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

Gel, Aytekin; Shahnam, Mehrdad; Musser, Jordan; Subramaniyan, Arun K.; Dietiker, Jean-François

doi:10.1021/acs.iecr.6b02506

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

Journal Article · Thu Oct 20 00:00:00 EDT 2016 · Industrial and Engineering Chemistry Research

DOI:https://doi.org/10.1021/acs.iecr.6b02506· OSTI ID:1480085

Gel, Aytekin ^[1]; Shahnam, Mehrdad ^[2]; Musser, Jordan ^[2]; Subramaniyan, Arun K. ^[3]; Dietiker, Jean-François ^[4]

ALPEMI Consulting, LLC, Phoenix, AZ (United States); National Energy Technology Lab. (NETL), Morgantown, WV (United States)
National Energy Technology Lab. (NETL), Morgantown, WV (United States)
General Electric (GE) Global Research Center, Niskayuna, NY (United States)
National Energy Technology Lab. (NETL), Morgantown, WV (United States); West Virginia Univ., Morgantown, WV (United States)

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.

View Accepted Manuscript (DOE)

Cite

Export

Save

Research Organization:: Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)

Sponsoring Organization:: USDOE Office of Fossil Energy (FE); USDOE Office of Science (SC)

Grant/Contract Number:: FE0004000; AC02-05CH11231

OSTI ID:: 1480085

Journal Information:: Industrial and Engineering Chemistry Research, Vol. 55, Issue 48; ISSN 0888-5885

Publisher:: American Chemical Society (ACS)Copyright Statement

Country of Publication:: United States

Language:: English

Citation Metrics:

Cited by: 8 works

Citation information provided by
Web of Science

References (8)

Validation and Uncertainty Quantification of a Multiphase Computational Fluid Dynamics Model Gel, Aytekin; Li, Tingwen; Gopalan, Balaji Industrial & Engineering Chemistry Research, Vol. 52, Issue 33 https://doi.org/10.1021/ie303469f	journal	March 2013
Applying uncertainty quantification to multiphase flow computational fluid dynamics Gel, A.; Garg, R.; Tong, C. Powder Technology, Vol. 242 https://doi.org/10.1016/j.powtec.2013.01.045	journal	July 2013
A comprehensive framework for verification, validation, and uncertainty quantification in scientific computing Roy, Christopher J.; Oberkampf, William L. Computer Methods in Applied Mechanics and Engineering, Vol. 200, Issue 25-28 https://doi.org/10.1016/j.cma.2011.03.016	journal	June 2011
Bayesian calibration of computer models Kennedy, Marc C.; O'Hagan, Anthony Journal of the Royal Statistical Society: Series B (Statistical Methodology), Vol. 63, Issue 3 https://doi.org/10.1111/1467-9868.00294	journal	August 2001
Study of factors affecting syngas quality and their interactions in fluidized bed gasification of lignite coal Karimipour, Shayan; Gerspacher, Regan; Gupta, Rajender Fuel, Vol. 103 https://doi.org/10.1016/j.fuel.2012.06.052	journal	January 2013
Predictive modeling of a radiative shock system Holloway, James Paul; Bingham, Derek; Chou, Chuan-Chih Reliability Engineering & System Safety, Vol. 96, Issue 9 https://doi.org/10.1016/j.ress.2010.08.011	journal	September 2011
Premixed burning in diffusion flames—the flame zone model of libby and economos Peters, Norbert International Journal of Heat and Mass Transfer, Vol. 22, Issue 5 https://doi.org/10.1016/0017-9310(79)90117-0	journal	May 1979
Catalytic activity of coal ash on steam methane reforming and water-gas shift reactions Chen, W. J.; Sheu, F. R.; Savage, R. L. Fuel Processing Technology, Vol. 16, Issue 3 https://doi.org/10.1016/0378-3820(87)90025-7	journal	June 1987

Cited By (1)

Experimental data for code validation: Horizontal air jets in a semicircular fluidized bed of Geldart Group D particles Fullmer, William D.; LaMarche, Casey Q.; Issangya, Allan AIChE Journal, Vol. 64, Issue 7 https://doi.org/10.1002/aic.16128	journal	February 2018

Similar Records

Uncertainty Quantification Analysis of Both Experimental and CFD Simulation Data of a Bench-scale Fluidized Bed Gasifier

Technical Report · Mon Oct 02 00:00:00 EDT 2017 · OSTI ID:1480085

Shahnam, Mehrdad; Gel, Aytekin; Subramaniyan, Arun K.; +2 more

CFD modeling of commercial-scale entrained-flow coal gasifiers

Conference · Sun Jan 01 00:00:00 EST 2012 · OSTI ID:1480085

Ma, J; Zitney, S

CFD modeling of entrained-flow coal gasifiers with improved physical and chemical sub-models