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Advanced Coal Characterization: A Review

机译:先进的煤炭表征:综述

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摘要

Coal is highly heterogeneous in nature, and for this reason, several analytical techniques are needed for its characterization so as to accurately predict its behavior during conversion processes such as combustion, gasification, or liquefaction. Conventional analyses such as proximate analysis, ash analysis, and ash fusion temperatures assume coal as a homogeneous material and provide only bulk properties. The performance correlations based on these analyses are unable to describe adequately the impact of coal quality on conversion efficiencies and plant performance. A number of advanced bulk analytical techniques, such as FTIR and ~(13)C NMR, provide information on the organic structure of coal. Chemical fractionation technique provides information on the inorganic matter present in coal in a form other than mineral grains. Bulk analysis techniques such as XRD and SIROQUANT provide information on the types of minerals present in coal. Thermomechanical analysis (TMA)—an advanced bulk analytical technique—provides detailed thermal behavior of ash relevant to power-plant operations. Several advanced characterization techniques have emerged recently which consider pulverized coal as a heterogeneous material made up of individual particles and are able to examine these coal particles in much greater detail. An automated reflectogram (AR) technique provides a variation of reflectivity— a measure of heterogeneity in the organic part. A computer-controlled scanning electron microscopy (CCSEM) analysis technique has been developed over the last 25 years to provide much more detailed information on mineral matter in coal and mineral—coal associations in pulverized coal. The paper discusses the details of these techniques and how the analysis from these techniques is used in modeling procedures to provide a better understanding of coal conversion behavior.
机译:煤炭本质上是高度异质的,因此,需要多种分析技术来表征煤炭,以便准确预测其在燃烧,气化或液化等转化过程中的行为。常规分析(例如近似分析,灰分分析和灰分熔融温度)假定煤为均质材料,并且仅提供整体性质。基于这些分析的绩效关联无法充分描述煤炭质量对转化效率和工厂绩效的影响。许多先进的本体分析技术,例如FTIR和〜(13)C NMR,可提供有关煤有机结构的信息。化学分馏技术提供了以矿物颗粒以外的形式存在于煤中的无机物信息。诸如XRD和SIROQUANT之类的大量分析技术可提供有关煤中矿物类型的信息。热力学分析(TMA)是一种先进的本体分析技术,可提供与电厂运行有关的灰分的详细热行为。最近出现了几种先进的表征技术,这些技术将煤粉视为由单个颗粒组成的异质材料,并能够更详细地检查这些煤颗粒。自动反射图(AR)技术提供了反射率的变化,即有机部分中异质性的一种度量。在过去的25年中,已经开发了一种计算机控制的扫描电子显微镜(CCSEM)分析技术,以提供有关煤中矿物质和煤粉中煤-矿物结合的详细信息。本文讨论了这些技术的细节,以及如何在建模过程中使用这些技术的分析结果以更好地了解煤炭转化行为。

著录项

  • 来源
    《Energy & fuels 》 |2007年第2期| p.451-460| 共10页
  • 作者

    Rajender Gupta;

  • 作者单位

    Department of Chemical and Materials Engineering, University of Alberta, Edmonton, Alberta T6G 2G6, Canada;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 TK-;
  • 关键词

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