Tibor Chován

Process dynamics and temperature control of fed-batch reactors

Abstract The dynamics of a fed-batch reactor was studied using the detailed first principle model of the system. The conditions of reaction runaway, the typical sources of hazardous operation in fed-batch techniques are determined. Considering these conditions a model-based control scheme is proposed to ensure robustness. When the stability criterion predicts that the range of operation is safe the cooling is set to its maximum and the temperature is controlled by the reactant feed. Otherwise the reactant feed is stopped and the flow rate of the cooling medium is the control variable.

Two variable semi-empirical and artificial neural-network-based modeling of peptide mobilities in CZE: The effect of temperature and organic modifier concentration

This work was focused on investigating the effects of two separation influencing parameters in CZE, namely temperature and organic additive concentration upon the electrophoretic migration properties of model tripeptides. Two variable semi‐empirical (TVSE) models and back‐propagation artificial neural networks (ANN) were applied to predict the electrophoretic mobilities of the tripeptides with non‐polar, polar, positively charged, negatively charged and aromatic R group characteristics. Previously published work on the subject did not account for the effect of temperature and buffer organic modifier concentration on peptide mobility, in spite of the fact that both were considered to be influential factors in peptide analysis. In this work, a substantial data set was generated consisting of actual electrophoretic mobilities of the model tripeptides in 30 mM phosphate buffer at pH 7.5, at 20, 25, 30, 35 and 40°C and at four different organic additive containing running buffers (0, 5, 10 and 15% MeOH) applying two electric field strengths (12 and 16 kV) to assess our mobility predicting models. Based on the Arrhenius plots of natural logarithm of mobility versus reciprocal absolute temperature of the various experimental setups, the corresponding activation energy values were derived and evaluated. Calculated mobilities by TVSE and back‐propagation ANN models were compared with each other and to the experimental data, respectively. Neural network approaches were able to model the complex impact of both temperature and organic additive concentrations and resulted in considerably higher predictive power over the TVSE models, justifying that the effect of these two factors should not be neglected.

Control Structures Based on Constrained Inverses

Present paper proposes a well structured control solution for the local control level allowing the integration of different types of engineering information into the control algorithm. Based on a comparative study of the structures of PID and IMC controllers a novel control structure with two degrees of freedom (or three if the possibility of adaptation is considered too) is defined. The application of the new control structure is illustrated by the example of the temperature control in a laboratory water heater system.

Hybrid convolution model and its application in predictive pH control

Abstract This paper presents a new method for synthesising chemical process models that combines prior knowledge and fuzzy models. The hybrid convolution model consists of a fuzzy model based steady-state, and an impulse response model based dynamic part. Prior knowledge enters to the dynamic part as a resident time distribution model of the process. The proposed approach is applied in the modelling and model based control of a highly nonlinear pH process.

CFD models in the development of electrical waste recycling technologies

Nowadays electrical waste (EW) recycling has become a practical way to provide raw material for new devices. Computer parts such as memory, motherboard or other parts contain large amount of metals from which the recovery of precious metals and copper represents the highest economical potential. With a proper chemical treatment these metals can be efficiently extracted and separated from the actual waste. For this task a specially designed leaching reactor, equipped with a perforated rotating drum, was used. This work is aimed at investigating if computational fluid dynamics (CFD) tools can be efficiently applied to model the chemical reactor used to dissolve the metals from the EW. First a hybrid CFD-compartment approach was developed to describe the dissolution process in the leaching reactor while the CFD models were used to model the hydrodynamics of the process. Based on the detailed model containing momentum and component mass balance the developed simulator could be used to enhance the performance of the existing reactor system. For the modelling studies COMSOL Multiphysics was used as CFD software.

Compartment model structure identification with qualitative methods for a stirred vessel

Solving process design, process optimization, safety analysis and other problems widely relies on mathematical models of the process. To solve problems related to mixing, detailed models such as compartment models or computational fluid dynamics (CFD) models are required. Compartment modelling generally uses four basic compartments: the mixer (M), the distributor (D), the perfectly mixed reactor and the ideal plug flow reactor (PFR). The main modelling tasks using compartment models are defining the structure of the compartment model and determining the parameters of the connections between the compartments. Hence, a qualitative approach was developed to support this identification process. Qualitative methods can be applied to analyse experimental data and to compress the information content of a time series. The primary goal of this study is to present an algorithm based on qualitative analysis that can be used to identify a compartment model structure based on the hydrodynamic measurement data of a stirred reactor.

Adaptive optimizing control algorithm for a CSTR

Abstract The optimizing adaptive control problem for a CSTR is formulated. The local control algorithm is based on the so-called predictor-corrector principle. The actual problem is the A + B → C (product) exothermic chemical reaction and the objective function is a linear combination of the product purity and the production rate. Some of the control parameters are determined a priori while others can be corrected on the basis of measurements. A detailed chemical engineering model makes possible the application of an adaptive inferential control scheme tracing back the product concentration to the measurement of temperature and flow rate. The good performance and robustness of the control algorithm are demonstrated by simulation studies.

Runaway of Chemical Reactors: Parametric Sensitivity and Stability

Although the runaway phenomenon is well known, an exact consistently used definition does not exist. Present paper is focused on the relation of reactor runaway and parametric sensitivity to stability. The relationship between criteria for reactor runaway and for thermal stability is also pointed out. Based on this critical review new methods based on parametric sensitivity and stability analysis for reactor runaway analysis are proposed in the paper. General runaway criteria based on the application of Ljapunov’s indirect method in the geometric and phase space have been developed. To illustrate the relation of the proposed reactor stability analysis to the commonly used runaway criteria a first order reaction was chosen. The application of the suggested method is also presented on a more complex problem, the Uckron-I test problem.

Tendency model-based improvement of the slave loop in cascade temperature control of batch process units

The dynamic behaviour of batch process units changes with time and this makes their precision control difficult. The aim of this paper is to highlight that the slave process of batch process units can have a more complex dynamics than the master loop has, and very often this could be the reason for the non-satisfying control performance. Since the slave process is determined by the mechanical construction of the unit, the above mentioned problem can be effectively handled by a model-based controller designed using an appropriate nonlinear tendency model. The paper presents the structure of the tendency model of typical slave processes and presents a case study where real-time control results show that the proposed methodology gives superior control performance over the widely applied cascade PID control scheme.

CFD Modelling and Video Analysis Based Model Validation for a Stirred Reactor

Abstract Investigation of mixing in a stirred tank is an important part of chemical reactor design, optimization or other complex engineering tasks. Computational Fluid Dynamics models are good tools to model the developing flow field in a stirred system; however, an experimental procedure is necessary to validate the model. In our research different geometries were analyzed, and a video based method was developed to validate the CFD simulation results.