Kinetic modeling of Fischer–Tropsch-to-olefins process via advanced optimization

The reaction kinetics of a Fischer–Tropsch (FT) process to produce lower olefins was modeled utilizing the experimental data produced using an in-house synthesized iron-based catalyst. Along with FT chain growth reaction that is assumed to follow alkyl mechanism, water–gas shift reaction was also taken into consideration due to its significance. Not only the rate constants but also apparent activation energies were obtained via an integrated approach utilizing multiobjective and constrained nonlinear minimization methods in order to define a model valid at a temperature range instead of a single point. The adaption of a hybrid optimization method utilizing both population- and individual-based techniques enhanced prediction accuracy compared with the case where only multiobjective genetic algorithm is used. Thanks to the developed model, the effect of process parameters on product distribution was investigated. Finally, the kinetic model was compared with Anderson–Schulz–Flory model and the deviations observed were discussed.