The mechanism models based on structure-oriented lumping (SOL) deliver a satisfactory prediction on the properties and yield distribution of the products from fluid catalytic cracking (FCC). However, with high complexity and low computing efficiency, such a model is increasingly unable to meet the needs of refineries to produce lighter and greener products using heavier and poorer feedstocks. Therefore, in this paper, a modeling approach hybridizing molecular mechanism and data models was proposed to describe the maximizing iso-paraffins (MIP) technology of the FCC process. This proposed model showed assured prediction accuracy with shortened computing time and thus was appropriate for online application. In this work, model simplification was carried out: less molecules and reactions (3078 and 5216, respectively) were adopted, along with a simplified reactor model, which largely reduced the computation load. CatBoost algorithm was also adopted for constructing a data model, to compensate for the accuracy loss resulting from the simplified SOL mechanism model. Combining with the mechanism model, it ensured the accuracy of prediction while greatly shortened the computing time. Furthermore, to overcome the strong coupling between the process variables to be solved, this work adopted the method of case-based reasoning (CBR) to optimize the process and expanded the case base with the prediction results of the hybrid model, which ensured the feasibility of the solution parameters and shortened the computing time. The hybrid model and the corresponding process optimization strategy proposed were then applied to an industrial FCC MIP process for verification. The results show that the hybrid model could assure the prediction accuracy (comparable with the conventional mechanism model) while the computing time was reduced from more than 20 h to less than 1 min. In the process optimization validation test, the total liquid yield increased by 1.19% on average for 43 out of 50 sets of operating configurations and the coke yield decreased by 1.05% on average. This work provides a good solution for the online process optimization of FCC.

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The objective of this study was to evaluate the application of Fourier transform infrared (FTIR) spectroscopy for detecting diffuse axonal injury (DAI) in a mouse model. Brain tissues from DAI mouse model were prepared with H&E, silver, and β-amyloid precursor protein (β-APP) immunohistochemistry stains and were also studied with FTIR. The infrared spectrum images showed high absorption of amide II in the subcortical white matter of the experimental mouse brain, while there was no obvious expression of amide II in the control mouse brain. The areas with high absorption of amide II were in the same distribution as the DAI region confirmed by the silver and β-APP studies. The result suggests that high absorption of amide II correlates with axonal injury. The use of FTIR imaging allows the biochemical changes associated with DAI pathologies to be detected in the tissues, thus providing an important adjunct method to the current conventional pathological diagnostic techniques.