Predicting the Profile Loss of High-Lift Low Pressure Turbines

The overall efficiency of low pressure turbines is largely determined by the two-dimensional profile loss, which is dominated by the contribution of the suction surface boundary layer. This boundary layer typically features a laminar separation bubble and is subjected to an inherently unsteady disturbance environment. The complexity of the flow behavior makes it difficult to numerically predict the profile loss. To address this problem, an empirical method is proposed for predicting the boundary layer integral parameters at the suction surface trailing edge, allowing the profile loss to be estimated. Extensive measurements have been conducted on a flat plate simulation of the suction surface boundary layer. The disturbance environment of real machines was modeled using a moving bar wake generator and a turbulence grid. From this data set, empirically based methods have been formulated using physical principles for the prediction of the momentum thickness and shape factor at the suction surface trailing edge. The predictions of these methods may be used to estimate the profile loss of a given cascade, which achieves reasonable agreement with the available data. By parameterizing the shape of the suction surface velocity distribution, the method is recast as a preliminary design tool. Powerfully, this may be used to guide the selection of the key design parameters (such as the blade loading and velocity distribution shape) and enables a reasonable estimation of the unsteady profile loss to be made at a very early stage of design. To illustrate the capabilities of the preliminary design tool, different styles of velocity distribution are evaluated for fixed blade loading and flow angles. The predictions suggest that relatively “flat-top” designs will have the lowest profile loss but good performance can also be achieved with front-loaded “peaky” distributions. The latter designs are more likely to have acceptable incidence tolerance.