Author : Ameya Deshpande and S. V. Dingare

The diesel fired furnace is being used to melt the alkaline salts. These melted salts are then treated to form granular of particular shapes. Such are then used for the process of purification of molten aluminum. The major energy consumption is from the furnace throughout the process. The furnace has the maximum heat transfer capacity being indicated by the parameters of the furnace. Hence it is necessary to study the relationship between operational conditions which can affect the furnace efficiency. The experimental study is carried out on the furnace involving critical parameters namely melting rate, furnace temperature, flue gas temperature, preheated air temperature and fuel consumption. The regression models are created to capture the combine effect of such parameters. These models are tested for root mean squared variation and the statistical parameters called R2, adjusted R2. It is found that the furnace runs optimum at the particular frequency of the input material with melting rate giving maximum efficiency. The regression models created are well approximated with the experimental data giving lesser mean average variation. This shows that the regression models are capable of capturing the combined effect of parameters and their function.

Keywords: Thermal performance, R2, Regression modeling, High Speed Diesel (HSD) oil, Flue gas.