ABSTRACT

A novel method has been developed to estimate coke reactivity index (CRI) from coal properties through a kinetic approach. The model was derived from mass balance with a kinetic model of batch reactor CRI test. The parameters of kinetic model were optimized using non-linear least squared method. Three main properties of coals, i.e., Fe₂O₃ content, volatile matter, and coal rank were selected to predict the CRI. The predicted CRI value was in a good agreement with the CRI data. The standard error was less than 5. Coke strength after reaction (CSR) was predicted using linear regression of the CSR and CRI data. The estimated CSR was in good agreement with the CSR data. The sensitivity analysis of coal properties to CRI was also performed using the developed kinetic model. The model was successfully applied for coal blending to predict CRI of the produced coke with standard error 3.7. This model can explain well the catalytic effect of coal and coal blend properties to coke reactivity during the CRI test.

摘要

已经开发了一种通过动力学方法从煤性质估计焦炭反应性指数 (CRI) 的新方法。该模型源自质量平衡，采用间歇反应器 CRI 测试的动力学模型。动力学模型参数采用非线性最小二乘法进行优化。煤的三大主要特性，即Fe ₂ O ₃选择含量、挥发物和煤阶来预测 CRI。预测的 CRI 值与 CRI 数据吻合良好。标准误差小于 5。使用 CSR 和 CRI 数据的线性回归预测反应后焦炭强度 (CSR)。估计的 CSR 与 CSR 数据非常吻合。煤性质对 CRI 的敏感性分析也使用开发的动力学模型进行。该模型成功应用于配煤，以标准误差 3.7 预测所生产焦炭的显色指数。该模型可以很好地解释CRI测试过程中煤和煤混合特性对焦炭反应性的催化作用。