Abstract
In this work, both CFD and ingestion models are used to assess ingestion in the low pressure turbine section of a jet engine at a high power condition, the CFD comprising URANS and zonal-hybrid URANS-LES methodologies. The prediction is compared with experimental data, obtained via engine testing. The level of seal clearance and coolant mass-flow inside the secondary air system cavities of the turbine has a range of uncertainty during testing. In the first part of this work a small-sector URANS computation with the boundary conditions reflecting the best understanding of the engine during testing is carried out and a miss-match with experiments found. As a result, a sensitivity analysis with the seal clearance and coolant mass-flow is undertaken, in which it is found that the inges tion prediction is largely affected by these two parameters. To assess the effect of the computation of turbulence, a zonal-hybrid URANS-LES computation is carried out at the condition with the best understanding of the test and it is found that the ingestion prediction improves compared to a URANS computation. The similar flow structures obtained between the two approaches suggests that the improvement is due to more accurate turbulent mixing being predicted by the zonal-hybrid URANS-LES computation. Finally, some ingestion models are tuned to the CFD data originating from the sensitivity analysis. An optimization study with the resulting sealing efficiency characteristic is then carried out and a condition that minimizes the error to the experimental data found. A new small-sector URANS computation at this condition is unable to match the experimental data, with a greater miss-match found in the more radially inwards region of the cavity. Due to the better agreement of the CFD solution to the ingestion models in the part of the cavity closer to the main annulus than in the more radially inwards part of the cavity, it is suggested that predicting the flow structure in this region is key to the ingestion prediction. Considering the improvement seen with the zonal-hybrid methodology it is argued that a similar optimization study using this methodology would have improved the alignment to the experimental condition.