Computational fluid dynamics and discrete element simulation of the formation of inorganic syngas contaminants during lignocellulosic biomass gasification

Oluwafemi Oyedeji, Nourredine Abdoulmoumine

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

We report in this study the development of a computational fluid dynamics and discrete element method (CFD-DEM) model to predict the yield of deleterious nitrogen and sulfur contaminants (NH3, HCN, H2S, COS, and SO2) during biomass gasification. Additionally, the yields of major producer gas species (CO, CO2, CH4, and H2) were predicted. The formation of nitrogen contaminants was assumed to follow a heterogeneous reaction producing HCN, which was later hydrolyzed to form NH3. Similarly, the formation of sulfur contaminants was assumed to follow a heterogeneous reaction producing H2S, which was later oxidized to form COS and SO2. The effects of two important gasification process variables (temperature and equivalence ratio) were evaluated. The results of the CFD-DEM simulation were validated against experimental data in the literature. The CFD-DEM model yield predictions for the main syngas species (CO, CO2, H2, and CH4) compares well with the experimental results. Also, the predicted yields of NH3 and H2S generally fit within a 95% confidence interval of the experimental data. However, the predicted yields of HCN were about 20-50% lower than the experimental data. The main outcome of this work is a computational tool that can be used to gain in-depth knowledge to better understand how to optimize process variables for mitigating the formation of nitrogen and sulfur contaminants during gasification.

Original languageEnglish
Pages (from-to)4219-4231
Number of pages13
JournalSustainable Energy and Fuels
Volume4
Issue number8
DOIs
StatePublished - Aug 2020

Funding

The authors would like to acknowledge funding support for this by South-eastern Sun Grant Center and the U.S. Department of Transportation, Research and Innovative Technology Administration, Grant No. DTO559-07-G-00050.

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