Prediction model of ash fusion temperature and viscosity in coal gasification

ZHENG Chang-hao; WANG Qian; ZHANG Jian-sheng

Volume 44 Issue 5

May 2016

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Article Navigation > Journal of Fuel Chemistry and Technology > 2016 > 44(5): 521-527

ZHENG Chang-hao, WANG Qian, ZHANG Jian-sheng. Prediction model of ash fusion temperature and viscosity in coal gasification[J]. Journal of Fuel Chemistry and Technology, 2016, 44(5): 521-527.

Citation:

ZHENG Chang-hao, WANG Qian, ZHANG Jian-sheng. Prediction model of ash fusion temperature and viscosity in coal gasification[J]. Journal of Fuel Chemistry and Technology, 2016, 44(5): 521-527.

ZHENG Chang-hao, WANG Qian, ZHANG Jian-sheng. Prediction model of ash fusion temperature and viscosity in coal gasification[J]. Journal of Fuel Chemistry and Technology, 2016, 44(5): 521-527.

Citation:

ZHENG Chang-hao, WANG Qian, ZHANG Jian-sheng. Prediction model of ash fusion temperature and viscosity in coal gasification[J]. Journal of Fuel Chemistry and Technology, 2016, 44(5): 521-527.

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Prediction model of ash fusion temperature and viscosity in coal gasification

Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Department of Thermal Engineering, Tsinghua University, Beijing 100084, China

Funds:

the National Natural Science Foundation of China 51176097

Received Date: 2015-12-31
Rev Recd Date: 2016-02-22

Available Online: 2021-01-23

Publish Date: 2016-05-10

Abstract

Abstract

Based on classification of silica and alumina content and silica alumina ratio in coal ash, optimized prediction models of coal ash melting point and viscosity related to ash components were built. Their relationship in a wide range of ash components was also discussed. An ash fusion temperature prediction model based on liquidus temperature from FactSage Thermodynamic software demonstrates accuracy improvement with error of less than ±40 ℃ and deviation of 25 ℃. The combination of Urbain and Roscoe model results in viscosity prediction error between prediction and experiment results within ±0.1 for relative low viscosity and ±0.2 for relative high viscosity. The results show that components classification model obtains better results than wide-covered model. Thus a better understanding of ash fusion mechanism is provided and gives reasonable guidance for blending and additives added to coal.
- coal gasification,
- ash fusion temperature,
- viscosity,
- prediction model

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References(24)

References

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