Analysis of the effective operating factors of Fischer-Tropsch synthesis; Investigation of modeling and experimental data
| Autor: | Hossein Atashi, Farhad Shahraki, Afshin Razmjooie |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Engineering
Mean squared error Correlation coefficient Artificial neural network business.industry Statistical parameter Energy Engineering and Power Technology Experimental data Statistical model 02 engineering and technology 021001 nanoscience & nanotechnology Geotechnical Engineering and Engineering Geology 01 natural sciences 010406 physical chemistry 0104 chemical sciences Fuel Technology Statistics Sensitivity (control systems) Response surface methodology 0210 nano-technology Biological system business |
| Zdroj: | Journal of Natural Gas Science and Engineering. 40:72-78 |
| ISSN: | 1875-5100 |
| DOI: | 10.1016/j.jngse.2017.02.004 |
| Popis: | In this study, the effect of three main variables such as pressure, temperature and H 2 /CO ratio at fixed space velocity, on Fishcer-Tropsch synthesis case study are investigated in a micro fixed-bed reactor by design experiment and artificial neural network. This study based on experimental data and statistical model. Response surface methodology and artificial neural network were applied for modeling and predicting of the experimental data for catalytic kinetic for the hydrogenation of carbon monoxide. We proposed a practical method to evaluate and modeling the experimental data by used two techniques. The capability and sensitivity analysis of two models were evaluated by some of statistical parameters such as correlation coefficient and mean square error. The error values of response surface methodology and artificial neural network model were calculated. There is a good unanimity between the experimental data and two models, but the artificial neural network model was stronger and more accurate than the response surface methodology model. Finally, all of statistical values and results were calculated. |
| Databáze: | OpenAIRE |
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