Critical heat flux (CHF) provides an important limitation on the operation of water cooled reactors and, consequently, has received a great deal of study. However, contrary to other parameters related to the CHF, little work has been done to identify the appropriate definitions for characteristic lengths that should be associated with CHF.
An exact understanding of heated length effect is important at least in two aspects: (a) to predict CHF in short channels by prediction models developed based on longer channels, and (b) to utilize the data for shorter channels in developing local-condition correlations.
With using artificial neural networks (ANNs), an analytical study related the heated length effect has been carried out to make an improvement of the prediction accuracy based on local condition correlations or table. It has been carried out to suggest a feasible criterion of the threshold L/D value in which heated length could affect on CHF. And within the criterion, a L/D correction factor has been developed through conventional regression.
In order to validate the developed L/D correction factor, experiments for various heated lengths have been carried out under low and intermediate pressure conditions.
The developed threshold L/D correlation provides a new feasible criterion of L/D threshold value.
The developed correction factor gives a reasonable accuracy for the original database, showing the error of -2.18% for average and 27.75% for RMS, and promising results for new experimental data.