Pyrolysis and combustion of bituminous coal fractions in an entrained-flow reactor

Accurate knowledge of char oxidation rate parameters is of paramount importance in modeling coal combustion behavior. Generally, an isothermal thermogravimetric analyzer (TGA) is used to determine the intrinsic rate parameters. However, despite operating in a kinetic controlled regime, i.e., at relatively lower reaction temperatures, the char reactivity profile (reaction rate versus burnoff) has often been observed to go through a maximum. The existence of a maximum in the reactivity profile poses a difficulty in extracting the intrinsic rate parameters. This present paper attempts to investigate the conditions that may lead to such a maximum and recommends a method to deduce the kinetic parameters from such a profile. To address this matter, a high volatile bituminous coal is pyrolzyed in a drop tube reactor (DTR) at different furnace temperatures and in a TGA. Physical and structural properties of the char samples generated in DTR were measured, and the reactivity of the resultant char samples was determined in a TGA. The results demonstrate that both the pyrolysis history and char oxidation temperature have a significant effect on the shape of the rate profile obtained in a TGA. It is proposed that such an occurrence of a maximum is due to a transition from a intraparticle diffusion controlled zone to a kinetic controlled zone. This was further confirmed by observation of similar estimated activation energy values at several conversion levels after the maximum.

Section: Resultsmentioning

confidence: 99%

Interpretation of Char Reactivity Profiles Obtained Using a Thermogravimetric Analyzer

Naredi

Pisupati

2007

“…The experimental results clearly show that the high-temperature VM for the D2 fraction is always greater than the D3 fraction for all coals. Tsai reported that the maximum weight loss in the entrained-flow reactor has a ranking similar to that of the proximate volatile matter on a dry, ash-free (daf) basis: that is, liptinite-rich > vitrinite-rich > inertinite-rich. The single-particle modeling approach reveals this trend clearly, whereas the bulk approach cannot.…”

Section: Resultsmentioning

confidence: 99%

A Mechanistic Approach To Characterize Coal Heterogeneity in Predicting High-Temperature Volatile Matter Yields

Tang¹,

Gupta²,

Sheng³

et al. 2004

The reflectance distribution of coal (the reflectogram), which shows the heterogeneity of coal, can be represented by several reflectance bins. In this paper, in considering the heterogeneity of coal, coal is regarded as a mixture of particles. Each particle is characterized by reflectance and is treated as being homogeneous, without considering the intraparticle heterogeneity. The chemical compositions (volatile matter (VM), carbon content (C%), ratio of hydrogen to carbon (H/C)) of a single particle have been estimated from previous works and are used to derive the 13C NMR parameters of this particle. These parameters are input into the chemical percolation devolatilization (CPD) model to predict the high-temperature VM yields of this particle. The total VM yields of the coal can be obtained by a summation of the results of all of the particles. In the experimental portion, the sink−float technique has been used to separate a series of coals into different maceral-rich fractions, which exhibit very different reflectance distributions. The high-temperature VM yields of these samples have been obtained from drop tube furnace pyrolysis experiments at 1400 °C to validate the model. The results from pyrolysis experiments and the single-particle modeling approach show that, under high temperature, the inertinite-rich fraction produces less VM than does the vitrinite-rich fraction of the same coal. The inertinite-rich fraction has a lower Q factor, which is defined as the ratio of high-temperature VM yields and proximate VM, than its vitrinite counterpart. The high-temperature VM yields also have been estimated from bulk properties of coal samples from the CPD model. These estimations do not agree with the experimental data. The model could not be applied to those coals that showed abnormal reflectance features.

“…The pulverized fuel process has been documented and is generally well-understood. − During pulverized fuel combustion the coal particles are rapidly pyrolyzed 2,3 (10−100 ms) to yield char particles which then burnout 4 (50−2000 ms). The importance of char morphology on burnout is also well-documented, − hence, the ability to describe chars in a meaningful way to those investigating char combustion behavior is very useful. , Oil immersion microscopy is a means of studying char morphology by observing sectioned char particles.…”

Section: Introductionmentioning

confidence: 99%

Advanced Automated Char Image Analysis Techniques

Lester

Cloke

2006

Char morphology is an important characteristic when attempting to understand coal behavior and coal burnout. In this study, an augmented algorithm has been proposed to identify char types using image analysis. On the basis of a series of image processing steps, a char image is singled out from the whole image, which then allows the important major features of the char particle to be measured, including size, porosity, and wall thickness. The techniques for automated char image analysis have been tested against char images taken from ICCP Char Atlas as well as actual char particles derived from pyrolyzed char samples. Thirty different chars were prepared in a drop tube furnace operating at 1300 °C, 1% oxygen, and 100 ms from 15 different world coals sieved into two size fractions (53-75 and 106-125 µm). The results from this automated technique are comparable with those from manual analysis, and the additional detail from the automated sytem has potential use in applications such as combustion modeling systems. Obtaining highly detailed char information with automated methods has traditionally been hampered by the difficulty of automatic recognition of individual char particles.