Correlation between the Flow Temperature and Mineral Factor for Coal Ashes Based on FactSage Calculation

Area of Science:

• Materials Science
• Chemical Engineering
• Combustion Science

Background:

• Accurate prediction of coal ash flow temperature (FT) is crucial for optimizing combustion processes and preventing operational issues like slagging.
• Current methods for determining FT can be complex and time-consuming, necessitating simpler predictive models.
• Understanding the relationship between ash composition and its thermal properties is key to effective ash management.

Purpose of the Study:

• To establish a straightforward method for predicting coal ash flow temperature (FT) using FactSage calculations.
• To explore and quantify the correlation between FT and the mineral factor (MF) of coal ash.
• To validate the reliability of the developed predictive model with experimental data.

Main Methods:

• Selection of 69 diverse coal ash samples for analysis.
• Utilizing FactSage software for mineral factor (MF) calculations.
• Establishing a linear regression model to correlate MF with experimental FT.
• Experimental validation of the predictive model using ten additional ash samples.

Main Results:

• An approximate linear relationship was identified: FT = 0.64MF + 1332.
• The model demonstrated a high correlation coefficient (R=0.94) and a standard deviation of 25.77 °C.
• Calculated FTs closely matched experimental values within the measurement error range.
• The predictive model showed higher reliability for coal ashes with low iron and calcium content.

Conclusions:

• A simple and reliable linear model has been developed to predict coal ash flow temperature from its mineral factor.
• The FactSage-based prediction method offers a practical alternative to experimental determination of FT.
• The findings suggest that the predictive accuracy is influenced by specific elemental compositions, particularly iron and calcium content.