Pulverized Coal-Fired Boilers Achieve Unprecedented Efficiency, Slashing Emissions and Costs
The researchers developed a neural network model to analyze carbon content in fly ash from a coal-fired boiler. They used 11 parameters like coal fineness and oxygen levels to predict carbon content with less than 6% error. The model can help understand how different factors affect carbon content in fly ash, allowing for better control and optimization of combustion efficiency in the boiler.