The Thermal and Structural Properties of a Hanna Basin Coal

1984 ◽  
Vol 106 (2) ◽  
pp. 266-271 ◽  
Author(s):  
R. E. Glass
Keyword(s):  
Structural Properties ◽  
Coal Gasification ◽  
Cavity Growth ◽  
Underground Coal Gasification ◽  
Growth Mechanisms ◽  
Hanna Basin ◽  
The Town ◽  
Thermomechanical Effects

In an effort to understand the cavity growth mechanisms occurring during an Underground Coal Gasification (UCG) test, a study of the thermomechanical effects has been initiated at Sandia National Laboratories. The first phase of this study has been the determination of the intrinsic thermal and structural properties of the Hanna Basin Coal that was utilized in a series of four UCG tests near the town of Hanna, Wyoming. The result of this study is a consistent set of thermal and structural properties of a Hanna Basin coal. This set has been used in a model that successfully simulated the growth of the cavity observed during the Hanna II UCG test.

Laboratory studies on combustion cavity growth in lignite coal blocks in the context of underground coal gasification

Energy ◽  
2010 ◽  
Vol 35 (6) ◽  
pp. 2374-2386 ◽  
Author(s):  
Sateesh Daggupati ◽  
Ramesh N. Mandapati ◽  
Sanjay M. Mahajani ◽  
Anuradda Ganesh ◽  
D.K. Mathur ◽  
...  
Keyword(s):  
Coal Gasification ◽  
Cavity Growth ◽  
Laboratory Studies ◽  
Underground Coal Gasification ◽  
Lignite Coal

scholarly journals Regression Models Utilization to the Underground Temperature Determination at Coal Energy Conversion

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5444
Author(s):  
Milan Durdán ◽  
Marta Benková ◽  
Marek Laciak ◽  
Ján Kačur ◽  
Patrik Flegner
Keyword(s):  
Coal Seam ◽  
Regression Model ◽  
Regression Models ◽  
Coal Gasification ◽  
Cavity Growth ◽  
Temperature Data ◽  
Ex Situ ◽  
Underground Coal Gasification ◽  
Gasification Process ◽  
Cavity Growth Rate

The underground coal gasification represents a technology capable of obtaining synthetic coal gas from hard-reached coal deposits and coal beds with tectonic faults. This technology is also less expensive than conventional coal mining. The cavity is formed in the coal seam by converting coal to synthetic gas during the underground coal gasification process. The cavity growth rate and the gasification queue’s moving velocity are affected by controllable variables, i.e., the operation pressure, the gasification agent, and the laboratory coal seam geometry. These variables can be continuously measured by standard measuring devices and techniques as opposed to the underground temperature. This paper researches the possibility of the regression models utilization for temperature data prediction for this reason. Several regression models were proposed that were differed in their structures, i.e., the number and type of selected controllable variables as independent variables. The goal was to find such a regression model structure, where the underground temperature is predicted with the greatest possible accuracy. The regression model structures’ proposal was realized on data obtained from two laboratory measurements realized in the ex situ reactor. The obtained temperature data can be used for visualization of the cavity growth in the gasified coal seam.

A Side Wall Burn Model for Cavity Growth in Underground Coal Gasification

1983 ◽  
Vol 105 (2) ◽  
pp. 145-155 ◽  
Author(s):  
T. L. Eddy ◽  
S. H. Schwartz
Keyword(s):  
Coal Gasification ◽  
Cavity Growth ◽  
Side Wall ◽  
Field Tests ◽  
Underground Coal Gasification ◽  
Convection Diffusion ◽  
Bituminous Coals ◽  
Thin Seam ◽  
Burn Through ◽  
Cavity Width

A mechanistic computer model is presented which predicts the 3-D cavity growth during the gasification phase of underground coal gasification. Developed for swelling bituminous coals, the model also obtains reasonable cavity width and length values for shrinking sub-bituminous coals. The model predicts cavity shape and burn-through times based on the coal properties, seam thickness, water reacting and the interwell distance. Employing a 2-D boundary layer model to determine the convective diffusion rate of oxygen to the reacting walls, it is found that natural convection diffusion must be included. The model includes flow in the injection region, the swirling, mixing effect in the cavity, and transitions from thick to thin seam geometry. Simulations of the Hanna II, Phase 2 and Pricetown I field tests, as well as a parametric study on Pittsburgh seam coal, are presented.

scholarly journals Determination of the Technological Parameters of Borehole Underground Coal Gasification for Thin Coal Seams

2013 ◽  
Vol 12 (3) ◽  
pp. 8-16 ◽  
Author(s):  
Volodymyr S. Falshtynskyi ◽  
Roman O. Dychkovskyi ◽  
Vasyl G. Lozynskyi ◽  
Pavlo B. Saik
Keyword(s):  
Coal Gasification ◽  
Underground Coal Gasification ◽  
Technological Parameters ◽  
Coal Seams

scholarly journals Determination of Ammonium Concentration in Post-Process Waters from Underground Coal Gasification

2016 ◽  
Vol 21 (1-2) ◽  
pp. 107-116
Author(s):  
Malwina Cykowska ◽  
Małgorzata Bebek ◽  
Aleksandra Strugała-Wilczek
Keyword(s):  
Flow Injection ◽  
Flow Injection Analysis ◽  
Coal Gasification ◽  
Ammonium Concentration ◽  
Hard Coal ◽  
Underground Coal Gasification ◽  
Permeable Membrane ◽  
Indicator Solution ◽  
Validation Parameters

AbstractA flow injection analysis method for spectrophotometric determination of ammonium in waters produced during underground coal gasification (UCG) of lignite and hard coal was described. The analysis of UCG water samples is very difficult because of their very complicated matrix and colour. Due to a huge content of organic and inorganic substances and intensive colour of samples (sometimes yellow, quite often dark brown or even black), most analytical methods are not suitable for practical application. Flow injection analysis (FIA) is based on diffusion of ammonia through a hydrophobic gas permeable membrane from an alkaline solution stream into an acid-base indicator solution stream. Diffused ammonia causes a colour change of indicator solution, and ammonia is subsequently quantified spectrophotometrically at 590 nm wavelength. The reliability of the results provided by applied method was evaluated by checking validation parameters like accuracy and precision. Accuracy was evaluated by recovery studies using multiple standard addition method. Precision as repeatability was expressed as a coefficient of variation (CV).

Sign in / Sign up

Export Citation Format

Share Document