(257e) Optimization of a Dynamic Model of Fixed Bed Catalytic Reactor Utilizing Genetic Algorithms Technique

In the last decades, with the increase of the competitiveness of the world market (reduction of costs, prices increase of the productivity and efficiency of the productive processes) there was a great interest in to improve and to optimize the processes of chemical industries. Several optimization classic techniques have been used with this intention, but many of those techniques are not efficient, mainly when the problem is complex, and typically a high number of variables of the processes, non-linearity models that supply many possible solutions, and constraints that have to be considered lead the problem to be of difficult solution. As alternative a class of algorithms, denominated of Genetic Algorithms (an evolutionary algorithms category) present good potential to be used as a tool for complex and large scale systems. Genetic Algorithms (GAs) are general-purpose search techniques for resolution of complex problems. They are based on the genetics and natural evolution principles of the species. The GAs work through repeated modifications in an artificial structures population denominated of individuals (chromosomes or set of solutions) applying the selection, crossover, and mutation operators. The evaluation of optimization happens with an objective function (fitness) that determines the performance of the genetic process. The fitness could be understood as the capacity of the individuals to survive in a natural environment. In the chemical industry, the fixed bed catalytic reactors have a recognized importance, so much for the volume of products generated by them as for the economical amount of such products. Fixed bed catalytic reactors present complex behaviour due to phenomena taking place in the system especially interactions among heat and mass transfer. In reactors where strong exothermic reactions occurs one of the principal characteristics are the occurrence of hot spot, which normally is located towards the system entrance, which suddenly raises the temperature of the reactor in direction to a maximum. Consequently, temperature profiles must be inside of certain limits, because it takes to undesirable consequences, such as decrease of selectivity in the case of competitive reactions, deactivation of catalyst and especially the appearance of reactor temperature runaway. Reliable models depend on the insight of how the dominant physic-chemical mechanisms and external factors which affect the overall performance of the system. However, for optimizations, simplified models have to be used which can keep the essential characteristics of the reactor. In this work, a model for a fixed bed catalytic reactor, based on pseudo-homogeneous approach, which incorporates the thermal capacity of the fluid and solid, (Cp)g and (Cp)s, respectively was developed. The model studied has shown the main characteristics of the dynamic behaviour of fixed bed catalytic reactors, including the predictions of the inverse response phenomena. The objective of this work is to determine the ideal reactor length taking into account the dynamic behaviour of the systems specially bearing in mind that the flow rate is usually a manipulated variable which impacts the residence time and the temperature profiles. It is shown that the evaluation of reactor length should take into account the dynamic behaviour if high performance operation is required.