Modeling a pilot fixed-bed hydrocracking reactor via a kinetic base and neuro-fuzzy method

Abstract

Hydrocracking is a very important refining process used to upgrade low cost vacuum gas oil (VGO) into precious products like gasoline and diesel. In this present work, the hydrocracking of VGO using a dual functional amorphous catalyst is studied. Hydrocracking is carried out at pilot plant scale under the following reaction conditions: pressure of 156 bar, hydrogen-to-oil ratio of 1780 Nm3/Sm3, LHSV from 0.5 to 2 h–1 and temperatures from 380 to 440°C. The effluent of the reactor based on the most value added products is characterized to dry gas, light naphtha, heavy naphtha, kerosene, diesel and unconverted VGO. Then, a 6-lump discrete lumping approach with a hydrocracking reaction scheme with 15 reactions is developed for the prediction of the yield of hydrocracking products. The pilot tests demonstrated that performing experiments beyond the recommended temperature and LHSV by catalyst vendor not only shows unstable conditions but also changes the hydrocracking behavior of the catalyst. Then, to simulate the behavior of the reactor, two kinds of models, kinetic base model and neuro-fuzzy logic model, were developed to estimate the yields of hydrocracking products and simulate the behavior of the hydrocracking reactor. It is concluded that the fuzzy-logic approach is better than the kinetic base approach in the estimation accuracy, but the kinetic base approach can give information on the reaction path and functionality of the catalyst.