Determination of Turbulent Mixing Rate for Single-Phase Flow in Simulated Subchannels of a Natural-Circulation Pressure Tube–Type BWR

The Advanced Heavy Water Reactor (AHWR) is a vertical pressure tube–type, heavy water–moderated, boiling light water–cooled, natural-circulation–based reactor. The fuel bundle of AHWR contains 54 fuel rods arranged in three concentric rings of 12, 18, and 24 fuel rods. This fuel bundle is divided into a number of imaginary interacting flow passages called subchannels. A single-phase-flow condition exists in the reactor rod bundle during the start-up condition and up to a certain length of rod bundle when it is operating at full power. Predicting the thermal margin of the reactor during the start-up condition has necessitated the determination of the turbulent mixing rate of the coolant among these subchannels. Thus, it is vital to evaluate the turbulent mixing between the subchannels of the AHWR rod bundle.

In this paper, experiments were carried out to determine the turbulent mixing rate in the simulated subchannels of the reactor. The size of the rod and the pitch in the test were the same as those of the actual rod bundle in the prototype. Three subchannels are considered in 1/12th of the cross section of the rod bundle. Water was used as the working fluid, and the turbulent mixing tests were carried out at the atmospheric condition without heat addition. The mean velocity in the subchannel was varied from 0 to 1.2 m/s. The flow conditions were closer to the actual reactor condition. The turbulent mixing rate was experimentally determined by adding tracer fluid in one subchannel and measuring the concentration of that in other subchannels at the end of the flow path. The test data were compared with existing models in literature. It was found that none of the models could predict the measured turbulent mixing rate in the rod bundle of the reactor. This is because the turbulent mixing rate is highly dependent on geometry. An empirical model is derived based on these experimental data, and it is found that this correlation can predict the turbulent mixing rate quite accurately.