Modeling of Rotorcraft Noise in Maneuvering Flight

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Kenneth S. Brentner, Dept. of Aerospace Engineering RCOE Review, May 3, 2005 1

Modeling of Rotorcraft Noise in Modeling of Rotorcraft Noise in Maneuvering FlightManeuvering Flight

PI: PI: Kenneth S. Brentner (814)865-6433, Kenneth S. Brentner (814)865-6433, [email protected]@psu.edu

Graduate Students: Graduate Students:

Hsuan-Nien Chen (started Dec 2002 – PhD)Hsuan-Nien Chen (started Dec 2002 – PhD)

2005 RCOE Program Review2005 RCOE Program Review

May 3, 2005May 3, 2005

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Kenneth S. Brentner, Dept. of Aerospace Engineering

Project: PS 4.1

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Overview of Work

Project Overview (Ken Brentner) Acoustic Analysis (Sam Chen) Summary (Ken Brentner)

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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

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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

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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)

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Overview of Work

Project Overview Acoustic Analysis Summary

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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

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Code Validation – BVI Condition

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

Mic 7 Mic 9

Predicted levels lowered by 20 Pa for clarity

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Transient Maneuver Noise Identified

OA

SP

L-T

hic

kness

(dB

)

Roto

rN

orm

alF

orc

eR

atio

50

60

70

80

0.7

0.9

1.1

1.3

Time (sec)

OA

SP

L-Loadin

g(d

B)

Roto

rN

orm

alF

orc

eR

atio

0 20 40 60 8060

75

90

0.7

0.9

1.1

1.3

Rotor Normal Force Ratio*

OASPL (dB)

Observer Location : (800, - 400, 0) m

* Rotor Normal Force / Gross Weight

Fixed Observer Location

Observer Location: 30R form rotor hub, 45º below rotor and 120º azimuth angle

Moving Observer Location

65

70

75

80

85Thickness Noise

Time (sec)

0 20 40 60 8080

85

90

95Total Noise

65

70

75

80

85Thickness Noise

Time (sec)

0 20 40 60 8080

85

90

95Total Noise

Time (sec)0 20 40 60 80

75

80

85

90

95

OA

SP

L(d

B)

Loading Noise

65

70

75

80

85Thickness Noise

Time (sec)

0 20 40 60 8080

85

90

95Total Noise

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Turn-Entry Maneuvering Flight

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. Left Turn

Right Turn

0.5 sec duration

1 sec duration

5 sec duration

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OASPL “spike” amplitude is a strong function of transient duration

OA

SP

L-

Th

ickn

ess

(dB

,re

f2

0P

a)

70

75

80

85

Retreating Side

Time (sec)

OA

SP

L-

Lo

ad

ing

(dB

,re

f2

0P

a)

0 2 4 6 8 1080

85

90

95

0.5 sec duration

1 sec duration

5 sec duration

Observer locations: 45º below rotor tip path plane 30 R from rotor hub Upstream ±60º from centerline

OA

SP

L-

Th

ickn

ess

(dB

,re

f2

0P

a)

65

70

75

80

Advancing Side

Time (sec)

OA

SP

L-

Lo

ad

ing

(dB

,re

f2

0P

a)

0 2 4 6 8 1075

80

85

90

95

Acoustic Signature with Different Roll Rates

Thickness noise

Loading noise

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Disk Loading in Right Turn-Entry Maneuver

0.5s duration 1.0s duration 5.0s duration

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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

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BVISPL Prediction in Right Turn-Entry Maneuver

1.0s duration0.5s duration 5.0s duration

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Disk Loading in Left Turn-Entry Maneuver


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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.

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BVISPL Prediction in Left Turn-Entry Maneuver


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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.

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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

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Disk Loading in the LRL Roll Reversal Maneuver

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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)

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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

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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

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Milestones 2001 2002 2004 2005CODE 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)

2003

Schedule and Milestones

CompleteIn Progress / Near TermLong TermMoved from last year’s schedule

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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

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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

Leveraging or Attracting Other Resources or ProgramsDURIP equipment funding for RCOE

124 processor RCOE parallel clusterRotorcraft 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” ProjectPhase I SBIR with Continuum Dynamics for real-time rotor noise prediction (NASA LaRC)

Other Impact

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Any Questions … ?

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Auxiliary Presentation Material

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Validation of GENHEL/PSU-WOPWOP: Comparison with Wind Tunnel Data

Normalized TimeA

cou

stic

Pre

ssu

re(P

a)

0 0.25 0.5 0.75 1-40

-20

0

20

Microphone 1, MAT=0.796

Normalized Time

Aco

ust

icP

ress

ure

(Pa

)

0 0.25 0.5 0.75 1-40

-20

0

20


Normalized Time

Aco

ust

icP

ress

ure

(Pa

)

0 0.25 0.5 0.75 1-20

-10

0

10

20


Normalized Time

Aco

ust

icP

ress

ure

(Pa

)

0 0.25 0.5 0.75 1-20

-10

0

10

20


Side View

Microphone 7

30 Deg.

1. 5 D

Microphone 1

Top View

1.5 D

1.5 D

In-plane Microphones

measured (Visintainer et al., 1993)

Predicted (GENHEL/PSU-WOPWOP)

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80-Second Maneuver Flight Simulation

Helicopter gross weight: 74800N 4-bladed articulated main rotor and tail

rotor Main rotor radius: 8.18 m

Maneuver Start Time End Time

Level t = 0 sec t = 1 sec

Climb t = 1 sec t = 14 sec

Acceleration t = 1 sec t = 18 sec


Coordinated Turn t = 22 sec t = 56 sec


La

tera

lCyc

lic(%

)

20

55

90

Lo

ng

.Cyc

lic(%

)

30

45

60

Pitc

hA

ng

le(d

eg

)

-15

-5

5

Ro

llA

ng

le(d

eg

)

-5

15

35

Ya

wA

ng

le(d

eg

)

-10

100

210

Co

llect

ive

(%)

30

50

70

Time (sec)

Ad

v.R

atio

0 20 40 60 800

0.1

0.2

0.3

Time (sec)

Pe

da

l(%

)

0 20 40 60 8040

55

70

Pilot controlsAircraft response

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Arrested Descent Wake (From UMD, Ananthan & Leishman)

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WOPWOP - Thickness

time (s)

Aco

ust

icp

ress

ure

(Pa

)

0.0255 0.026 0.0265 0.027-140

-120

-100

-80

-60

-40

-20

0

20

40PSU-WOPWOP - Isom thickness

PSU-WOPWOP - Thickness

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)

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Main rotor blade description

Lower surface

Upper surface

Tip

Permeable surface formulation Coupling with CFD

for high-speed-impulsive noise

Object oriented approach Modularity and

flexibility for complex rotor configuration

PSU-WOPWOP Features

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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.

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Acoustic Pressure Prediction

Free Vortex-Wake Model

– ● – Pitt-Peters Inflow ModelObserver location Ψ=135º, 22º below the helicopter and 7R away.

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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.

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X (m)

Z(m

)

De

cele

ratio

n(m

/s2)

0 20 40 60 80-3

-2.5

-2

-1.5

-1

-0.5

0

-4

-2

0

2

4

6

8heightdeceleration

time (s)

colle

ctiv

ep

itch

(de

g)

0 0.5 1 1.5 2-2

0

2

4

6

8

Arrested Descent

• Case Description– Initial condition: 3 degree steady

descent– Total time: 2 sec – Flight speed: 40 m/s

0 100 200 300-2

0

2

4

6

8

10RollPitchYaw

AircraftAttitude,

deg

X, ftDescent arrested by collective pulse

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time (s)

Aco

ust

icp

ress

ure

(Pa

)

0 0.5 1 1.5 2

-2

0

2

4

6

Sound Pressure Level Computation

Discrete Fourier Transform

Compute sound pressure level

Move slice of

data

• Frequency analysis issues– Non-periodic signal– Noise widely fluctuating in amplitude and frequency

Extract slice of data

Apply Hanning Window

Documents

Modeling of Rotorcraft Noise in Maneuvering Flight