DOI: https://doi.org/10.14710/ijred.2023.54032

Computational prediction of green fuels from crude palm oil in fluid catalytic cracking riser

1Research Center for Energy Conversion and Conservation, National Research and Innovation Agency, South Tangerang, Indonesia

2Department of Chemical Engineering, Faculty of Engineering, Universitas Indonesia, Depok, 16424, Indonesia

3Department of Chemistry, Pharmaceutical Sciences Programs, Faculty of Medicine, Sultan Agung islamic of University, Semarang, Indonesia

Received: 3 May 2023; Revised: 4 Aug 2023; Accepted: 16 Aug 2023; Available online: 23 Aug 2023; Published: 1 Sep 2023.
Editor(s): Rock Keey Liew
Open Access Copyright (c) 2023 The Author(s). Published by Centre of Biomass and Renewable Energy (CBIORE)
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

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Abstract
Fluid catalytic cracking could convert crude palm oil into valuable green fuels to substitute fossil fuels. This study aimed to predict the phenomenon and green fuels yield in the industrial fluid catalytic cracking riser using computational fluid dynamics. A three-dimensional transient simulation using the Eulerian-Lagrangian with the multiphase particle-in-cell is to investigate reactive gas-particle hydrodynamics and the four-lump kinetic network model with the rare earth-Y catalyst for crude palm oil cracking behaviors. The study results show that the fluid and catalyst velocity profile increase in the middle of the riser reactor because the cracking reaction process that produces OLP and Gas products has a lighter molecular weight. The endothermic reaction causes the temperature profile to decrease because the heat of the reaction comes from the catalyst. This analysis shows that the simulation accurately predicts green fuel products from crude palm oil. As a result, the crude palm oil conversion, organic liquid product yield, and Gas yield correspond to 70 wt%, 28.8 wt%, and 27.5 wt%, respectively. Compared to the experimental study, the computational prediction of yield products showed good agreement and determined the optimal riser dimension. The methodology and results are guidelines for optimizing the FCC riser process using CPO.
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Keywords: CFD; CPO; Gas-particle; Green fuels; Riser; Rare earth-Y catalyst

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Section: Original Research Article
Language : EN
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