Effect of Process-Condition-Dependent Chain Growth Probability and Methane Formation on Modeling of the Fischer–Tropsch Process

Autor: Maki Matsuka, Katsuya Shimura, Tomohisa Miyazawa, Satoshi Hirata, Roger David Braddock, Toshiaki Hanaoka
Rok vydání: 2016
Předmět:
Zdroj: Energy & Fuels. 30:7971-7981
ISSN: 1520-5029
0887-0624
Popis: The Fischer–Tropsch (FT) process can be described by the Anderson–Schulz–Flory model, although it does not handle the methane kinetics accurately. The value of chain growth probability (α) in the model is largely dependent upon the process conditions. The purpose of the research is to combine a CH4 kinetic model and process-condition-dependent chain growth probability α model and to calibrate the model parameters against experimental data from the literature. The combined model clearly improved the model predictions when compared to experimental data. Sensitivity analysis of the combined model showed the importance of adsorption coefficients to the outputs from the combined model. Testing the reactor temperature and feedstock composition shows that the outputs can be optimized, depending upon the length of carbon chains required in the output, and also suggested the importance of incorporating the effects of process conditions in the modeling of the FT product distribution.
Databáze: OpenAIRE