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ISSN 0148-7191Copyright 2006 SAE International

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ABSTRACT

Computational Fluid Dynamics (CFD) is an integral partof product development at Visteon Climate Systems witha validated set of CFD tools for airflow and thermalmanagement processes. As we increasingly build CAEcapabilities to design not only thermal comfort, but quietsystems, developing noise prediction capabilitiesbecomes a high priority.

Two Broadband Noise Source (BNS) models will bepresented, namely Proudmans model for quadrupolesource and Curles boundary layer model for dipolesource. Both models are derived from Lighthills acousticanalogy which is based on the Navier-Stokes equations.BNS models provide aeroacoustic tools that are effectivein screening air handling systems with higher noiselevels and identifying components or surfaces thatgenerate most of the noise, hence providingopportunities for early design changes.

In this paper, BNS models were used as aeroacousticdesign tools to redesign an automotive HVAC centerduct with high levels of NVH. The design directionsuggested by BNS tools were later supported by physicaltest data. These models were found to be valuable andcost effective tools in providing reliable design directionearly in the development cycle.

INTRODUCTION

The ability of an analysis tool to characterize a systemslevel of noise and its spectral distribution at a receiver

location is a powerful design tool. It could be used as avirtual test lab to measure whether a given system meetsits design requirements. Currently, such capability is notavailable within a development cycle for complexindustrial applications. This is due to the fact that noiseinformation at receiver locations requires the solution ofboth the flow field and the acoustic field. However,during early stages of the product development, noiseinformation at receiver locations is not critical. Rather,reliable system noise information at the source may besufficient to provide design direction during development.

Noise information at the source requires only a CFDsolution that captures unsteady flow structure. At earlystages of the development cycle, a CFD tool thatprovides a measure of noise levels at the source for agiven system in order to provide a design direction wouldbe very useful. In addition, if that tool is able to identifycomponents or surfaces that generate most of the noiseit would provide, to the development team, a valuablemeans to derive design optimization.

Broadband Noise Source (BNS) models that requiresteady state solution can be used as effective andinexpensive design tools [1, 2]. Here, Proudmansquadrupole model and Curles boundary layer model arepresented [3, 4]. Both models assume isotropicturbulence, low Mach number flows, and broadbandnoise and can only provide noise information at thesource.

The intent of this paper is to show the effectiveness of

BNS models during the development process. However,before presenting these models, a brief description ofaeroacoustic modeling and options available to a productdesign team in industrial environments is discussed.

AEROACOUSTIC MODELING

Aeroacoustic behavior can be completely characterizedby solving the compressible Navier-Stokes equations. Inother words, aeroacoustic phenomena can be explainedthrough the use of the principles of mass, momentum,and energy conservation. For simple problems, Direct

Numerical Simulation (DNS) that solves thecompressible Navier-Stokes equations is able to solvefor both the aerodynamic flow field and the acoustic field.However, for problems of industrial applications, thisapproach becomes impossible due to the fact that theacoustic energy is several levels of magnitude smallerthan the hydrodynamic energy. In addition, the acousticpressure perturbations are several levels of magnitudesmaller than the hydrodynamic pressure. Further, lengthand time scales of the two fields are not compatible.Therefore, the need to separate the two flow fieldsbecomes apparent.

2006-01-1192

Broadband Noise Source Models as Aeroacoustic Tools inDesigning Low NVH HVAC Ducts

Omar M. Mohamud and Perry Johnson

Visteon CorporationCopyright 2006 SAE International

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be used together with semi-empirical correlations toprovide a measure of the broadband source noise.Aeroacoustic models that quantify the broadband sourcenoise generated by the flow, per unit surface or volume,are termed Broadband Noise Source (BNS) models.

Though BNS models are attractive aeroacoustic designtools they present major limitations. These models donot provide any tonal noise information or noise spectraat receiver locations. Instead they provide only anapproximate measure of the radiated noise at thesource.

There are a number of BNS models [1]. In this paper,Proudmans model for quadrupole source [3] and Curlesboundary layer model for dipole source [4] will bepresented. Both models are derived from Lighthillsacoustic theory which is based on Navier-Stokesequations.

PROUDMANS NOISE SOURCE MODEL

In 1952, immediately after Lighthills acoustics theory,Proudman [3] using Lighthills theory considered noisegenerated by a homogenous isotropic turbulence. Usingstatistical models he derived the following analyticalexpression for the Acoustic Power (AP) per unit volume:

Where is a constant, 0 is the density, 0a is thespeed of sound, l is length scale, and u is turbulentvelocity defined as:

Here, k is the turbulent kinetic energy.

Equation 3 can be written in terms of k and as:

Where

0

2a

k M t =

Later Lilley [9] reexamined Proudmans expression andadded a correction for time correlation effects previouslyneglected by Proudman. Sarkar and Husseini [10]computed numerically radiated acoustic noise using DNSand found results that are in agreement with Proudmansanalytical expression. However, they recalibrated theconstant for better agreement with DNS data. Here,Fluent 6.2 Solver [1], used for this work, implements thecalibrated constant and provides a measure of the

quadrupole noise generated at the source from anisotropic turbulence.

BOUNDARY LAYER NOISE SOURCE MODEL

The second model is based on Curles [4] integral wherethe radiated acoustic pressure was derived as a functionof the fluctuating surface pressure of the rigid bodysurface. The following formulation assumes low Machnumber and only accounts for dipole contribution of thesource noise.

Where, is the emission time, p is the surfacepressure, n is the wall normal direction, p is theacoustic pressure, and 0a the speed of sound.

Including the correlation area and manipulating Equation5, the Surface Acoustic Power (SAP) radiated from thebody surface can be computed by:

Where A c is the correlation area and 0 is the density.2

t p

is the mean-square time derivative of the source

surface pressure, x is the receiver coordinate, y is thecoordinate of the source surface, and S is the sourcesurface.

The mean-square derivative is computed from turbulentkinetic energy, turbulent dissipation rate, and wall shearstress.

Leclercq and Symes [11] compared experimental workand numerical implementation of Curles integral of bluffbodies in fluctuating flow field. They found that Curlestheoretical development, Equation 6, predicted theradiated noise. Khondge et al [2] applied BNS models to

predict aeroacoustic performance of a duct and foundthat predicted noise was directionally supported byexperimental data.

Proudmans quadrupole model and Curles dipole modelwere selected in this paper. These two models, basedon Lighthills analogy, require little computational effort inextracting, from a steady state CFD solution, theAcoustic Power (AP) and the Surface Acoustic Power(SAP). Both aeroacoustic variables are accessed withinthe Fluent Solver as an aeroacoustic post-processingtool. AP provides Proudmans quadrupole noise

50

53

0 )(a

ul

u AP = (3)

k u3

22 =

)(),()(

4

1),(

20

ydS yt

pr

n y x

at x p

S

iii

= (5)

50 t M AP = (4)

)()(12

12

300

ydS t

p y A

aSAP c

= (6)

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generation, whereas SAP provides Curles surface dipolenoise generation.

These two aeroacoustic variables are well suited to AirHandling Subsystem (AHS) applications which representa complex internal flow that includes rotating parts(blowers), heat exchangers, and distribution ducts. Inthese low Mach number flows, surface dipole noiseradiation generally contributes most of the system noise.However, turbulent generated quadrupole generationbecomes important around the blower blades.

APPLICATION - HVAC PANEL DUCTS

Automotive HVAC systems are used to provideconditioned air into the cabin for comfort and safety.Outside fresh air is drawn in at the base of the vehiclewindshield by the AHS that moves conditioned air intothe vehicle cabin. The AHS, including a blower, scroll,two heat exchangers, housing, and blend and modedoors, is packaged below the instrument panel. In panelmode, outlet panel registers mounted on the instrumentpanel and the panel distribution ducts supply conditionedair into the cabin. Noise requirements are prescribed atthe vehicle level and microphones are placed near thedriver and passenger ear locations to measure noiselevels. However, during development, component noisecontribution to the overall system noise becomesimportant.

Here, a case will be studied where the initial level designof an automotive HVAC panel duct did not meet itsdesign requirements due to high levels of NVH, pooroverall sound quality, and low airflow to the outboardregisters. Confidential customer requirements will not beshared here. However, CFD predicted airflow and NVH

levels will be presented and compared with test airflowand NVH data. The geometry of the panel duct with flowinlet and outlets is presented in Figure 1. As shown inFigure 1, the panel duct has three major parts, namelythe center duct, the outboard duct, and the registers.

Figure 1: Panel duct geometry - Initial

In automotive HVAC systems, panel ducts supply air intothe cabin through the instrument panel registers. Panelduct air supply design in terms of noise and comfort iscritical due to its proximity to the front seat occupants. Inthis paper, BNS models were used as design tools tooptimize the panel duct design for noise and airflow.

CFD MODEL

A CFD model, based on steady state RANS with

k turbulence model, of the entire AHS and distributionducts was simulated. First, baseline AHS performancewas established in terms of noise and airflow using theinitial design. Then panel ducts and registers weremodeled separately with a velocity profile applied at theinlet. This sub-model, shown in Figure 1 and referredhere to as Panel Duct (PD) model, behaves as if it werepart of the entire system. This modeling method wasnecessary during the design optimization process andsaved computer resources and execution time.

A cross-section of the PD model mesh is shown inFigure 2. Figures 3 and 4 show mesh resolution of thecenter duct neck and the vent registers, respectively.

Figure 2: Panel duct model mesh

Figure 3: Panel duct model mesh-center duct neck close-up

Center Duct

Airflow Inlet

Airflow Outlet

Outboard

Registers

Vent Registers

Center Duct Neck

Cross section @ y = 60 mm

Cross section @ y = 60 mmCenter Duct Mesh Close-up

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The PD model had 900,000 tetra cells and required anexecution time of 104 minutes on a 4 node HP Itanium 2processor with 1 Gb RAM per node.

Figure 4: Panel duct model mesh-vent registers zone close-up

Fluent 6.2, used for this work, offers both Proudmansquadrupole model, Equation 4, and the boundary layerdipole model, Equation 6, as post-processing tools.Physical quantities extracted from steady state solutionsuch as turbulence velocity, turbulence length scale, andmean-square surface pressures were used to computeAP and SAP. AP (w/m 3) is the turbulent generatedquadrupole noise, whereas SAP (w/m 2) is the surfacegenerated dipole noise. Both of these quantities areevaluated at the source and provide an approximatemeasure of the local contribution to the total system

generated noise.

The accuracy of BNS aeroacoustic models will dependstrongly on the accurate characterization of the mainflow. To validate the steady state CFD solution,predicted and measured system airflow in panel recircmode (MAX AC) is presented in Table 1. The datashows good agreement between measured andpredicted total airflow and airflow distribution andsuggests that the CFD solution characterizes thephysical system.

Table 1: AHS airflow in panel recirc mode, m 3 /hr

LHO LHC RHC RHO Total

CFD 36.85 34.79 36.67 34.61 142.91

Test 35.32 34.61 40.61 34.61 145.15

Change -1.53 -0.18 +3.94 0.00 +2.24

Utilizing BNS tools, noise characteristics of the initial ductwere extracted from the CFD solution of the panel ductsub-model in terms of total SAP and AP generatedsource noise. Further, components and surfaces withhigh noise generation were identified. Guided by theCFD results, high noise source regions of the center ductwere redesigned. To save design time and cost, designmodifications were performed within the CFD post-processor tool. After only few iterations, a center ductdesign with a baffle at the inlet was proposed.

RESULTS

Figure 5 shows that most of the dipole noise wasgenerated from the center duct with very littlecontribution from the outboard ducts and registers. Thecontour plot of the quadrupole noise generation in Figure6 shows that the neck area of the center duct radiatesmost of the noise. In addition, Figure 7 shows surfaceacoustic power level iso-surfaces of radiated dipole noisewith significant generation at the neck.

Figure 5: Initial design component source noise

Figure 6: Acoustic Power level contours - Initial

0.0E+00

5.0E-06

1.0E-05

1.5E-05

2.0E-05

2.5E-05

3.0E-05

3.5E-05

Center Outboards Registers

Component

S A P ( W a t

t s )

Cross section @ y =60 mm

Vent RegistersMesh Close-up

High Noise Generation

Cross Section @ y=60 mm

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Figure 7: Surface Acoustic Power level iso-surfaces - Initial

All noise data of the initial design indicates that thecenter duct should be redesigned. Guided by the CFDresults, high noise source regions of the center ductwere redesigned. After several iterations, a center ductdesign with a baffle at the inlet was proposed, see Figure8. The function of the baffle is to split incoming airflowbetween outboard and center vent registers. This designis referred to as Redesign.

Figure 8: Panel duct geometry - redesign with baffle

Results of the Redesign duct are shown in Figures 9 and10 and show significant reduction in noise generationrelative to the initial design.

Figure 9: Surface Acoustic Power level iso-surfaces - Redesign

Figure 11 shows a comparison of dipole noise radiation(SAP) between the Initial design and the Redesign panelducts. The figure shows a significant reduction in centerduct noise generation with slight noise reduction of theoutboard ducts and registers for the Redesign.

Figure 10: Acoustic Power level contours - Redesign

Table 2 presents BNS predicted source noise andcompares a sub-model of the initial center duct with asub-model of the redesigned center duct. The datashows that computed Surface Acoustic Power at thesource indicates a 60% noise reduction for theredesigned duct. In addition, Surface Acoustic Powerlevel at the source is reduced by 4.0 dB.

Table 3 presents Lab NVH bench data measured at theAHS level and compares a system with the initial centerduct and a system with the redesigned center duct. Thedata shows a 4.9 dB reduction in recirc mode (MAX AC)and 4.4 dB reduction in panel fresh mode for theredesigned duct.

High NoiseLow Noise

Split Baffle

Center Duct

Noise Reduced

Cross-section @ y = 60 mm

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Figure 11: Initial and Redesign component source noise

It is important to emphasize that Table 2 and Table 3data should not be directly compared. Table 2 presentsCFD predicted aeroacoustic noise at the source with asub-model that included only outboard ducts, centerducts, and registers. Whereas, Table 3 data refers tothe entire AHS noise measured at the driver ear location.However, it is worthy to note that measured noise inTable 3 shows 4.9 dB reduction at the receiver andconfirmed the design direction originally suggested bythe BNS models early in the development process.

Table 2: BNS predicted source noise- PD sub-model

ModelSAP

Source(Watts)

SAP LevelSource

(dB)Initial 4.34e-5 66.4

Redesign 17.32e-6 62.4

Change 60 % -4.0

Table 3: AHS NVH bench data Driver side

Recirc.(dB)

Fresh(dB)

Initial 71.3 66.9

Redesign 66.4 62.5Change -4.9 -4.4

CONCLUSION

BNS models are found to be effective tools in screeningsystems with higher noise levels and identifying

components or surfaces with high noise generation,hence providing opportunities for early design changes.

Aeroacoustic variables at the source were used to drivethe design optimization process which resulted inreduced noise levels, better sound quality, and a moreefficient airflow supply into the vehicle cabin.

BNS models of the panel duct sub-model predicted a 4.0dB noise reduction at the source, whereas a lab NVHtest of the entire AHS measured a 4.9 dB reduction atthe receiver. This indicates that BNS models providedreliable design direction early in the developmentprocess and proved to be valuable and cost effectiveaeroacoustic design tools.

REFERENCES

1. Fluent 6.2 Users Guide, Fluent Inc., Lebanon NH,2005.

2. Khondge, A.D, Sovani, S.D., Kim, S., Guzy, S.C.,Farag, A.A. On Predicting AeroacousticPerformance of Ducts with Broadband NoiseSource Models, SAE Paper, 2005-01-2495, 2005.

3. Proudman, I., The Generation of Noise by IsotropicTurbulence, Pro. Roy. Soc. A214, pp. 219, 1952.

4. Curle, N., The Influence of Solid Boundaries uponAerodynamic Sound, Proc. Roy. Soc. A2314, pp.505-514, 1955.

5. Lighthill, M.J. On the Sound GeneratedAerodynamically: Part I General Theory , Proc.Roy. Soc. A211, pp.564-587, 1952.

6. Ffowcs Williams, J.E., Hawkings, D.L., SoundGeneration by Turbulence and Surfaces in ArbitraryMotion, Phil. Trans. Roy. Soc., A264 (1151), 321-

243, 1969.7. Kim, S-E., Dai, Y., Koutsavdis, K., Sovani, S.,Kadam, N., Ravuri, M.R. A VersatileImplementation of Acoustic Analogy Based NoisePrediction Method in a General-Purpose CFDCode AIAA Paper N0. 2003-3202, 2003.

8. Ayar, A, Ambs, R., Capellmann, C., Schillemeit, B.,Matthes, M. Prediction of Flow-Induced Noise inAutomotive HVAC Systems Using a CombinedCFD/CA Approach, SAE Paper, 2005-01-0509,2005.

9. Lilley, G.M., The Radiated Noise From IsotropicTurbulence Revisited, NASA Contract Report No.93-75, NASA Langley Research Cnter, Hampton,VA 24681, 1993.

10. Sarkar, S, Hussaini, M.Y. Computation of theSound Generated by Isotropic Turbulence, NASAContract Report No. 93-74, NASA LangleyResearch Center, Hampton VA 24681, 1993.

11. Leclercq, D. J. J., Symes, M. K., Predicting theNoise Generated by a Bluff Body in a FluctuatingFlow, AIAA Paper 2004-20917, 2004.

0.0E+00

5.0E-06

1.0E-05

1.5E-05

2.0E-05

2.5E-05

3.0E-05

3.5E-05

Center Outboards Registers

Component

S A P

( W a t

t s )

Current

Redesign