A two-dimensional discrete lumped model for a trickle-bed vacuum gas oil hydrocracking reactor

Hydrocracking: A Perspective towards Digitalization

In a world of fast technological advancements, it is increasingly important to see how hydrocracking applications can benefit from and adapt to digitalization. A review of hydrocracking processes from the perspective of modeling and characterization methods is presented next to an investigation on digitalization trends. Both physics-based and data-based models are discussed according to their scope of use, needs, and capabilities based on open literature. Discrete and continuous lumping, structure-oriented lumping, and single event micro-kinetic models are reported as well as artificial neural networks, convolutional neural networks, and surrogate models. Infrared, near-infrared, ultra-violet and Raman spectroscopic methods are given with their examples for the characterization of feed or product streams of hydrocracking processes regarding boiling point curve, API, SARA, sulfur, nitrogen and metal content. The critical points to consider while modeling the system and the soft sensor are reported as well as the problems to be addressed. Optimization, control, and diagnostics applications are presented together with suggested future directions of interdisciplinary studies. The links required between the models, soft sensors, optimization, control, and diagnostics are suggested to achieve the automation goals and, therefore, a sustainable operation.

Computational Fluid Dynamic Modeling and Simulation of Hydrocracking of Vacuum Gas Oil in a Fixed-Bed Reactor

A four-lump computational fluid dynamic (CFD) model was proposed for the investigation of vacuum gas oil hydrocracking in a trickle-bed reactor. The experiment was conducted at 360-390 °C and 146 bar in the reactor at three different flow rates. It was found that the modeling predictions of vacuum gas oil cracking agreed well with the experimental measurements. Furthermore, the developed model analyzed the effects of the feed flow rate in the reactors on the concentration distribution and product yield. The maximum yields of the products including distillate (31%), naphtha (14%), and gas (3%) were obtained at the lowest feed flow rate. However, the feed flow rate enhancement from 0.1568 to 0.2059 kg·h^-1 led to the increasing feed concentration and reducing the product concentration at the outlet of the reactor. The latter phenomenon was happened due to the decreasing feed residence time with the increasing mass flow rate.

Modeling and Evaluating Zeolite and Amorphous Based Catalysts in Vacuum Gas Oil Hydrocracking Process

Hydrocracking is a significant process in a refinery which is commonly used for converting heavy fractions such as vacuum gas oil (VGO) to the valuable products such as naphtha and diesel. In this research, VGO hydrocracking process was studied in a pilot scale plant in the presence of a zeolite and two amorphous based commercial catalysts called RK-NiY, RK-MNi and KF-101, respectively. In order to study the effect of support on the yield of the process, a discrete 4-lump kinetic model, including feed (vacuum gas oil and unconverted materials), distillate (diesel and kerosene), naphtha and gas was proposed for each catalyst. At first, each network had six reaction paths and twelve kinetic coefficients, and then by using the model reduction methodology, only four main routes for RK-MNi and RK-NiY, and three ones for KF-101 were designated. Results showed that the absolute average deviation (AAD%) of reduced models decreased from 5.11 %, 10.1 % and 21.8 % to 4.54 %, 8.9 % and 19.67 % for RK-MNi, KF-101 and RK-NiY, respectively. Moreover, it was confirmed that amorphous and zeolite catalysts could be selected for producing middle distillate and naphtha products, respectively.