Residue Fluid Catalytic Cracking Research Articles

Industrial Investigation of the Combined Action of Vacuum Residue Hydrocracking and Vacuum Gas Oil Catalytic Cracking While Processing Different Feeds and Operating under Distinct Conditions

Ebullated bed vacuum residue hydrocracking and fluid catalytic cracking (FCC) are among the most profitable processes in modern refining. Their optimal performance is vital for petroleum refining profitability. That is why a better understanding of their combined action and the interrelations between these two heavy oil conversion processes in a real-world refinery could provide valuable information for further performance optimization. Nine distinct petroleum crudes belonging to the extra light, light, and medium petroleum crude types were processed in the LUKOIL Neftohim Burgas refinery to study the combined performance of two processes: FCC of vacuum gas oil and ebullated bed vacuum residue H-Oil hydrocracking. The operating conditions along with the characterization data of the feeds and products of both processes were evaluated through the employment of intercriteria analysis to define the variables with statistically significant relationships. Maple 2023 Academic Edition mathematics software was used to develop models to predict the vacuum residue conversion level under different operating conditions. The plug flow reactor model with an activation energy of 215 kJ/mol and a reaction order of 1.59 was found to provide the highest accuracy of vacuum residue conversion, with an average absolute deviation of 2.2%. H-Oil yields were found to correlate with the vacuum residue conversion level and the content of FCC slurry oil (SLO), the recycling of partially blended fuel oil, a material boiling point below 360 °C, and the vacuum gas oil (VGO) in the H-Oil feed. FCC conversion was found to depend on the H-Oil VGO content in the FCC feed and the content of FCC SLO in the H-Oil feed.

Integrating Artificial Immune Genetic Algorithm and Metaheuristic Ant Colony Optimizer with Two-Dose Vaccination and Modeling for Residual Fluid Catalytic Cracking Process

Integrating Artificial Immune Genetic Algorithm and Metaheuristic Ant Colony Optimizer with Two-Dose Vaccination and Modeling for Residual Fluid Catalytic Cracking Process

Effects of PET and RFCC on the dynamic modulus, phase angle, and complex viscosity of asphalt concrete

With economic and social development, the total amount of domestic and industrial solid waste discharged is considerable. In 2020, Vietnam generated about 2.2 million tons of plastic waste and 2 million tons of industrial solid waste. And most of them are landfilled and take a long time to decompose. This has dramatically affected the environment, costly land resources, and considerable transportation, burial, and management costs of those landfills. Therefore, many scientists have studied to recycle these wastes. There are two approaches to using recycled waste in hot mix asphalt (HMA). Waste plastic changes the properties of the asphalt binder, and solid waste replaces coarse particles in an asphalt mixture. During the research on using recycled waste for asphalt concrete, PET (Poly Ethylene Terephthalate) and RFCC (Residue Fluid Catalytic Cracking) were chosen for the study. This paper presents a study on the influence of PET (with 0.2% content in HMA) and RFCC (with 5% content in HMA) on the viscoelastic property of asphalt concrete based on dynamic modulus, phase angle, and complex viscosity values. At high temperatures, HMA using PET and RFCC exhibit complete elastic behavior (φ ≈ 50) in contrast to the viscous elastic behavior of the control sample (φ ≈ 150). Compared control sample, RFCC significantly increased the stiffness of HMA at low and high temperatures; with the dynamic modulus of HMA using RFCC increased 1.1 times at low and 1.6 times at high temperatures; the viscosity of HMA using RFCC and PET decreased 10 times and 7 times at low temperatures.

Development of heavy metal passivators in residue fluid catalytic cracking process

The advancement of residual fluid catalytic cracking (RFCC) is significantly influenced by the development of heavy metals passivation technology. Resids often include larger concentrations of heavy metals (Ni, V, and Fe) than gas oils, primarily in the form of porphyrin complexes and salts of organic acids. Under cracking conditions, metals, especially Ni and V in residues and gas oil deposit on the cracking catalyst and induce adverse dehydrogenation reactions. The catalyst's zeolite component is destroyed by these metals. While reducing the yield of gasoline, active metals increase the yields of coke and hydrogen. Because most cracking FCC units can only tolerate limited amounts of coke and hydrogen, the level of heavy metals on the catalyst needs to be kept under control in order to achieve maximum productivity and profit. Metal passivation enhances catalytic activity and/or selectivity to more desired products by minimizing the detrimental effects of contaminating metals. In this study, we will review heavy metals deactivation mechanism in RFCC process and the potential technological solutions to the catalyst deactivation concern.

Biofuel production from olive pomace via thermal and catalytic pyrolysis using an RFCC catalyst

AbstractThermal and catalytic pyrolysis of olive pomace as a second generation of biomass for the production of valuable bio‐oil has been investigated. The achieved results indicate that the maximum bio‐oil production yield through the non‐catalytic pyrolysis process is 56% at a temperature of 500°C, with a high content of oxygenated compounds. Since the main focus of this study was the catalytic upgrading of pyrolysis‐derived bio‐oil to valuable fuels, an industrial residue fluid catalytic cracking (RFCC) catalyst has been examined using different catalyst to biomass ratios. For a catalyst to biomass ratio of 0.5, the highest bio‐oil production yield was 44 wt% at 500°C and for a catalyst to biomass ratio of 5, the highest bio‐oil yield was 39 wt% at 400°C. The obtained experimental results indicate that, although the bio‐oil production yield decreases through catalytic pyrolysis, application of RFCC catalysts reduces the oxygenated compounds as undesirable products and increases aromatic and cyclic compound content in the bio‐oil, significantly. By increasing the temperature, the production of aromatic compounds as valuable products intensifies, and this compound group is identified as the main content of the derived bio‐oil. It is inferred that RFCC catalysts are appropriate candidates for use in the pyrolysis process for developing biofuel production on an industrial scale. © 2022 Society of Chemical Industry and John Wiley & Sons, Ltd.

Acids treatment for improving catalytic properties and activity of the spent RFCC catalyst for cracking of palm oil to kerosene-diesel fraction fuels

In this study, the reactivation and modification of the spent Residue Fluid Catalytic Cracking (RFCC) catalyst using sulfuric acid and citric acid as acids treatment was evaluated by varying the acid solution concentrations. The effect of acid types and acid-solution concentrations on structural, textural, and acidic properties of spent RFCC catalyst was observed using X-ray diffraction, X-ray fluorescence, N2-sorption and pyridine-probed Fourier transform infrared measurements. Catalytic cracking of palm oil was used to evaluate the catalytic activity of the acid-treated catalysts. All the results showed the different beneficial effects of the sulfuric acid- and citric acid- treatments on the physicochemical properties of the modified catalyst with an improvement of surface area and pore volume of catalysts as well as the crystallinity due to the metal and matrix material removal. The sulfuric acid-treated catalysts have higher Brønsted/Lewis (B/L) ratio than the citric acid treatment, while the citric acid-treated catalysts have lower B/L ratio due to the enhancement of Lewis acid site. The acid-treated catalysts showed better performance than the non-treated catalyst. The selectivity of the kerosene-diesel range product fraction increased with the acid concentrations treatment.

Catalytic cracking of three-ring polycyclic aromatic hydrocarbons in the presence of hydrogen donors

Catalytic cracking of three-ring polycyclic aromatic hydrocarbons (PAHs) in the residue fluid catalytic cracking (RFCC) process was investigated. Catalytic cracking of mixtures of three-ring PAHs and various model hydrocarbons was carried out using RFCC equilibrium catalysts. Most of the three-ring PAHs were converted to coke in the absence of hydrogen donors, whereas coke formation was suppressed and decomposition of three-ring PAHs was promoted in the presence of aliphatic hydrocarbons, saturated rings, and aromatic ring side chains. Three-ring PAHs were first converted to noncondensed two-ring PAHs and subsequently decomposed to monocyclic aromatic hydrocarbons and condensed two-ring PAHs. This reaction can be depicted by partial hydrogenation of three-ring PAHs by hydrogen transfer reaction with coexisting hydrogen donors and sequential cracking of saturated rings. When a hydrogen donor was sufficiently present, cracking of saturated rings was the rate-determining step, and the reaction can be accelerated by increasing the reaction temperature or using a catalyst with a high acid content. These results are expected to lead to the effective utilization of heavy oil by promoting PAH cracking in the RFCC process.

Maximizing margins and optimizing operational conditions for residue fluid catalytic cracking with an artificial intelligence hybrid reaction model

AbstractBecause of the recent declining demand for gasoline, the key to making refineries competitive is to maximize the yields of propylene and aromatics by converting heavier feedstock into basic petrochemicals through the residue fluid catalytic cracking (RFCC) process. This study presents an artificial intelligence (AI) hybrid reaction model to optimize the catalyst make‐up rate and maximize the product yield in a real‐time operation by (1) developing a catalyst activity evaluation method, (2) integrating the catalyst to oil (Cat/Oil) ratio to evaluate the reaction performance, and (3) incorporating the yield prediction model into the latest digital technologies. To this end, the catalyst deactivation function, which uses a deep neural network of the basic machine learning method, was added to the past RFCC reaction model. Under actual operational conditions, this study shows that the AI hybrid reaction model using the catalyst deactivation function can minimize catalyst loss and produce an accurate yield prediction as a production planning support tool.

Pore structure and surface property design of silicon carbide membrane for water-in-oil emulsification

In recent years, ceramic membranes have been applied as emulsification media in preparing emulsified heavy oils for residue fluid catalytic cracking units. In this case, silicon carbide (SiC) material is used for harsh environments due to its excellent chemical and thermal stabilities. Herein, a superhydrophobic SiC emulsified functional membrane was prepared by using an in-situ sintering method and subsequent grafting modification. The open porosity of these prepared membranes can be controlled from 26% to 48%, and the water contact angle of the membranes under oil was approximately 170°. The decrease of open porosity improved the bending strength of the membranes and also affected the emulsification performance. The size of water droplets decreased from 1.16 μm to 0.98 μm as the open porosity decreased from 48% to 26%. Moreover, the SiC membranes exhibited high flux and stability during the preparation of water-in-oil (W/O) emulsions, and the fouled membranes can be conveniently and effectively regenerated by ultrasonic cleaning with ethanol. Hence, the SiC membranes produced W/O emulsions with small droplets in harsh environments, such as the emulsification of heavy oil and high-viscosity oil at high temperature. • Pore structure and surface property of SiC membranes were successfully tailored. • High bending strength and excellent underwater superhydrophobicity were achieved. • Open porosity was revealed to dominate the membrane emulsification performance. • SiC membranes showed high flux and stability in preparing water-in-oil emulsions. • SiC membranes can be effectively regenerated by ultrasonically cleaning in ethanol.

THE USE OF BIO-MOLECULAR SUBSTANCE OF MARINE BIOTA AS AN ALTERNATIVE EARLY INDICATOR OF OIL POLLUTED ENVIRONMENT: A NEW APPROACH FOR MONITORING CONSIDERATION

THE USE OF BIO-MOLECULAR SUBSTANCE OF MARINE BIOTA AS AN ALTERNATIVE EARLY INDICATOR OF OIL POLLUTED ENVIRONMENT: A NEW APPROACH FOR MONITORING CONSIDERATION

Reactivation of the Spent Residue Fluid Catalytic Cracking (RFCC) Catalyst through Acid Treatment for Palm Oil Cracking to Biofuels

This work discusses the treated spent Residue Fluid Catalytic Cracking (RFCC) catalysts using sulfuric or citric acids to examine the impact of acid treatment on the catalyst physicochemical properties and structural characteristics. The catalysts were characterized by X-ray diffraction (XRD), X-ray fluorescence (XRF), and Brunauer−Emmett−Teller-Barrett−Joyner−Halenda (BET-BJH) methods. The catalytsts were performed in a continuous fixed-bed reactor for catalytic cracking of palm oil. Changes of the catalyst characteristics and catalytic performance testing of the catalyst after the acid treatment for palm oil cracking process were discussed. It was found that the acid treatment on the spent RFCC catalyst can increase the surface area and pore volume of catalysts as well as the crystallinity. The closed pores in the spent RFCC are opened by acid treatment by eliminating heavy metals. Concerning to the catalytic performance, the acid-treated catalysts had better performance than the non-treated catalyst, which could increase selectivity of the kerosene-diesel range fraction from 47.89% to 55.41%. It was interested, since the non-treated catalyst could not produce gasoline fraction, while the acid-treated catalsysts could produce gasoline fraction at selectivity range of 0.57 – 0.84%. It was suggested that both sulfuric or citric acids treatment could increase the cracking performance of spent RFCC catalyst by shifting the product to lower hydrocarbons.

Real-time refinery optimization with reduced-order fluidized catalytic cracker model and surrogate-based trust region filter method

Since its initial development in the 1980′s, Real-Time Optimization (RTO) has been widely appreciated as an efficient way to optimize process decision variables and improve economic performance of refineries. RTOs consist of nonlinear optimization models with hundreds of thousands of equations, which are built within equation-oriented (EO) modeling platforms. With increasing size and complexity of RTO applications, there is increased demand for improved optimization strategies. To address this demand, surrogate models for complex refinery units have been embedded within the general EO framework for RTO. Moreover, the recent trust region filter (TRF) optimization strategy allows great flexibility in the choice of surrogates, while ensuring convergence to the optimum of the rigorous RTO model. This study considers this approach for a real-world refinery. The Petrobras S.A. RECAP unit in Mauá, Brazil runs an RTO refinery model with an Aspen RTO optimizer to maximize the profit within two hour cycles. To reduce the computational burden, we embed a reduced model (RM) to replace the detailed (truth) model for the residue fluid catalytic cracking (RFCC) unit, and implement a TRF optimization strategy. The TRF driver is written in Python and integrates with the RFCC truth model, the Aspen-EO RECAP model, and the Aspen RTO optimizer. The approach is illustrated on three real-world scenarios in order to demonstrate the effectiveness and efficiency of this RM-based optimization strategy.

Industrial Simulation of the 12-Lumped Kinetic Model for Residue Fluid Catalytic Cracking

Industrial Simulation of the 12-Lumped Kinetic Model for Residue Fluid Catalytic Cracking

Low-oxygenated biofuels production from palm oil through hydrocracking process using the enhanced Spent RFCC catalysts

Utilization of the enhanced Spent Residue Fluid Catalytic Cracking (SRFCC) catalysts through the acid treatment was conducted for the palm oil hydrocracking process to produce biofuels. The catalysts were characterized using Pyridine-probed Fourier Transform Infrared (Pyridine-FTIR) spectroscopy and Brunauer−Emmett−Teller-Barrett−Joyner−Halenda (BET-BJH) method. The higher number of Brønsted acid sites on the enhanced SRFCC catalysts leads to the lower conversion of palm oil as well as lower deoxygenation activity because of the slower carbocations formation process as the initiation reaction. On the other hand, the Lewis acid sites on the enhanced SRFCC catalysts have a significant role in the deoxygenation reaction mechanism. Meanwhile, the catalysts surface area and pore size are responsible for tailoring the diffusion mechanism of the mass transfer process of reactant molecules. The introduction of hydrogen gas in the reaction system has a significant role in deoxygenation, double bond cleavage, and de-coking process mechanisms.

Enhancing Brønsted and Lewis Acid Sites of the Utilized Spent RFCC Catalyst Waste for the Continuous Cracking Process of Palm Oil to Biofuels

Catalyst waste from the Residue Fluid Catalytic Cracking (RFCC) plant process can still be utilized to catalyze the catalytic cracking of palm oil to fuels. However, the catalyst waste should be re...

Impact of H-Oil vacuum residue hydrocracking severity on fluid catalytic cracking unit performance

The performance of both ebullated bed H-Oil vacuum residue (VR) hydrocracking and fluid catalytic cracking (FCC) of vacuum gas oils (VGO) is interrelated. The increase of H-Oil unit reaction temperature maximizes VR conversion and augments the aromaticity and density of the hydrocracked heavy oils. The FCC of VGO blends that contain more aromatic H-Oil VGOs is featured by a lower VGO conversion. It was found in this study that the reactivity of the H-Oil heavy oils depends on their molecular weight (T50) instead on their aromatics content as observed during catalytic cracking of straight run VGOs reported in other studies.

Heat transfer of water-based carbon nanotube nanofluids in the shell and tube cooling heat exchangers of the gasoline product of the residue fluid catalytic cracking unit

In this study, a series of low-concentration carbon nanotubes (CNT) water-based nanofluids (0.0055, 0.055, 0.111 and 0.278 vol%) were used as coolants in a shell and tube cooler of the residue fluid catalytic cracking gasoline product to analyze their effects on heat performance of the heat exchanger. The coolants and gasoline flow in tube side and shell side, respectively. This work was performed through simulating the heat exchanger by ASPEN HTFS+ 7.3 software. The performance of the nanofluids to heat transfer was analyzed in comparison with cooling water. Results illustrated that 0.055% CNT concentration could enhance heat transfer properties of the heat exchanger such as Nusselt number, total heat transfer coefficient and heat transfer rate more than other concentrations. Therefore, the lowest temperature of outlet shell-side fluid was also observed at this concentration. Moreover, increment in mass flow rates of both the tube-side and shell-side fluids caused enhancement of the heat transfer, especially with 0.055 vol% CNT. Although there is an optimum concentration among the studied CNT volume fractions, all nanofluids exhibit better thermal performance of the heat exchanger than cooling water, whereas pressure drop increases with CNT loading.

A simplified multi-objective particle swarm optimization algorithm

Particle swarm optimization is a popular nature-inspired metaheuristic algorithm and has been used extensively to solve single- and multi-objective optimization problems over the last two decades. Several local and global search strategies, and learning and parameter adaptation strategies have been included in particle swarm optimization to improve its performance over the years. Most of these approaches are observed to increase the number of user-defined parameters and algorithmic steps resulting in an increased complexity of the algorithm. This paper presents a simplified multi-objective particle swarm optimization algorithm in which the exploitation (guided) and exploration (random) moves are simplified using a detailed qualitative analysis of similar existing operators present in the real-coded elitist non-dominated sorting genetic algorithm and the particle swarm optimization algorithm. The developed algorithm is then tested quantitatively on 30 well-known benchmark problems and compared with a real-coded elitist non-dominated sorting genetic algorithm, and its variant with a simulated binary jumping gene operator and multi-objective non-dominated sorting particle swarm optimization algorithm. In the comparison, the developed algorithm is found to be superior in terms of convergence speed. It is also found to be better with respect to four recent multi-objective particle swarm optimization algorithms and four differential evolution variants in an extended comparative analysis. Finally, it is applied to a newly formulated industrial multi-objective optimization problem of a residue (bottom product from the crude distillation unit) fluid catalytic cracking unit where it shows a better performance than the other compared algorithms.

Hydrogenation and TMP Coupling Process: Novel Process Design, Techno-Economic Analysis, Environmental Assessment and Thermo-Economic Optimization

The production of high-quality gasoline and light olefins harbors tremendous industrial and economic significance. In this paper, a novel process is proposed for converting inferior light cycle oil (LCO) into propylene and ethylene, as well as the high-octane-number gasoline with rich BTX contents. The unique feature for the novel process is the integration of LCO selective hydrogenation unit with two-stage riser catalytic cracking. For comparative techno-economic and environmental analyses, typical two-stage riser catalytic cracking for maximizing the propylene (TMP) process and conventional residue fluid catalytic cracking (RFCC) process models are developed. Based on the detailed process modeling and simulation results, techno-economic evaluation and environmental assessment have been performed. It is found that the novel process, coupled hydrogenation and TMP process, has a favorable impact on both the economic and environmental performances. The HTMP process has the highest net present value that means 2.13 times of TMP and 4.94 times of RFCC process, and reduces 15.26 t CO2 equivalents per million dollars output value compared with the TMP process. Moreover, we conduct the thermo-economic optimization for the HTMP process based on the exergy analysis. The result shows that full scale hydrogenation and recycling of hydro-LCO and increasing of the second riser outlet temperature could significantly increase the profitability of this novel process.

Preparation of nanozeolite-based RFCC catalysts and evaluation of their catalytic performance in RFCC process

Abstract The NaY zeolites with different particle sizes of about 20–30 nm and 1–2 µm were synthesized by hydrothermal routes and characterized by XRD, FT-IR, BET and SEM techniques. The XRD analyses demonstrated the formation of NaY zeolites with high crystallinity and the BET analyses showed that the nanozeolite possessed a higher external surface area (102 m2/g) than microzeolite (11 m2/g). In order to evaluate the effect of zeolite particle size and zeolite content on the catalytic performance of the residue fluid catalytic cracking (RFCC) catalyst, nanozeolite-based and microzeolite-based catalysts were prepared using silica as inactive matrix. It is clearly demonstrated that the acidity improves with the reduction of zeolite particle size. On the other hand, in equal zeolite content (30 wt%), the nanozeolite-based catalyst possessed higher acidity (2.30 mmol NH3/g catalyst) than microzeolite-based catalyst (1.53 mmol NH3/g catalyst). The microactivity tests (MAT) demonstrated that in equal zeolite content the nanozeolite-based catalysts showed higher catalytic performance than microzeolite-based catalysts. Moreover, the nanozeolite-based catalyst with 30 wt% zeolite (NC30) and a BET area of 346 m2/g showed the optimum catalytic performance in RFCC process, with the highest gasoline yield (32 wt%) and gasoline selectivity (56 wt%).