Parametric Studies of Coal Gasification in an Entrained-Flow Gasifier

2015 ◽  
Author(s):  
Cheng Zhang ◽  
Kiel Schultheiss ◽  
Aniruddha Mitra ◽  
Mosfequr Rahman

Although alternative energy sources, such as nuclear, wind, and solar, are showing great potential, hydrocarbon fuels are expected to continue to play an important role in the near future. There is an increasing interest in developing technologies to use hydrocarbon fuels cleanly and efficiently. The gasification technology that converts hydrocarbon fuels into syngas is one of these promising technologies. Entrained-flow gasifiers are the preferred gasifier design for future deployment due to their high carbon conversion, high efficiency and high syngas purity. Current designs of entrained-flow gasifiers still have serious problems such as injector failure, refractory failure, slag blockages, downstream fouling and poisoning, poor space efficiency, and lack of dynamic feedstock flexibility. To better understand the entrained-flow gasification process, we performed parametric studies of coal gasification in the laboratory-scale gasifier developed at Brigham Young University (BYU) using ANSYS FLUENT. An Eulerian approach was used to describe the gas phase, and a Lagrangian approach was used to describe the particle phase. The interactions between the gas phase and particle phase was modeled using the particle-source-in-cell approach. Turbulence was modeled using the standard k-ε model. Turbulent particle dispersion was taken into account by using the discrete random walk model. Devolatilization was modeled using a version of the chemical percolation devolatilization (CPD) model, and char consumption was described with a shrinking core model. Turbulent combustion in the gas phase was modeled using a finite-rate/eddy-dissipation model. Radiation was considered by solving the radiative transport equation with the discrete ordinates model. Second-order upwind scheme was used to solve all gas phase equations. First, the numerical model was validated by using experimental data for the mole fractions of the major species (CO, CO2, H2, and H2O) along the gasifier centerline. Then, the effects of concentrations of steam and oxygen at the inlets, and steam preheat temperature were studied. Model predictions found that increasing the steam concentration or steam preheat temperature in the secondary inlet generally decreases CO concentration, while increasing CO2 and H2 concentrations. Increasing the steam concentration in the secondary inlet showed no significant effects on predicted gas temperature in the gasifier. Increasing the oxygen concentration in the primary inlet generally increases gas temperature, CO and CO2 concentrations, while decreasing H2 concentration.

Author(s):  
Rongbin Li ◽  
Mingzhuang Xie ◽  
Hui Jin ◽  
Liejin Guo ◽  
Fengqin Liu

AbstractThe three-dimensional (3-D) comprehensive mathematical model was developed to simulate the coal gasification process in an entrained flow gasifier with a swirl burner. The models employed or developed includes the coal devolatilization model, the char combustion and gasification model, the gas homogeneous reaction model, the random-trajectory model, gas turbulence model, and the P-1 radiation model. The solution of models was executed based on the computational fluid dynamics (CFD). By qualitatively comparing the results at different swirl number, the significant influences of swirl on characteristics of coal gasification such as flow distributions, gas temperature and product composition including hydrogen (H2), carbon monoxide (CO), etc., and on the performance of coal gasification such as averaged exit product composition, carbon conversion rate and cold gas efficiency, were in detail discussed. Especially, a proper swirl number (S ≤ 0.65) in favor of gasification was found for the investigated gasifier in this paper.


Author(s):  
Shaoping Shi ◽  
Christopher Guenther ◽  
Stefano Orsino

Gasification converts the carbon-containing material into a synthesis gas (syngas) which can be used as a fuel to generate electricity or used as a basic chemical building block for a large number of uses in the petrochemical and refining industries. Based on the mode of conveyance of the fuel and the gasifying medium, gasification can be classified into fixed or moving bed, fluidized bed, and entrained flow reactors. Entrained flow gasifiers normally feature dilute flow with small particle size and can be successfully modeled with the Discrete Phase Method (DPM). For the other types, the Eulerian-Eulerian (E-E) or the so called two-fluid multiphase model is a more appropriate approach. The E-E model treats the solid phase as a distinct interpenetrating granular “fluid” and it is the most general-purposed multi-fluid model. This approach provides transient, three-dimensional, detailed information inside the reactor which would otherwise be unobtainable through experiments due to the large scale, high pressure and/or temperature. In this paper, a transient, three-dimensional model of the Power Systems Development Facility (PSDF) transport gasifier will be presented to illustrate how Computational Fluid Dynamics (CFD) can be used for large-scale complicated geometry with detailed physics and chemistry. In the model, eleven species are included in the gas phase while four pseudo-species are assumed in the solid phase. A total of sixteen reactions, both homogeneous (involving only gas phase species) and heterogeneous (involving species in both gas and solid phases), are used to model the coal gasification chemistry. Computational results have been validated against PSDF experimental data from lignite to bituminous coals under both air and oxygen blown conditions. The PSDF gasifier geometry was meshed with about 70,000, hexahedra-dominated cells. A total of six cases with different coal, feed gas, and/or operation conditions have been performed. The predicted and measured temperature profiles along the gasifier and gas compositions at the outlet agreed fairly well.


Author(s):  
Cheng Zhang

The gasification technology has been applied in Integrated Gasification Combined Cycle (IGCC) plants for the production of power, and polygeneration plants for the production of industrial chemicals, fuels, hydrogen, and power. The major advantages of the gasification technology are its potential for feed-stock flexibility, product flexibility, and relative simple removal of harmful emissions of nitrogen oxides (NOx), sulfur oxides (SOx), and CO2. Entrained-flow gasifiers are the preferred gasifier design for future deployment due to their high carbon conversion, high efficiency and high syngas purity. Current entrained-flow gasifier designs still have serious problems such as injector failure, refractory failure, slag blockages, downstream fouling and poisoning, poor space efficiency, and lack of dynamic feedstock flexibility. To better understand the entrained-flow gasification process, we performed steady Reynolds-averaged Navier-Stokes (RANS) modeling of the laboratory-scale gasifier developed at Brigham Young University (BYU) using ANSYS Fluent. An Eulerian approach is used to describe the gas phase, and a Lagrangian approach is used to describe the particle phase. The interactions between the gas phase and particle phase is modeled using the particle-source-in-cell approach. Turbulence is modeled using the shear-stress transport (SST) k–ω model. Turbulent particle dispersion is taken into account by using the discrete random walk model. Devolatilization is modeled using a version of the chemical percolation devolatilization (CPD) model, and char consumption is described with a shrinking core model. Turbulent combustion in the gas phase is modeled using a finite-rate/eddy-dissipation model. Radiation is considered by solving the radiative transport equation with the discrete ordinates model. Second-order upwind scheme is used to solve all gas phase equations. First, to validate the flow solver, we performed numerical modeling of a non-reacting particle-laden bluff-body flow. For the non-reacting flow, the predicted mean velocities of the gas phase and the particle phase are in good agreement with the experimental data. Next, we performed numerical modeling of the gasification process in the BYU gasifier. The predicted profiles of the mole fractions of the major species (i.e. CO, CO2, H2, and H2O) along the centerline are in reasonable agreement with the experimental data. The predicted carbon conversion at the gasifier exit agrees with the experimental data. The predicted temperature at the gasifier exit agrees with the estimated value based on water-gas shift equilibrium considerations. The numerical model was further applied to study the effects of the equivalence ratio, particle size, and swirl on the gasification process.


Author(s):  
Hiroaki Watanabe ◽  
Kazuyoshi Ichikawa ◽  
Maromu Otaka ◽  
Jun Inumaru

The objective of this study is to develop an evaluation tool for a design and performance of a coal gasifier by a numerical simulation technique. In the present paper, a gas-particle two phase reacting flow calculation is carried out for a prediction of phenomena in an entrained flow coal gasifier due to coal and ash particles behavior, such as ash deposition on the wall. A transportation of the coal particles is modeled via a Lagrangian manner. The ash particle adhesion on the wall of the gasifier is discriminated by an empirical ash adhesion model based on a liquid phase fraction concept in the ash particle. The gas phase properties are calculated by three dimensional time-mean Eulerian conservation equations. The turbulent flow field is determined by the k-ε two equations model. Radiative heat transfer is calculated by the discrete transfer radiation method. Coal gasification reaction model is composed of three chemical processes in the current model: a pyrolysis, a char gasification and gas phase reactions. 2 tons/day (t/d) air-blown pressurized entrained flow coal gasifier, which has been constructed and operated by Central Research Institute of Electric Power Industry (CRIEPI) was targetted. As a result, a relationship between an operating condition (air ratio) of the gasifier and the gasifier performance is presented. The trend of the ash deposition on the gasifier inner wall is also presented. Comparison between the computational and the experimental results shows that the most feature of the gasifier performance and the profile of the ash deposition have been captured by the present model. It was confirmed that the numerical simulation approach is very useful for the assessment of gasifier performance and operation support.


Energies ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 6467
Author(s):  
Jakub Mularski ◽  
Norbert Modliński

This paper examines the impact of different chemistry–turbulence interaction approaches on the accuracy of simulations of coal gasification in entrained flow reactors. Infinitely fast chemistry is compared with the eddy dissipation concept considering the influence of turbulence on chemical reactions. Additionally, ideal plug flow reactor study and perfectly stirred reactor study are carried out to estimate the accuracy of chosen simplified chemical kinetic schemes in comparison with two detailed mechanisms. The most accurate global approach and the detailed one are further implemented in the computational fluid dynamics (CFD) code. Special attention is paid to the water–gas shift reaction, which is found to have the key impact on the final gas composition. Three different reactors are examined: a pilot-scale Mitsubishi Heavy Industries reactor, a laboratory-scale reactor at Brigham Young University and a Conoco-Philips E-gas reactor. The aim of this research was to assess the impact of gas phase reaction model accuracy on simulations of the entrained flow gasification process. The investigation covers the following issues: impact of the choice of gas phase kinetic reactions mechanism as well as influence of the turbulence–chemistry interaction model. The advanced turbulence–chemistry models with the complex kinetic mechanisms showed the best agreement with the experimental data.


2021 ◽  
pp. 1-13
Author(s):  
Li Tan ◽  
Ning Wang ◽  
Yingjian Dong ◽  
Siyuan Li ◽  
Xuehan Wang ◽  
...  

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