Yearly Archives: 2026

Application Model: FCC Feed Vaporization and API Tool

Fluid Catalytic Cracking (FCC) units are the beating heart of modern oil refineries, providing exceptional value by converting low-value heavy hydrocarbon fractions into high-demand products like gasoline, diesel, and olefins. Within the FCC riser reactor, pre-heated liquid feed is atomized and injected into a turbulent stream of hot, fluidized zeolite catalyst, initiating rapid endothermic cracking reactions. The complex vapor-liquid-solid hydrodynamics, extreme conductive and convective heat transfer, and rapid feed evaporation in this zone directly dictate operational success. Incomplete vaporization severely hampers catalytic efficiency, accelerating unwanted thermal cracking, excessive coke formation, and long-term equipment degradation.

This application model uses Barracuda Virtual Reactor to simulate an industrial-scale FCC riser, focusing on the critical vaporization dynamics of multi-component feed droplets interacting with a dense catalyst flow. Based on the staged-injection configuration of Berrouk et al. (2017), the model captures the distinct reaction environments created by lower-elevation light gas feeds, mid-elevation mixed temperature control (MTC) heavy gas oil injections, and higher-elevation slurry oil quenching. To accurately resolve the varying volatility of real FCC feedstocks, the simulation incorporates a newly developed API correlation-based Python tool that translates True Boiling Point (TBP) curves and Watson K factors into high-resolution, temperature-dependent material properties for the evaporating droplets.

Results demonstrate the detailed evaporation profiles of liquid droplets over the height of the riser, highlighting how individual hydrocarbon cuts vaporize at varying rates based on their unique boiling point distributions. The model illustrates the intense thermal gradients and momentum transfer near the injection nozzles, showing how staged feeding successfully manipulates local temperatures to prevent the over-cracking of lighter species while ensuring heavy oils receive sufficient headroom to vaporize.

This application model provides a practical foundation for studying FCC riser hydrodynamics, evaluating multi-component feed vaporization, mitigating thermal cracking and coke buildup, and optimizing injection strategies to maximize catalytic efficiency and refinery yield.

Application Model: Proppant Transport in a Single Hydraulic Fracture Using MP-PIC CFD and a Graph Neural Network – Reduced Order Model (GNN-ROM)

This application model uses Barracuda Virtual Reactor to simulate proppant transport and bed formation within a single hydraulic fracture using the Multiphase Particle-in-Cell (MP-PIC) method. A non-Newtonian drag correction accounts for the shear-thinning behavior of the slickwater carrying the proppant, and the resulting settling and bed formation behavior are validated against the single-fracture experimental measurements of Zhou et al. (2023). The simulation captures the heel-skewed bed geometry and particle size segregation that govern how much of the fracture remains conductive after treatment. This validated CFD solution also serves as the benchmark for a Graph Neural Network reduced-order model (GNN-ROM), demonstrating a pathway toward fast, physics-based proppant transport prediction at the scale of full multi-fracture completions.