Research Papers: Fuel Combustion

Investigation of the Predicting Ability of Single-Phase Chemical Equilibrium Modeling Applied to Circulating Fluidized Bed Coal Gasification

[+] Author and Article Information
Ekin Kaya

Department of Chemical Engineering,
Hacettepe University,
Ankara 06800, Turkey;
New and Clean Energy Sources Research and
Application Center,
Hacettepe University,
Ankara 06800, Turkey
e-mail: ekinkaya@hacettepe.edu.tr

Murat Köksal

Department of Mechanical Engineering,
Hacettepe University,
Ankara 06800, Turkey
e-mail: koksalm@hacettepe.edu.tr

1Corresponding author.

Contributed by the Advanced Energy Systems Division of ASME for publication in the JOURNAL OF ENERGY RESOURCES TECHNOLOGY. Manuscript received October 26, 2015; final manuscript received November 12, 2015; published online January 5, 2016. Editor: Hameed Metghalchi.

J. Energy Resour. Technol 138(3), 032203 (Jan 05, 2016) (12 pages) Paper No: JERT-15-1402; doi: 10.1115/1.4032207 History: Received October 26, 2015; Revised November 12, 2015

In this study, a nonstoichiometric single-phase chemical equilibrium model was developed to simulate atmospheric circulating fluidized bed (CFB) coal gasifiers in reference to the available experimental and simulation data. In the literature, since the single-phase model assumes complete conversion of the solid particles to gas phase, the predictions for the resulting products of the gasifiers considerably deviate from the measured product concentrations. Two different model modifications for carbon conversion and temperature to improve the model results were tested. Particularly, carbon conversion modification has been found to improve the predictive ability significantly. The main reasons of the inaccuracy in the tested cases as well as the performance of some other modifications (quasi-equilibrium approach, empirical correlation for carbon conversion, etc.) were also discussed in comparison with the literature data. An alternative mathematical procedure that simplifies the formulation and numerical implementation was suggested as well.

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Grahic Jump Location
Fig. 1

Flowchart of the numerical procedure and the RAND algorithm implemented in matlab

Grahic Jump Location
Fig. 2

Simulation with the single-phase base model (case 1) and the two-phase base model (case 2)

Grahic Jump Location
Fig. 3

ΔT modification for the base model (case 3)

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Fig. 4

C_conversion modification with the exact experimental value

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Fig. 5

C_conversion modification with the empirical formulation for the single-phase base model (case 5) and the two-phase base model (case 6)

Grahic Jump Location
Fig. 6

Change in SSPD with increasing ER



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