An experimental investigation of clocking effects on turbine aerodynamics using a modern

AN EXPERIMENTAL INVESTIGATION OF CLOCKING EFFECTS ON TURBINE AERODYNAMICS USING A MODERN 3-D ONE AND ONEHALF STAGE HIGH PRESSURE TURBINE FOR CODE VERIFICATION AND FLOW MODEL DEVELOPMENT DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Charles W HaldemanIV, M.S ***** The Ohio State University 2003 Dissertation Committee: Approved by Professor Michael G Dunn, Advisor Professor James Scott Advisor Professor Mohammad Samimy Dr Robert Bergholz Graduate Program in Aeronautical and Astronautical Engineering ABSTRACT This research uses a modern and 1/2 stage high-pressure (HP) turbine operating at the proper design corrected speed, pressure ratio, and gas to metal temperature ratio to generate a detailed data set containing aerodynamic, heat-transfer and aero-performance information The data was generated using the Ohio State University Gas Turbine Laboratory Turbine Test Facility (TTF), which is a short-duration shock tunnel facility The research program utilizes an uncooled turbine stage for which all three airfoils are heavily instrumented at multiple spans and on the HPV and LPV endwalls and HPB platform and tips Heat-flux and pressure data are obtained using the traditional shocktube and blowdown facility operational modes Detailed examination show that the aerodynamic (pressure) data obtained in the blowdown mode is the same as obtained in the shock-tube mode when the corrected conditions are matched Various experimental conditions and configurations were performed, including LPV clocking positions, off-design corrected speed conditions, pressure ratio changes, and Reynolds number changes The main research for this dissertation is concentrated on the LPV clocking experiments, where the LPV was clocked relative to the HPV at several different passage locations and at different Reynolds numbers Various methods were used to evaluate the effect of clocking on both the aeroperformance (efficiency) and aerodynamics (pressure loading) on the LPV, including time-resolved measurements, time-averaged measurements and stage performance measurements A general improvement in overall efficiency of approximately 2% is demonstrated and could be observed using a variety of independent methods Maximum efficiency is obtained when the time-average pressures are highest on the LPV, and the time-resolved data both in the time domain and frequency domain show the least amount of variation The gain in aeroperformance is obtained by integrating over the entire airfoil as the three-dimensional effects on the LPV surface are significant ii This experimental data set validates several computational research efforts that suggested wake migration is the primary reason for the perceived effectiveness of LPV clocking Previous experimental work that supported those computational research efforts was not representative of modern turbine machines, and it was unclear before this work started, if the main mechanism hypothesized in the previous work would translate to more complex machines In addition, this data set provides for the designer key insight into the energy transfer that occurs in the time-resolved data between frequencies as a function of clocking position While it was clear that these transfers did not affect the overall efficiency of the machine, it is for the engine designers to know if these transfers will add to a high-cycle fatigue or other structural problem Wake migration predictions nothing for the engine designer’s concerns about structural problems This limits their information to either experimental data sets such as this one, or full results from 3D Navier-Stokes codes, which are almost as rare as the data sets iii ACKNOWLEDGMENTS This dissertation has been a long time in the creation Getting the chance to the work took years Tasks such as getting the laboratory running, taking classes, and keeping up with contract research kept this dissertation from happening sooner And as any person submitting a dissertation will tell you, it would not be possible without a major effort from a variety of people, all of who cannot be thanked enough for their efforts To begin with, without the help and support of my wife Margaret, none of this would have been possible She has endured this work for years, when I am sure that she thought there was no end in sight (and for a long time no beginning either!) She has made countless sacrifices for this work and for the OSU GTL in general, and I can never thank her enough for her support The rest of my family and friends from all phases of my life have also been critical in helping me to keep this work in perspective, which is sometimes not easy to when you are in the middle of it I am sure that most of my friends from the U of R expected me to be the first to get a Ph.D and I am grateful that they have not harassed me too much about being the last The seeds of this work actually date back to my days at MIT and I need to thank both Prof Alan Epstein and Dr Gerry Guenette for my initial exposure to the world of short-duration experimentation The time I spent building the WPAFB ATARR facility with Dr Charles MacArthur was also a major contributor to some of the ideas and techniques that have come to fruition in this dissertation and I would like to thank him for his many insights into turbine research I would also like to thank the researchers at Calspan that could not come with us to OSU for contributions they made to the various projects all through the 1990’s that have developed key techniques and insights that are present in this work For the group that came to OSU, the fact that we broke all kinds of iv time records in getting the new laboratory up and running was a direct result of everyone’s hard work Getting the laboratory functional early on made this work possible Jeff Barton, the laboratory’s facility manager, has been instrumental in keeping the place running and translating ideas into working projects The data contained in this dissertation would not have been possible without his help Nor would it have been possible without the distinct efforts of the rest of the support staff: Ken Copley, Michael Jones, and Packy Underwood, all of whom played key roles in this project There are also several graduate and undergraduate students that have helped in this project over the years Matt Krumanaker, who was responsible for the detailed heat-flux gauge calibrations, did the most extensive work I would also like to personally thank Colin Scrivener of Rolls-Royce and Prof Mike Giles of Oxford University for their help with UNSFLO-2D Dr Scrivener was instrumental in obtaining formal permission for the OSU GTL to use UNSFLO-2D and Prof Giles was extremely helpful in the resurrection of the code on our machines I learned a great deal about how these large codes are assembled from our discussions and am deeply indebted to him for the time he spent with me on this work I would like to personally thank Matt Weaver, Corso Padova and Prof Reza Abhari, for their friendship, guidance, and insight over the many phases of this work I would also like to thank the various groups that I have interacted with at GE over the course of this project for their guidance, insight, and patience The GE-USA program, which is the overall program under which this research was accomplished, has proven to be a great success There are too many people to mention specifically, but I would like to acknowledge the contributions of David Wisler, Monty Shelton, Bob Bergholz, and Fred Buck for all their help in this project and in making the GE-USA program the success that it is at OSU Their support has involved much more than the financial support GE provides to the project In addition Fred Buck, Bob Bergholz, and David Wisler have spent a great deal of their own time in reviewing the preliminary work presented in this dissertation and their collective suggestions have been critical in the update of this work, which hopefully will make it easier for others to digest v Finally, I would like to thank my advisor and mentor, Prof Mike Dunn for the many years of collaboration, guidance, and support in both this dissertation and our past projects I consider myself lucky and privileged to have been able to work so closely with one of the founders of this area of research vi VITA 1963 Born- Lexington, Massachusetts 1985 B.S Mechanical Engineering, University of Rochester, Rochester NY 1989 M.S Aeronautical and Astronautical Engineering, Massachusetts Institute of Technology 1990 M.S Technology and Policy Program, Massachusetts Institute of Technology 1986-1990 Research Assistant, MIT Gas Turbine Lab 1990-1996 Research Engineer, Calspan Corporation, Buffalo New York 1996-Present Senior Research Engineer, Ohio State University Gas Turbine Lab vii PUBLICATIONS Archival Publications “Time-Averaged Heat-flux for a Recessed Tip, Lip, and Platform of a Transonic Turbine Blade”; M Dunn and C Haldeman, ASME Journal of Turbomachinery, Oct 2000, Vol 122, pp 692-698 “Influence of Vane/Blade spacing on the Heat Flux for a Transonic Turbine”; M Dunn, C Haldeman, R Abhari, and M McMillan, ASME Journal of Turbomachinery, Oct 2000, Vol 122, pp 684-691 “Influence of Vane-blade spacing on Transonic turbine Stage Aerodynamics: Part I: Time Resolved Data and Analysis” B Venable, R Delaney, J Busby, R Davis, D Dorney, M Dunn, C Haldeman, R Abhari, ASME Journal of Turbomachinery, Oct 1999, Vol 121, pp.663-672 “Influence of Vane-blade spacing on Transonic turbine Stage Aerodynamics: Part II: Time Resolved Data and Analysis”; J Busby, R Davis, D Dorney, M Dunn, C Haldeman, R Abhari, B Venable, R Delaney, ASME Journal of Turbomachinery, Oct 1999, Vol 121, pp.673-682 “High-Accuracy Turbine Performance Measurements in Short-Duration Facilities”; C Haldeman and M Dunn, ASME Journal of Turbomachinery, Jan 1998, Vol 120, pg 1-9 “Phase-Resolved Surface Pressure and Heat-Transfer Measurements on the Blade of a Two-Stage Turbine”, M Dunn and C Haldeman, Journal of Fluids Engineering, December 1995, Vol 117, pg 653-658 Refereed Conference Papers “Influence of Clocking and Vane/Blade Spacing on the Unsteady Surface Pressure Loading for a Modern Stage and One-Half Transonic Turbine”, C Haldeman, M Krumanaker, and M Dunn, GT2003-38724 (accepted for publication in the ASME Journal of Turbomachinery) “Heat Transfer Measurements and Predictions for the Vane and Blade of a Rotating High-Pressure Turbine Stage”, C Haldeman and M Dunn, GT2003-38726 (accepted for publication in the ASME Journal of Turbomachinery) “Experimental Investigation of the Aerodynamic Effects of Clocking Vanes and Blade Rows in a 1/3 Scale Model Turbine”, D B M Jouini, D Little, E Bancalari, M Dunn, C Haldeman, P.D Johnson, GT2003-38872, Proceedings of the ASME International Gas Turbine Institute, Turbo-Exposition, Atlanta, GA, June 15-19, 2003 “Unsteady Interaction Between a Transonic Turbine Stage and Downstream Components”, R.L Davis, J Yao, J.P Clark, G Stetson, J.J Alonso, A Jameson, C.W Haldeman, M.G Dunn, 2002-GT-30364, Proceedings of the ASME viii International Gas Turbine Institute Turbo-Exposition, Amsterdam, Netherlands June 3-6, 2002 “The Effect of Airfoil Scaling on the Predicted Unsteady Pressure Field in a 1+1/2 Stage Transonic Turbine and a Comparison with Experimental Results”, J.P Clark, G.M Stetson, S.S Magge, C.W Haldeman, M.G Dunn, 2000-GT-0446, Proceedings of ASME International Gas Turbine Institute Turbo-Expo, Munich, Germany May 8-11, 2000 “Experimental and Computational Investigation of the Time-Averaged and TimeResolved Pressure Loading on a Vaneless Counter-Rotating Turbine”, C Haldeman, M Dunn, R Abhari, P Johnson, and X Montesdeoca, 2000-GT-0445, Proceedings of the ASME International Gas Turbine Institute Turbo Expo, Munich, Germany May 8-11, 2000 “Time-Resolved and Time-Averaged Pressure and Heat-Transfer Measurements on the Blade of a Two-Stage Turbine” M Dunn and C Haldeman, International Symposium on Unsteady Flows in Aeropropulsion: Recent Advances in Experimental and Computational Methods, 1994 ASME Winter Annual Meeting, Chicago, IL, November 6-11, 1994 Conference Papers “Summary of Time-Averaged and Phase-Resolved Pressure Measurements on the First Stage Vane and Blade of the SSME Fuel-Side Turbine”, 1994 Earth to Orbit Conference, Huntsville, AL, May 1994 “The USAF Advanced Turbine Aerothermal Research Rig (ATARR)”; C Haldeman, M Dunn, C MacArthur and C Murawski; AGARD Conference Proceedings 527, Heat Transfer and Cooling in Gas Turbines, 1992 “Uncertainty Analysis of Turbine Aerodynamics Performance Measurements in Shortduration Test Facilities” C Haldeman, M Dunn, J Lotsof, C MacArthur, and Lt B Cohrs; Paper No AIAA-91-2131 AIAA/SAE/ASME/ASEE 27th Joint Propulsion Conference, June 24-26, 1991, Sacramento, CA FIELDS OF STUDY Major Field: Aeronautical and Astronautical Engineering ix % Change in Mechanical Efficiency Mechanical Efficiencies based on Individual Group Windows and Acceleration over Window MGroup MGroup MGroup 6 Run 13 Run 14 -2 -4 -6 0.2 0.4 0.6 Clocking (actual) 0.8 Figure D.20 Mechanical Efficiency over Time window As a last piece of evidence, the isentropic and mechanical efficiencies were calculated using a set of time windows that not incorporate all the innovations applied in this analysis as a comparison of the different techniques These time windows were chosen in a more traditional manner by matching the pressure ratios for each run These are shown to illustrate the kind of effect all of the analysis improvements have on the data set 306 Variation in Isentropic Efficiency from Average Using "Traditional Windowing Technique" % Change in Efficiency -2 Group Group Group Group -4 -6 -8 0.2 Group Group Group Group 15 % Change in Efficiency 10 0.4 0.6 Clocking (actual) 0.8 Variation in Mechanical Efficiency Based Using "Traditional Windowing" Technique -5 -10 -15 0.2 0.4 0.6 Clocking (actual) 0.8 Figure D.21 Traditional Windowing Technique Results Figure D.18 to Figure D.21 contain a great deal of information, and the differences among the figures reveals a lot of information about the flow through the machine 1) One has to be cognizant of the fact that the definitions of mechanical and thermodynamic (isentropic) efficiencies used are more than just two different techniques using slightly different measures to obtain similar values The isentropic definition of efficiency used in this case does not account for heat transfer that occurs from the fluid to the surrounding metal This is the reason many people use this same formula and describe it as the thermodynamic measure of efficiency This is the efficiency of the machine operated in this 307 condition, but it is not a representative measurement of the adiabatic efficiency that is often used to characterize a turbine This is just another instance of the long debate over what the best characterization of efficiency is for an isothermal environment and how that should be translated into more traditional engineering efficiencies used for design needs The latest work done on this issue was that of Keogh et al [5], which is an extension of the first work done looking at this particular problem by Haldeman et al [4] 2) As a comparison, the mechanical efficiency measures the physical work extracted from the turbine directly As a result it does not care about the heattransfer losses that occur in the system, and thus intrinsically it should provide a better indication of the actual adiabatic efficiency of the machine Even if losses affect the measurements, in the mechanical case, one is only looking at the effect to the turbine airfoils and not to the entire surface area between the rakes used in the thermodynamic measurements 3) Noting that the two systems measure different characteristics of the machine, one would not expect the differences one sees between the mechanical and thermodynamic measures of efficiency in Figure 6.1 If the difference was just due to heat transfer losses, then one would expect similar line shapes between the two figures since the runs are all nominally at the same condition For the thermodynamic plot, outside of the variation between points A and E, one can see a pattern that all the groups support However, that variation is not as discernable in the mechanical efficiency This is due to the fact that in both Figure 6.1 and Figure 6.2 the mechanical efficiency was calculated over the entire test-time (from start to the center of the window) This provides a more robust measurement of acceleration, which is derived completely from the difference in speed from the beginning of the evaluation period to the end (which in this case is about 200 rpm) The idea being that even if the turbine was not operating at exactly the proper conditions over this entire time, at least it should be operating in a similar manner for all the runs (since they are 308 started at the same conditions) As a comparison, the mechanical efficiency is calculated over just the time-window and is shown in Figure 6.3 4) The difference between Figure 6.1 and Figure 6.2 (note that in Figure 6.2, the X-axis was changed to show the difference between points A and E) is subtle Just examining the thermodynamic measures of efficiency, Mgroup shows a strong sinusoidal pattern when the individual time windows are used This pattern seems to be supported by MGroup 6, although there seems to be an offset A more cupped shaped pattern is seen with MGroup 3, but it is important to realize that for Entry 1, the vane was not as accurately positioned for the intermediate positions (A-B, C-D, etc) because alignment holes did not exist In addition, the vane ring was clamped only by friction and not with any alignment bolts On the 60-psi cases, the vane was observed to slip a little during the run, so these intermediate positions may not be in their exact locations 5) The mechanical efficiency for Figure 6.2 does not have as robust a pattern as the thermodynamic measurement To see if this could be due to the fact that the thermodynamic efficiency was being measured over one revolution, but the mechanical over the entire experiment, the acceleration resolution was sacrificed and a measure of the mechanical efficiency was done over one revolution (shown in Figure 6.3) In this case the change in speed is about 1/10 that of the data used in Figure 6.2 However, outside of the measured efficiency for MGroup and point C-D (0.625) and MGroup clock D, the pattern looks a lot more like the thermodynamic efficiency measured in Figure 6.2 Looking at the speed traces for these two runs, one can see some small oscillations that may be affecting the acceleration measurements on this small time scale As a result, one could claim that the thermodynamic measurement of efficiency from Figure 6.2 would best be compared to the mechanical efficiency changes shown in Figure 6.3, and the patterns and changes look comparable 309 6) To show the cumulative effect of all the small changes done in the data reduction to obtain a more accurate representation of the clocking data, the original plots using a traditional windowing technique where the run windows were selected based on matching the pressure ratios for all runs is shown in Figure 6.4 The isentropic efficiency shows a pattern similar to that in Figure 6.2, although the absolute levels are washed out a little There is no real comparison with the mechanical efficiency though The absolute levels are off dramatically and the pattern is difficult to discern This is really not surprising since many of the changes involve better calculation of the acceleration and the time-windows, which mostly affect the mechanical efficiency calculations For the thermodynamic efficiencies the current system still tries to match the pressure ratios and the corrected speeds, but not on all runs just one runs of similar clock position (D in this case) and then use the same windows (corrected for the initial start times) for the other runs in that sequence Thus, one would expect similar result for the thermodynamic measurements D.2.1.3 Frequency Analysis The frequency analysis, like the time average data and the envelope data before, will be split into different figures that show how the average trend varies with gauge location, and then how clocking influences these values In addition, the range bars used on the percentage variation figures will come from the maximum ranges observed on the repeat runs associated with clock position D But before that data is presented, to validate the techniques used a few sample plots will be shown that discuss the uncertainty bands and the accuracy of the frequency estimates, since almost all of the plots will deal specifically with amplitudes The first series of figures will examine the uncertainty associated with estimating the fundamental and harmonic frequencies The sorting routines have a user set limit on how exact the frequencies need to be to be considered blade passing, first harmonic, second harmonic etc And these frequencies change if the observer is riding on the blade 310 or the vane (typical values are 8544 Hz for HPV or LPV sensors, and 4509 for HPB: Note ratio 8544/4509 = #of blades/# of vanes = 72/38 = 1.8947) The typical frequency resolution for the base FFT work is about 118 Hz (of course interpolation refines that) The frequency accuracy will be examined for both Bound Group and (Clock D variation and time variation on Run 25) FUNDAMENTAL FREQ (RUN 25_O) FUNDAMENTAL FREQ (RUN 25_N) FUNDAMENTAL FREQ (RUN 25_L) FREQ (RUN 25_O) FREQ (RUN 25_N) FREQ (RUN 25_L) FREQ (RUN 25_O) FREQ (RUN 25_N) FREQ (RUN 25_L) Variable Mean FUNDAMENTAL (RUN 25_O) -0.0052615777 FUNDAMENTAL (RUN 25_N) -0.0051769472 FUNDAMENTAL (RUN 25_L) 0.010549044 FREQ (RUN 25_O) -0.063988506 FREQ (RUN 25_N) 0.030738391 FREQ (RUN 25_L) 0.032503146 FREQ (RUN 25_O) -0.01418676 FREQ (RUN 25_N) -0.03008758 FREQ (RUN 25_L) 0.044885626 Std Deviation 0.489743 0.35424406 0.46203572 0.44206873 0.29458038 0.45295332 0.27166116 0.44003534 0.32393173 % Variation in Harmonic Frequencies From Average due to Time window shifts % change in Frequencies -1 -2 -3 -4 PLV26 PLV31 PLV43 PR22 PR11 DAS LABEL PVO5 PV4 PV13 Figure D.22 Frequency Estimation Accuracy for Bound Group (Time Variations) There is quite a lot of interesting information in this figure To begin with all the frequencies that we will look at (fundamental, first and second harmonics) are plotted for the three different window shifts (1/4 rev apart) from the average for the condition The statistics for each trace is given in the upper right corner These values are already in terms of percentage of the standard deviation on the first line of 0.49 is 0.49% The averages should all be close to zero (and they are) One can see that there are a few sensors that have variations greater than 1%, but in general, the variation for all the 311 frequencies has a range lower the ±0.5% It is important to note that this frequency changes with physical speed, and the speed variation that would be expected over these time shifts approaches this value This can also be interpreted not just as an indication on the stability of the measurement as one changes time windows, but also as how well the interpolation schemes work to pick out the maximum amplitude/frequency combination since the raw FFT resolution is about 114 Hz Observed accuracies for a given run based on different windowing techniques might be about 0.04% A final note shows that the technique for producing the sorting is working in that there are large gaps in the PV’s where there are no frequencies This corresponds to those locations on the HPV where there is no blade-induced periodicity A similar plot can be produced for the Bound Group data (Clock D run variations) FUNDAMENTAL FREQ (RUN 9_P) FUNDAMENTAL FREQ (RUN 25_J) FUNDAMENTAL FREQ (RUN 32_M) FREQ (RUN 9_P) FREQ (RUN 25_J) FREQ (RUN 32_M) FREQ (RUN 9_P) FREQ (RUN 25_J) FREQ (RUN 32_M) Variable Mean FUNDAMENTAL FREQ (RUN 9_P) -0.35910546 FUNDAMENTAL FREQ (RUN 25_J) 0.14565378 FUNDAMENTAL FREQ (RUN 32_M) 0.22843555 FREQ (RUN 9_P) -0.32122639 FREQ (RUN 25_J) 0.15041756 FREQ (RUN 32_M) 0.19114012 FREQ (RUN 9_P) -0.33032764 FREQ (RUN 25_J) 0.20865788 FREQ (RUN 32_M) 0.16969813 Std Deviation 0.34087255 0.26914812 0.25836933 0.26902541 0.24640777 0.20696226 0.29299002 0.26121539 0.18117874 % Variation in Harmonic Frequencies for different runs at same Clock Position (D) % change in Frequencies -1 -2 -3 PLV14 PR41 DAS LABEL PVI10 PV4 Figure D.23 Frequency Estimation Accuracy for Bound Group (Clock D Variations) 312 As in Figure D.22, the variation in frequency is very small The offsets are probably due to the fact that exact matches were not made in the physical speed Runs 32_M and 25_J were only RPM different in speed, but run 9_P was about 36 RPM off This translates into difference from the average of about 0.2% for Runs 25 and 32 and about 0.36% for Run 9, which is very similar to the range shown in the graph Using this data as the basis, no more attention will be paid to the actual frequencies It will be assumes that for the purpose of the harmonic analysis that the frequencies under investigation can be referred to simply as the fundamental and first and second harmonics and that we are reproducing these frequencies with enough precision for our work The next task is to show the bounds for the uncertainty bands when calculating the changes from clocking positions As was done in the time-averaged data and the envelope data, the ranges generated from the two bound groups will be evaluated and are shown for the main amplitudes of interest in Figure D.24 One can see from these figures that the variation due to repeat runs (clock D variation) is slightly higher than the variation due to time windows This is a little different from the results shown in Figure D.10, where there was a more marked difference between the bound groups There also does not seem to be any dramatic pattern between the airfoil types, with similar ranges being seen throughout the machine To remain consistent, Bound Group (the clock D variations) will be used as the source of the range data 313 Maximum Range (%) 70 60 50 Range Uncertainty Estimate Comparision for Fundamental Amplitude Bound Group (Clock D Variation) Bound Group (Run 25, Time Variation) BGroup (Clock D) BGroup (Run 25) 40 30 20 10 70 PLV26 PLV31 PLV43 PR22 PR11 DAS LABEL Maximum Range (%) PV4 PV13 Range Uncertainty Estimate Comparision for First Harmonic Amplitude Bound Group (Clock D Variation) Bound Group (Run 25, Time Variation) Bound Group (Clock D) Bound Group (Run 25) 60 50 40 30 20 10 -10 60 Maximum Range (%) PVO4 PLV26 PLV31 PLV43 PR22 PR11 DAS LABEL PVO4 PV4 PV13 Range Uncertainty Estimate Comparision for Second Harmonic Amplitude Bound Group (Clock D Variation) Bound Group (Run 25, Time Variation) Bound Group (Clock D) Bound Group (Run 25) 50 40 30 20 10 PLV26 PLV31 PLV43 PR22 PR11 DAS LABEL PVO4 PV4 Figure D.24 Uncertainty Ranges for FFT Analysis 314 PV13 BIBLIOGRAPHY Venable, B.L., Delaney, R.A., Busby, J.A., Davis, R.L., Dorney, D.J., Dunn, M.G., Haldeman, C.W., and Abhari, R.S., Influence of Vane-Blade Spacing on Transonic Turbine Stage Aerodynamics, Part I: Time-Averaged Data and Analysis ASME, 1998(Paper No 98-GT-481) Dunn, M.G., Convective Heat Transfer and Aerodynamics in Axial Flow Turbines ASME J Turbomachinery, 2001 113: p 637-686 Bunker, R A Review of Turbine Blade Tip Heat Transfer in International Symposium on Heat Transfer in Gas Turbine Systems 2000 Izmir, Turkey Haldeman, C.W., M Dunn, J Lotsof, C MacArthur, and B Cohrs, Uncertainty Analysis of Turbine Aerodynamic Performance Measurements in Short-Duration Test Facilities 1991 Keogh, R.C., G.R Guenette, and T.P Sommer, Aerodynamic Performance Measurements of a Fully Scaled Turbine in a Short-Duration Facility 2000 Denton, J.D., Loss Mechanisms in Turbo machines ASME Journal of Turbomachinery, 1993(115): p 621-658 Huber, F.W., P.D Johnson, O.P Sharma, J.B Steinbach, and S.W Gaddis, Performance Improvement Through Indexing of Turbine Airfoils: Part 1Experimental Investigation ASME Journal of Turbomachinery, 1996 118: p 630-635 Jouini, D.B.M., D Little, B E, M Dunn, C Haldeman, and P.D Johnson, Experimental Investigation of the Aerodynamic Effects of clocking Vanes and Blade Rows in a 1/3 Scale Model Turbine 2003 315 Dunn, M.G., P.J Seymour, S.H Woodward, W.K George, and R.E Chop, Phase resolved Heat-flux Measurements on a Blade of a Full-Scale Rotating Turbine ASME Journal of Turbomachinery, 1989 111: p 8-19 10 Huber, F.W., P.D Johnson, O.P Sharma, J.B Steinbach, and S.W Gaddis, Performance Improvement Through Indexing of Turbine Airfoils: Part 2Numerical Simulation ASME Journal of Turbomachinery, 1996 118: p 636-642 11 Haldeman, C.W and M.G Dunn, High-Accuracy Turbine Performance Measurements in Short-Duration Facilities ASME J Turbomachinery, 1998 120 12 Dorney, D.J and K Gundy-Berlet, Hot-Streak Clocking Effects in a 1-1/2 Stage Turbine ASME, 1995(Paper No 95-GT-202) 13 Dorney, D.J and O.P Sharma, A Study of Turbine Performance Increases Through Airfoil Clocking AIAA, 1996(Paper No 96-2816) 14 Eulitz, F., K Engel, and H Gibing, Numerical Investigation of the Clocking Effects in a Multistage turbine 1996 15 Johnston, D.A and S Fleeter, Turbine Blade Unsteady Heat Transfer Change Due To Stator Indexing 1999 16 Arnone, A., M Marconi, R Puccini, C Shipman, and E Span, Numerical Investigation of Airfoil Clocking in a Three-Stage Low Pressure Turbine 2001 17 Reinmoller, U., B Stephan, S Schmidt, and R Nichols, Clocking Effects in a 1.5 Stage Axial Turbine- Steady and Unsteady Experimental Investigations Supported by Numerical Simulations 2001 18 Clark, J.P., G.M Stetson, S.S Magge, C.W Haldeman, and M.G Dunn, The effect of Airfoil Scaling on the Predicted Unsteady Pressure Field in a +1/2 Stage Transonic Turbine and Comparison with Experimental Results 2000 19 Haldeman, C.W., M Krumanaker, and M.G Dunn, Influence of Clocking and Vane/Blade Spacing on the Unsteady Surface Pressure Loading for a Modern Stage and One-half Transonic Turbine 2003 316 20 Krumanaker, M., Aerodynamics and Heat Transfer for a Modern Stage and OneHalf Turbine, in Aero-Astor Engineering 2002, Ohio State University: Columbus, OH p 137 21 Dunn, M.G., Muller, J.C., and Steel, R.C., Operating Point Verification for a Large Shock Tunnel Test Facility WRDC-TR-2027, 1989 May 22 Dunn, M.G., Heat-Flux Measurements for the Rotor of a Full-Stage Turbine: Part - Time-Averaged Results ASME J Turbomachinery, 1986 108: p 90-97 23 Dunn, M.G., Bennett, W.A., Delaney, R.A., and Rio, K.V., Investigation of Unsteady Flow Through a Transonic Turbine Stage: Data/Prediction Comparison for Time-averaged and Phase-Resolved Pressure Data ASME J Turbomachinery, 1992 114: p 91-99 24 Dunn, M.G and C.W Haldeman, Phase-Resolved Surface Pressure and HeatTransfer Measurements on the Blade of a Two-Stage Turbine ASME J Fluids Engineering, 1995 117: p 653-658 25 Bergholz, R.F., Dunn, M.G., and Steeper, G.D., Rotor/Stator Heat Transfer Measurements and CFD Predictions for Short-Duration Turbine Rig Tests ASME, 2000(Paper No 2000-GT-208) 26 Belington, P.R and D.K Robinson, Data Reduction and Error analysis for 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