Research Papers

The Effect of Grid Resolution and Reaction Models in Simulation of a Fluidized Bed Gasifier Through Nonintrusive Uncertainty Quantification Techniques

[+] Author and Article Information
Mehrdad Shahnam

National Energy Technology Laboratory (NETL),
Morgantown, WV 26505
e-mail: mehrdad.shahnam@netl.doe.gov

Aytekin Gel

ALPEMI Consulting,
Phoenix, AZ 85044

Jean-François Dietiker

West Virginia University Research Corporation,
Morgantown, WV 26506

Arun K. Subramaniyan

GE Global Research Center,
Niskayuna, NY 12309

Jordan Musser

National Energy Technology Laboratory (NETL),
Morgantown, WV 26505

1Corresponding author.

Manuscript received May 20, 2016; final manuscript received December 6, 2016; published online January 9, 2017. Assoc. Editor: Sumanta Acharya.The United States Government retains, and by accepting the article for publication, the publisher acknowledges that the United States Government retains, a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for United States government purposes.

J. Verif. Valid. Uncert 1(4), 041004 (Jan 09, 2017) (9 pages) Paper No: VVUQ-16-1014; doi: 10.1115/1.4035445 History: Received May 20, 2016; Revised December 06, 2016

To improve quality of numerical models used in simulations of a fluidized bed gasifier at any scale, the sources of uncertainty in the simulation have to be identified and quantified. There are several sources of uncertainty that can affect any simulation result and scale up process such as uncertainty in the model input values, uncertainty in the reaction models and kinetic rates, uncertainty in selection of the appropriate numerical models affecting the hydrodynamics, uncertainty in selection of adequate computational grid resolution (uncertainty due to discretization error), uncertainty in the selection of proper numerical techniques required for solution of the discretized conservation equations, and many more. The current study aims to investigate the effect that reaction models for gasification, char oxidation, carbon monoxide oxidation, and water gas shift will have on the syngas composition at different grid resolution, along with bed temperature, which affects the reactions. The global sensitivity analysis conducted showed that among various reaction models employed for water gas shift, gasification, char oxidation, the choice of reaction model for water gas shift has the greatest influence on syngas composition, with gasification reaction model being second. Syngas composition also shows a small sensitivity to temperature of the bed. The hydrodynamic behavior of the bed did not change beyond grid spacing of 18 times the particle diameter. However, the syngas concentration continued to be affected by the grid resolution as low as 9 times the particle diameter. This is due to a better resolution of the phasic interface between the gas and solid that leads to stronger heterogeneous reactions.

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Fig. 1

Snap shots of the instantaneous voidage at two different time for three mesh resolution

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Fig. 2

Time-averaged coal volume fraction (left) and its standard deviation (right) at three different grid resolutions

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Fig. 3

Time-averaged sand volume fraction (left) and its standard deviation (right) at three different grid resolutions

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Fig. 4

Frequency spectrum of CO mole fraction at three grid resolutions

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Fig. 5

Instantaneous contours of voidage (a), steam mass fraction (b), CO2 mass fractions (c), steam gasification reaction rates (d), and CO2 gasification reaction rate (e)

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Fig. 6

H2 behavior as a function of steam to oxygen ratio and multiplier to pre-exponent kinetic constant in gasification reaction model: (a) Ψ = 35, (b) Ψ = 18, and (c) Ψ = 9

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Fig. 7

Posterior distribution of the multiplier to gasification rate, after Bayesian calibration

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Fig. 8

CO mole fraction predictions for calibrated and uncalibrated gasification reaction rate

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Fig. 9

Variance of the global sensitivity of A: gasification reaction model, B: CO oxidation model, C: water gas shift reaction model, D: char oxidation model, and E: bed temperature




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