Minimizing Data Reduction Uncertainty during Heat-Transfer Equipment Testing (OR-16-C080)

The accuracy of experimental results has always concerned engineers and scientists. The uncertainty of each parameter is desired to be minimized because these uncertainties will propagate in the data reduction process. In heat-transfer equipment testing, there are usually two independent measurements of heat-transfer rate in the hot and cold stream respectively (Q_h and Q_c). It is proposed in this paper that Q_ave should be calculated based on a form of weighted-linear average, with weighting factors depending on the individual uncertainties in Q_h and Q_c. Heat-transfer rate which has higher uncertainty will be weighed less in the average, and the other one with lower uncertainty will be weighed more accordingly. Implementing this new methodology will minimize the uncertainty in heat-transfer coefficient and Colburn j factors, which will consequently provide more accurate data for use in the development of correlations or for performance comparison purposes.