Uncertainty analysis for the experimental estimation of heat transfer correlations combining the Wilson plot method and the Monte Carlo technique

The analysis is focused on a specific problem where the heat transfer correlation to be obtained has three unknowns; however, the analysis is quite general and could be extended to more complex problems. Results show that weighted nonlinear regression models give more consistent results that unweighted methods; whereas unweighted simple linear regression analyses are not recommended. Finally, the suitability of implementing a Monte Carlo simulation is shown in terms of properly propagating the measured data uncertainty distribution through the heat transfer model.