Loren Garrison Purdue University School of Aeronautics and Astronautics W.N. Dalton

9th AIAA/CEAS Aeroacoustics Conference

1Purdue University School of Aeronautics and Astronautics

An Investigation of Extensions of the Four-Source Method for Predicting the Noise From Jets With Internal Forced Mixers

Loren GarrisonPurdue University

School of Aeronautics and Astronautics

W.N. DaltonRolls-Royce Corporation

A.S Lyrintzis and G.A. BlaisdellPurdue University

School of Aeronautics and Astronautics


Purdue University School of Aeronautics and Astronautics 2

Outline• Summary of the Four-source coaxial jet noise

prediction method

• Internally forced mixed jet configurations

• Comparisons of mixer experimental data to coaxial and single jet predictions

• Modified four-source formulation

• Modified Method Parameter optimization

• Modified Method Results



Four-Source Coaxial Jet Noise Prediction

Vs

Vs

Vp

Initial Region

Interaction Region

Mixed Flow Region

Secondary / Ambient Shear Layer

Primary / Secondary Shear Layer



– Secondary Jet:

– Effective Jet:

– Mixed Jet:

– Total noise is the incoherent sum of the noise from the three jets

ffff s ,Flog10θ,,D,VSPLθ,SPL U10sss

pspepe V,T,TΔdBθ,,D,VSPLθ,SPL ff

ffff ,Flog10θ,,D,VSPLθ,SPL 1D10mmm

sss /DVf

mm1 /DVf

Four-Source Coaxial Jet Noise Prediction


5Purdue University School of Aeronautics and Astronautics

Forced Mixer

H

Lobe Penetration (Lobe Height)

H:



Internally Forced Mixed Jet

Bypass Flow

Mixer

Core Flow

Nozzle

Tail Cone

Exhaust Flow

Exhaust / Ambient Mixing Layer

Lobed Mixer Mixing Layer



Noise Prediction Comparisons

• Experimental Data– Aeroacoustic Propulsion Laboratory at NASA Glenn

– Far-field acoustic measurements (~80 diameters)

• Single Jet Prediction– Based on nozzle exhaust properties (V,T,D)

– SAE ARP876C

• Coaxial Jet Prediction– Four-source method

– SAE ARP876C for single jet predictions




Low Penetration Mixer High Penetration Mixer











Modified Four-Source Formulation

Variable Parameters:

sU10ssss dB),(F10log),,D,T,SPL(V),(SPL ffff s

mD10mmmm dB),(F10log),,D,T,SPL(V),(SPL ffff m

eD10eppe dB),(F10log),,D,T,SPL(V),(SPL ffff e

Single Jet Prediction

Source Reduction

Spectral Filter

(dB) Reductions Source ΔdB,ΔdB,ΔdB

sFrequencie off-CutFilter Spectral ,,

mes

mes fff



Modified Formulation Variable Parameters

dB

dB

fc fc



Parameter Optimization Algorithm

• Frequency range is divided into three sub-domains

• Start with uncorrected single jet sources

• Evaluate the error in each frequency sub-domain and adjusted relevant parameters

• Iterate until a solution is converged upon

Low Frequency Sub-Domain

dBm ,dBe

fs

Mid Frequency Sub-Domain

dBs ,dBm ,dBe

fs , fm , fe

High Frequency Sub-Domain

dBs

fm ,fe



Parameter Optimization AlgorithmMid Frequency

Sub-DomainHigh Frequency

Sub-DomainLow Frequency

Sub-Domain



Parameter Optimization Results

Case dBsdBm f c

Maximum Error [dB]

Average Error [dB]

Optimized Solution

7.85 -3.52 19020 4.7 1.2

Four-Source Method

0.00 0.00 1000 9.2 5.0

Single Jet - - - 7.3 1.4

Case dBsdBm f c

Maximum Error [dB]

Average Error [dB]

Optimized Solution

9.92 -5.74 4982 3.6 1.2

Four-Source Method

0.00 0.00 1000 13.2 5.6

Single Jet - - - 8.1 2.8

Low Penetration

Mixer

High Penetration

Mixer



Modified Method with Optimized Parameters












Optimized Parameter Trends

• dBs (Increased)

– Influenced by the convergent nozzle and mixing of the secondary flow with the faster primary flow

– The exhaust jet velocity will be greater than the secondary jet velocity resulting in a noise increase




• dBm (Decreased)

– Influenced by the effect of the interactions of the mixing layer generated by the mixer with the outer ambient-exhaust shear layer

– The mixer effects cause the fully mixed jet to diffuse faster resulting in a larger effective diameter and therefore a lower velocity, resulting in a noise reduction




• fc (Increased)

– Influenced by the location where the turbulent mixing layer generated by the lobe mixer intersects the ambient-exhaust shear layer



Summary• In general the coaxial and single jet prediction methods do

not accurately model the noise from jets with internal forced mixers

• The forced mixer noise spectrum can be matched using the combination of two single jet noise sources

• Currently not a predictive method

• Next step is to evaluate the optimized parameters for additional mixer data– Additional Mixer Geometries

– Additional Flow Conditions (Velocities and Temperatures)

• Identify trends and if possible empirical relationships between the mixer geometries and their optimized parameters

Documents

Loren Garrison Purdue University School of Aeronautics and Astronautics W.N. Dalton