On the Identification and Decomposition of the Unsteady Losses in a Turbine Cascade

Abstract

The present paper describes the application of proper orthogonal decomposition (POD) to large eddy simulation (LES) of the T106A low-pressure-turbine profile with unsteady incoming wakes at two different flow conditions. Conventional data analysis applied to time averaged or phase-locked averaged flow fields is not always able to identify and quantify the different sources of losses in the unsteady flow field as they are able to isolate only the deterministic contribution. A newly developed procedure allows such identification of the unsteady loss contribution due to the migration of the incoming wakes, as well as to construct reduced order models that are able to highlight unsteady losses due to larger and/or smaller flow structures carried by the wakes in the different parts of the blade boundary layers. This enables a designer to identify the dominant modes (i.e., phenomena) responsible for loss, the associated generation mechanism, their dynamics, and spatial location. The procedure applied to the two cases shows that losses in the fore part of the blade suction side are basically unaffected by the flow unsteadiness, irrespective of the reduced frequency and the flow coefficient. On the other hand, in the rear part of the suction side, the unsteadiness contributes to losses prevalently due to the finer scale (higher order POD modes) embedded into the bulk of the incoming wake. The main difference between the two cases has been identified by the losses produced in the core flow region, where both the largest scale structures and the finer ones produces turbulence during migration. The decomposition into POD modes allows the quantification of this latter extra losses generated in the core flow region, providing further inputs to the designers for future optimization strategies.

Free-Stream Turbulence Induced Boundary-Layer Transition in Low-Pressure Turbines

“…The vortical disturbances are present in the freestream, with significantly higher levels of vorticity. The freestream vortical disturbances penetrate the boundary-layer and manifest themselves as streaky structures (as seen in the previous plane), that appears as counter-rotating vortices in this crossstream plane as also observed in [30]. These counter-rotating vortices facilitate the exchange of momentum by transporting the low-momentum fluid away from the wall and pushing the highmomentum fluid towards the wall.…”

Challenges and opportunities for artificial intelligence and high-fidelity simulations in turbomachinery applications: A perspective

“…Still LES does offer the opportunity to retire design risk with a small number of component or sub-system simulations, as done by (Meloni et al, 2019) who ran LES to verify the insurgence of combustion dynamics in a heavy-duty combustor, and by (Andreini et al, 2017) who investigated hot streaks in combustor-turbine interaction. High-fidelity simulations have also been used to identify performance top offenders and the relative design parameters to concentrate on, as discussed by (Legani et al, 2019) who analysed an LPT stator-rotor interaction LES with the aid of POD. With LES, or DNS when possible, performed at realistic operating conditions and with enough geometry details the simulations are accurate enough to represent a sort of "virtual test" the accuracy and resolution of which is superior to experimental test.…”

Flow Coefficient and Reduced Frequency Effects on Wake-Boundary Layer Interaction in Highly Accelerated LPT Cascade

“…In particular, turbulence production occurs where the principal direction of the Reynolds stresses and the mean flow strain tensor are aligned [3]. Since the integral of these two terms on a control volume gives the total pressure losses from the inlet to the outlet of the measuring domain [6], a loss coefficient ω can be defined…”

“…In particular, turbulence production occurs where the principal direction of the Reynolds stresses and the mean flow strain tensor are aligned [3]. Since the integral of these two terms on a control volume gives the total pressure losses from the inlet to the outlet of the measuring domain [6], a loss coefficient ω can be defined in order to quantify the overall fluid dynamic losses produced in the volume Ω as in Equation ( 4), where p ref is the reference dynamic pressure at the outlet of the cascade. In the present work, the overall region framed by the cameras has been considered as the control volume.…”

“…The process is even more complicated by smaller scale structures carried within the bulk of the wake, as documented by the measurements carried out by Stieger and Hodson [5], that revealed high turbulent activity just in the region of impinging wakes. In this scenario, a step forward in the understanding of wake related effects is provided in [6], where the capability of proper orthogonal decomposition (POD) in identifying different flow structures is discussed, allowing the identification of different mechanisms responsible for loss generation.…”