COMPUTATIONAL AERO-ACOUSTICS OF VEHICLE A-PILLAR AT VARIOUS WINDSHIELD RADII

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1 Fifth Internatinal Cnference n CFD in the Prcess Industries CSIRO, Melburne, Australia December 2006 COMPUTATIONAL AERO-ACOUSTICS OF VEHICLE A-PILLAR AT VARIOUS WINDSHIELD RADII Nurul M. MURAD 1, Jamal NASER 1, Firz ALAM 2 and Simn WATKINS 2 1 Faculty f Engineering and Industrial Science Swinburne University f Technlgy, VIC, 3122 AUSTRALIA 2 Schl f Aerspace, Mechanical and Manufacturing Engineering RMIT University, VIC, 3083 AUSTRALIA ABSTRACT Flw separatin behind the A-pillar regin can lead t aer-acustics generatin, which presents prblems such as annyance and discmfrt t vehicle ccupants (Huch, 1998). The prpagatin f aerdynamic nise surrunding the vehicle can be mdelled numerically in rder t investigate the aer-acustics surce and hence minimise the prblems. This paper attempts t investigate ne f the several methds available t mdel aeracustics prpagatin. In this paper, three generic vehicle scale mdels with different windshield radii were used as a case study and mdelled using CAA under labratry perating cnditins. CAA mdelling was cnducted using a cmmercial cde called AVL SWIFT-CAA. AVL SWIFT-CAA ffered a mre ecnmical avenue t mdel fr CAA. Investigatins were carried ut at inlet velcity f 60, 100 and 140km/h at 0º and 15 yaw angles. Cmparisns were cnducted between CAA results and experimental results f Alam (2000) t investigate the capabilities f the SWIFT-CAA mdelling capabilities. NOMENCLATURE CFD Cmputatinal Fluid Dynamics CAA Cmputatinal Aer-Acustics RANS Reynlds Average Navier Stkes Equatins LEE Linearized Euler Equatins C p RMS Rt Mean Square Cefficient f Pressure PSD Pwer Spectral Density INTRODUCTION Flw separatin behind the vehicle A-pillar regin can lead t aer-acustics generatin. Aer-acustics generated is then transferred t the passenger cabin causing annyance and much discmfrt t the vehicle ccupants (Huch, 1998). The prpagatin f aerdynamic nise surrunding the exterir and interir f the vehicle can be mdelled numerically. One methd f aer-acustics mdelling is t use either DNS r LES CFD mdelling. The perfrmance f these methds hwever, is limited by the spatial and tempral reslutin that can be achieved in rder t effectively mdel the required frequency and amplitude range, Tam (2002), Lkhande et al. (2003). The ther methd f aer-acustics mdelling invlve extracting acustical surce term frm either a transient r steady CFD mdel and calculate the prpagatin f aerdynamic nise at the far-field receiver using an acustic slver. Lyrintzis (1994) and Kumarasamy et al. (1999) defined this methd as the acustic-analgy methd and listed several f the different techniques available, namely the Lighthill Acustic Analgy (LAA) Methd, Kirchff Methd, Pertubatin Methd and the Linearised Euler Equatin (LEE) Methd. This purpse f this paper is t investigate the capability f a CAA mdelling cde called the hybrid SWIFT-CAA, develped by AVL/TNO. The hybrid SWIFT-CAA apprach ffers a nvel way t ecnmically mdel aeracustics by using RANS-CFD data cupled with a statistical mdel as a basis t slve fr the acustical surce term. This bypass the need t generate a transient CFD mdel that utilises a cmputatinal dmain with high rder spatial and tempral reslutin needed t slve fr aer-acustics prpagatin that extends t the far field range. The capabilities f the hybrid SWIFT-CAA was investigated thrugh cmparisn with the experimental wrk f Alam (2000), in which measurement f C p RMS and PSD distributin behind the vehicle A-pillar regin were btained. Alam (2000) used three generic vehicle scale mdels with different circular windshield radii and yaw rientatins, subjected t varius wind tunnel velcities. The fllwing sectin will describe the methdlgy used in this study. This includes the general descriptin f the hybrid SWIFT-CAA apprach and the strategy used fr the CAA mdelling. The results and discussin are then presented thrugh cmparisn f C p RMS and PSD results distributin at 0 and 15 yaw between the experimental and CAA mdelling apprach f surface acustic fluctuating pressure behind the mdel A-pillar regin. METHODOLOGY The methdlgy f the hybrid SWIFT-CAA apprach can be categrised int tw steps. The first step cnsists f generatin f acustical surce term by mean f transferring 3D statistical turbulent quantities btained frm RANS-CFD mdelling t a separate CAA dmain, meshed with unstructured tetrahedral grid f lw density. The transfer f 3D statistical turbulent quantities (turbulent kinetic energy, eddy length scale and dissipatin rate) were cnducted using a statistical mdel that incrprate the inverse Furier transfrm thrugh a sub-rutine in the CAA slver, called the Unstructured Kinematic Surce Generatr (UKSG). The statistical mdel develped by Bechera (1996) and Lngatte (1998) are given as: 1

2 N ~ u t ( x, t ) = 2 = u ( + + ) n n nx n nt 1 cs κ ψ ω σ n (1) where σ n is the directin f turbulent velcity vectr, which is perpendicular t κ n the wave vectr. ω n is the radial frequency, ψ n was a randm phase and ữ n is the mdel amplitude, which cntains the statistical turbulent quantities btained frm the RANS-CFD mdelling. The equatin fr turbulent fluctuatins is then used t determine a time accurate acustic surce term fr the perturbatin term f the mass, mmentum and energy equatin: ρ a ' +. ( ρ u a + ρ au ) = S M S (2) A1 t p t + ua + t ρ ρ a ( U. ) u a + ( u a. ) U pa p + ( ρ ) = S I S A2 a ( ) 2 +. ρ 2 ( U pa + γ u a p ) ( γ 1) ' ( γ 1) pa. U = S E S A3 (3) u a. p (4) which represents the surce terms with subscripts A1 t A3 in equatin 2 t 4. The final step in the SWIFT-CAA apprach was t determine the aer-acustics prpagatin (surce t receiver in the far-field) thrugh slving fr the acustic pressure (p a ). Using the acustic surce terms, the CAA slver determine the aer-acustics prpagatin using the LEE apprach, which invlves cnversin f the terms n the right hand side f equatin 2 t 4, tgether with a time dmain calculatin cnducted using a Quadrature Free Discntinuus Galerkin Spatial discretizatin apprach. In this apprach, the revised surce term btained prgressively at each time interval frm the UKSG subrutine was interplated t the CAA slver. A new time step interval was then btained thrugh the use f a furth-rder Runge-Kutta algrithm, AVL (2003). Vehicle Gemetry and Bundary Cnditins The gemetry cnfiguratins and bundary cnditins used in the CFD mdelling, prir t the CAA mdelling were btained frm Alam (2000). Generic scale (40%) vehicle mdels with varying lcal windshield radii namely Small Ellipsidal (299-mm elliptic radius), Semi Circular (374-mm) and Large Ellipsidal (449-mm) were cnstructed at yaw angle rientatins f 0, -15 and +15 respectively. The mdels were expsed t wind tunnel inlet velcities f 60, 100 and 140-km/h. The windshield fr the mdels was at a slant angle f 60 frm the vertical axis (Figure 1). The external surface f the CAA vlume dmain was assigned bundary cnditins f either reflecting (wall f the CAA dmain) r nn-reflecting (inlet and utlet f the CAA dmain) (Figure 2). In the CAA dmain, tw rws (bttm and tp rw) f mnitring lcatins (96-mm apart) were assigned t each mdel t capture fluctuating pressures behind the A-pillar regin. Each rw had 16 mnitring pints, which were 32.0-mm apart (Figure 1). Figure 1: Simplified Vehicle Mdel Gemetry with Varying A-pillar Windshield Radius (After Alam, 2000) Figure 2: Unstructured Tetrahedral Grids in CAA Dmain Mesh Generatin AVL Fame Hybrid was used t generate grids fr the CAA dmain. The CAA dmain was created by first selecting an area f interest surrunding the A-pilar regin frm within the CFD dmain. The surrunding surface f the selected CAA dmain was first meshed with triangulate surface grids. The CAA dmain vlume was then meshed with unstructured tetrahedral grids (Figure 2). Each grid cell in the CAA dmain must adhere t an aspect rati f smaller than 3.3 in rder t maintain ptimum accuracy. Each tetrahedral grids generated varies in between 50-mm t 100-mm in size. The final ttal grid cunt generated varies in between 14,000 t 35,000 depending n the mdel radius cnfiguratin and yaw angle rientatin. Numerical Scheme and Strategy The RANS-CFD mdelling cnducted using SWIFT-CFD used a turbulence intensity and length scale value f 1.8% and 5.8 mm (1.0% mdel height) respectively. The numerical scheme used during the initial stage f calculatin was first rder upwind scheme and central differencing scheme. Once cnvergence was reached, the AVL smart bund higher rder scheme was then used. The cnvergence level fr residuals was set t 0.1% with SIMPLE pressure-velcity cupling used tgether with 3D, steady and incmpressible flw envirnment. Turbulence mdels used in the initial calculatin was standard k-ε befre switching t the Reynlds Stress turbulence mdel (RSM). Mre details f the RANS-CFD mdelling cnducted using SWIFT-CFD are well dcumented in Murad (2006) and will nt be discussed further in this paper. 2

3 Fr CAA mdelling cnducted using SWIFT-CAA, a CAA Mapper sub-rutine was first used t map the 3D statistical turbulence quantities btained frm the CFD results t the CAA dmain. The CAA Mapper divided the CAA dmain int several rectangular partitins r bins t expedite the mapping and interplatin prcess. The amunt f CFD ndes interplated in each bin must be sufficiently high t ensure an accurate mapping. In this study, the nde interplatin value was set as ten, the recmmended default value. Once the mapping and interplatin prcess was cmplete, the CAA Mapper was then able t establish an initial time step t be used in the CAA slver. The initial time step was given autmatically and was based n the frmulatin that utilises the mean velcity tgether with the grid size and the Curant number. The time interval generated fr the CAA slver varies between 3.0 t 16.0 micrsecnds and required 160,000 t 270,000 time steps t cmplete a ttal f 1.0-secnd time interval prpagatin. In setting up the CAA slver t simulate fr the aerdynamic acustic prpagatin, the input parameters fr Turbulence Realizatin Sampling Frequency was assigned a value f 40-kHz, which was the maximum allwed. This was clse t the value f 48-kHz, which was used by Alam (2000). Fr this study, the simulatin f the acustic prpagatin carried ut by the CAA slver tk between ne t fur days t finish. Calculatin f the CAA slver fr this prject was dne using a single prcessr in the Swinburne University Super Cmputer cluster. The results were analysed using pst-prcessing features available in SWIFT-CAA. PSD analysis were cnducted by prviding input such as the number f Furier Fast Transfrm (FFT) blcks, Number f FFT verlap pints and viewing Windw fr each Furier blck. Fr this study, the inputs used were as fllws: Number f FFT blcks 4096 Number f FFT verlap pints 50% Viewing Windw fr each blck Hanning COMPARISON AND DISCUSSION OF CAA AND EXPERIMENTAL RESULTS Cmparisn f f Numerical and Experimental Results fr Reynlds Number Sensitivity, Small Ellipsidal Mdel, SE60,BR0 SE100,BR0 SE140,BR0 SE60,TR0 SE100,TR0 SE140,TR0 Exp SE60,BR0 Exp SE100,BR0 Exp SE140,BR0 Exp SE60,TR0 Exp SE100,TR0 Exp SE140,TR0 Figure 3: C p RMS fr Small Ellipsidal Mdel at 0 Cmparisn f f Numerical and Experimental Results fr Reynlds Number Sensitivity, Small Ellipsidal Mdel, -15 SE60,BR-15 SE100,BR-15 SE140,BR-15 SE60,TR-15 SE100,TR-15 SE140,TR-15 Exp SE60,BR-15 Exp SE100,BR-15 Exp SE140,BR-15 Exp SE60,TR-15 Exp SE100,TR-15 Exp SE140,TR Figure 4: C p RMS fr Small Ellipsidal Mdel at -15 Cmparisn f f Numerical and Experimental Results fr Reynlds Number Sensitivity, Small Ellipsidal Mdel, +15 SE60,BR+15 SE100,BR+15 SE140,BR+15 SE60,TR+15 SE100,TR+15 SE140,TR+15 Exp SE60,BR+15 Exp SE100,BR+15 Exp SE140,BR+15 Exp SE60,TR+15 Exp SE100,TR+15 Exp SE140,TR+15 CAA Mdelling Results f Surface Fluctuating Pressure Small Ellipsidal Mdel, C p RMS and PSD Results Cmparisn f C p RMS distributin btained frm CAA and experimental results fr Small Ellipsidal mdel at 0, -15 (Leeward) and +15 (Windward) yaw can be seen in Figures 3, 4 and 5. Gd crrelatins were btained fr bth bttm and tp rw mnitring lcatins at 0 and +15 yaw. Hwever, a small C p RMS discrepancy f arund exists at -15 yaw twards the halfway pint f the bttm rw mnitring lcatins and twards the end f the tp rw mnitring lcatins respectively. Cmparisn f PSD distributin between CAA mdel and experimental results fr Small Ellipsidal mdel at 100 km/h can be seen in Figures 6 and 7. The discrepancies btained fr peak PSD values fr 0 yaw, +15 and - 15 yaw were 1.0, 3.0 and 14.0 db respectively. The verall PSD distributin fr Small Ellipsidal mdel shwed best crrelatin at yaw angle f +15, fllwed by yaw angles f 0 and -15, with ttal mean discrepancies measured at 5.0, 7.3 and 13.3-dB respectively. 1.1 Figure 5: C p RMS fr Small Ellipsidal Mdel at +15 PSD (db) Pwer Spectral Density (Max RMS Pressure), Small Ellipsidal, 0 Degree, +15 and -15 Degree Angle +15,100-15,100 0, Frequency (Hz) Figure 6: CAA Mdelling f Spectral Energy Density Distributin fr Small Ellipsidal Mdel at -15, 0 and +15 3

4 mdel was 7.0, 12.0 and 15.0-dB, crrespnding t yaw angles at 0, +15 and -15 respectively (Figures 11 and 12). Cmparisn f f Numerical and Experimental Results fr Reynlds Number Sensitivity, Semi Circular Mdel, +15 Semi60,BR Semi100,BR Semi140,BR Semi60,TR Semi100,TR Semi140,TR EXP Semi60,BR EXP Semi100,BR EXP Semi140,BR EXP Semi60,TR EXP Semi100,TR EXP Semi140,TR Figure 7: Experimental Results f Spectral Energy Density Distributin fr Small Ellipsidal Mdel at -15, 0 and +15 (After Alam, 2000)Semi Circular Mdel, C p RMS and PSD Results Cmparisn f C p RMS distributin btained frm CAA and experimental results fr Semi Circular mdel at 0 yaw yield gd crrelatins fr bth the bttm and tp rw mnitring lcatins. Hwever, cmparisn f C p RMS distributin between CAA and experimental results shwed slight discrepancy at bth -15 and +15 yaw rientatin, particularly twards the rear prtin f the bttm and tp rw mnitring pints with values f arund and 0.02 respectively (Figures 8, 9 and 10). Figure 10: C p RMS fr Semi Circular Mdel at +15 PSD (db) Pwer Spectral Density (Max RMS Pressure), Semi Circular, 0, +15 and -15 Degree Angle CAA CAA CAA Cmparisn f f Numerical and Experimental Results fr Reynlds Number Sensitivity, Semi Circular Mdel, 0 Semi60,BR Semi100,BR Semi140,BR Semi60,TR Semi100,TR Semi140,TR EXP Semi60,BR EXP Semi100,BR EXP Semi140,BR EXP Semi60,TR EXP Semi100,TR EXP Semi140,TR Frequency (Hz) Figure 11: CAA Mdelling f Spectral Energy Density Distributin fr Semi Circular Mdel at -15, 0 and +15 Figure 8: C p RMS fr Semi Circular Mdel at 0 Cmparisn f f Numerical and Experimental Results fr Reynlds Number Sensitivity, Semi Circular Mdel, -15 Semi60,BR Semi100,BR Semi140,BR Semi60,TR Semi100,TR Semi140,TR EXP Semi60,BR EXP Semi100,BR EXP Semi140,BR EXP Semi60,TR EXP Semi100,TR EXP Semi140,TR Figure 9: C p RMS fr Semi Circular Mdel at -15 Cmparisn f peak PSD values between CAA and experimental results at 100 km/h yielded lwest discrepancy at 0 yaw, fllwed by -15 and +15 yaw, measuring 14.0, 18.0 and 19-dB respectively. The verall PSD distributin discrepancy btained fr Semi Circular Figure 12: Experimental Results f Spectral Energy Density Distributin fr Semi Circular Mdel at -15, 0 Large Ellipsidal Mdel, C p RMS and PSD Results Cmparisn C p RMS distributin btained frm CAA and experimental results fr Large Ellipsidal mdel at 0 and - 15º and +15 yaw yield gd crrelatins fr bth the bttm and tp rw mnitring lcatins with discrepancy f C p RMS bserved at values less than 0.02 (Figures 13, 14 and 15). Cmparisn f peak PSD values btained frm CAA and experimental results at 100 km/h prduced discrepancies f 5.0, 13.0 and 15.0-dB, crrespnding t yaw angles at 0º, -15 and +15 respectively. The verall PSD discrepancies fr Large Ellipsidal was the lwest at 0 yaw, fllwed by yaw angles at -15 and +15, measuring 3.0, 6.8 and 10.0-dB respectively (Figures 16 and 17). 4

5 Cmparisn f f Numerical and Experimental Results fr Reynlds Number Sensitivity, Large Ellipsidal Mdel, 0 LE60,BR LE100,BR LE140,BR LE60,TR LE100,TR LE140,TR EXP LE60,BR EXP LE100,BR EXP LE140,BR EXP LE60,TR EXP LE100,TR EXP LE140,TR Figure 13: C p RMS fr Large Ellipsidal Mdel at 0 Cmparisn f f Numerical and Experimental Results fr Reynlds Number Sensitivity, Large Ellipsidal Mdel, -15 LE60,BR LE100,BR LE140,BR LE60,TR LE100,TR LE140,TR EXP LE60,BR EXP LE100,BR EXP LE140,BR EXP LE60,TR EXP LE100,TR EXP LE140,TR Figure 14: C p RMS fr Large Ellipsidal Mdel at -15 Capabilities f SWIFT-CAA in mdelling fr Fluctuating Surface Cmparisn f f Numerical and Experimental Results fr Reynlds Number Sensitivity, Large Ellipsidal Mdel, +15 LE60,BR LE100,BR LE140,BR LE60,TR LE100,TR LE140,TR EXP LE60,BR EXP LE100,BR EXP LE140,BR EXP LE60,TR EXP LE100,TR EXP LE140,TR Figure 17: Experimental Results f Spectral Energy Density Distributin fr Large Ellipsidal Mdel at -15, 0 and +15 (After Alam, 2000) The study f Alam (2000) shwed that aerdynamic prperties behind the A-pillar regin fr mdels with variable windshield radii were a mixture f attached and separated flw with aerdynamic nise generatin caused largely by the presence f intense turbulence bundary layer distributed underneath the flw. SWIFT-CAA prvided gd crrelatin against results btained experimentally in mdelling fr the C p RMS distributin behind the A-pillar regin, particularly fr mdel psitined at 0 yaw and +15 yaw. Hwever, a maximum discrepancy f was displayed when predicting the at -15 yaw. This was due t the generatin f small scale separatin as the flw mves dwnstream t the rear regin f the mnitring lcatin, which was a direct cnsequence t the leeward yawing angle f the mdel. The discrepancies caused in mdelling fr the C p RMS prvided a direct implicatin in the utcme f the PSD distributin. The cmparisn f results btained shwed under predictin f PSD distributin by the CAA mdelling. A maximum discrepancy f arund 0.02 btained frm the C p RMS distributin translates t a maximum mean PSD discrepancy f arund 10-dB. A maximum discrepancy f arund translates t a maximum mean PSD discrepancy f arund 15-dB. Cmparisn dne n literature review based n CAA mdelling behind a bluff bdy regin shwed similar discrepancies, Lkhande et al. (2003), Ogawa et al. (1999), Struml et al. (1998), Uchida et al. (1999). Figure 15: C p RMS fr Large Ellipsidal Mdel at Pwer Spectral Density (Max RMS Pressure), Large Ellipsidal, 0, +15 and -15 Degree Angle Cntur visualisatin f the acustic pressure prpagatin and verall sund pressure level (OASPL) distributin can be seen in Figures 18, 19 and 20. Despite the under predictin shwed by the quantitative results btained frm the CAA mdelling, the presence f turbulence bundary layer intensity and small scale separatin was still captured thrugh the cntur visualisatin CAA PSD (db) CAA CAA Frequency (Hz) Figure 16: CAA Mdelling f Spectral Energy Density Distributin fr Large Ellipsidal Mdel at -15, 0 and +15 CONCLUSION In summary, this study has shwn that the AVL SWIFT- CAA has gd CAA mdelling capabilities in predicting the aeracustics prpagatin behind the A-pillar regin f scale mdels with variable windshield radii and yawing angle. The maximum discrepancies f and 15-dB fr predicting C p RMS and PSD distributin btained frm using AVL SWIFT-CAA were cmparable t similar studies f CAA mdelling. In additin, imprtant aer- 5

6 acustics characteristics were captured thrugh the visualisatin f acustic pressure and OASPL cnturs. Figure 18: Acustic Pressure Prpagatin, Small Ellipsidal Mdel at 0 Figure 19: Overall SPL Distributin, Small Ellipsidal Mdel at 15 ACKNOWLEDGMENTS The authrs wuld like t thank the Swinburne Centre fr Astrphysics and Supercmputing fr prviding assistance with cmputing supprt and resurces. REFERENCES ALAM, F., (2000), The Effects f Car A-Pillar and Windshield Gemetry and Angles n Lcal Flw and Nise: PhD Thesis, RMIT University, Australia. AVL SWIFT, (2003), AVL User Manual, Ver. 3.1, Austria. BECHERA, W., LAFON, P., BAILLY, C. and CANDEL, S. (1996), Applicatin f a k-ε Turbulence Mdel t the Predictin f Nise frm Simple and Caxial Free Jets, J. Sund and Vibr., 97, N. 6, GEORGE, A.R., (1990), Autmbile Aerdynamic Nise, SAE Paper, N HUCHO, W.H. ed., (1998), Aerdynamics f Rad Vehicles, 2 nd edn, Butterwrths, Lndn. KUMARASAMY, S. and KARBON, K. (1999), Aeracustics f an Autmbile A-Pillar Rain Gutter: Cmputatinal and Experimental Study, SAE Paper, N LOKHANDE, B., SOVANI, S. and XU, J. (2003), Cmputatinal Aeracustics Analysis f a Generic Side View Mirrr, SAE Paper, N LONGATTE, E., (1998), Mdélisatin de la prpagatin et de la génératin du bruit au sein des éculements turbulents internes, These présentée pur l btentin du Dcrat de l Ecle Central Paris. LYRINTZIS, A.S. (1993), The use f Kirchff s Methd in Cmputatinal Aeracustics, Cmputatinal Aer and Hydr-Acustics, ASME. MURAD, N.M., NASER, J., ALAM, F. and WATKINS, S., (2002), CFD Mdelling f Vehicle A-Pillar Aerdynamics, Prceedings f the Secnd Internatinal Cnference n Cmputatinal Fluid Dynamics, Sydney Australia, July MURAD, N.M. (Cmplete in 2006), Cmputatinal Fluid Dynamics f Vehicle Aerdynamics and Assciated Acustics: PhD Thesis, Swinburne University, Australia. OGAWA, S. and KAMIOKA, T. (1999), Review f Aerdynamic Nise Predictin Using CFD, SAE Paper, N STRUMOLO, G., BABU, V. and TOMAICH, T. (1998), A Lattice-Based Analysis f Vehicle Aerdynamic Nise, WUA-CFD 4 th Wrld Cnference and Exhibitin in Applied Fluid Dynamics, Freiburg Germany, June TAM, C.K.W. (2002), Cmputatinal Aeracustics: An Overview, 10 th Annual Cnference f the CFD Sciety f Canada, Windsr ON, Canada, June UCHIDA, K. and OKUMURA, K. (1999), Aerdynamic Nise Simulatin based n Lattice Bltzmann Methd (Surface Pressure Fluctuatins arund A-pillar), SAE Paper, N and +15 (After Alam, 2000) Figure 20: Overall SPL Distributin, Semi Circular Mdel at 15 6