Grant: Alliance Grants
The University of Western Ontario
$50,000.00
Advanced hybrid modelling of Fluid Catalytic Cracking (FCC) units
FY 2023-24
Summary
This research will be developed in partnership with Imperial Oil Canada, with the aim of improving FCC (fluidizing catalytic cracking) processes, in their refineries. The research approach proposed involves: a) The establishment of catalytic cracking kinetics using the catalysts and VGO (vacuum gas oil) provided by Imperial Oil, in the CREC Riser Simulator Mark II (RS) , b) The advancement of FPMs (First Principle Models) for large scale FCC units, using Barracuda CPFD (Computational Particle Fluid Dynamics), for the assessment of steady state and non steady state operations, c) The development of FPMs that account for both the FCC and catalyst regenerator units, d) The establishment of AI (Artificial Intelligence) models involving adjustable parameters, model trainers, FPM project data library and Imperial Oil operational data, e) The development of an engineer refinery operator easy to use, CREC-Hybrid AI (Artificial Intelligence) algorithm in the Matlab/Python software.This project addresses technical and operational challenges faced nowadays by Imperial Oil refineries, as well as other refineries in North America. These issues are the result of rapid changes in the cost of VGO feedstocks, gasoline specifications, as well as the more stringent CO2 and other greenhouse gas targets set for Canadian FCC refineries. Thus, the CREC Riser Simulator together with AI training models for FCC will provide a unique platform to establish the best approaches to enhance the performance of FCC processes and VGO refinery operations worldwide.
Program
Alliance Grants
Recipient
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
586936-2023
Name nom
De Lasa, Hugo HI
Department département
Chemical and Biochemical Engineering
Organization id
36
Institution établissement
The University of Western Ontario
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2023
Competition year année de concours
2023
Award amount
50000
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
300
Area of application group en
Energy resources
Area of application group fr
Ressources d'énergie
Area of application en
Energy resources (including production, exploration, processing, distribution and use)
Area of application fr
Ressources d'énergie (production, exploration, traitement, distribution et utilisation de l'énergie)
Research subject code
1800
Research subject group en
Chemical engineering
Research subject group fr
Chemical engineering
Research subject en
Génie chimique
Research subject fr
Génie chimique
Application title
Advanced hybrid modelling of Fluid Catalytic Cracking (FCC) units
Keyword
Artificial Intelligence; Catalytic Cracking; Data Driven Models; First Principles Models; Kinetics
Application summary
This research will be developed in partnership with Imperial Oil Canada, with the aim of improving FCC (fluidizing catalytic cracking) processes, in their refineries. The research approach proposed involves: a) The establishment of catalytic cracking kinetics using the catalysts and VGO (vacuum gas oil) provided by Imperial Oil, in the CREC Riser Simulator Mark II (RS) , b) The advancement of FPMs (First Principle Models) for large scale FCC units, using Barracuda CPFD (Computational Particle Fluid Dynamics), for the assessment of steady state and non steady state operations, c) The development of FPMs that account for both the FCC and catalyst regenerator units, d) The establishment of AI (Artificial Intelligence) models involving adjustable parameters, model trainers, FPM project data library and Imperial Oil operational data, e) The development of an engineer refinery operator easy to use, CREC-Hybrid AI (Artificial Intelligence) algorithm in the Matlab/Python software.This project addresses technical and operational challenges faced nowadays by Imperial Oil refineries, as well as other refineries in North America. These issues are the result of rapid changes in the cost of VGO feedstocks, gasoline specifications, as well as the more stringent CO2 and other greenhouse gas targets set for Canadian FCC refineries. Thus, the CREC Riser Simulator together with AI training models for FCC will provide a unique platform to establish the best approaches to enhance the performance of FCC processes and VGO refinery operations worldwide.
