Energy & Fuels, Vol.26, No.3, 1557-1564, 2012
Temperature Dependence of the Laminar Burning Velocity of Methanol Flames
To better understand and predict the combustion behavior of methanol in engines, sound knowledge of the effect of the pressure, unburned mixture temperature, and composition on the laminar burning velocity is required. Because many of the existing experimental data for this property are compromised by the effects of flame stretch and instabilities, this study was aimed at obtaining new, accurate data for the laminar burning velocity of methanol air mixtures. Non-stretched flames were stabilized on a perforated plate burner at 1 atm. The heat flux method was used to determine burning velocities under conditions when the net heat loss from the flame to the burner is zero, Equivalence ratios and initial temperatures of the unburned mixture ranged from 0.7 to 1.5 and from 298 to 358 K, respectively. Uncertainties of the measurements were analyzed and assessed experimentally. The overall accuracy of the burning velocities was estimated to be better than +/-1 cm/s. In lean conditions, the correspondence with recent literature data was very good, whereas for rich mixtures, the deviation was larger. The present study supports the higher burning velocities at rich conditions, as predicted by several chemical kinetic mechanisms. The effects of the unburned mixture temperature on the laminar burning velocity of methanol were analyzed using the correlation u(L) = u(L0)(T-u/T-u0)(alpha). Several published expressions for the variation of the power exponent alpha with the equivalence ratio were compared against the present experimental results and calculations using a detailed oxidation kinetic model. Whereas most existing expressions assume a linear decrease of alpha with an increasing equivalence ratio, the modeling results produce a minimum in alpha for slightly rich mixtures. Experimental determination of alpha was only possible for lean to stoichiometric mixtures and a single data point at phi = 1.5. For these conditions, the measurement data agree with the modeling results.