Sensitivity of high pressure nozzle guide vane capacity to trailing edge cooling

High pressure (HP) nozzle guide vane (NGV) capacity is one of the most important parameters for setting overall turbine power output, for stage matching, and for understanding turbine performance. In accelerated engine development programmes in particular, accurate and early assessment of NGV capacity is a significant advantage. Whilst the capabilities of computational methods have improved rapidly in recent years, the accuracy of absolute capacity prediction capability is lower than experimental techniques by some margin. Thus, experimental measurement of NGV capacity is still regarded as an essential part of many engine programmes.
The semi-transient capacity measurement technique has been developed and refined at the University of Oxford over the last ten years. It allows rapid and accurate measurement of engine component (typically fully-cooled NGVs) capacity at engine-representative conditions of Mach number, Reynolds number, and coolant-to-mainstream pressure ratio. The technique has been demonstrated to offer considerable advantages over traditional (industrial steady-state) techniques in terms of accuracy, time and operating cost.
The present work describes in detail improvements made to the semi-transient method to optimise its uncertainty, and presents a detailed uncertainty analysis of the updated facility which is shown to achieve a bias uncertainty of ±0.495% (to 95% confidence) and a precision uncertainty of ±0.025%. The extremely low precision uncertainty in particular allows very small changes in capacity to be resolved. This, combined with rapid interchangeability of test modules, allows studies of the sensitivity of capacity to secondary influences with much greater flexibility than was previously possible.
In the present work, this capability is used to examine the effect of changing trailing edge (TE) geometry—particularly suction side (SS) TE overhang length—on the flow capacity. Experimental measurements and complementary numerical predictions of capacity are presented for four geometries bridging the gap between a classical centred ejection design and a SS-overhang design. A monotonic increase in capacity is observed as TE overhang length reduces, but with a greatly reduced gradient when overhang length becomes very short. Strong agreement was achieved between experiment and CFD in terms of both absolute capacity prediction (average error of 0.67%) and capacity changes between TE geometries (average error of 0.20%).
Comprehensive examination is given to the fundamental mechanisms responsible for the observed capacity changes. Two models of the vane are proposed which describe the interactions between multiple controlling areas which can be defined from the physical geometry. Whilst these models are incomplete, they represent an important aspect of the changing flow interactions between different TE geometries and help to explain the change in flow behaviour when overhang length becomes very short. Further insight is gained by studying the area and static pressure changes at several controlling areas, although this approach is demonstrated to be somewhat arbitrary. Whilst the capacity trend can be explained by considering particular controlling areas in this way, a more complete system description is provided by holistically analysing the aerodynamic change in the entire controlling region of the vane passage.
The SS-overhang TE design has generally been favoured by HP NGV designers in recent years because it has been presumed to be aerodynamically advantageous on account of providing a thinner ultimate TE than the equivalent centred ejection geometry (at the cost of increased cooling requirement for the overhanging length). The prior literature is not in consensus on this point, however, and so the present work re-examines the impact of TE overhang length on NGV aerodynamic loss characteristics.
High-fidelity experimental traverse measurements downstream of the HP NGV cascade are presented, and compared against steady and unsteady RANS CFD predictions. This is a highly useful data set for benchmarking typical CFD methods for absolute loss prediction of cooled engine components. URANS CFD under-predicts the rate of mixing out of the non-uniform flow-field, and significantly over-predicts the profile loss coefficient in a particular axial plane by an average of 17.9%. The agreement for mixed-out loss coefficient is much better, differing by just 4.0%. Detailed examination is given to local distributions of loss coefficient. A significant feature of the experimentally-measured flow-field is a radial non-uniformity caused by internal cooling features within the TE slot. This sort of effect would be very difficult to detect without testing engine components. Significant differences in local loss coefficient distributions between different radial sections are also observed due to the 3D shaping (lean, sweep, turning) of the engine component geometry. Analysis of the development of these distributions provides the basis for a model of wake profile decay based on streamwise path length.
Detailed analysis of aerodynamic loss measurements are then brought together with comparison of the parametric set of TE designs with four different TE overhang lengths. Unsteady pressure fluctuations in the wake predicted by URANS CFD show a large rise in magnitude, and fall in shedding frequency, when overhang length becomes short. This is attributed to a change in shedding mode from one in which small vortices are shed at relatively high frequency from the overhanging SS TE, to one in which larger vortices are shed at lower frequency from the entire base region. Experiment and CFD are largely in agreement regarding the trend in mixed-out average loss coefficient, corrected for changes in TE thickness, between TE geometries: loss coefficient gradually rises before plateauing at short overhang length. However, the experimental data show an additional large increase in loss coefficient at intermediate overhang length which is not predicted by URANS. This discrepancy is attributed to the shedding of pressure waves associated with vortex shedding in the transonic range, which is not captured in the CFD simulations (a known limitation of the URANS method). Analysis of the base region pressure distributions predicted by URANS shows that the PS base region pressure falls substantially with reducing overhang length, whilst the SS base pressure is almost insensitive to overhang length. The differing behaviours of the PS and SS base regions are explained by interactions with changes in the entire vane aerodynamic at their different locations. There does not seem to be a simple relationship between changes in base region pressure and loss coefficient, suggesting that the overall loss trend cannot be understood without studying the aerodynamic change in the entire passage more holistically.
The experimental and numerical study of NGV aerodynamic loss characteristics presented in this work additionally provided the opportunity to consider a more fundamental aspect of performance evaluation in complex 3D flows. Performance parameters such as total pressure or kinetic energy loss coefficients can be represented in various different ways ranging from line and plane averages to fully mixed-out values. There are further considerations to be made for each of these representations such as weighting methods, mixing methods and so forth. The present work analyses the sensitivities of a range of different representations of performance parameter to axial measurement location, radial averaging range, and exit Mach number, in order to provide guidance on the accuracy of each method in a relevant, practical application. In particular, the area-weighted-average, despite its simplicity (which makes it a common choice in the literature), is demonstrated to be strongly sensitive to axial plane which makes it an extremely poor choice for comparing between CFD and experiment or between different experiments.

Keywords: Gas turbines
experimental methods
CFD
flow capacity
aerodynamics
turbomachinery
Advisor: Povey, T