Abstract

We report on a series of highly resolved large-eddy simulations of the LS89 high-pressure turbine (HPT) vane, varying the exit Mach number between Ma = 0.7 and 1.1. In order to accurately resolve the blade boundary layers and enforce pitchwise periodicity, we for the first time use an overset mesh method, which consists of an O-type grid around the blade overlapping with a background H-type grid. The simulations were conducted either with a synthetic inlet turbulence condition or including upstream bars. A quantitative comparison shows that the computationally more efficient synthetic method is able to reproduce the turbulence characteristics of the upstream bars. We further perform a detailed analysis of the flow fields, showing that the varying exit Mach number significantly changes the turbine efficiency by affecting the suction-side transition, blade boundary layer profiles, and wake mixing. In particular, the Ma = 1.1 case includes a strong shock that interacts with the trailing edge, causing an increased complexity of the flow field. We use our recently developed entropy loss analysis (Zhao and Sandberg, 2019, “Using a New Entropy Loss Analysis to Assess the Accuracy of RANS Predictions of an HPT Vane,” ASME Turbo Expo 2019: Turbomachinery Technical Conference and Exposition, Paper No. GT2019-90126) to decompose the overall loss into different source terms and identify the regions that dominate the loss generation. Comparing the different Ma cases, we conclude that the main mechanism for the extra loss generation in the Ma = 1.1 case is the shock-related strong pressure gradient interacting with the turbulent boundary layer and the wake, resulting in significant turbulence production and extensive viscous dissipation.

References

1.
Arts
,
T.
,
Lambertderouvroit
,
M.
, and
Rutherford
,
A. W.
,
1990
, “
Aero-Thermal Investigation of a Highly Loaded Transonic Linear Turbine Guide Vane Cascade
,”
Technical Report, von Karman Institute for Fluids Dynamics, Brussels
.
2.
Sieverding
,
C. H.
,
Arts
,
T.
,
Dénos
,
R.
, and
Martelli
,
F.
,
1996
, “
Investigation of the Flow Field Downstream of a Turbine Trailing Edge Cooled Nozzle Guide Vane
,”
ASME J. Turbomach.
,
118
(
2
), pp.
291
300
.
3.
Pichler
,
R.
,
Sandberg
,
R. D.
,
Michelassi
,
V.
, and
Bhaskaran
,
R.
,
2016
, “
Investigation of the Accuracy of RANS Models to Predict the Flow Through a Low-Pressure Turbine
,”
ASME J. Turbomach.
,
138
(
12
), p.
121009
.
4.
Sandberg
,
R. D.
, and
Michelassi
,
V.
,
2019
, “
The Current State of High-Fidelity Simulations for Main Gas Path Turbomachinery Components and Their Industrial Impact
,”
Flow Turbul. Combust.
,
102
(
4
), pp.
797
848
.
5.
Pichler
,
R.
,
Sandberg
,
R. D.
,
Laskowski
,
G.
, and
Michelassi
,
V.
,
2017
, “
High-Fidelity Simulations of a Linear HPT Vane Cascade Subject to Varying Inlet Turbulence
,”
ASME Turbo Expo 2017: Turbomachinery Technical Conference and Exposition, Paper No. GT2017-63079
.
6.
Zhao
,
Y.
, and
Sandberg
,
R. D.
,
2020
, “
Bypass Transition in Boundary Layers Subject to Strong Pressure Gradient and Curvature Effects
,”
J. Fluid Mech.
,
888
(
A4
), pp.
1
34
.
7.
Bhaskaran
,
R.
, and
Lele
,
S. K.
,
2010
, “
Large Eddy Simulation of Freestream Turbulence Effects on Heat Transfer to a High-Pressure Turbine Cascade
,”
J. Turbul.
,
11
(
6
), pp.
1
15
.
8.
Gourdain
,
N.
,
Gicquel
,
L.
, and
Collado
,
E.
,
2012
, “
Comparison of RANS and LES for Prediction of Wall Heat Transfer in a Highly Loaded Turbine Guide Vane
,”
J. Propul. Power
,
28
(
2
), pp.
423
433
.
9.
Segui
,
L.
,
Gicquel
,
L.
,
Duchaine
,
F.
, and
de Laborderie
,
J.
,
2017
, “
LES of the LS89 Cascade: Influence of Inflow Turbulence on the Flow Predictions
,”
Proceedings of 12th European Conference on Turbomachinery Fluid dynamics and Thermodynamics ETC12
,
Stockholm, Sweden
,
Apr. 3–7
, pp.
3
7
.
10.
Harnieh
,
M.
,
Gicquel
,
L.
, and
Duchaine
,
F.
,
2017
, “
Sensitivity of Large Eddy Simulations to Inflow Condition and Modeling if Applied to a Transonic High-Pressure Cascade Vane
,”
ASME Turbo Expo 2017: Turbomachinery Technical Conference and Exposition, Paper No. GT2017-64686
.
11.
Zhao
,
Y.
, and
Sandberg
,
R. D.
,
2019
, “
Using a New Entropy Loss Analysis to Assess the Accuracy of RANS Predictions of an HPT Vane
,”
ASME Turbo Expo 2019: Turbomachinery Technical Conference and Exposition, Paper No. GT2019-90126
.
12.
Sandberg
,
R. D.
,
Michelassi
,
V.
,
Pichler
,
R.
,
Chen
,
L.
, and
Johnstone
,
R.
,
2015
, “
Compressible Direct Numerical Simulation of Low-Pressure Turbines—Part I: Methodology
,”
ASME J. Turbomach.
,
137
(
5
), p.
051011
.
13.
Kim
,
J. W.
, and
Sandberg
,
R. D.
,
2012
, “
Efficient Parallel Computing With a Compact Finite Difference Scheme
,”
Comput. Fluids
,
58
, pp.
70
87
.
14.
Kennedy
,
C. A.
,
Carpenter
,
M. H.
, and
Lewis
,
R. M.
,
2000
, “
Low-Storage, Explicit Runge–Kutta Schemes for the Compressible Navier–Stokes Equations
,”
Appl. Numer. Math.
,
35
(
3
), pp.
177
219
.
15.
Michelassi
,
V.
,
Chen
,
L.
,
Pichler
,
R.
, and
Sandberg
,
R. D.
,
2015
, “
Compressible Direct Numerical Simulation of Low-Pressure Turbines—Part II: Effect of Inflow Disturbances
,”
ASME J. Turbomach.
,
137
(
7
), p.
071005
.
16.
Wheeler
,
A. P. S.
,
Sandberg
,
R. D.
,
Sandham
,
N. D.
,
Pichler
,
R.
, and
Michelassi
,
V.
,
2016
, “
Direct Numerical Simulations of a High-Pressure Turbine Vane
,”
ASME J. Turbomach.
,
138
(
7
), p.
071003
.
17.
Pichler
,
R.
,
Zhao
,
Y.
,
Sandberg
,
R. D.
,
Michelassi
,
V.
,
Pacciani
,
R.
,
Marconcini
,
M.
, and
Arnone
,
A.
,
2018
, “
LES and RANS Analysis of the End-Wall Flow in a Linear LPT Cascade: Part I—Flow and Secondary Vorticity Fields Under Varying Inlet Condition
,”
ASME Turbo Expo 2018: Turbomachinery Technical Conference and Exposition, Paper No. GT2018-76233
.
18.
Marconcini
,
M.
,
Pacciani
,
R.
,
Arnone
,
A.
,
Michelassi
,
V.
,
Pichler
,
R.
,
Zhao
,
Y.
, and
Sandberg
,
R. D.
,
2019
, “
Large Eddy Simulation and RANS Analysis of the End-Wall Flow in a Linear Low-Pressure-Turbine Cascade—Part II: Loss Generation
,”
ASME J. Turbomach.
,
141
(
5
), p.
051004
.
19.
Bogey
,
C.
,
De Cacqueray
,
N.
, and
Bailly
,
C.
,
2009
, “
A Shock-Capturing Methodology Based on Adaptative Spatial Filtering for High-Order Non-Linear Computations
,”
J. Comput. Phys.
,
228
(
5
), pp.
1447
1465
.
20.
Kim
,
J. W.
, and
Lee
,
D. J.
,
2003
, “
Characteristic Interface Conditions for Multiblock High-Order Computation on Singular Structured Grid
,”
AIAA J.
,
41
(
12
), pp.
2341
2348
.
21.
Deuse
,
M.
, and
Sandberg
,
R. D.
,
2020
, “
Implementation of a Stable High-Order Overset Grid Method for High-Fidelity Simulations
,”
Comput. Fluids
,
211
, p.
104449
.
22.
Chesshire
,
G.
, and
Henshaw
,
W. D.
,
1990
, “
Composite Overlapping Meshes for the Solution of Partial Differential Equations
,”
J. Comput. Phys.
,
90
(
1
), pp.
1
64
.
23.
Klein
,
M.
,
Sadiki
,
A.
, and
Janicka
,
J.
,
2003
, “
A Digital Filter Based Generation of Inflow Data for Spatially Developing Direct Numerical or Large Eddy Simulations
,”
J. Comput. Phys.
,
186
(
2
), pp.
652
665
.
24.
Nicoud
,
F.
, and
Ducros
,
F.
,
1999
, “
Subgrid-Scale Stress Modelling Based on the Square of the Velocity Gradient Tensor
,”
Flow Turbul. Combust.
,
62
(
3
), pp.
183
200
.
25.
Sandberg
,
R. D.
, and
Sandham
,
N. D.
,
2006
, “
Nonreflecting Zonal Characteristic Boundary Condition for Direct Numerical Simulation of Aerodynamic Sound
,”
AIAA J.
,
44
(
2
), pp.
402
405
.
26.
Wu
,
X.
,
2017
, “
Inflow Turbulence Generation Methods
,”
Annu. Rev. Fluid Mech.
,
49
, pp.
23
49
.
27.
Denton
,
J. D.
,
1993
, “
Loss Mechanisms in Turbomachines
,”
ASME J. Turbomach.
,
115
(
4
), pp.
621
656
.
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