Donatas Levišauskas

The optimization of biodiesel fuel production from microalgae oil using response surface methodology.

Biodiesel fuel was produced by the transesterification of microalgae oil using sodium hydroxide as a catalyst. The oil was extracted from heterotrophic cultivated algae biomass. The transesterification process was optimized using response surface methodologyto increase the yield of methyl esters. The Box–Behnken design and fractional factorial design 24-1 points were used to investigate the interaction of process variables, such as the methanol/oil molar ratio, the percentage of sodium hydroxide, the temperature, and the reaction time in the production of biodiesel fuel, and to predict the optimum process conditions for the FAME yield. Based on the results, the optimal conditions for the synthesis of biodiesel fuel were as follows: methanol/oil molar ratio, 7:1; catalyst concentration, 1.0% (by weight of algae oil); temperature, 67°C, and reaction time, 51 minutes. The yield of FAME was confirmed by gas chromatography analysis.

Inferential control of the specific growth rate in fed-batch cultivation processes

Inferential control algorithms and systems for set-point control of the specific growth rate in fed-batch cultivation processes are presented. Realization of the proposed control systems does not require mathematical model and a priori knowledge of the culture of microorganisms under control. Feed-back signal in PID control loops of the investigated systems is based on measurements of the O2 concentration in exhaust gas and the air supply rate, however, measurements of the other technological parameters related to the culture growth dynamics can also be applied.

Model based calculation of substrate/inducer feed-rate profiles in fed-batch processes for recombinant protein production

A model-based feed-rate profile optimization problem is discussed for the fed-batch recombinant protein production. Two optimization procedures, an evolutionary programming technique and a simplified method using the dynamic programming concept, are discussed and compared. Modeling as well as experimental results are presented.

An algorithm for adaptive control of dissolved oxygen concentration in batch culture

An effective automatic control algorithm for set-point control of dissolved oxygen concentration in batch culture has been developed. Adaptation of PI controller to the variable state of batch culture is based on analytically obtained functional relations between the controller parameters and the state variables: oxygen uptake rate, stirring speed, and saturation value of dissolved oxygen concentration, which are measured or estimated on-line. Results of experimental investigation of the adaptive control system are presented.

Model-based optimization of biosurfactant production in fed-batch culture Azotobacter vinelandii

Fed-batch cultivation of Azotobacter vinelandii 21was optimized for biosurfactant production. Optimization of feed-rate time profile and concentration of nutrient medium components in feeding solution is based on a hybrid mathematical model consisting of mass-balance equations for biomass, biosurfactant, volume of cultural liquid and substrate components: glucose, ammonia nitrogen and phosphate phosphorus. The rate of cultural liquid emulsification activity growth as well as the rates of ammonia nitrogen and phosphate phosphorus consumption is modelled by means of artificial neural network, while the rates of the other biochemical transformations are modelled by adequate kinetic relationships.

Data-based optimization of protein production processes

Abstract While data-based modeling is possible in various ways, data-based optimization has not been previously described. Here we present such an optimization technique. It is based on dynamic programming principles and uses data directly from exploratory experiments where the influence of the adjustable variables u were tested at various values. Instead of formulating the performance index J as a function of time t within a cultivation process it is formulated as a function of the biomass x. The advantage of this representation is that in most biochemical production processes J(x) only depends of the vector u of the adjustable variables. This given, mathematical programming techniques allow determining the desired optimal paths uopt(x) from the x-derivatives of J(x). The resulting uopt(x) can easily be transformed back to the u(t) profiles that can then be used in an improved fermentation run. The optimization technique can easily be explained graphically. With numerical experiments the feasibility of the method is demonstrated. Then, two optimization runs for recombinant protein formations in E. coli are discussed and experimental validation results are presented.

Technology for Treatment of Lipid-Rich Wastewater and Pipelines Clogged by Lipids Using Bacterial Preparation

Abstract The complex, effective and innovative cleaning technology for lipid-rich wastewater and pipelines contaminated by lipids, was developed. For this purpose, laboratory experiments were performed to verify the efficiency of bacterial preparation (Enterobacter aerogenes E13, Arthrobacter sp. N3 and Bacillus coagulans S1) to degrade the grease in water and in drainpipes. The results showed that selected microorganisms intensively degrade grease to light odourless precipitate, water and CO2, thus could be applied in industry. For optimization of technological cleaning processes, the response surface methodology was used. The optimal parameters for biological model wastewater treatment were determined: concentration of grease − 4.5–6.0 g/l, amount of bacterial preparation −5.5–6.0%, pH – 8–9. Due to optimization, the grease degradation rate increased by 20–30%. The optimization of drainpipe cleaning technology was achieved in two stages. During the first stage, the experiments were performed in laborato...

From Physics to Bioengineering: Microbial Cultivation Process Design and Feeding Rate Control Based on Relative Entropy Using Nuisance Time

For historic reasons, industrial knowledge of reproducibility and restrictions imposed by regulations, open-loop feeding control approaches dominate in industrial fed-batch cultivation processes. In this study, a generic gray box biomass modeling procedure uses relative entropy as a key to approach the posterior similarly to how prior distribution approaches the posterior distribution by the multivariate path of Lagrange multipliers, for which a description of a nuisance time is introduced. The ultimate purpose of this study was to develop a numerical semi-global convex optimization procedure that is dedicated to the calculation of feeding rate time profiles during the fed-batch cultivation processes. The proposed numerical semi-global convex optimization of relative entropy is neither restricted to the gray box model nor to the bioengineering application. From the bioengineering application perspective, the proposed bioprocess design technique has benefits for both the regular feed-forward control and the advanced adaptive control systems, in which the model for biomass growth prediction is compulsory. After identification of the gray box model parameters, the options and alternatives in controllable industrial biotechnological processes are described. The main aim of this work is to achieve high reproducibility, controllability, and desired process performance. Glucose concentration measurements, which were used for the development of the model, become unnecessary for the development of the desired microbial cultivation process.

An Approach To Identification Of Dynamic Model For Optimization Of Fed-Batch Fermentation Processes

A computation procedure is developed for identification of dynamic model intended for solving the biomass growth-related optimization problems at fed-batch fermentation processes. The model identification relies on exploiting a versatile structure model that covers several particular structure models commonly used in bioprocess engineering practice. The model parameters are found by using experimental data of batch or fed-batch fermentation processes and a consecutive identification procedure, which include the parameters preliminary estimation. Practical application of the proposed model identification procedure is demonstrated for solving the feed-rate optimization problem in fed-batch culture E.coli . DOI: http://dx.doi.org/10.5755/j01.itc.42.1.927

A SYSTEM FOR DISSOLVED OXYGEN CONTROL IN INDUSTRIAL AERATION TANK

The control system is developed for accurate set-point control of dissolved oxygen concentration in industrial aeration tank based on adaptation of PI controller to time-varying dynamics of the controlled process. The controller adaptation algorithm refers to the process state model-based transfer function that follows changes in process dynamics by updating the function parameters with on-line measurements of process variables, and the controller tuning rules developed for typical structure transfer function models. The control system was investigated via computer simulation of the dissolved oxygen concentration set-point control in an industrial aeration tank under process disturbances and set-point step changes. The control system demonstrates fast adaptation of PI controller parameters and noticeably higher accuracy control compared to that of ordinary fixed gain PI controller. DOI: http://dx.doi.org/10.5755/j01.itc.41.1.921