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Title: Comprehensive model for predicting elemental composition of coal pyrolysis products

Abstract

Large-scale coal combustion simulations depend highly on the accuracy and utility of the physical submodels used to describe the various physical behaviors of the system. Coal combustion simulations depend on the particle physics to predict product compositions, temperatures, energy outputs, and other useful information. The focus of this paper is to improve the accuracy of devolatilization submodels, to be used in conjunction with other particle physics models. Many large simulations today rely on inaccurate assumptions about particle compositions, including that the volatiles that are released during pyrolysis are of the same elemental composition as the char particle. Another common assumption is that the char particle can be approximated by pure carbon. These assumptions will lead to inaccuracies in the overall simulation. There are many factors that influence pyrolysis product composition, including parent coal composition, pyrolysis conditions (including particle temperature history and heating rate), and others. All of these factors are incorporated into the correlations to predict the elemental composition of the major pyrolysis products, including coal tar, char, and light gases.

Authors:
 [1];  [1];  [1]
  1. Brigham Young Univ., Provo, UT (United States)
Publication Date:
Research Org.:
Univ. of Utah, Salt Lake City, UT (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1363887
Report Number(s):
DOE-UTAH-DENA0002375-FLETCHER-0006
DOE Contract Number:
NA0002375
Resource Type:
Conference
Resource Relation:
Journal Issue: 3; Conference: 10th U.S. National Combustion Meeting, Eastern States Section of the Combustion Institute, College Park, MD (United States), 23-26 Apr 2017
Country of Publication:
United States
Language:
English
Subject:
01 COAL, LIGNITE, AND PEAT; Pyrolysis; Coal; Modeling

Citation Formats

Ricahrds, Andrew P., Shutt, Tim, and Fletcher, Thomas H. Comprehensive model for predicting elemental composition of coal pyrolysis products. United States: N. p., 2017. Web.
Ricahrds, Andrew P., Shutt, Tim, & Fletcher, Thomas H. Comprehensive model for predicting elemental composition of coal pyrolysis products. United States.
Ricahrds, Andrew P., Shutt, Tim, and Fletcher, Thomas H. Sun . "Comprehensive model for predicting elemental composition of coal pyrolysis products". United States. doi:.
@article{osti_1363887,
title = {Comprehensive model for predicting elemental composition of coal pyrolysis products},
author = {Ricahrds, Andrew P. and Shutt, Tim and Fletcher, Thomas H.},
abstractNote = {Large-scale coal combustion simulations depend highly on the accuracy and utility of the physical submodels used to describe the various physical behaviors of the system. Coal combustion simulations depend on the particle physics to predict product compositions, temperatures, energy outputs, and other useful information. The focus of this paper is to improve the accuracy of devolatilization submodels, to be used in conjunction with other particle physics models. Many large simulations today rely on inaccurate assumptions about particle compositions, including that the volatiles that are released during pyrolysis are of the same elemental composition as the char particle. Another common assumption is that the char particle can be approximated by pure carbon. These assumptions will lead to inaccuracies in the overall simulation. There are many factors that influence pyrolysis product composition, including parent coal composition, pyrolysis conditions (including particle temperature history and heating rate), and others. All of these factors are incorporated into the correlations to predict the elemental composition of the major pyrolysis products, including coal tar, char, and light gases.},
doi = {},
journal = {},
number = 3,
volume = ,
place = {United States},
year = {Sun Apr 23 00:00:00 EDT 2017},
month = {Sun Apr 23 00:00:00 EDT 2017}
}

Conference:
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  • Coals come in various ranks and from different geological origins. Substantially different characteristics are commonly observed for coals of different ranks. Coal samples from the same seam can exhibit large variations in their devolatilization and related thermal and combustion behavior. Such variations have large impacts to the design and operating conditions of coal combustion systems. This paper presents a general method that provides a direct correlation between coal elemental composition and the input paramaeters of a general coal devolatilization model which can predict the yields of tar, volatile species, molecular weight distribution, and char fluidity.
  • An interpolation method was proposed to correlate the input parameters of a coal devolatilization model functional group-depolymerization, vaporization, cross-linking (FG-DVC) to coals of a wide range of ranks, and is conceptually applicable to other devolatilization models. This method uses a set of well-defined coals (library coals) to form a triangular mesh in the van Krevelen diagram. If an unknown coal is within a triangle formed by three library coals, the model input parameters for this unknown coal can be interpolated from those of the three library coals based solely on the elemental composition. This method extends the FC-DVC model tomore » be able to model any coal that can be interpolated, without the requirement for any additional characterization of the coal. It is also easy to accommodate more library coals so that a wider range of coal types can be covered. The validity of this method was demonstrated by comparing the tar yield measurements and the predictions for 27 coals over a wide range of pressures and heating rates. For most of the coals, the predictions compare very well with the data. For selected coals, data were available on the variation of the yield of total volatiles with pressure and heating rate, and again, good agreement was obtained. The model could be improved by using additional parameters to describe the exchangeable cation content, sulfur content, and/or the maceral composition.« less
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