Computational Fluid Dynamic Simulations of a Pilot-Scale Transport Coal Gasifier: Evaluation of Reaction Kinetics

Li, Tingwen; Chaudhari, Kiran; VanEssendelft, Dirk; Turton, Richard; Nicoletti, P.; Shahnam, Mehrdad; Guenther, Chris

doi:10.1021/ef401887r

Cited by 22 publications

(6 citation statements)

References 36 publications

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“…The char–steam gasification rate from MGAS model (A = 2.25 × 10 3 atm −1 s −1 ) is used; however, the predicted mole fraction of CO and H 2 out of the riser is lower than the experimental data. Similarly, Li et al and Guenther et al also found that MGAS model underestimated the mole fraction of CO and H 2 in the simulations of gasification processes of Kellogg Brown & Root, Inc. (KBR) gasifier, because of the low steam gasification rate in MGAS model . The char–steam reaction rate is dependent on coal type.…”

Section: Resultsmentioning

confidence: 93%

Computational fluid dynamics simulation and parametric study of coal gasification in a circulating fluidized bed reactor

Zhang

Lei

Xiao

2015

Asia-Pacific J Chem Eng

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A computational fluid dynamics model based on the Eulerian-Eulerian multiphase framework was implemented to simulate the coal gasification processes in a circulating fluidized bed gasifier. The standard k-ε turbulence model is used for gas phase, and the solid phases are modeled with kinetic theory of granular flow. A lumped chemical reaction model was compiled based on the chemical percolation devolatilization model and the METC Gasifier Advanced Simulation gasification model. The user-defined functions are developed to calculate rates of chemical reactions and to recirculate solids from the riser exit to the solid recycle inlet. Sensitivity analysis was performed on char-steam gasification reaction to choose an appropriate kinetic rate in this study. The calculated gas composition out of the riser was first compared with experimental data; then, the flow fields such as solid volume fraction, solid velocity, and species profiles were analyzed, indicating that the model gave reasonable predictions. Furthermore, the effects of the operating temperature, the steam/coal ratio, and the air/coal ratio on the exiting gas composition were numerically studied, and the predicted trends vs these parameters are reasonable and consistent with the findings in the literature, which shows the applicability of the Eulerian multiphase model to simulate coal gasification processes in circulating fluidized bed gasifiers.

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Section: Resultsmentioning

confidence: 93%

Computational fluid dynamics simulation and parametric study of coal gasification in a circulating fluidized bed reactor

Zhang

Lei

Xiao

2015

Asia-Pacific J Chem Eng

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“…The CPD model includes rates for bridge breaking and side chain release, percolation lattice statistics to relate the number of broken bridges to the distribution of clusters that detach from the lattice, vapor-liquid equilibrium to determine the sizes of detached clusters that vaporize to form tar, and crosslinking of non-vaporized detached fragments that become part of the char. The CPD model has been shown to agree with pyrolysis data for a wide range of coals, heating rates, temperatures, and pressures, [3,12, and hence is used as an example reference model in this paper.…”

Section: Cpd Modelmentioning

confidence: 99%

“…Niksa [10,11] developed a method for a given heating rate to determine coefficients for a 1-step devolatilization model from PC Coal Lab using his Flashchain network model and other similar char chemistry models. Li et al [12] also developed a package to interface with computational fluid dynamics software to develop coefficients for a 1-step devolatilization model based on several different network models for coal combustion, called Carbonaceous Chemistry for Computational Modeling, nicknamed C3M . Hashimoto et al [13] used an iterative technique to generate coal devolatilization rate parameters for a CFD model, taking the particle temperature history from each previous CFD particle trajectory to determine rate parameters for the next iteration.…”

Section: Introductionmentioning

confidence: 99%

A comparison of simple global kinetic models for coal devolatilization with the CPD model

Richards

Fletcher

2016

Fuel

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Simulations of coal combustors and gasifiers generally cannot incorporate the complexities of advanced pyrolysis models, and hence there is interest in evaluating simpler models over ranges of temperature and heating rate that are applicable to the furnace of interest. In this paper, six different simple model forms are compared to predictions made by the Chemical Percolation Devolatilization (CPD) model. The model forms included three modified one-step models, a simple two-step model, and two new modified two-step models. These simple model forms were compared over a wide range of heating rates (5  10 3 K/s to 10 6 K/s) at final temperatures up to 1600 K. Comparisons were made of total volatiles yield as a function of temperature, as well as the ultimate volatiles yield.Advantages and disadvantages for each simple model form are discussed. A modified two-step model with distributed activation energies seems to give the best agreement with CPD model predictions (with the fewest tunable parameters).

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“…Following this validation hierarchy, a series of validation experiments and corresponding simulation runs have been performed. The CFD simulations are based on an open-source multiphase flow computer code MFIX (https://mfix.netl.doe.gov), which has been validated successfully for multiphase flow simulations including those with chemical reactions [10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Hierarchical calibration and validation of computational fluid dynamics models for solid sorbent-based carbon capture

Lai

Pan

et al. 2016

Powder Technology

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To quantify the predictive confidence of a device scale solid sorbent-based carbon capture design where there is no direct experimental data available, a hierarchical validation methodology is first proposed. In this hierarchy, a sequence of increasingly complex "unit problems" are validated using a statistical calibration framework. This paper describes the computational fluid dynamics (CFD) multi-phase reactive flow simulations and the associated data flows within each unit problem. Each validation requires both simulated and physical data, so the bench-top experiments used in each increasingly complex stage were carefully designed to follow the same operating conditions as the simulation scenarios. A Bayesian calibration procedure is employed and the posterior model parameter distributions obtained at one unitproblem level are used as prior distributions for the same parameters in the next-tier simulations.Overall, the results have demonstrated that the calibrated multiphase reactive flow models within MFIX can be used to capture the bed pressure, temperature, CO2 capture capacity, and kinetics © 2015. This manuscript version is made available under the Elsevier user license http://www.elsevier.com/open-access/userlicense/1.0/ 2 with quantitative accuracy. The CFD modeling methodology and associated uncertainty quantification techniques presented herein offer a solid framework for estimating the predictive confidence in the virtual scale up of a larger carbon capture device. KeywordsComputational fluid dynamics, carbon capture, hierarchical model validation methodology, multiphase reactive flow models, Bayesian calibration, MFIX.

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Computational Fluid Dynamic Simulations of a Pilot-Scale Transport Coal Gasifier: Evaluation of Reaction Kinetics

Cited by 22 publications

References 36 publications

Computational fluid dynamics simulation and parametric study of coal gasification in a circulating fluidized bed reactor

Computational fluid dynamics simulation and parametric study of coal gasification in a circulating fluidized bed reactor

A comparison of simple global kinetic models for coal devolatilization with the CPD model

Hierarchical calibration and validation of computational fluid dynamics models for solid sorbent-based carbon capture

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