5 years ago

Parametric Study and Multiobjective Optimization of Fixed-Bed Fischer–Tropsch (FT) Reactor: The Improvement of FT Synthesis Product Formation and Synthetic Conversion

Parametric Study and Multiobjective Optimization of Fixed-Bed Fischer–Tropsch (FT) Reactor: The Improvement of FT Synthesis Product Formation and Synthetic Conversion
Miroslaw Lech Wyszynski, Nima Moazami, Athanasios Tsolakis, Kiyarash Rahbar
A mathematical model of a fixed-bed reactor for Fischer–Tropsch synthesis (FTS) over 37% Co/SiO2 catalyst was developed to investigate the performance of the whole process for products’ selectivity and syngas conversion. The model was capable of calculating the changes of reactant and products’ concentrations, partial pressures, conversion, and selectivity. In a previous study, a series of combined novel FT and water gas shift (WGS) reaction mechanisms (eight elementary FT reaction pathways along with seven WGS kinetics models) were developed in order to calibrate and validate the mathematical model along with reaction kinetics at different experimental conditions. Such mathematical models with reaction networks can be used as a key tool to emphasize the most significant facts of FTS catalysis and chemistry. Integration of the global search optimization algorithm with the developed model was explained for estimation of kinetics parameters. Data analyses were carried out to ensure that the predicted model results as well as kinetic parameters are significantly relevant and physically meaningful. Parametric studies were performed to numerically investigate the effects of operating conditions (e.g., reaction temperature, total pressure, space velocity, and H2/CO molar ratio) on products’ selectivity and reactant conversion. These parameters were then included in a multiobjective optimization in MATLAB using NSGA-II to optimize the CO2 and HC products’ selectivity and syngas conversion. The optimization process gives rise to a set of trade-off optimal solutions (Pareto-optimal solutions) which is used as a dynamic database depending on the specific requirement. A different operating condition can be selected from such a database which privileges the optimization of a particular output (e.g., conversion and selectivity).

Publisher URL: http://dx.doi.org/10.1021/acs.iecr.7b02025

DOI: 10.1021/acs.iecr.7b02025

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