Modeling and Simulation of a FT Reactor for the Process Scale-up for Gtl-FPSO Development

GTL processes are emerging as a form of alternative energy sources. Korean Government is sponsoring research on several GTL processes, and GTL-FPSO aims to enable an FPSO system producing synthetic fuel out of stranded gas wells.

One of the most challenging parts of reactor and reaction systems is parameter estimations in reaction models minimizing differences between predicted and experimental values. Due to the dynamic complexity, combinatorial and highly nonlinear property of the models, conventional optimization theories used to fail. In this work, particle swarm optimization (PSO) method as a novel metaheuristic optimization is adopted for estimations of model parameters in reaction systems. Additionally, modifications of the essential model parameters in PSO are brought in. The new method takes advantages of nonlinearly changing adaptive strategy (aPSO) and defines a new changing combination of inertia weight and study factors. The proposed aPSO improves the performances of the basic version greatly and succeeds in parameter estimations in the three study cases of highly nonlinear (bio)chemical systems.