Identification and quantification of losses in a LPT cascade by POD applied to LES data

Lengani, Davide; Simoni, Daniele; Pichler, Richard; Sandberg, Richard D.; Michelassi, Vittorio; Bertini, Francesco

doi:10.1016/j.ijheatfluidflow.2018.01.011

Cited by 42 publications

(38 citation statements)

References 51 publications

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“…The post-processing methodology adopted in the present paper is based on the capability of POD of representing the flow field on a modal basis, see also Lengani et al [32] for more details. In order to understand the contribution of each unsteady dynamical feature to the loss production rate, the Reynolds averaged Navier-Stokes equations are considered.…”

Section: Fundamental Equationsmentioning

confidence: 99%

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

Lengani

Simoni

Pichler

et al. 2019

Journal of Turbomachinery

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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.

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Section: Fundamental Equationsmentioning

confidence: 99%

“…where κ is the thermal conductivity, while, K is the kinetic energy of the mean flow. Equations 3 and 4 are then written in non-dimensional form, neglecting the diffusive terms [32]:…”

Section: Fundamental Equationsmentioning

confidence: 99%

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

Lengani

Simoni

Pichler

et al. 2019

Journal of Turbomachinery

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“…In the direct POD method, the spatial correlation matrix is difficult to solve this problem directly when the number of spatial points is large. Sirovich proposed the new mathematical processing method of the snapshot POD method, which is generally applicable to cases where the number of space points is much larger than the number of samples [12][13][14][15]. Owing to its reduced order and feature extraction characteristics, POD methods are increasingly being used to study complex flow phenomena.…”

Section: Introductionmentioning

confidence: 99%

Proper Orthogonal Decomposition Analysis and Dispersion Characteristics of Resonant Acoustic Flow

Wang

Zhu

Song³

et al. 2020

Shock and Vibration

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The investigation on the flow field and mixing characteristics of resonant sound mixing is of great significance for the dispersion mixing of superfine materials. In order to simulate the flow field and dispersion characteristics of resonant acoustic mixing, a gas-liquid-solid three-phase flow model based on the coupled level-set and volume-of-fluid (CLSVOF) and discrete particle model (DPM) was established. The CLSVOF model solves the gas-liquid interface, and the DPM model tracks the particle position. Then, the particle image velocimetry (PIV) experiment was performed using a self-made resonance acoustic hybrid prototype under different oscillation accelerations, and the radial velocity distribution between the experiment and simulation was compared. Finally, the proper orthogonal decomposition (POD) is used to decompose the flow field under different oscillation accelerations and fill levels, and the energy distribution law and the energy structure of different scales are extracted. The results show that the energy of the instantaneous flow field of the resonant sound is mainly concentrated in the low-order mode, and a close relationship was revealed between the energy distribution law and dispersion behavior of particles. The larger the small-scale coherent structures distribute, the more energy it has and the more favorable it is for fast and uniform dispersion.

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“…Such periodic transition, possibly re-laminarization, is beneficial in preventing the boundary layer separation and this allows for higher loading. In this context, ultra-high lift blade can be proficiently applied either to reduce the aero-engine weight or to power the fan (among others [25][26][27][28]).…”

Section: Introductionmentioning

confidence: 99%

Stator-Rotor Interaction in Axial Turbine: Flow Physics and Design Perspective

Gaetani¹

2018

Aircraft Technology

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The stator-rotor interaction is an important issue in turbomachinery design when the highest performances are targeted. Different characters mark the interaction process in high-pressure or low-pressure turbines depending both on the blade height and on the Reynolds number. For small blade heights, being the stator secondary flows more important, a more complex interaction is found with respect to the high blades, where the stator blade wake dominates. In low-pressure turbines, the stator wake promotes the transition to turbulent boundary layer, allowing for an efficient application of ultra-high lift blades. First, a detailed discussion of the flow physics is proposed for high-and low-pressure turbines. Some off-design conditions are also commented. Then, a design perspective is given by discussing the effect of the axial gap between the stator and the rotor and by commenting the effects of three-dimensional design on the interaction.

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Identification and quantification of losses in a LPT cascade by POD applied to LES data

Cited by 42 publications

References 51 publications

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

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

Proper Orthogonal Decomposition Analysis and Dispersion Characteristics of Resonant Acoustic Flow

Stator-Rotor Interaction in Axial Turbine: Flow Physics and Design Perspective

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