure) on microfiltration of distillery stillage. Experiments were conducted in the presence of a Kenics static mixer as a turbulence promoter, and its influence on the flux improvement and specific energy consumption was examined. Response surface methodology was used to investigate the effect of selected factors on microfiltration performances. The results showed that response surface methodology is an appropriate model for mathematical presentation of the process. It was found that the use of a static mixer is justified at the feed flow rates higher than 100 L/h. In contrast, the use of a static mixer at low values of feed flow rate and transmembrane pressure has no justification from an economic point of view. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. TR 31002

Artificial neural network approach to modeling of alcoholic fermentation of thick juice from sugar beet processing

In this paper the bioethanol production in batch culture by free Saccharomyces cerevisiae cells from thick juice as intermediate product of sugar beet processing was examined. The obtained results suggest that it is possible to decrease fermentation time for the cultivation medium based on thick juice with starting sugar content of 5-15 g kg-1. For the fermentation of cultivation medium based on thick juice with starting sugar content of 20 and 25 g kg-1 significant increase in ethanol content was attained during the whole fermentation process, resulting in 12.51 and 10.95 dm3 m-3 ethanol contents after 48 h, respectively. Other goals of this work were to investigate the possibilities for experimental results prediction using artificial neural networks (ANNs) and to find its optimal topology. A feed-forward back-propagation artificial neural network was used to test the hypothesis. As input variables fermentation time and starting sugar content were used. Neural networks had one output value, ethanol content, yeast cell number or sugar content. There was one hidden layer and the optimal number of neurons was found to be nine for all selected network outputs. In this study transfer function was tansig and the selected learning rule was Levenberg-Marquardt. Results suggest that artificial neural networks are good prediction tool for selected network outputs. It was found that experimental results are in very good agreement with computed ones. The coefficient of determination (the R-squared) was found to be 0.9997, 0.9997 and 0.9999 for ethanol content, yeast cell number and sugar content, respectively