Abstract :
[en] An important question for turbomachine designers is how to deal with blade and flowpath geometric variabilities stemming from the manufacturing process or erosion during the component lifetime. The challenge consists in identifying where stringent manufacturing tolerances are absolutely necessary and where looser tolerances can be used, as some geometric variations have little or no effects on performance, while others do have a significant impact. Because numerical simulations based on Reynolds Averaged Navier-Stokes (RANS) equations are computationally expensive for a stochastic analysis, an alternative approach is proposed, in which these simulations are complemented by cheaper through-flow (TF) simulations to provide a finer exploration of the range of variations, in particular in a context of robust design. The overall goal of the present study is to evaluate the adequacy of a viscous time-marching TF solver to predict geometric variability effects on compressor performance and, in particular, to capture the main trends. Although the computational efficiency of such a low-fidelity solver is useful for parametric studies, it is known that the involved assumptions and approximations associated with the TF approach introduce errors in the performance prediction. Thus, the model is first evaluated with respect to its underlying assumptions and correlations. To do so, TF simulations are compared to RANS simulations applied to the CME2 compressor stage and a modern low-pressure compressor designed by Safran Aero Boosters. On the one hand, the TF simulations are fed with the exact radial distribution of the correlation parameters using RANS input data in order to isolate the modeling error from correlation empiricism. Moreover, in the context of multi-fidelity optimisation, such distributions can be predicted using the more detailed RANS simulations which are performed on selected operating points. On the other hand, correlations from the literature are assessed and improved. It is shown that the solver provides realistic predictions of performance but is highly sensitive to the underlying correlations. Then, two modeling aspects linked to the blade leading edge, namely the incidence correction and the camber line computation, are discussed. As geometric variability precisely at the blade leading edge has a significant impact on the performance, we assess how these two aspects influence the variability propagation in this region. Moreover, we propose a strategy to mitigate these model uncertainties. Finally, within the scope of this preliminary study, the following perturbations are introduced in the low-pressure compressor: blade angle perturbations, blade thickness perturbations, rotor tip-gap perturbations, three-dimensional position perturbations of undeformed blades, and hub and shroud contour deformations. Their range is defined based on the tolerance limits typically imposed in the industry and on observed manufacturing variability. It is found that the TF model broadly provides realistic predictions of performance variations resulting from the imposed geometric variations. These results are a promising first step towards the use of the through-flow modeling approach for geometric uncertainty quantification.
