  Rapid compression machines (RCMs) have been widely used in the combustion
literature to study the low-to-intermediate temperature ignition of many fuels.
In a typical RCM, the pressure during and after the compression stroke is
measured. However, measurement of the temperature history in the RCM reaction
chamber is challenging. Thus, the temperature is generally calculated by the
isentropic relations between pressure and temperature, assuming that the
adiabatic core hypothesis holds. To estimate the uncertainty in the calculated
temperature, an uncertainty propagation analysis must be carried out. Our
previous analyses assumed that the uncertainties of the parameters in the
equation to calculate the temperature were normally distributed and
independent, but these assumptions do not hold for typical RCM operating
procedures. In this work, a Monte Carlo method is developed to estimate the
uncertainty in the calculated temperature, while taking into account the
correlation between parameters and the possibility of non-normal probability
distributions. In addition, the Monte Carlo method is compared to an analysis
that assumes normally distributed, independent parameters. Both analysis
methods show that the magnitude of the initial pressure and the uncertainty of
the initial temperature have strong influences on the magnitude of the
uncertainty. Finally, the uncertainty estimation methods studied here provide a
reference value for the uncertainty of the reference temperature in an RCM and
can be generalized to other similar facilities.
