CFD Simulation of Entrained Flow Gasification With Improved Devolatilization and Char Consumption Submodels

Mayank Kumar, Cheng Zhang, Rory F. D. Monaghan, Simcha L. Singer, Ahmed F. Ghoniem

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

In this work, we use a CFD package to model the operation of a coal gasifier with the objective of assessing the impact of devolatilization and char consumption models on the accuracy of the results. Devolatilization is modeled using the Chemical Percolation Devolitilization (CPD) model. The traditional CPD models predict the rate and the amount of volatiles released but not their species composition. We show that the knowledge of devolatilization rates is not sufficient for the accurate prediction of char consumption and a quantitative description of the devolatilization products, including the chemical composition of the tar, is needed. We incorporate experimental data on devolatilization products combined with modeling of the tar composition and reactions to improve the prediction of syngas compositions and carbon conversion. We also apply the shrinking core model and the random pore model to describe char consumption in the CFD simulations. Analysis of the results indicates distinct regimes of kinetic and diffusion control depending on the particle radius and injection conditions for both char oxidation and gasification reactions. The random pore model with Langmuir-Hinshelwood reaction kinetics are found to be better at predicting carbon conversion and exit syngas composition than the shrinking core model with Arrhenius kinetics. In addition, we gain qualitative and quantitative insights into the impact of the ash layer surrounding the char particle on the reaction rate. Copyright © 2010 by ASME.
Original languageEnglish (US)
Title of host publicationVolume 3: Combustion Science and Engineering
PublisherASME International
Pages383-395
Number of pages13
ISBN (Print)9780791843765
DOIs
StatePublished - 2009
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This research is funded by the BP-MIT ConversionResearch Program. Mayank Kumar was supported byMASDAR. The computational facilities were supported inpart by KAUST.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

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