Liquid lead bismuth alloy has become the preferred coolant for fourth generation lead based reactors due to its excellent neutron slowing down and heat transfer properties. In response to the insufficient research on the internal flow characteristics and structural parameter influence of Y-shaped filters under lead bismuth high-temperature metal media, this paper uses the SST k-ω turbulence model and porous media filter model to conduct three-dimensional numerical simulations of small-diameter Y-shaped filters. The system studied the influence of six characteristic dimensions, including the inlet size, outlet size, angle between the chamber and the pipeline axis, chamber length, central cylinder diameter, and filter cartridge porosity, on the pressure loss coefficient of the filter and the proportion of high flow velocity zone in the filter cartridge. The results indicate that the weights of the influence of each feature on the pressure loss coefficient are, in order, the inlet size of the filtering chamber, the outlet size, the porosity of the filter cartridge, the axis angle, the central cylinder diameter size, and the chamber length; The weight of the influence on the proportion of high flow rate zone in the filter cartridge is in the order of inlet size, axis angle, center cylinder diameter, outlet size, cavity length, and porosity. Structural optimization is carried out with the synergistic goal of low pressure loss coefficient and high filter cartridge utilization rate. The angle between the cavity axis is set to 55 °, the ratio of the central cylinder diameter to the pipe diameter is set to 1.125, and the porosity of the filter cartridge is set to 46.21%. After optimization, the overall pressure loss of the filter decreased by an average of about 57.63%, and the proportion of high flow velocity zone in the filter cartridge increased to 34.24%, significantly improving the uniformity of the flow field.
 

Liquid lead bismuth; Y-shaped filter; numerical simulation Pressure loss; Filter cartridge utilization rate; structural optimization