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Introduction

Fluidized catalytic cracking involves the loosening of various polymeric chains in crude oil into smaller and less heavier chains in the presence of a suitable catalyst on a fluidized bed.  The convolution of the feedstock makes it almost impossible to characterize, so attempts have been made to characterize various secondary compounds into different families in order to depict the complicated process reactions (Dasila et al., 2011).   From literature, numerous models have been used to project the various characterization in the lumping in fluidized catalytic cracking (Singh et al., 2017).

The cracking reaction begins instantaneously.  The resulting vapor-particles mixture move upwards due to a pressure differential along the reactor length. As the motion occurs, cracking reaction also occurs simultaneously. As a result of cracking, the velocity of the vapors increase along the riser height.  The reactions along the reactor length are known to be endothermic (Heydari et al., 2010).  The rate at which the feed vaporizes at the entry zone is a key performance indicator of the catalytic cracking reaction.  At a point in the riser-reactor, the cracking reaction halts due to deposition of coke on the catalyst surface causing catalyst deactivation and a short contact time between the catalyst and the vaporized feed (Kim et al., 2019).

Basically, there are majorly  two modes in which we characterize the lumping in the  catalytic cracking of  vacuum gas oil.  The first strategy is to lump molecules according to their molecular weight and to consider chemical reactions between these lumps (Paul et al., 2015).  These lumps are usually the feedstock and the final cracking products, like gasoline, light gases, and coke.  The second strategy is to lump different products based on main chemical families such as paraffins, olefins, naphthenes, and aromatics (Paul et al., 2015).

Apart from the unidentified multiple reactions, modeling of the riser reactor is very complex due to the complexity of the hydrodynamics, mass transfer and heat transfer resistances.  Furthermore, the operating conditions keep fluctuating along the riser height due to cracking which causes molar expansion in the gas phase and affects the axial and radial catalyst density in the riser (Guan et al., 2019).  In literature, numerous models of FCC riser are available with varying degrees of simplifications and assumptions.

With presence of the high efficiency feed injection system in modern FCC units, all cracking in the riser occur during the short time about 1-5 sec (Ebrahimi et al., 2018).

After feed vaporization occurs, only solid phase (catalyst & coke) and vapor phase (steam, hydrocarbon feed and product vapor) are left.  The simplest hydrodynamic models assume plug flow for both phases.  However, there is considerable back mixing in the solid phase because of slip between the solid and vapor phase which makes the prediction of solid velocity profile difficult (Sharma, 2011).  Circulating Fluidized Bed (CFB) risers, utilize different mathematical formulations to predict the relationship between solid concentration, operating conditions, and riser geometry.

The physio-chemical composition of the FCCU feedstock is a standout amongst the most significant properties in deciding the fundamental yield structure from the FCC unit. Each type of hydrocarbon responds under catalytic cracking conditions in very prevaricative ways (Hudec, 2011). The significant contrast among hydrocarbons types is in their “crackability” or degree of change for a given arrangement of working conditions. In all cases, for each kind of particle, expanding the molecular weight or carbon number builds the crackability. A mix of essential and auxiliary reactions occur during catalytic cracking.  These incorporate chain breakage, isomerization, cyclization, dehydrogenation, polymerization, hydrogen transfer, and condensation.  Subsequently, the consequence of breaking even a basic molecule, for example, typical paraffin is unpredictable, (Bollas, et al., 2007).

Characterizing an FCC feedstock involves determining both its chemical and physical properties. Because sophisticated analytical techniques are not practical on a daily basis, physical properties are used (Long et al., 2018). They provide qualitative measurement of the feed’s composition. The refinery laboratory is usually equipped to carry out these physical property tests on a routine basis (Lappas et al., 2017).

This study is proposed to determine the mode in which various process variables need to be changed to achieve the optimum yield of the various lumps from the fluidized cracking of vacuum gas oil in an industrial FCC reactor (Dasila et al., 2011).

Problem Statement

The objective of fluid catalytic cracking is to maximize the yield of high octane gasoline and minimize coke formation to make it economically attractive (Dagde and Puyate, 2012).  In the present day, about 50% of the world’s gasoline is produced from this method as opposed to thermal cracking because of the high-octane gasoline produced.

Presently, there are issues with respect to determining the optimum process variables and process operations to consider when aiming for the maximum yield of high-octane gasoline from fluidized catalytic cracking (Pelissari et al., 2018).

This work seeks to propose optimum process variables at which the maximum yields of the important lumps can be attained from fluidized cracking (Ahmed et al., 2013; Ahmed et al., 2014).

Aim and Objectives

The aim of this study is to carry out a thorough parametric sensitivity analysis on an industrial Fluid Catalytic Cracking Unit (FCCU).  It has the following objectives;

• Objective 1: Development of a feasible and comprehensive model for the riser reactor of an industrial FCCU accounting for the mass and heat transfer resistances, catalyst deactivation function.
• Objective 2: Development of a feasible and comprehensive model for the regenerator of an industrial FCCU accounting for the deposition of coke on the regenerator.
• Objective 2:  Development of a detailed hydrodynamic model for both the riser-reactor and regenerator (if required) of the industrial FCCU.
• Objective 3: Obtaining numerical solutions of the developed models using a suitable simulation software.
• Objective 4:  Comparison of the simulated results with plant data from the industrial FCCU with the aim of revealing the accuracy and efficiency of the developed models to imitate the real time situation in the FCCU.  This comparison would be done with respect to the various lump yields, the fluids pressure drop, solid phase temperature and other important process parameters.
• Objective 5:  Carrying out sensitivity analysis on the developed models.

Research Questions

The identified research questions for this project are provided below:

• How does a change in various process parameters affect the different lump yields?
• What constraints are considered in developing the models representing the industrial situation in the FCCU?
• How do the various constraints affect the various lump yields?
• How would the plant data for the industrial FCCU be gotten?
• How is the sensitivity analysis carried out (Dasila et al., 2011)?

Deliverables

The deliverables of these project are a project report, mathematical models, simulated results and a sensitivity analysis. The models should be able to consistently mimic the real time situation in the industrial FCCU. Also, the report should contain a complete documentation of how the mathematical models were arrived at, and tables of the simulated results after carrying out a sensitivity analysis on the process variables.

Relevance

This project mainly focuses on carrying out a sensitivity analysis on the industrial situation in the FCCU.

Methodology

This project focuses on secondary research, development of mathematical models and model simulation, and they are discussed below:

Secondary research

The secondary research in this project will utilize a systematic approach (Johnson et al., 2016) to review the works of literature. The steps involved in the systematic review of the literature are provided below:

• Step 1: Identify the research questions that can be used for the project.
• Step 2: Identify the keywords that should be used to research the works of literature.
• Step 3: Extract the journals and books that are appropriate for this project.
• Step 4: Write the literature review chapter.

Model development

The development of mathematical models for the industrial FCCU and simulating the developed models. The development of the mathematical models are in stages:

• Stage 1:  Model development for the vaporizer subsystem
• Stage 2: Using a preferred and appropriate kinetics of catalytic cracking in the FCCU’s riser-     reactor.
• Stage 3:  Developing an appropriate catalyst deactivation model (Dagde and Puyate, 2012).
• Stage 4: Developing an appropriate hydrodynamic model along the reactor length (American Petroleum Institute, 1992).
• Stage 5: Taking an appropriate mass balance around the riser-reactor of the industrial FCCU (Geankoplis, 2011).
• Stage 6: Taking an appropriate energy balance around the riser-reactor of the industrial FCCU.
• Stage 7: Carrying out an appropriate force balance around the riser-reactor of the industrial  FCCU.
• Stage 8: Taking an appropriate mass balance around the industrial FCCU’s regenerator.
• Stage 9: Taking an appropriate energy balance  around the industrial FCCU’s regenerator.
• Stage 10: Carrying out an appropriate force balance around the industrial FCCU’s regenerator.
• Stage 11: Using Process analysis to combine the material, force and energy balance(s) of both the riser-reactor and the regenerator of the industrial FCCU.

Model simulation

The developed models would be transformed and simulated on an appropriate software.

The codes and simulated results would be documented as Excel spreadsheets.

Evaluation

The risk assessment conducted for this project is provided in the table below:

Table 1:  Risk assessment