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Modeling of Rotorcraft Noise in Maneuvering Flight

Project: PS 4.1. Modeling of Rotorcraft Noise in Maneuvering Flight. PI: Kenneth S. Brentner (814)865-6433, ksbrentner@psu.edu Graduate Students: Hsuan-Nien Chen (started Dec 2002 – PhD) 2005 RCOE Program Review May 3, 2005. Kenneth S. Brentner, Dept. of Aerospace Engineering.

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Modeling of Rotorcraft Noise in Maneuvering Flight

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  1. Project: PS 4.1 Modeling of Rotorcraft Noise in Maneuvering Flight PI: Kenneth S. Brentner (814)865-6433, ksbrentner@psu.edu Graduate Students: Hsuan-Nien Chen (started Dec 2002 – PhD) 2005 RCOE Program Review May 3, 2005 Kenneth S. Brentner, Dept. of Aerospace Engineering

  2. Overview of Work • Project Overview (Ken Brentner) • Acoustic Analysis (Sam Chen) • Summary (Ken Brentner)

  3. Background/Problem Statement: • Current rotor aerodynamics and noise prediction primarily for steady flight conditions • Noise of maneuvering rotorcraft can be significantly higher than for a similar steady flight condition • A tool is needed that is able to predict noise generated by rotorcraft in maneuver — including the transient aircraft motion and blade loading. Technical Barriers or Physical Mechanisms to Solve: • Acoustics • Very complex source motion and time dependence • Complicated time-dependent noise directivity • Transient blade loading and motion are an “additional” noise source • Aeromechanics • Nonperiodic blade loading and motion is unique to each blade • Rotor-wake interaction extremely challenging problem

  4. Task Objectives: • Develop a noise prediction capability for rotors in steady AND transient maneuvers (including multiple rotors) • Gain better understanding of noise directivity in maneuvering flight—especially the components (thickness, loading, transients, etc.) of maneuver noise • Quantify the importance of transients • Assess the requirements for wake fidelity and airloads accuracy in the context of maneuver noise-prediction • Improve maneuver noise prediction through the utilization and/or development of maneuvering wake  

  5. Approach: • Develop acoustics code with full rotor-blade motion and complete aircraft motion • Utilize best available comprehensive analysis tools for initial developmental work, accepting known weaknesses • Incorporate advanced maneuver airloads/wake modeling as it becomes available Emphasis is on approaching the problem from the acoustics point of view, then working to provide required input data Expected Research Results or Products: • A new rotorcraft noise prediction code—much more useful and general purpose than the current generation of codes • Understanding of the extra noise generated in maneuvers • Guidance for the development of maneuver aerodynamics and flight dynamics (acoustic requirements)

  6. Overview of Work • Project Overview • Acoustic Analysis • Summary

  7. Maneuver Noise Analyzed • Several maneuvers were analyzed: • Arrested descent • Left turn entry (with three different roll rates) • Right turn entry (with three different roll rates) • Left-right-left roll reversal maneuver • Right-left-right roll reversal maneuver • Quick stop maneuver • Level acceleration maneuver • Climb maneuver • Focus of this presentation on maneuvers with roll motion

  8. Code Validation – BVI Condition Mic 7 Mic 9 Predicted levels lowered by 20 Pa for clarity • Compared predictions with DNW acoustic measurement • Contemporary design 4-bladed rotor for utility helicopter • μ = 0.2 and CT=0.0056 and zero shaft tilt angle (wind tunnel conditions not fully reported) • Two mic positions, Mic 9: Ψ=150º and 25º below; Mic 7: Ψ=150º in-plane. • Aerodynamic calculation was performed by RCAS free vortex-wake model

  9. Transient Maneuver Noise Identified Rotor Normal Force Ratio* OASPL (dB) Moving Observer Location Fixed Observer Location Observer Location: 30R form rotor hub, 45º below rotor and 120º azimuth angle Observer Location : (800, - 400, 0) m * Rotor Normal Force / Gross Weight

  10. Turn-Entry Maneuvering Flight 0.5 sec duration 1 sec duration 5 sec duration • Both right and left turn-entry maneuvering flights. • Three different turn transient duration settings: 0.5, 1 and 5 seconds. • Focus on the helicopter roll maneuver. Right Turn Left Turn

  11. Acoustic Signature with Different Roll Rates 0.5 sec duration 1 sec duration 5 sec duration Thickness noise Loading noise Observer locations: • 45º below rotor tip path plane • 30 R from rotor hub • Upstream ±60º from centerline • OASPL “spike” amplitude is a strong function of transient duration

  12. Disk Loading in Right Turn-Entry Maneuver 0.5s duration 1.0s duration 5.0s duration

  13. Rotor Wake Geometry for Right Turn • Wake bundling effect starts from Rev 27 • Interaction of wake bundle and blade result in a “Super BVI” • occurs in both Revs 28 and 29 • Helicopter roll overshoot during maneuver is partially responsible

  14. BVISPL Prediction in Right Turn-Entry Maneuver 0.5s duration 1.0s duration 5.0s duration

  15. Disk Loading in Left Turn-Entry Maneuver 0.5s duration 1.0s duration 5.0s duration

  16. Rotor Wake Geometry for Left Turn • The wake bundling effect observed in the retreating side. • The wake bundling effect also occurred in the advancing side but less interaction with rotor blades. • The strength of the “super BVI” is less than what we observe in the right turn.

  17. BVISPL Prediction in Left Turn-Entry Maneuver 0.5s duration 1.0s duration 5.0s duration

  18. Summary for Turn Maneuvers • Both right and left turns experienced vortex bundling in the transient maneuver condition. Right turn maneuver has stronger bundling and interaction in the aggressive turn. • The overshoot in roll attitude results in strong BVI during the right turn maneuver. It is like a mini roll-reversal maneuver. • A more aggressive maneuver triggers a stronger wake bundling condition. As this bundled tip vortices encounter the rotor during the maneuver has the potential to generate very high level of impulsive loading and BVI noise. • Right turn maneuver generated higher noise level than the left turn.

  19. A More Complex Example:LRL Roll Reversal Maneuver • The LRL roll reversal maneuver consists of three components within 6 sec: • A -50º left roll over approximately 2 sec. • A 100º right roll over approximately 2 sec. • A second left to zero roll angle over approximately 2 sec. • The advance ratio for maneuver was relatively low, μ=0.093

  20. Disk Loading in the LRL Roll Reversal Maneuver

  21. LRL Roll Reversal Maneuver • The high level BVISPL concentrated in the forward area at beginning of the right roll (t =7.24 s) • The very large BVISPL levels ahead of the rotor at t = 8.25 s and t = 8.65 s are primarily caused by BVI loading during Revs 36 and 37 • As helicopter returns to level flight, both advancing and retreating side BVI are present (t = 10.66 s)

  22. Summary for Roll Reversal Maneuver • In these maneuvers, BVI noise dominates • BVI noise during a transient maneuver is different than in steady flight • Vortex bundling • Dynamic state of vortex system (not steady after start of maneuver) • The formation of the vortex bundle and its subsequent interaction with the rotor blades was strongly influenced by the pilot overshoots in the turn-entry maneuver • Due to the short duration of maneuver duration, the helicopter is constantly in the transient maneuver state and the noise generated in this condition can be considered as transient maneuver noise

  23. Accomplishments • 2004 Accomplishments • Limited noise prediction system validation against wind tunnel measurement for both thickness and loading noise • Systematically unraveling the source of maneuver noise • Transient maneuver noise for climb, acceleration maneuver flights. • Compute maneuver noise with BVI using UMD maneuver wake • Rotor wake interaction analyzed for elemental maneuvers • Roll maneuver, quick stop, roll reversal maneuvers • 2005 Planned Accomplishments • Investigate issues of signal processing for aperiodic conditions • RCAS maneuver model with free vortex-wake model

  24. Schedule and Milestones Complete In Progress / Near Term Long Term Moved from last year’s schedule 2001 2002 2005 2003 2004 Milestones • CODE DEVELOPMENT: • Initial aircraft motions and complete rotor motions • Validate with WOPWOP • Self-scheduling parallel implementation • Coordinate transformation enhancements • Acoustic analysis of non-periodic time history data • “Flight-test” modeling (GENHEL coupling) • Efficiency enhancements (real-time?) • ANALYSIS • Determine spatial regions where noise depends strongly on wake. • Simple maneuvers analysis • Simple flight path and attitude determination • Validation (with data – flight or wind tunnel) • Advanced wake modeling (RCAS or UMD maneuver wake)

  25. Technology Transfer Activities • Papers: • AHS Specialists’ Meeting, San Francisco, Jan 2004 • AIAA Aerospace Science Meeting and Exhibit, Jan 2004 • AIAA/CEAS Aeroacoustics Conference, May 2005 • AHS Annual Forum, Grapevine, TX, June 2005 • Other Interactions: • Collaboration with Gordon Leishman, University of Maryland • Work with Professor Horn: GENHEL coupling and work toward acoustic prediction capability in new flight simulator

  26. Recommendations at the last review (2004) It is recommended to pick concrete physical problems and a firm plan is needed to solve physics or physical mechanisms, such as effects of roll or Lock number on noise. And also validation of analysis is needed for steady flight first, before deeply involved with maneuvering flight conditions. Actions Taken (2004) Some validation for steady flight performed Focus on physical mechanisms of associated with aircraft roll, including BVI noise in maneuver Gaining understanding of role of BVI and nonimpulsive noise in maneuver Other Impact • Leveraging or Attracting Other Resources or Programs • DURIP equipment funding for RCOE • 124 processor RCOE parallel cluster • Rotorcraft flight simulator with acoustic simulation capability • NASA LaRC contract for high-speed maneuver noise prediction modifications to PSU-WOPWOP (Burley/Boyd) • Teamed with Georgia Tech for DARPA “Helicopter Quieting” Project • Phase I SBIR with Continuum Dynamics for real-time rotor noise prediction (NASA LaRC)

  27. Any Questions … ?

  28. Auxiliary Presentation Material

  29. Validation of GENHEL/PSU-WOPWOP: Comparison with Wind Tunnel Data measured (Visintainer et al., 1993) Predicted (GENHEL/PSU-WOPWOP) Microphone 7 Top View 1.5 D 30 Deg. 1.5 D Microphone 1 Microphone 1, MAT=0.796 Microphone 1, MAT=0.690 Side View Microphone 7, MAT=0.796 Microphone 7, MAT=0.690 1. 5 D In-plane Microphones

  30. 80-Second Maneuver Flight Simulation Aircraft response Pilot controls • Helicopter gross weight: 74800N • 4-bladed articulated main rotor and tail rotor • Main rotor radius: 8.18 m

  31. Arrested Descent Wake (From UMD, Ananthan & Leishman)

  32. PSU-WOPWOP ValidationComparison with WOPWOP  Thickness and loading noise predictions validated • Operating conditions: • UH-1H model scale untwisted rotor • MH=0.88 • Observer at 3.09 R in plane • Rotation only (hover)

  33. PSU-WOPWOP Features Upper surface Lower surface Tip Main rotor blade description • Permeable surface formulation • Coupling with CFD for high-speed-impulsive noise • Object oriented approach • Modularity and flexibility for complex rotor configuration

  34. Arrested Descent Maneuver • Starts from 6º flight path angle and μ=0.186. • A half-doublet collective pitch input applied between t = 5 and t = 6 s. • At the end of the maneuver, the helicopter is pitched up by over 20º.

  35. Acoustic Pressure Prediction  Free Vortex-Wake Model – ● –Pitt-Peters Inflow Model Observer location Ψ=135º, 22º below the helicopter and 7R away.

  36. Summary For Arrested Descent • This arrested descent maneuver is a simple maneuver by applying collective pitch input. • In the steady descent condition, BVI is not dominant source of noise due to steep flight path angle. • In this maneuver, the primary effect of the maneuver is that the rotor wake goes through the rotor disk resulting in several BVIs in the rear of the disk that are nearly parallel to the rotor blade during the interactions. • Less BVIs were observed after the maneuver due to helicopter attitude.

  37. Arrested Descent height deceleration • Case Description • Initial condition: 3 degree steady descent • Total time: 2 sec • Flight speed: 40 m/s Descent arrested by collective pulse

  38. Sound Pressure Level Computation • Frequency analysis issues • Non-periodic signal • Noise widely fluctuating in amplitude and frequency Extract slice of data Apply Hanning Window Move slice of data Discrete Fourier Transform Compute sound pressure level

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