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Title: Nonintrusive Uncertainty Quantification of Computational Fluid Dynamics Simulations of a Bench-Scale Fluidized-Bed Gasifier

Abstract

Uncertainty quantification (UQ) analysis is increasingly becoming one of the major requirements of simulation-based engineering to assess the confidence in the results and make better-informed decisions based on the insight derived from the simulations. In an earlier study, Bayesian UQ analysis was applied to existing bench-scale fluidized-bed gasifier experiment results. In the current study, a series of simulations were carried over with the open-source computational fluid dynamics software MFiX to reproduce the experimental conditions, where three operating factors, i.e., coal flow rate, coal particle diameter, and steam-to-oxygen ratio, were systematically varied to understand their effect on the syngas composition. Bayesian UQ analysis was this time performed on the numerical results for comparison purposes. This is part of ongoing research efforts to explore the applicability of advanced UQ methods and processes such as Bayesian methods for large-scale complex multiphase flow simulations. As part of Bayesian UQ analysis, a global sensitivity analysis was performed based on the simulation results, which shows that the predicted syngas composition is strongly affected not only by the steam-to-oxygen ratio (which was observed in experiments as well) but also by variation in the coal flow rate and particle diameter (which was not observed in experiments). The carbonmore » monoxide mole fraction is underpredicted at lower steam-to-oxygen ratios and overpredicted at higher steam-to-oxygen ratios. The opposite trend is observed for the carbon dioxide mole fraction. These discrepancies are attributed to either excessive segregation of the phases that leads to the fuel-rich or -lean regions or alternatively the selection of reaction models, where different reaction models and kinetics can lead to different syngas compositions throughout the gasifier.« less

Authors:
 [1];  [2];  [2];  [3];  [4]
+ Show Author Affiliations
  1. ALPEMI Consulting, LLC, Phoenix, AZ (United States); National Energy Technology Lab. (NETL), Morgantown, WV (United States)
  2. National Energy Technology Lab. (NETL), Morgantown, WV (United States)
  3. General Electric (GE) Global Research Center, Niskayuna, NY (United States)
  4. National Energy Technology Lab. (NETL), Morgantown, WV (United States); West Virginia Univ., Morgantown, WV (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)
Sponsoring Org.:
USDOE Office of Fossil Energy (FE); USDOE Office of Science (SC)
OSTI Identifier:
1480085
Grant/Contract Number:  
FE0004000; AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
Industrial and Engineering Chemistry Research
Additional Journal Information:
Journal Volume: 55; Journal Issue: 48; Journal ID: ISSN 0888-5885
Publisher:
American Chemical Society (ACS)
Country of Publication:
United States
Language:
English
Subject:
01 COAL, LIGNITE, AND PEAT; 10 SYNTHETIC FUELS; 37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; 42 ENGINEERING

Citation Formats

Gel, Aytekin, Shahnam, Mehrdad, Musser, Jordan, Subramaniyan, Arun K., and Dietiker, Jean-François. Nonintrusive Uncertainty Quantification of Computational Fluid Dynamics Simulations of a Bench-Scale Fluidized-Bed Gasifier. United States: N. p., 2016. Web. doi:10.1021/acs.iecr.6b02506.
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Gel, Aytekin, Shahnam, Mehrdad, Musser, Jordan, Subramaniyan, Arun K., & Dietiker, Jean-François. Nonintrusive Uncertainty Quantification of Computational Fluid Dynamics Simulations of a Bench-Scale Fluidized-Bed Gasifier. United States. https://doi.org/10.1021/acs.iecr.6b02506
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Gel, Aytekin, Shahnam, Mehrdad, Musser, Jordan, Subramaniyan, Arun K., and Dietiker, Jean-François. Thu . "Nonintrusive Uncertainty Quantification of Computational Fluid Dynamics Simulations of a Bench-Scale Fluidized-Bed Gasifier". United States. https://doi.org/10.1021/acs.iecr.6b02506. https://www.osti.gov/servlets/purl/1480085.
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@article{osti_1480085,
title = {Nonintrusive Uncertainty Quantification of Computational Fluid Dynamics Simulations of a Bench-Scale Fluidized-Bed Gasifier},
author = {Gel, Aytekin and Shahnam, Mehrdad and Musser, Jordan and Subramaniyan, Arun K. and Dietiker, Jean-François},
abstractNote = {Uncertainty quantification (UQ) analysis is increasingly becoming one of the major requirements of simulation-based engineering to assess the confidence in the results and make better-informed decisions based on the insight derived from the simulations. In an earlier study, Bayesian UQ analysis was applied to existing bench-scale fluidized-bed gasifier experiment results. In the current study, a series of simulations were carried over with the open-source computational fluid dynamics software MFiX to reproduce the experimental conditions, where three operating factors, i.e., coal flow rate, coal particle diameter, and steam-to-oxygen ratio, were systematically varied to understand their effect on the syngas composition. Bayesian UQ analysis was this time performed on the numerical results for comparison purposes. This is part of ongoing research efforts to explore the applicability of advanced UQ methods and processes such as Bayesian methods for large-scale complex multiphase flow simulations. As part of Bayesian UQ analysis, a global sensitivity analysis was performed based on the simulation results, which shows that the predicted syngas composition is strongly affected not only by the steam-to-oxygen ratio (which was observed in experiments as well) but also by variation in the coal flow rate and particle diameter (which was not observed in experiments). The carbon monoxide mole fraction is underpredicted at lower steam-to-oxygen ratios and overpredicted at higher steam-to-oxygen ratios. The opposite trend is observed for the carbon dioxide mole fraction. These discrepancies are attributed to either excessive segregation of the phases that leads to the fuel-rich or -lean regions or alternatively the selection of reaction models, where different reaction models and kinetics can lead to different syngas compositions throughout the gasifier.},
doi = {10.1021/acs.iecr.6b02506},
journal = {Industrial and Engineering Chemistry Research},
number = 48,
volume = 55,
place = {United States},
year = {Thu Oct 20 00:00:00 EDT 2016},
month = {Thu Oct 20 00:00:00 EDT 2016}
}
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https://doi.org/10.1021/acs.iecr.6b02506
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Works referenced in this record:

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