No abstract

No abstract

During underground coal gasification (UCG), a cavity is formed in the coal seam when coal is converted to gaseous products. This cavity grows three dimensionally in a nonlinear fashion as gasification proceeds. The cavity shape is determined by the flow field, which is a strong function of various parameters such as the position and orientation of the inlet nozzle and the temperature distribution and coal properties such as thermal conductivity. In addition to the complex flow patterns in the UCG cavity, several phenomena occur simultaneously. They include chemical reactions (both homogeneous and heterogeneous), water influx, thermomechanical failure of the coal, heat and mass transfer, and so on. Thus, enormous computational efforts are required to simulate the performance of UCG through a mathematical model. It is therefore necessary to simplify the modeling approach for relatively quick but reliable predictions for application in process design and optimization. The primary objective of this work is to understand the velocity distribution and quantify the nonideal flow patterns in a UCG cavity by performing residence time distribution (RTD) studies using computational fluid dynamics (CFD). The methodology of obtaining RTD by CFD is validated by means of of representative laboratory-scale tracer experiments. Based on the RTD studies, the actual UCG cavity at different times is modeled as a simplified network of ideal reactors, called compartments. The compartment model thus obtained could offer a computationally less expensive and easier option for determining UCG process performance at any given time, when used in a reactor-scale model including reactions. The network of ideal reactors can be easily simulated using a flowsheet simulator (e.g., Aspen Plus). We illustrate the proposed modeling approach by presenting selected simulation results for a single gas-phase second-order water−gas shift reaction.

Gasification of four Indian coals is carried out in a CO2 atmosphere, using a thermogravimetric analyzer (TGA) to determine the intrinsic kinetics over a temperature range of 800–1050 °C with different partial pressures of CO2. The applicability of three models, viz., the volumetric reaction model, the shrinking core model and the random pore model, is evaluated. Of these three models, the random pore model is found to be the most suitable for all the coals considered in the current study. The dependence of the reaction rate on the gas-phase partial pressures is explained by the Langmuir–Hinshelwood model, and the parameters for the inhibition due to CO and CO2 are determined by performing experiments at different partial pressures. In underground coal gasification, the reaction takes place on reasonably large sized coal particles, wherein diffusion effects are significant. A one-dimensional reaction diffusion model is therefore developed in order to determine the diffusional resistance in the coal particle, and values of diffusivity are estimated.

Process development for the production of syngas by gasification of biomass, a carbon-neutral source of energy, has been researched very extensively in the recent past. One of the technical challenges in biomass gasification is to produce clean syngas with no tar. Tar removal by employing secondary bed is a solution, but it faces higher cost and reliability issues. Hence, extensive work is directed to produce syngas with no tar formation in the gasifier bed itself, by employing a suitable catalyst or other options. In the present work, a dual fluidized bed process for catalytic gasification of biomass is proposed for the production of high-quality syngas. This process employs an alkali-impregnated alumina or silica-alumina catalyst that eliminates tar formation completely while increasing the H2-to-CO molar ratio to more than 10. The catalyst is able to completely gasify the volatiles and solid char generated from biomass in the temperature range of 500–750 °C, at near-atmospheric pressure, with catalyst-to-biomass ratio of 10–20 and steam-to-biomass ratio of 1.0. The present work established for the first time a new solid–solid catalytic reaction mechanism based on the novel concept of “migratory catalysis”, which is supported by in-depth microreactor studies and phase identification by in situ X-ray diffraction (XRD) and conventional XRD. It has been established in this work that potassium from the catalyst particles becomes mobile and migrates to feed carbon particles through mass transfer of volatile potassium intermediate, which has low vapor pressure, <2.4 × 10–2 Pa, at temperature of 600–910 °C, but sufficient enough for required mass transfer at gasification conditions. However, potassium migrates back to the catalyst particles by the reaction of KOH with carbon dioxide in the reaction environment. Thus, there is no effective loss of potassium (K) from the bed. Such migration of intermediate species between solid catalyst and solid feed particles demonstrates a new pathway of catalysis among solid particles.

No abstract

Characterization of reactant gas flow patterns in the underground coal gasification (UCG) cavity is important, because the flow is highly nonideal and likely to influence the quality of the product gas. In our earlier work [Daggupati et al., Energy 2010, we have demonstrated a computational fluid dynamics (CFD)-based modeling approach to analyze the flow patterns in the cavity. A compartment model (network of ideal reactors) for the UCG cavity was developed based on the CFD simulation results. These studies were performed assuming that the UCG cavity is isothermal. In reality, large temperature gradients may prevail under certain conditions and, in turn, may influence the flow patterns. In this work, we consider different possible nonisothermal scenarios in the UCG cavity and propose a simplified compartment modeling strategy to reduce the computational burden. We also examine the effect of various operating and design parameters such as coal spalling, feed flow rate, feed temperature, and orientation of the inlet nozzle. All these effects are quantified by determining the corresponding compartment model parameters. The sensitivity of the compartment model parameters, with respect to the changes in various conditions, is studied. Furthermore, we validate the compartment modeling approach by comparing predicted conversions for a water-gas shift reaction with that of reaction-enabled CFD simulations under nonisothermal conditions. The results presented here provide adequate insight into the UCG process and can be conveniently used in the development of a computationally inexpensive phenomenological process model for the complex UCG process.