首页> 外文会议>Proceedings of the Combustion Institute >MODELING CHAR COMBUSTION: THE INFLUENCE OF PARENT COAL PETROGRAPHY AND PYROLYSIS PRESSURE ON THE STRUCTURE AND INTRINSIC REACTIVITY OF ITS CHAR
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MODELING CHAR COMBUSTION: THE INFLUENCE OF PARENT COAL PETROGRAPHY AND PYROLYSIS PRESSURE ON THE STRUCTURE AND INTRINSIC REACTIVITY OF ITS CHAR

机译:模拟焦炭燃烧:母体煤层照相和热解压力对其炭的结构和内在反应性的影响

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Chars were made from four Australian coals of varying vitrinite content at pressures of 5, 10, and 15 atm. The morphology of the chars was correlated with the petrography of the parent coal. The intrinsic reaction rates of the chars at high pressures were measured, and no systematic effect of pyrolysis pressure or maceral concentration was found. It is concluded that observed variations in conversion rates under process conditions are likely to be due to char structural properties and not a result of variation in the intrinsic reactivity of the carbon in the chars. Consequently, this paper presents a char structural submodel that is integrated into an existing char combustion model to account for the combustion behavior of char particles of different morphologies. The char morphology used in the model was predicted using the developed correlation with parent coal petrography, so that a petrographic analysis as well as the proximate and ultimate analyses is required for model input. Validation of the model shows that chars produced at high pressure with a high percentage of cenospherical types burn more rapidly under process conditions than those at low pressure, with model predictions matching measurements. It is suggested that incorporating the char structural submodel into the existing char combustion model improves its predictability.
机译:来自四个澳大利亚煤中的特征,在5,10和15个atm的压力下不同的玻毛酸盐含量。字符的形态与母煤的岩画相关。测量了高压下的CASs的固有反应速率,未发现热解压或丙烯浓度的系统效果。得出结论,在工艺条件下观察到的转化率的变化可能是由于炭结构特性,而不是碳中碳中固有反应性的变化的结果。因此,本文呈现了一种炭结构子模型,该子模型集成到现有的Char燃烧模型中,以考虑不同形态的Char颗粒的燃烧行为。使用与母煤岩画的相关相关性的模型中使用的CHAR形态,从而需要岩体分析以及模型输入所需的近似和最终分析。该模型的验证表明,在高百分比的高压下产生的Chars在工艺条件下比低压下的过程条件燃烧得更快,模型预测匹配测量。建议将Char结构子模型结合到现有的炭燃烧模型中提高了其可预测性。

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