(257f) Selectivity Maximization of Maleic Anhydride Production through Genetic Algorithm Technique

Maleic anhydride has numerous industrial uses and is of significant commercial interest worldwide. The primary use of maleic anhydride is in the manufacture of polyester and alkyd resins. These resins are added to fiberglass reinforced plastics to make a strong, lightweight, and corrosion resistant material that is found in boats, autos, trucks, pipelines and electrical goods. In a secondary capacity, maleic anhydride (MA) is employed in the manufacture of lacquers, lube-oil additives, and agricultural products. The addition of MA to drying oils decreases the required drying time and improves the coating quality of lacquers; dispersants derived from MA prolong oil change intervals and improve the efficiency of automotive engines. Agricultural products made from MA include herbicides, pesticides, and plant growth regulators. Furthermore, fumaric and maleic acid are important MA derivatives used in paper sizing resins and as food and beverage acidulants. One of the synthesis routes for the production of maleic anhydride is based on the direct air oxidation of Benzene over vanadium pentoxide catalyst. An excess of air is applied, and a low Benzene concentration must be utilized in order not to exceed the flammability limit of the mixture, but the reactant Benzene cannot be recovered economically so the reactor must operate at high yields. In order to achieve high operational performance (high conversion, yield and selectivity) an optimization study is necessary since the process is multivariable and non-linear. Bearing this in mind, a pseudo-homogeneous bidimensional dynamic model for fixed bed catalytic reactors was developed taking into account variations in the physical properties of the fluid and their impact on the heat and mass transfer coefficients, with the objective to maximize the selectivity of Maleic Anhydride through the Genetic Algorithm (GAs) technique. The genetic algorithms are based on the genetics and natural evolution principles of the species. The mechanism of the Genetic Algorithms technique occurs with successive modifications of the individuals or chromosomes (artificial structures) of population through the application of selection, crossover, and mutation operators. The application of Genetic Algorithms needs to develop a representative objective function of the reactor model, where this objective function evaluates the quality of determined solutions, being used as main criterion in approaches of great potential in industrial applications. The coding basic recommendations were considered. The interest of this work is to show that the Genetic Algorithms technique can be useful to MA production maximization, obtaining good results with operational improvements (reduction of undesired product rate ? the main by-products of the reaction are CO2 and H2O). The results shown that, the method can be use in a robust procedure which allows the reactor to be operated at high level of performance.