Prediction of flammability limits for ethanol-air blends by the Kriging regression model and response surfaces
CHALLENGE - Flammability limits must be identified in order to assess and control handling risks of particular processes according to combustion product composition and environmental conditions. The present paper aims to present a model that can predict flammability limits for ethanol-air blends with at different moisture concentrations by Kriging interpolation techniques.
SOLUTION - Experimental data were processed through the Kriging data interpolation statistical technique by using a Gaussian variogram. The modeFRONTIER software was used for data processing, which allows generating a Java code algorithm that allowed predicting flammability indexes for ethanol-air blends under specific conditions. Once the prediction algorithm was obtained, its validation procedure was performed. For such a purpose, 342 experimental data records were used through which a good performance of the generated algorithm was evidenced.
BENEFITS - The designed algorithm predicted the flammability condition of ethanol-air blends at temperatures ranging between 20 °C and 210 °C, pressure between 40 kPa and 101.3 kPa, ethanol moisture concentration at 0.5% and 8%, and ethanol volume percentages between 1% and 35%.