Research Papers

The Effect of Manufacturing Variations on Unsteady Interaction in a Transonic Turbine

[+] Author and Article Information
John P. Clark

Turbomachinery Branch,
Turbine Engine Division,
Aerospace Systems Directorate,
Air Force Research Laboratory,
1864 4th Street,
Wright-Patterson AFB, OH 45433
e-mail: john.clark.38@us.af.mil

Joseph A. Beck

Wright-Patterson AFB, OH 45433

Alex A. Kaszynski, Angela Still

Universal Technology Co.,
Dayton, OH 54532

Ron-Ho Ni

AeroDynamic Solutions, Inc.,
Danville, CA 94526

1Corresponding author.

Contributed by the International Gas Turbine Institute (IGTI) of ASME for publication in the JOURNAL OF TURBOMACHINERY. Manuscript received October 23, 2017; final manuscript received November 27, 2017; published online April 30, 2018. Editor: Kenneth Hall. This work is in part a work of the U.S. Government. ASME disclaims all interest in the U.S. Government's contributions.

J. Turbomach 140(6), 061007 (Apr 30, 2018) (9 pages) Paper No: TURBO-17-1197; doi: 10.1115/1.4039361 History: Received October 23, 2017; Revised November 27, 2017

This effort focuses on the comparison of unsteadiness due to as-measured turbine blades in a transonic turbine to that obtained with blueprint geometries via computational fluid dynamics (CFD). A Reynolds-averaged Navier–Stokes flow solver with the two-equation Wilcox turbulence model is used as the numerical analysis tool for comparison between the blueprint geometries and as-manufactured geometries obtained from a structured light optical measurement system. The nominal turbine CFD grid data defined for analysis of the blueprint blade were geometrically modified to reflect as-manufactured turbine blades using an established mesh metamorphosis algorithm. The approach uses a modified neural network to iteratively update the source mesh to the target mesh. In this case, the source is the interior CFD surface grid while the target is the surface blade geometry obtained from the optical scanner. Nodes interior to the CFD surface were updated using a modified iterative spring analogy to avoid grid corruption when matching as-manufactured part geometry. This approach avoids the tedious manual approach of regenerating the CFD grid and does not rely on geometry obtained from coordinate measurement machine (CMM) sections, but rather a point cloud representing the entirety of the turbine blade. Surface pressure traces and the discrete Fourier transforms (DFT) thereof from numerical predictions of as-measured geometries are then compared both to blueprint predictions and to experimental measurements. The importance of incorporating as-measured geometries in analyses to explain deviations between numerical predictions of blueprint geometries and experimental results is readily apparent. Further analysis of every casting produced in the creation of the test turbine yields variations that one can expect in both aero-performance and unsteady loading as a consequence of manufacturing tolerances. Finally, the use of measured airfoil geometries to reduce the unsteady load on a target blade in a region of interest is successfully demonstrated.

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Sharma, O. P. , Pickett, G. F. , and Ni, R. H. , 1992, “Assessment of Unsteady Flows in Turbines,” ASME J. Turbomach., 114(1), pp. 79–90. [CrossRef]
Paniagua, G. , and Denos, R. , 2007, “Unsteadiness in HP Turbines,” Advances in Turbomachinery Aero-Thermo-Mechanical Design Analysis (VKI Lecture Series 2007-02), The von Karman Institute for Fluid Dynamics, Rhode Saint Genèse, Belgium.
Kielb, J. J. , and Abhari, R. S. , 2001, “Experimental Study of Aerodynamic and Structural Damping in a Full-Scale Rotating Turbine,” ASME Paper No. 2001-GT-0263.
Carassale, L. , Marre-Brunenghi, M. , and Patrone, S. , 2015, “Estimation of Damping for Turbine Blades in Non-Stationary Working Conditions,” ASME Paper No. GT2015-42945.
Meinzer, C. E. , Bittner, S. L. , Schmitt, S. , Kielb, R. E. , and Seume, J. R. , 2015, “Design of a Single Stage Turbine for Quantification of Aerodynamic Damping,” ASME Paper No. GT2015-42641.
Jennions, I. K. , and Adamczyk, J. J. , 1997, “Evaluation of the Interaction Losses in a Transonic Turbine HP Rotor/LP Vane Configuration,” ASME J. Turbomach., 119(1), pp. 68–75. [CrossRef]
Clark, J. P. , Aggarwala, A. S. , Velonis, M. A. , Magge, S. S. , and Price, F. R. , 2002, “Using CFD to Reduce Resonant Stresses on a Single-Stage, High-Pressure Turbine Blade,” ASME Paper No. GT2002-30320.
Dunn, M. G. , 2001, “Convective Heat Transfer and Aerodynamics in Axial Flow Turbines,” ASME J. Turbomach., 123(4), pp. 637–686. [CrossRef]
Adamczyk, J. J. , 2000, “Aerodynamic Analysis of Multi-Stage Turbomachinery Flows in Support of Aerodynamic Design,” ASME J. Turbomach., 122(2), pp. 189–217. [CrossRef]
Davis, R. L. , Yao, J. , Clark, J. P. , Stetson, G. , Alonso, J. J. , Jameson, A. , Haldeman, C. W. , and Dunn, M. G. , 2004, “Unsteady Interaction Between a Transonic Turbine Stage and Downstream Components,” Int. J. Rotating Mach., 10(6), pp. 495–506. [CrossRef]
Clark, J. P. , Koch, P. J. , Ooten, M. K. , Johnson, J. J. , Dagg, J. , McQuilling, M. W. , Huber, F. , and Johnson, P. D. , 2009, “Design of Turbine Components to Answer Research Questions in Unsteady Aerodynamics and Heat Transfer,” Air Force Research Laboratory, Wright-Patterson Air Force Base, OH, Report No. AFRL-RZ-WP-TR-2009-2180.
Clark, J. P. , 2012, “Design Strategies to Mitigate Unsteady Forcing,” Structural Design of Aircraft Engines: Key Objectives and Techniques (VKI Lecture Series 2012-06), G. Paniagua , ed., NATO Research and Technology Office, Brussels, Belgium, Report No. RTO EN-AVT-207.
Ooten, M. K. , Anthony, R. J. , Lethander, A. T. , and Clark, J. P. , 2016, “Unsteady Aerodynamic Interaction in a Closely Coupled Turbine Consistent With Contrarotation,” ASME J. Turbomach., 138(6), p. 061004.
Hancock, B. J. , and Clark, J. P. , 2014, “Reducing Shock Interactions in Transonic Turbine Via Three-Dimensional Aerodynamic Shaping,” AIAA J. Propul. Power, 30(5), pp. 1248–1256. [CrossRef]
Davis, R. L. , and Clark, J. P. , 2014, “Geometry/Grid Generation for 3D Multi-Disciplinary Simulations in Multi-Stage Turbomachinery,” AIAA J. Propul. Power, 30(6), pp. 1502–1509. [CrossRef]
Davis, R. L. , Dannenhoffer, J. F. , and Clark, J. P. , 2011, “Conjugate Design/Analysis Procedure for Film-Cooled Turbine Airfoil Sections,” AIAA J. Propul. Power, 27(1), pp. 61–70. [CrossRef]
Ni, R. H. , Humber, W. , Ni, M. , Capece, V. R. , Ooten, M. K. , and Clark, J. P. , 2016, “Aerodynamic Damping Predictions for Oscillating Airfoils in Cascades Using Moving Meshes,” ASME Paper No. GT2016-57017.
Gottleib, J. , Davis, R. L. , and Clark, J. P. , 2013, “Simulation Strategy for Film-Cooled Multistage Turbine Design and Analysis,” AIAA J. Propul. Power, 29(6), pp. 1495–1498. [CrossRef]
Garzon, V. E. , 2002, “Probabilistic Aerothermal Design of Compressor Airfoils,” Ph.D. thesis, Massachusetts Institute of Technology, Cambridge, MA.
Goodhand, M. N. , Miller, R. J. , and Lung, H. W. , 2012, “The Sensitivity of 2D Compressor Incidence to In-Service Geometric Variation,” ASME Paper No. GT2012-68633.
Goodhand, M. N. , and Miller, R. J. , 2012, “The Impact of Real Geometries on Three-Dimensional Separation in Compressors,” ASME J. Turbomach., 134(2), p. 021007. [CrossRef]
Lange, A. , Voigt, M. , Vogeler, K. , Schrapp, H. , Johann, E. , and Gümmer, V. , 2012, “Impact of Manufacturing Variability and Nonaxisymmetry on High-Pressure Compressor Stage Performance,” ASME J. Eng. Gas Turbines Power, 143(3), p. 032504. [CrossRef]
Garzon, V. E. , and Darmofal, D. L. , 2003, “Impact of Geometric Variability on Axial Compressor Performance,” ASME J. Turbomach., 125(4), pp. 692–703. [CrossRef]
Bammert, K. , and Sandstede, H. , 1976, “Influences of Manufacturing Tolerances and Surface Roughness of Blades on the Performance of Turbines,” ASME J. Eng. Power, 98(1), pp. 29–36. [CrossRef]
Andersson, S. , 2007, “A Study of Tolerance Impact on Performance of a Supersonic Turbine,” AIAA Paper No. 2007-5513.
Reitz, G. , Schlange, S. , and Freidrichs, J. , 2016, “Design of Experiments and Numerical Simulation of Deteriorated High Pressure Compressor Airfoils,” ASME Paper No. GT2016-56024.
Dow, E. A. , and Wang, Q. , 2015, “The Implications of Tolerance Optimization on Compressor Blade Design,” ASME J. Turbomach., 137(10), p. 101008. [CrossRef]
Buske, C. , Krumme, A. , Schmidt, T. , Dresbach, C. , Zur, S. , and Tiefers, R. , 2016, “Distributed Multidisciplinary Optimization of a Turbine Blade Regarding Performance, Reliability, and Castability,” ASME Paper No. GT2016-56079.
Marcu, B. , Tran, K. , and Wright, B. , 2002, “Prediction of Unsteady Loads and Analysis of Flow Changes Due to Turbine Blade Manufacturing Variations During the Development of Turbines for the MD-XX Advanced Upper Stage Engine,” AIAA Paper No. 2002-4162.
Schnell, R. , Lengyel-Kampmann, T. , and Nicke, E. , 2013, “On the Impact of Geometric Variability on Fan Aerodynamic Performance, Unsteady Blade Row Interaction, and Its Mechanical Characteristics,” ASME J. Turbomach., 136(9), p. 091005. [CrossRef]
Holtzhausen, S. , Schreiber, S. , Schöne, C. , Stelzer, R. , Heinze, K. , and Lange, A. , 2009, “Highly Accurate Automated 3D Measuring and Data Conditioning for Turbine and Compressor Blades,” ASME Paper No. GT2009-59902.
Kaszynski, A. A. , Beck, J. A. , and Brown, J. M. , 2013, “Uncertainties of an Automated Optical 3D Geometry Measurement, Modeling, and Analysis Process for Mistuned Integrally Bladed Rotor Reverse Engineering,” ASME J. Eng. Gas Turbines Power, 135(10), p. 102504. [CrossRef]
Kaszynski, A. A. , Beck, J. A. , and Brown, J. M. , 2014, “Automated Finite Element Model Mesh Updating Scheme Applicable to Mistuning Analysis,” ASME Paper No. GT2014-26925.
Kaszynski, A. A. , Beck, J. A. , and Brown, J. M. , 2015, “Experimental Validation of a Mesh Quality Optimized Morphed Geometric Mistuning Model,” ASME Paper No. GT2015-43150.
Anthony, R. J. , and Clark, J. P. , 2013, “A Review of the AFRL Turbine Research Facility,” ASME Paper No. GT2013-94741.
Dunn, M. G. , and Haldeman , C. W., Jr. , 1995, “Phase-Resolved Surface Pressure and Heat Transfer Measurements on the Blade of a Two-Stage Turbine,” ASME J. Fluids Eng., 117(4), pp. 653–658. [CrossRef]
Beck, J. A. , Brown, J. M. , Cross, C. J. , and Slater, J. C. , 2014, “Component-Mode Reduced-Order Models for Geometric Mistuning of Integrally Bladed Rotors,” AIAA J., 52(7), pp. 1345–1356. [CrossRef]
Lewalle, J. , 1994, “Wavelet Analysis of Experimental Data—Some Methods and the Underlying Physics,” AIAA Paper No. 94-2281.
Lewalle, J. , 2007, “Wavelet Transforms,” Springer Handbook of Experimental Fluid Mechanics, C. Tropea , A. Yarin , and J. F. Foss , eds., Springer, New York.


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Fig. 1

CFD surface (red) overlaid onto nominal finite element model mesh (white)

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Fig. 2

Quantitative 3D CFD discrepancies based on nominal and as-measured geometries (suction side)

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Fig. 3

Quantitative 3D CFD discrepancies based on nominal and as-measured geometries (pressure side)

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Fig. 4

The mean of surface distance variation for the 105 measured blades with respect to the blueprint geometry. Suction- and pressure-side views are on the left and right, respectively.

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Fig. 5

The standard deviation of surface distance variation between the 105 measured blades and the blueprint geometry. Suction- and pressure-side views are on the left and right, respectively.

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Fig. 6

Two-dimensional cross section for the population of airfoils at 50% span (red) versus that of nominal design (dash blue)

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Fig. 7

Histogram of as-measured trailing-edge diameter at the nominal 50% span

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Fig. 8

Histogram of as-measured trailing-edge metal angle at the nominal 50% span

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Fig. 9

Histogram of as-measured trailing-edge wedge angle at the nominal 50% span

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Fig. 10

The three airfoil rows in the transonic turbine of this study with color scale indicative of instantaneous static pressure

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Fig. 11

The standard deviation of unsteady surface pressure magnitude (left) as a percent of Ptin at 46E and the phase angle in degrees (right). Also plotted are the locations of sensors on the blade suction side downstream of the throat.

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Fig. 12

Unsteady pressures (top), DFT magnitudes (middle), and a spectrogram for experimental data from sensor #7 on Fig.11

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Fig. 13

Mean and peak-to-peak variation in calculated DFT magnitude at 46E for all sensor locations in Fig. 11. N.B. All simulation results are represented and compared to experimental data.

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Fig. 14

DFT magnitude at 46E as a percent of Ptin on blade 20 for a full-wheel simulation (left) and a 2:4:2 model containing only measured blades 20 through 23 (right)

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Fig. 15

The DFT magnitude at 46E as a percent of Ptin on blade 20 for a full-wheel simulation (left) and a 2:4:2 model containing only measured blade 20 and three measured blades selected to reduce unsteadiness at sensor 7 (right)

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Fig. 16

Unsteady pressure signals and wavelet scalograms for a kulite sensor on the downstream vane pressure side at 52% span and 20% axial chord. Results of simulations with blueprint- and as-measured blades are shown in the top and bottom scalograms, respectively. Ensemble-averaged experimental data is shown in the center scalogram.



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