Accuracy Assessment of the Sellers Model in Predicting the Multi-Row Film Cooling Performance

Abstract Multi-row film cooling is widely applied in modern gas turbine cooling designs. However, there are few effective methods to predict local cooling effectiveness and the Sellers model based on the existing 1-D correlation is popular in the community but its prediction accuracy is questionable in some cases. The primary work of the current study is to analyze the prediction error of the Sellers model and to reveal the underlying flow mechanism. Considering the lateral uniformity assumption of the 1-D Sellers model, the effect of pitchwise row-to-row misalignment can hardly be included and the 2-D Sellers model is, therefore, proposed. Numerical simulations under density ratio near 1.0 are conducted on the double-row film cooling. Configurations of inline and staggered arrangements and blowing ratios from 0.5 to 2.0 are included. Cooling effectiveness can be theoretically decomposed into two parts contributed by separate rows, and this method has been validated. The footprint of coolant can, therefore, be tracked. Based on vortical interaction analysis, conclusions are obtained that pitchwise row-to-row spacing determines the overestimation or underestimation of the model-predicted result and the blowing ratio affects the absolute value of the prediction error. By comparing prediction accuracy of the two rows, the conclusion can be drawn that the prediction error is, to a greater extent, contributed by the row #2 because it is more likely to be affected by the row-to-row interaction.