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A Thesis Proposal Presented to The Faculty of the Division of Graduate Studies By Gang Wang Advisor: Dr. T. C. Lieuwen. Prediction of Rotorcraft Noise with A Low-Dispersion Finite Volume Scheme. Background Approach Results Conclusions Proposed Work. OUTLINE.
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A Thesis Proposal Presented to The Faculty of the Division of Graduate Studies By Gang Wang Advisor: Dr. T. C. Lieuwen Prediction of Rotorcraft Noise with A Low-Dispersion Finite Volume Scheme
Background Approach Results Conclusions Proposed Work OUTLINE
Helicopter has a wide range of military and civil applications. However, the high noise level associated with it greatly restricts its further applications. BACKGROUND
Three categories of rotor noise Rotational noise Broadband noise Impulsive noise High Speed Impulsive (HSI) noise Blade Vortex Interaction (BVI) noise BACKGROUND
BACKGROUND High Speed Impulsive noise
BACKGROUND Blade Vortex Interaction noise
Many efforts have been spent on quantifying and minimizing rotorcraft noise. Three noise prediction techniques: High resolution aerodynamics in the near field and acoustic analogy for radiation in far field High resolution aerodynamics in the near field and Kirchhoff’s formula for radiation in far field Fully computational aerodynamics and acoustics BACKGROUND
BACKGROUND Far Field Observer Acoustic calculation Region Blade CFD calculation Region
Much progress has been made during the past two decades in understanding and predicting rotorcraft noise characteristics with the aid of Computational Fluid Dynamics. However, dispersion and dissipation errors accompanied with conventional CFD methods alter the observed noise characteristics even a short distance away from the rotor. BACKGROUND
Significant computing resources are needed to reduce these errors. This precludes the prediction methodology from use in engineering design and development. Dispersion and dissipation phenomena can be simply shown by tracking rectilinear propagation of a Gaussian sound pulse: BACKGROUND
BACKGROUND Gaussian Pulse Distribution
BACKGROUND T=0 T=50 Magnitude drops as wave propagates… Dissipation T=100 Dissipation Phenomenon
BACKGROUND T=50 T=100 T=0 Dispersion Errors- some waves travel slower than the rest. Dispersion Phenomenon
Develop an improved algorithm with low dispersion and dissipation errors. The schemes should be simple enough so that they can find immediate use in CFD codes which are widely used in industry. It should not sacrifice aerodynamic resolution for acoustic resolution, and vice versa. OBJECTIVES
The integral form of Navier-Stokes equations may be written as: The flux across the cell boundary is split into two parts and : APPROACH
Data is stored at cell centers Information is needed at cell faces. APPROACH i+1/2,j,k L R i-1, j, k i, j, k i+1, j, k
Let us approximate qi+1/2 in the uniform transformed plane with three points: i+1/2 i+1 i-1 i APPROACH
Using classical Taylor series method, we can obtain three expansion equations of qi+1, qi, and qi-1 about i+1/2, for example: With these three equations, we can determine coefficients ai+1, ai, and ai-1 (Traditional Method). APPROACH
In our approach, we impose a further restriction to match the Fourier transformation (in space) of approximation for qi+1/2with its exact transformation. The Fourier transformation of approximate expression for qi+1/2 is: APPROACH F.T.
The following error expression should be minimized: with respect to coefficients . This leads to an over-determined system. Solved by Least Square method. APPROACH
Standard 3rd Order Monotone Upstream-centered Scheme for the Conservative Law (MUSCL Scheme): Present Scheme: APPROACH
High-Speed Impulsive noise modeling Preliminary studies of Blade-Vortex Interaction noise Tip vortex system prediction RESULTS
1/7 scale model of untwisted rectangular UH-1H blades in hover condition NACA0012 airfoil Non-lifting case Shock Noise Test Parameters
Microphone Shock wave R Blade r/R=1.78 r/R=1.111 Shock Noise Measurement Locations and Method
Variation of Acoustic Pressure p´ with time for a Non-lifting Rotor, MTip= 0.88, r/R=1.136, Grid size 1335535
Variation of Acoustic Pressure p´ with time for a Non-lifting Rotor, MTip= 0.88, r/R=3.09, Grid size 1335535
Variation of Acoustic Pressure p´ with time for a Non-lifting Rotor, MTip = 0.9, r/R=1.111, Grid size 1335535
Variation of Acoustic Pressure p´ with time for a Non-lifting Rotor, MTip = 0.9,r/R=3.09, Grid size 1335535
Variation of Acoustic Pressure p´ with time for a Non-lifting Rotor, MTip= 0.95, r/R=1.053, Grid size 1335535
Variation of Acoustic Pressure p´ with time for a Non-lifting Rotor, MTip= 0.95,r/R=3.09, Grid size 1335535
BLADE-VORTEX PROXIMITY Zv Y X VORTEX GENERATOR NEAR FIELD MICROPHONES Z +CCW VORTEX ROTATION V +v Parallel BVI Study Schematic of experimental set-up in wind tunnel test section
Untwisted, rectangular blade NACA 0012 airfoil Mtip=0.71, Advance ratio=0.2 Vortex 0.25 chord below blade Non-lifting case Parallel BVI Test Parameters
Parallel BVI Study(169 45 57) Near-field acoustic pressure for microphone 7
1/7 scale model of Operational Load Survey (OLS) blades Rectangular blades with 8.2 of twist from root to tip Mtip=0.664, Advance ratio=0.164 Grid size 110 45 40 AH-1 Forward Flight Test Parameters
AH-1 Forward Flight Self-induced wake Descending direction Interaction of tip vortices with rotor disk in descending flight
=90 Advancing Side Inlet Flow =0 =180 Tip Vortex Retreating Side AH-1 Forward Flight Schematic of flow field
AH-1 Forward Flight Blade Surface Pressure Coefficient Distribution, r/R=0.955, =0
AH-1 Forward Flight Blade Surface Pressure Coefficient Distribution, r/R=0.955, =90
AH-1 Forward Flight Blade Surface Pressure Coefficient Distribution, r/R=0.955, =180
How well does the Low Dispersion Scheme model tip vortices? Schematic of hover rotor wake structure
Untwisted rectangular NACA0012 blades Hovering condition MTip=0.44 Collective Pitch c=8 Caradonna & Tung Rotor Test Parameters
TURNS-MUSCL TURNS-LDFV Vortex I Vortex I Vortex II Vorticity Magnitude Contour Caradonna & Tung RotorMTip=0.44
Caradonna & Tung RotorMTip=0.44, r/R=0.80, Grid size 79 45 31 Blade Surface Pressure Distribution
A Low-Dispersion Finite Volume scheme has been developed and implemented into TURNS, a finite volume CFD code. Encouraging agreement between the predicted results and experiment data has been obtained for shock noise on coarse grid. CONCLUSIONS
Basic characteristics of BVI noise are predicted with satisfactory accuracy. TURNS-LDFV can capture main features of the tip vortex system with good resolution on coarse grids. CONCLUSIONS
Determine the minimum number of grid points needed to predict shock noise. Identify the contributions of different noise sources. PROPOSED WORK
Repeat forward flight BVI calculation on fine grid; Incorporate trim effects. Further investigation of BVI noise investigated in Higher harmonic control Aeroacoustic Rotor Test (HART) program. PROPOSED WORK