(599ap) 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.