Eugeniusz Molga

Aromatic nitrations by mixed acid. Slow liquid-liquid reaction regime

Aromatic nitrations by mixed acid have been selected as a specific case of a heterogeneous liquid-liquid reaction. An extensive experimental programme has been followed using adiabatic and heat-flow calorimetry and pilot reactor experiments, supported by chemical analysis. A series of nitration experiments has been carried out to study the influences of different initial and operating conditions such as temperature, stirring speed and sulphuric acid concentration. In parallel, a mathematical model to predict the overall conversion rate has been developed. In this paper the mathematical modelling and the implementation and experimental validation for benzene, toluene and chlorobenzene mononitration in the kinetic control regime (slow liquid-liquid reaction) are presented and discussed.

Neural network approach to support modelling of chemical reactors: problems, resolutions, criteria of application

Abstract New aspects of neural modelling of chemical reactors have been investigated in this study. An universal method to create a family of neural models, useful for the reactor and reacting system of any type, has been elaborated and presented. Based on this method a detailed analysis of the neural models has been performed. The proposed methods of modelling as well as a comparative analysis of the obtained results have been illustrated with the data obtained for a complex, catalytic hydrogenation of 2,4-dinitrotoluene performed at non-steady state conditions in a multiphase stirred tank reactor. The methods of choosing the input–output signals, the net architecture, the learning method, the number and quality of learning data have been proposed and their influence on the accuracy of obtained predictions have extensively been discussed. A comparison of two types of neural models: a global neural model and a hybrid neural model to a conventional reactor modelling has been performed. General conclusions and useful criteria have been formulated.

Dynamic filtration in biotechnology

In this paper the effectiveness of separation in different systems of dynamic filtration, both mechanical and crossflow filtration, has been compared. Apart from the filtration rate obtained under comparable conditions the energy demand for these processes has also been compared. The obtained results show that dynamic mechanical filtration can in some cases be more effective than the more commonly used crossflow filtration.

Aromatic nitrations by mixed acid. Fast liquid-liquid regime

Aromatic nitration by mixed acid was selected as a specific case of heterogeneous liquid-liquid reaction. An extensive experimental programme was followed using adiabatic and heat flow calorimetry and pilot reactor experiments, supported by chemical analysis. A series of nitration experiments was carried out to study the influence of different initial and operating conditions, such as temperature, stirring speed, feed rate and sulphuric acid concentration. In parallel, a mathematical model to predict the overall conversion rate was developed. In this paper, the mathematical modelling, implementation and experimental validation for mononitrations of benzene, toluene and chlorobenzene in the mass transfer controlled regime of fast liquid-liquid reactions are presented and discussed.

Modelling and Optimization of Semibatch Toluene Mononitration with Mixed Acid from Performance and Safety Viewpoints

Abstract The mononitration of toluene by mixed acid has been taken as a specific case of a heterogeneous reaction and a mathematical model that simultaneously takes into account mass transfer phenomena and chemical kinetics has been developed. Further, the effect of phase inversion on the overall reaction rate has been included. An extensive experimental programme has been followed using adiabatic and heat flow calorimetry, supported by chemical analysis. A series of toluene nitration experiments have been carried out to study the influences of different operating conditions such as temperature, stirring speed, feeding rate and H2SO4 concentration, and to compare these with the simulation predictions. The results and their implications for analysing and subsequently optimizing these type of processes from both performance and safety points of view are then discussed.

Mass transfer in gas-liquid Couette-Taylor flow in membrane reactor

A concept of membrane CTF (Couette-Taylor flow) reactor applicable to gas-liquid processes has been presented. Its fundamental hydrodynamic and kinetic properties have been discussed. In the experiments high values of the mass transfer coefficients, k L a, of the order of 0.1 s -1 have been obtained and a relatively weak influence of the liquid viscosity on the values of the mass transfer coefficients has been observed. To eliminate moving elements of the reactor, a replacement of the rotor by a static helical ribbon guide which forces the helicoidal flow of the fluid has been proposed for the same operating conditions.

Neural networks for modelling of chemical reaction systems with complex kinetics : oxidation of 2-octanol with nitric acid

Application of neural networks to model the conversion rates of a heterogeneous oxidation reaction has been investigated — oxidation of 2-octanol with nitric acid has been considered as a case study. Due to a more complex and unknown kinetics of the investigated reaction the proposed approach based on application of neural networks is an efficient and accurate tool to solve modelling problems. The elaborated hybrid model as well as the modelling procedure have been described in detail. Learning data used to train the networks have been extracted from the experimental results obtained in an extensive investigation programme performed with a RC1 Mettler-Toledo reaction calorimeter. The influence of different operating conditions on the accuracy and flexibility of the obtained results has been investigated and discussed. It has been found that with the proposed approach the behaviour of a semi-batch reactor, i.e. its concentration and heat flow time profiles, can be predicted successfully within a singular series of experiments; however, the generalisation of the neural network approach to all series of experiments was impossible.

Hybrid first-principle-neural-network approach to modelling of the liquid-liquid reacting system

Abstract Detailed investigations have been carried out to check the ability of multilayer neural networks to model the simultaneous mass transfer and chemical reaction in the liquid–liquid reacting system. In this approach the intrinsic reaction kinetics and diffusive mass transfer are represented by a black-box and only the input–output signals are analysed. The data for training of the net have been taken from the experiments performed in a RC1 Mettler Toledo reaction calorimeter. The hydrolysis of propionic anhydrite catalysed with sulphuric acid has been chosen as a testing reaction. The hybrid, first-principle–neural-network model has been defined to describe batch and semibatch stirred tank reactors operating at different conditions. Good accuracy and flexibility of the proposed approach have been obtained for a properly defined experimental programme supplying data for learning.

The Effect of Phase Inversion during Semibatch Aromatic Nitrations

The effect of phase inversion during semibatch aromatic nitrations is experimentally characterized and analysed. The influence of various parameters, i.e. interfacial area, effective heat-transfer coefficient and overall mass-transfer coefficient, is studied. The implications for optimizing nitrations are discussed from performance and safety points of view. The accumulation of unreacted nitric acid can be dangerous if accompanied by a phase inversion, owing to the fact that the rate may increase suddenly.

Axial dispersion in packed beds: the effect of particle size non-uniformities

Abstract The effect of particle size non-uniformities on axial dispersion coefficients during laminar liquid flow through packed beds has been studied. The investigations were carried out for binary mixtures of particles with diameters d1 = 0.169 mm and d1 = 0.360 mm. A generalized function to determine the increase of the axial dispersion coefficients in non-uniform beds relative to those obtained in uniform beds has been proposed.