Optimization Of Chemical Reactors Research Articles

KINETICS QUASIINVARIANTS OF CHEMICAL REACTIONS IN OPEN SYSTEMS

The methods of nonequilibrium multi-experiments are one of the new approaches to solving inverse problems of chemical kinetics and optimization of chemical reactors. Currently, these methods are developed only for closed isothermal systems. In this paper, a generalization of the dual-experiment method and its extended version of the multi-experiment method for open systems is obtained, which allows to determine the approximate kinetic invariants (quasiinvariants) of chemical reactions in open continuous stirred tank reactor. The multi-experiment method for open systems is based on conducting two or more special nonequilibrium (unsteady) experiments under certain conditions. For nonlinear reactions of arbitrary complexity (multi-step, multi-equilibria), simple relations are obtained that allow to calculate the conditions for nonequilibrium experiments necessary for the identification of the reaction mechanism under study. The method allows to use any permissible values, except equilibrium ones, as initial values of reagent concentrations. The technique of carrying out multi-experiments and performing the necessary numerical calculations based on the multiple integration of systems of ordinary differential equations under different initial conditions is developed. The examples of using the developed method for one-stage linear and two-stage nonlinear reactions with two and three reagents are given. Found with the help of this method, the kinetic curves of the nonequilibrium quasiinvariants compared with the nonequilibrium curves of change of concentrations during the whole reaction. It is shown that quasiinvariant curves change within narrower limits than concentrations in different experiments, i.e. remain practically constant in time. The obtained results are also applicable for open nonisothermal systems.

Optimal industrial reactor design: development of a multiobjective optimization method based on a posteriori performance parameters calculated from CFD flow solutions

The increase in the use of biofuels raised new challenges to engineering problems. In this context, the optimization of chemical reactors, particularly bioreactors and photobioreactors, is crucial to improve the production of biofuels in a sustainable manner. This paper reports the development of an optimization method and its application to the design of a continuous flow bioreactor envisaged to be used in industrial fermentation processes. Mass and momentum conservation equations are simulated via CFD and specific a posteriori performance parameters, determined from the flow solution, are fed into a multiobjective evolutionary algorithm to obtain corrections to the parameters of the geometrical configuration of the reactor. This heuristics is iterated to obtain an optimized configuration vis-à-vis the flow aspects portrayed by the performance parameters, such as the shear stress and the residence time variations. An open source computer package (PyCFD-O) was developed to perform CFD simulations and the optimization processes automatically. First, it calls the pre-processor to generate the computational geometry and the mesh. Then it performs the simulations using OpenFOAM, calculates the output parameters and iterates the procedure. The PyCFD-O package has proved reliable and robust in a test case, a ∼1 m3 continuous fermentation reactor. The multiobjective optimization procedure actually corresponds to search for the Pareto frontier in the solution space characterized by its geometric parameters and the associated performance parameters (dispersion o residence times and shear stresses). Optimal design configurations were obtained representing the best tradeoff between antagonistic objectives, i.e. the so-called non-dominant solutions.

Hp-Adaptive spectral element solver for reactor modeling

The study, analysis and optimization of chemical reactors has shown a significant increase in complexity of the models used during the last decades. This complexity increased the computational cost of the models demanding the development of efficient solution techniques. This paper discusses the implementation of an hp-adaptive refinement technique applied to a least-squares spectral element formulation as a mathematical framework for reactor modeling. The refinement is based on an estimate of the local Sobolev regularity index of the underlying solution by monitoring the decay rate of its Legendre expansion coefficients. The performance of the method is demonstrated numerically by using an analytical test case.

Core of Chemical Reaction Engineering: One Industrial View

Chemical reaction engineering (CRE) is expanding in scope and breadth through the application of the core CRE principles to new problems in emerging technologies, through the application of new techniques to the more effective solution of traditional problems, and through the integration of the widely varied CRE activities into broad, powerful systems descriptions. Catalysis, chemical kinetics, transport phenomena, applied mathematics, and the modeling, design, and optimization of chemical reactors are the core and the intellectual basis of CRE. The CRE discipline will contribute significant, tangible improvements to the emerging technologies, such as biotechnology, microelectronics, and advanced materials; will further advance existing technologies in petroleum refining, petrochemicals, chemicals, and pharmaceuticals; will contribute to protecting the environment; and above all will provide new systematic knowledge and generic tools. New analytical instrumentation is providing more quantitative information on complex reaction and product mixtures, on catalyst structures, and on catalytic reaction mechanisms. Major advances in computing speed and marked changes in computer architecture, e.g., massively parallel processing, are providing new opportunities for advancement of catalyst, reactor, and process technologies and for rapid quantification and advancement in the emerging technologies, which will extend from the microscale molecular level to macroscale integration into processes and total systems. To meet the challenges of the future, strenghtening core components of CRE through interdisciplinary teaming will experts in other fields is essential. This effective teaming should be enhanced by powerful global computer networks, could reduce fragmentation of the CRE profession, and provides a mechanism for enhanced development of its core disciplines

Recent Progress in the Development of Algorithms and Software for Large Scale Parameter Estimation Problems in Chemical Reaction Systems

Abstract Problems of modelling, simulation and optimization of chemical reactors have steadily grown in importance and complexity in recent years. The present paper intends to outline some new developments in numerical algorithms for parameter estimation problems that have proven a powerful aid in the difficult and involved modelling process. Special emphasis is put on the practical performance of new algorithmic concepts, and on their realization in fast, reliable and widely applicable software tools.

The optimization of chemical reactors by the delayed addition of reactant

In certain cases it is possible to selectively increase the yield of a desired product from a batch reactor of given batch time or tubular reactor of given length by delaying the addition of one or more reactants to the reacting mixture. A general criterion is derived to distinguish cases in which delay is advantageous, and the complete optimum addition rate policy is derived for one particular set of parallel reactions.

Optimization of chemical reactors with respect to flow configuration

An algebraic structure is derived which relates changes in reactor performance to small changes in the mixing pattern, or flow configuration, of the system in which the reactions are carried out. This can serve as a basis for optimization of the performance, with respect to the flow configuration, by successive small improvements.

The determination of optimum operating conditions by the methods of dynamic programming

AbstractThe mathematical technique known as dynamic programming is here introduced as a tool in the optimization of chemical reactors. The structure of the optimal problem is first analysed and two of the simpler problems (optimal conditions for a single reaction in a sequence of stirred tanks and a tubular reactor) are solved. A more abstract presentation of the principles of dynamic programming is then given followed by an exposition of its application to quite general optimal problems with three of the principle types of reactor, namely the stirred tank, the adiabatic bed and the tubular or batch reactor.