Fig. 9: Sensitivity analysis and optimal process condition results for naphtha 2 FCC. | Nature Communications

Fig. 9: Sensitivity analysis and optimal process condition results for naphtha 2 FCC.

From: Scale-up of complex molecular reaction system by hybrid mechanistic modeling and deep transfer learning

Fig. 9

a Effect of catalyst temperature on product yield. The line represents the predicted values, and the dots denote the experimental data. b Effect of catalyst temperature on gasoline composition. The line represents the predicted values, and the dots denote the experimental data. c Pareto frontier obtained using the NSGA-II algorithm, with maximum gasoline and i-paraffin yields as optimization objectives. The singled-out point represents the process conditions with the lowest gasoline yield (80.62 wt%) and the highest i-paraffin yield (34.24 wt%) within the Pareto solution set. The corresponding process conditions are listed in the inset table. d Carbon number distribution for naphtha 2. The size and color of the dots indicate the content of each substance in the feedstock. e Product carbon number distribution for tuned process condition. The size and color of the dots indicate the content of each substance in the product. Process condition: Feedstock temperature = 78 °C, Catalyst temperature = 670 °C, Catalyst-to-oil ratio (CTO) = 5.7, and Reaction time = 3.6 s. f Product molecular composition for tuned process condition. Process condition: Feedstock temperature = 78 °C, Catalyst temperature = 670 °C, CTO = 5.7, and Reaction time = 3.6 s. Source data are provided as a Source data file.

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