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Alexander A. Nikolsky Honorary Lectureship

Explore the evolution of dynamic wake models in rotorcraft aerodynamics, from foundational concepts to contemporary applications. Learn how these intuitive models, based on engineering physics, have proven crucial in explaining complex aerodynamic phenomena. Discover the significance of hierarchical model development and the continued relevance of simple models in the competitive realm of rotorcraft analysis. Delve into the historical insights and innovative contributions that have shaped the dynamic wake modeling landscape.

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Alexander A. Nikolsky Honorary Lectureship

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  1. Alexander A. Nikolsky Honorary Lectureship Annual Forum, AHS International Montreal, Canada April 29, 2008 Alexander A. Nikolsky 1903 –1963

  2. How Dynamic Inflow Survives in the Competitive World of Rotorcraft Aerodynamics David A. Peters McDonnell Douglas Professor of Engineering Washington University in St. Louis 2008 Alexander Nikolsky Lecture

  3. AcknowledgementsKurt Hohenemser Alexander A. Nikolsky 1903 –1963

  4. Acknowledgements Bob Ormiston [2015 Nikolsky]: “Dave, some day you will bring me a curve with a glitch, and I will ask you what it is. If you say, ‘I don’t know, that’s the way it came out of the computer,’ you’re fired.” Dewey Hodges [2014 Nikolsky]: “Structures and dynamics are the exact sciences, aerodynamics and thermodynamics are the inexact sciences.” Rose Brower: Design and production Debbie Peters: “The Love of my Life”

  5. Ecological Niches of Aerodynamics CFD 2008 Alexander Nikolsky Lecture Free Wake Prescribed Wake Dynamic Wake

  6. How Dynamic Wake Models Have Survived Is there still room for simple models in the competitive world of rotorcraft analysis? • These models have been developed in response to pressing needs to explain physical phenomena found in experimental data. • These models are physically intuitive. • These models have been consistently based on engineering physics rather than on any heuristic mathematical fit of data. • These models bring in just enough physics to explain the important behavior. • These models are hierarchical so that each improvement includes all earlier versions and so that some version of the model can run in real time on any given computing platform. 2008 Alexander Nikolsky Lecture

  7. What is a dynamic wake model? • It is a model that—given the time history of blade loading—predicts the flow being pumped passed the rotor blades as a function of time, radius, and azimuth. • It is a model that represents this evolution of inflow in first-order form in terms of a finite number of state variables. [M]{dvn/dt} + [C]{vn} = {Fm} • It is a model that allows the number of states to vary with user needs. 2008 Alexander Nikolsky Lecture

  8. Foundation 1950 – 1969 2008 Alexander Nikolsky Lecture

  9. Seminal Conjecture Ken (1950) found that the measured roll damping of helicopters was roughly twice that predicted by the mathematical theories of his day. 2008 Alexander Nikolsky Lecture Ken Amer 1988 Nikolsky

  10. Amer Conjecture “The . . . discrepancy between the data and the theory appears to be due primarily to the changes in induced velocity which occur during rolling because of changes in the distribution of thrust around the rotor disk. These changes in induced velocity are not taken into account in the theoretical calculations because of the excessive labor that would be involved.” Ken Amer NACA TN 2136 October 1950, p.11. 2008 Alexander Nikolsky Lecture Figure 1: Source of damping in roll for a helicopter undergoing a rolling velocity.

  11. G. J. Sissingh, 1952 2008 Alexander Nikolsky Lecture

  12. G. J. Sissingh, 1952 Sissingh, in England, applied momentum theory to Ken Amer’s insight, but he applied it in a new way in terms of moments––in addition to thrust. Sissingh was able to obtain formulas for the gradient in inflow for the cases of hover and forward flight. 2008 Alexander Nikolsky Lecture

  13. Classical Approach Bob Loewy (1955, 1957) realized that rotor inflow, unlike fixed-wing inflow, is dominated by the returning layers of vorticity below the rotor plane. Robert G. Loewy 1984 Nikolsky 2008 Alexander Nikolsky Lecture

  14. Wake Layers 2008 Alexander Nikolsky Lecture

  15. Loewy Function 2008 Alexander Nikolsky Lecture

  16. Lessons Learned • It is better not to use any Wake Model at all than to use Theodorsen Theory for a rotating wing. • The buckets of the real part of the Loewy Function (including  = 0) are the identical lift deficiency thatwas found by Amer and Sissingh. • The imaginary part of the Loewy function shows that there is a time lag in the development of that lift deficiency. 2008 Alexander Nikolsky Lecture

  17. Classical Approach Rene Miller of MIT (1964) added a three-dimensional correction. Rene Miller 1983 Nikolsky 2008 Alexander Nikolsky Lecture

  18. Development 1970 – 1989 2008 Alexander Nikolsky Lecture

  19. H.C. “Pat” Curtiss, Jr.2000 Nikolsky Pat Curtiss and Norm Shupe (1971) show that the Sissingh Lift Deficiency could be formally cast as an equivalent Lock number with the same lift deficiency as that of Loewy  = acR4/Iy a*/a = [1 + a/8V]-1 Curtiss also realized that it was sometimes necessary to put a time delay into the dynamic inflow 2008 Alexander Nikolsky Lecture

  20. REXOR Had Dynamic Inflow Lockheed’s REXOR Program also had Sissingh’s inflow effect with a time constant 2008 Alexander Nikolsky Lecture

  21. Appendix on Dynamic Wake

  22. Robert A. Ormiston Ormiston [2015 Nikolsky] (1970) was analyzing data from the NASA 40x80 and 7x10 wind tunnels. He discovered large discrepancies and wondered if they might be due to elastic blade bending, reversed flow, higher harmonics, tip loss, or root cut-out. 2008 Alexander Nikolsky Lecture

  23. New Hire Dave Peters had just arrived at Ames and was given the job to create a code that would solve the blade flapping problem including all of the aforementioned effects. The results still showed large discrepancies with data; and Bob Ormiston postulated the effect reported by Amer, Sissingh, and Curtiss. 2008 Alexander Nikolsky Lecture David Peters 2008 Nikolsky

  24. First Correlations The calculations showed that the inflow effect corrected steady results in hover but not forward flight and not unsteady results in either case. 2008 Alexander Nikolsky Lecture

  25. Apparent Mass Bob Ormiston postulated an apparent mass and inertia of the wake as posed by Carpenter and Fridovitch (1953) Simple potential flow theory gave the numbers. 2008 Alexander Nikolsky Lecture

  26. Correlation was excellent in hover but lousy in forward flight 2008 Alexander Nikolsky Lecture

  27. Correlation was excellent in hover but lousy in forward flight 2008 Alexander Nikolsky Lecture

  28. Kurt Hohenemser Independently, Kurt Hohenemser was trying to correlate some wind tunnel data taken by him and Sam Crews at Washington University. Hohenemser postulated a lift deficiency and phase lag of the inflow to explain the data and Dev Banerjee did parameter identification to find the gains and time constants. 2008 Alexander Nikolsky Lecture

  29. Parameter Identification The identified values were within 2% of the values used by Ormiston and Peters from the Sissingh theory and potential flow for apparent mass. 2008 Alexander Nikolsky Lecture

  30. Anton J. “Jack” Landgrebe In the meantime, efforts by Peters and Ormiston to find a forward flight version of dynamic inflow were fruitless. However, Vortex Lattice Models were coming into their own as computational speed and memory increased. 2008 Alexander Nikolsky Lecture

  31. Free-Vortex Wake • Trailing Tip Vortex • Trailing Vortex Filaments • Vortex Lattice • Vortex Sheet 2008 Alexander Nikolsky Lecture

  32. Dale Pitt Dave Peters returned to Washington University in 1975 and Dale Pitt came as his first doctoral student in 1977. Pitt had a better idea and discovered Prandtl, Kinner and Mangler/Squire. 2008 Alexander Nikolsky Lecture

  33. Circular Wing Theory Kinner Paper 2008 Alexander Nikolsky Lecture Wieslaw Z. “Steppy” Stepniewski 1981 Inaugural Nikolsky Recipient

  34. Pitt - Peters Model . 2008 Alexander Nikolsky Lecture

  35. Connections By the way, Pitt ran Landgrebe, too, with the same results. 2008 Alexander Nikolsky Lecture

  36. Gopal Gaonkar Gaonkar helped with the correlations. 2008 Alexander Nikolsky Lecture IT WAS LIKE MAGIC!

  37. Bousman and Johnson William G. Bousman took some ground resonance data. [2011 Nikolsky] Wayne Johnson tried to correlate it with his new comprehensive code, CAMRAD. [2010 Nikolsky] 2008 Alexander Nikolsky Lecture

  38. Inflow Mode Wayne proved that there was an inflow mode. Soon every stability and handling qualities code had some form of dynamic inflow in it. 2008 Alexander Nikolsky Lecture

  39. Peretz P. Friedmann As other aeroelasticians began to understand the importance of aero- dynamics as states, Friedmann [2013 Nikolsky] began to compare Loewy Theory and dynamic inflow theory and discovered what appeared to be a discrepancy. 2008 Alexander Nikolsky Lecture

  40. Singularity The discrepancy was simply that Loewy theory has a singularity for the collective mode at zero frequency. But looking at that got Dave Peters thinking. 2008 Alexander Nikolsky Lecture

  41. Plea to NASA - Army In January 1985, Dave Peters pitched an idea to Bob Ormiston and Bill Warmbrodt that we could generalize the wake. 2008 Alexander Nikolsky Lecture

  42. Dynamic Flow Diagram 2008 Alexander Nikolsky Lecture

  43. Time Constants at Harmonic Numbers Extension of Pitt Model: T = 0.75 / (1.5 + m) Loewy function at r = ¾: T = 0.75/m 2008 Alexander Nikolsky Lecture

  44. Georgia Tech In 1985, Dave Peters joined Georgia Tech 2008 Alexander Nikolsky Lecture Dan Schrage 1999 Nikolsky Robin Gray 1991 Nikolsky

  45. Cheng Jian He Cheng Jian He came as Dave Peter’s first Georgia Tech doctoral student (déjà vu all over again). He came up with closed-form matrices for all harmonics and distributions. 2008 Alexander Nikolsky Lecture

  46. Langley Wind Tunnel Data This was just in time for the Langley data. Why did dynamic wake out perform vortex lattice? 2008 Alexander Nikolsky Lecture

  47. Hover Test Stand Data This was also just in time to correlate with hover test stand data taken by Komerath. 2008 Alexander Nikolsky Lecture Ay Su

  48. Theory and Experiment When the theory did not agree with the experiment, it turned out that Narayanan M. Komerath discovered a phasing error in the data extraction. (No one believes the theory except the one who derived it, and everyone believes the data except the one who took it.) 2008 Alexander Nikolsky Lecture

  49. Refinement 1990 – 2008 Alexander Nikolsky Lecture

  50. Back to Washington University In 1991 Dave Peters returned to Washington University. Cheng Jian He was now at Advanced Rotorcraft Technology (ART), and dynamic wake models were now being put into real-time flight simulations, including FLIGHTLAB. 2008 Alexander Nikolsky Lecture

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