首页|期刊导航|煤质技术|配合煤奥阿膨胀度b值的预测方法

配合煤奥阿膨胀度b值的预测方法OA

Prediction method for Audibert-Arnu dilatation(b)of blended coal

中文摘要英文摘要

奥阿膨胀度能很好地反映煤的膨胀性能,是反映炼焦煤黏结性和结焦性的重要指标之一.但由于无法预测配煤的奥阿膨胀度指标,严重限制了该指标的有效使用.笔者以9 种炼焦煤为基础,开展了二元、三元、四元、九元总计近 300 个方案的单种煤与配煤黏结性能指标的检测,研究了各指标之间的关系.发现二元配煤奥阿膨胀度b实测值不但与其加和值、初始软化温度T1相关性强,而且与黏结指数加和值的相关性很高,从而将黏结指数加和值与奥阿膨胀度b的加和值引入奥阿膨胀度b的预测模型中,取得很好的效果.随后,在此基础上,进一步建立了三元配煤情况下的b值预测模型,并逐步成功地应用于四元乃至九元配煤情况下的奥阿膨胀度指标的预测,取得很好的效果.

The Audibert-Arnu dilatation effectively reflects the swelling properties of coal and serves as one of the critical indicators for assessing the caking and coking properties of coking coal.However,the practical application of this parameter has been significantly constrained due to the inability to predict the Audibert-Arnu dilatation(b)in blended coals.Based on 9 types of coking coal,the author conducted testing on the bonding performance indicators of single coal and blended coal for nearly 300 schemes including two,three,four,nine types,and studied the rela-tionship between each indicator.Through analytical studies on seven individual coal types and their binary blends,it was discovered that the measured Audibert-Arnu dilatation(b)of binary blended coal exhibits strong correlations not only with its additive values and initial softening temperature T1,but also with the summed caking index values.Con-sequently,the summed values of the caking index and Audibert-Arnu dilatation(b)were successfully employed to predict the Audibert-Arnu dilatation(b).Building on this binary coal blending research,further investigations into ternary blends led to the development of a predictive model for Audibert-Arnu dilatation in ternary blended coals.This model was subsequently validated using experimental data from quaternary and nine-component blended coals.

刘洋;李东涛;曲世光;代鑫;赵鹏;郭德英

首钢集团有限公司技术研究院,北京 100043首钢集团有限公司技术研究院,北京 100043通化钢铁股份有限公司,吉林 通化 134000首钢集团有限公司技术研究院,北京 100043首钢集团有限公司技术研究院,北京 100043首钢集团有限公司技术研究院,北京 100043

化学化工

配合煤奥阿膨胀度黏结指数加和值预测方法

blended coalAudibert-Arnu dilatationcaking indexsum up valueprediction method

《煤质技术》 2026 (1)

72-80,9

首钢集团有限公司科研资金资助项目(K202300140Y)

10.3969/j.issn.1007-7677.2026.01.10

评论