scope:

It is a widely adopted practice-even adopted in ASHRAE/ANSI/ARI engineering standards-to use the arithmetic mean of two heat transfer measurements for the evaluation of heat-exchanger performance. However, this approach does not generally lead to a minimized experimental uncertainty because uncertainties of redundant measurements can vary considerably depending on the experimental techniques and the test conditions. Moreover, based on this approach it is preferred to discard information when its uncertainty exceeds some limit. 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 larger uncertainty will be weighed less in the average, and the other one with smaller 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. Through analysis of experimental data with different uncertainties, the benefit of weighted average method was demonstrated. The results showed that the weighted averaging method recuded the average relative uncertainty in j factors from 11% to 10.3% for dry condition data, and from 21.8% to 13.1% for wet condition data. The benefit was more pronounced as the air-side Reynolds number increased. Because the air-side uncertainty is usually much higher under wet operating conditions, the weighted average method is highly recommended for data reduction with dehumidifying conditions.