A New Two-Dimensional CFD Model to Predict the Performance of Natural Draught Wet-Cooling Towers Packed With Trickle or Splash Fills

In the design of a modern natural draught wet-cooling tower, structural and performance characteristics must be considered. Air flow distortions and resistances must be minimised to achieve optimal cooling which requires that the cooling towers must be modelled two-dimensionally and ultimately three-dimensionally to be optimized. It is found that CFD models in literature are limited to counterflow cooling towers packed with film fills which are porous in one direction only and generally have a high pressure drop, as well as purely crossflow cooling towers packed with splash fill, which simplifies the analysis considerably. Many counterflow cooling towers are however packed with trickle and splash fills which have anisotropic flow resistances, which means the fills are porous in all flow directions and thus air flow can be oblique through the fill, particularly near the cooling tower air inlet. This provides a challenge since available fill test facilities and subsequently fill performance characteristics are limited to purely counter- and crossflow configuration. This paper presents a CFD model to predict the performance of natural draught wet-cooling tower with any type of fill configuration, which can be used to investigate the effects of different atmospheric temperature distributions, air inlet and outlet geometries, air inlet heights, variations in radial water loading and fill depth, fill configurations, rain zone drop size distributions, and spray zone performance characteristics on cooling tower performance for optimization purposes. Furthermore the effects of damage or removal of fill in annular sections and boiler flue gas discharge in the centre of the tower can be investigated. The fill performance characteristics for oblique air flow are determined by linear interpolation between counter- and crossflow fill characteristics in terms of the air flow angle. The CFD results are validated by means of corresponding one-dimensional computational model data.