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Reactor design and optimization for converting crude (and refinery wastes) to chemicals in one step through revamped fluidized catalytic cracking

    Problem Statement

    Direct catalytic cracking of crude oil to chemicals could soon dominate the petrochemical industry, with lower fuel consumption and increased production of light olefins and aromatics. We aim to simplify the refinery into a single-step conversion scheme to produce the most demanded petrochemicals.

    Using a bottom-up holistic approach, we design a catalytic crude-to-chemicals process toward this goal. We investigate advanced reactors with intrinsic kinetic data and controlled hydrodynamics to improve the process. We study nonlinear multiscale phenomena by coupling hydrodynamics, heat transfer, and reaction kinetics.

    We use particle image velocimetry and optical probes, kinetic modeling, computational particle-fluid dynamics, and optimization approaches to improve operating scenarios and develop innovative reactor prototypes.

    We focus on the catalyst, reactor, and process levels to enhance and intensify the system. We are optimizing several state-of-the-art laboratory- and pilot-scale units, including a CircuBed®, a downer, and a multifunctional fluidized bed reactor.

    C2C-FCC

    Goals

    • Develop and scale up advanced reactors for converting crude oil to chemicals through fluid catalytic cracking, approaching intrinsic kinetics
    • Model process dynamics using reactive particle fluid dynamics coupled with experimental validations
    • Establish a design workflow for short-contact time reactors based on modeling, prototyping, and testing
    • Analyze the novel process developments in fluid catalytic cracking: novel feedstock, process modifications, etc.

    Related People

    Sherif Alabi
    Muhammed Ikbal Arikan
    Daffer AlYami
    Manel Nasfi
    Jose Ignacio Bielma Velasco
    Talal Aldugman
    Mengmeng Cui

    Related Publications

    A Data-Driven Reaction Network for the Fluid Catalytic Cracking of Waste Feeds

    by Alvira, Hita, Rodriguez, Arandes, Castaño
    Processes Year: 2018

    Extra Information

    Open Access.

    Abstract

    Establishing a reaction network is of uttermost importance in complex catalytic processes such as fluid catalytic cracking (FCC). This step is the seed for a faithful reactor modeling and the subsequent catalyst re-design, process optimization or prediction. In this work, a dataset of 104 uncorrelated experiments, with 64 variables, was obtained in an FCC simulator using six types of feedstock (vacuum gasoil, polyethylene pyrolysis waxes, scrap tire pyrolysis oil, dissolved polyethylene and blends of the previous), 36 possible sets of conditions (varying contact time, temperature and catalyst/oil ratio) and three industrial catalysts. Principal component analysis (PCA) was applied over the dataset, showing that the main components are associated with feed composition (27.41% variance), operational conditions (19.09%) and catalyst properties (12.72%). The variables of each component were correlated with the indexes and yields of the products: conversion, octane number, aromatics, olefins (propylene) or coke, among others. Then, a data-driven reaction network was proposed for the cracking of waste feeds based on the previously obtained correlations.

    Keywords

    FCC W2C MKM