Prediction of Acoustic Comfort of a Trainset using Ray-Tracing Technology

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1 Prediction of Acoustic Comfort of a Trainset using Ray-Tracing Technology P. Gabet 1, V. Drobecq 1, N. Noé 2, P.Jean 2 1: Alstom Transport, 48 rue Albert Dhalenne, Saint-Ouen Cedex 2: CSTB, 84 avenue Jean Jaurès, Champs-sur-Marne, Marne-la-Vallée Cedex 2 Abstract: To make accurate and fast internal noise predictions in its trains, Alstom Transport worked with CSTB in order to develop a software based on ray-tracing methods. This software should be dedicated to railway applications, allowing to take into account all kind of acoustic sources on the train, and to do parametrical studies on the panels insulations, external loads or absorption properties of the trainset. The software that was developed is name OSCAR, and makes acoustic calculations in two stages: the first stage is a geometric calculation between sources and receivers, and the second one is an acoustic calculation to compute transfer functions between them. The validation of the process was done first with a numerical model, and then on a full scale model. Keywords: acoustic comfort, noise, train, trainset, beam-tracing, icare 1. Introduction Alstom Transport is number one worldwide in the high and very high speed train market, and ranks second in the urban and regional market. For both sectors, travellers are more and more demanding about the quality of their trip, and among other factors, acoustic comfort is very important: people want to have a quiet environment, to relax and sleep for some of them, to work and read for some others. Alstom Transport has been aware of the importance of noise annoyance for years and has proven to be very implicated in the acoustic field to build trains as quiet and acoustically comfortable as possible. For each project, the acoustic work starts as soon as the tender starts, and is continued until the full scale validation of the train. Alstom has been developing a real state of the art in acoustics, along with tools to predict acoustic characteristics of the various types of rolling stocks sold, but the need of a more efficient and dedicated tool to predict internal noise as a function of the various encountered parameters on a train recently appeared. This tool must be reliable, accurate enough, fast, and easy to use. SEA (Statistical Energy Analysis) methods that were formerly used did not satisfy those criteria, requiring too much time to build a new model. Alstom Transport decided to work with CSTB, and to use CSTB s acknowledged experience in the acoustic field, to develop a software called OSCAR (Outil de Simulation du Confort Acoustique d une Rame Modelling tool of a trainset acoustic comfort), based on beam tracing methods (ICARE software) with the contribution of Vibratec company. This paper aims at presenting what are the inputs for an OSCAR calculation, how to make a model with it, how it works and how CSTB validated it, and finally to show some comparisons between OSCAR results and experimental results, and between SEA and raytracing methods. 2.1 Rolling noise 2. Noise contributors on the train The most important noise source on a train is the rolling noise. It is explained by the combined interaction of the wheel and the rail due to their roughness. Surface defects of both the wheel and the rail make them vibrate along with the sleepers. Noise is then propagated. Figure 1: Wheel / Rail interaction The Twins software [9] allows predicting the rolling noise at the requested speed, from the knowledge of the track and wheels characteristics. Prediction of Acoustic Comfort of a Trainset using Ray-Tracing Technology Page 1/8

2 2.2 Traction motors and gearboxes Traction motors and gearboxes are contributing to the bogie noise in the case of self-propelled cars. Acoustic power of those sources is known from primarily predictions or from measurements. 2.5 Synthesis Noise sources are synthesized on the following figure. By applying the correct external load (wall pressures) on the train, OSCAR is able to take into account all of them. Sound pressure level db(a) Sound pressure level as function of train speed Traction noise Rolling noise Aerodynamic noise Total 80 Figure 2 : Traction motor on test bench 2.3 Other equipments HVACs, traction converters, electrical transformers, air compressors are noisy sources and can be placed in the under frame or on the roof (for a tramway for instance). Those equipments cannot be neglected, especially for noise at standstill Train speed [km/h] Figure 4: Synthesis of noise sources on a train 3. OSCAR s fundamentals 3.1 Calculation principles Inputs data are: external wall pressures: They are computed thanks to the use of an internal software, from geometrical characteristics of the train, and from noise sources. Pmax x Figure 3: Electric equipments on the roof of a tramway (Bordeaux Citadis) 2.4 Aerodynamic noise Aerodynamic noise usually appears at high speeds, see figure 4. It is due to air turbulence caused by some geometric characteristics of the train, such as: its nose bogie cavity gap between two cars pantograph doors bars, foot steps, some bumps or cavities Figure 5: External wall pressures on a tramway roof and side panels transmission losses: Pmin x TL = -10 log 10 (I transmitted / I incident ) [1] Prediction of Acoustic Comfort of a Trainset using Ray-Tracing Technology Page 2/8

3 absorption: α = I absorbed / I incident [2] In addition, the user defines internal and external noise sources, and also the location of the sound receivers where the noise levels are computed. A geometric calculation between sources and receivers is first performed, followed by an acoustic calculation. Two types of calculations are possible, and therefore two types of outputs can be obtained: pressure levels at the receivers positions, and room acoustic criteria such as Sound Transmission Index or Reverberation Time. 3.2 Geometric calculation This first part of the global process aims at determining the geometric acoustic trajectories between all the sources and all the receivers. In addition to the calculation depth chosen by the user, the only influent parameter of this calculation is the train geometry. Source on wall Receiver 4. Simulation method The problem consists in computing the radiated acoustic pressure inside a big volume, given an external pressure load and taking into account the transmission by the walls. Other noise sources (speakers, cooling systems ) inside the car also have to be simulated. Asymptotic methods such as ray-tracing or beamtracing are well suited for the internal radiation simulation (they are fast and provide accurate results for mid and high frequencies, and because of the train dimensions they can be expected to work even at lower frequencies) but have to be improved to handle external sources. 4.1 Pre-existing beam-tracing software The simulation method presented here is based upon a beam-tracing software called ICARE [1,2]. It is suited to compute narrow band FRF from point to points or from vibrating area sources onto points. Its principle is to shoot beam (wavefronts) from points, and adaptively split them according to the geometry, (see figure 7) until they reach the receivers. Once a receiver is reached, the exact path between the source and the receivers is computed. All the paths are stored. Figure 6: One trajectory with 5 reflections between one source on the roof and one receiver over the bogie 3.3 Acoustic calculation Given the previous results, and using the acoustic data of sources and panels, the acoustic calculation performed with ICARE determines the transfer functions between sources and receivers. One of the major advantages of this methodology is the possibility to modify one or more parameters such as absorption or transmission loss, and to restart the acoustic calculation without restarting the whole process. It is interesting as the geometric calculation is often more time consuming. Therefore, it is easy to iterate on acoustic parameters until reaching satisfactory results. Figure 7: Beam tracing (left: a beam, right: adaptive subdivision of a beam) In case of vibrating area sources, the shooting is done from the receivers points, until the beams catch the area source. Volumic paths are then stored. As a second stage FRFs are computed by assigning acoustic properties to the geometry. 4.2 External noise simulation method Previous work: The first method that was expected to be used to solve the problem was the GRIM method [3]. It allows precise computation of the pressure at any point inside a volume. The main advantage of this method is its computation time since beam tracing (as implemented in ICARE software) is very fast at handling area sources. A beam intersecting a boundary surface does not have to be discretized (as opposed to using point sources). Prediction of Acoustic Comfort of a Trainset using Ray-Tracing Technology Page 3/8

4 Unfortunately this method cannot be used here as only a coarse mesh of pressure levels in octave thirds on the outer surface is available. Furthermore a lost of phase in the velocity field (module only) leads the pressure to tend toward zero as frequency increases. As a consequence, a simplified half-energetic method derived from Faurecia's Vehicle Acoustic Synthesis Method [4] was used. External sources to internal sources: The external noise is described by sparse parietal pressures {p ext } on a set of panels of the car. For each panel of surface S : First the incident power from these pressures is computed with a diffuse field hypothesis with W ext = (p ext ² S) / (4 c) Second, this power is transmitted using the transmission loss of the underlying panel with W int = τ W ext (TL = -10 log τ) Third this internal power W int is dispatched on point sources meshes on the inside of the panel. Each of these sources will be uncorrelated to the others. material to geometry, is under control in a numerical environment) and it also served to set up the final method. A first stage was to determine whether or not to use uncorrelated sources inside the volume. As expected, it has been shown that uncorrelated sources give better results, otherwise leading to unrealistic interferences. Virtual Test case: The test case (see figure 9) is a 3x3x2.5 m 3 unbaffled volume, 1 m above a rigid ground. The lower wall is made of 10 mm steel, the upper wall of 3 mm steel. The front and back walls are rigid. The left and right walls are made of 10 mm glass. The external point source is between the lower wall and the ground. Figure 9: Numerical validation case Figure 8: External pressure to internal power sources The process is detailed on figure 8. Each internal source lies exactly on the boundary of the panel so it has to take into account the reflection on this panel. Two strong hypotheses are made: a diffuse incoming power and an uncorrelated internal pressure field on the walls. These restrictions will be discussed in the next paragraph. 4.3 A numerical-to-numerical validation stage of the method This validation stage was done using exact analytic or simulation methods on a virtual simplified case. This was done in order to avoid risky direct comparisons with measures (everything, from Validation process: The four walls are independent each one from the other and no physical link exists between them. The validation process is to: a) compute the incident pressure on the walls using an (exact) 2.5D BEM method [5], b) compute analytically the transmission losses with a modal approach [6], c) compute the internal pressure using method described in 4.2 with input data a) & b), d) compute a reference solution with modal calculation [7] using module and phase load on each wall. The results of c) and d) are compared for different points (M1, M2, M3, M4) inside the volume. Results: The error between the exact solution [2] and the method implemented in OSCAR is shown on figure 10. The latter method always overestimates the internal pressure and gives better results for mid and high frequencies. Prediction of Acoustic Comfort of a Trainset using Ray-Tracing Technology Page 4/8

5 solution is the better since that way each panel will be discretized into at least one source, allowing us to take into account thin noisy sources such as joints between doors. The study has shown that an optimal value for the mesh step exists, and that it is not necessary to use finer meshes: lower meshing steps will increase the number of sources (then the computation time) without any precision increase. Figure 10: Errors between OSCAR and exact solution [2] Results inside a tunnel: The previous model is now placed inside a tunnel (see figure 11). Figure 11: Test case in a rigid tunnel The method implemented in OSCAR now gives better results as shown on figure 12. This is mostly due to the incident field being more diffuse, hence the incident power estimation being more accurate. Figure 12: Errors between OSCAR and exact solution [2] in a tunnel As a consequence the chosen method (OSCAR) gives acceptable results so studies can be continued further with real cases validation. 4.4 Optimized implementation of internal radiation Meshing step: The quality of the results depends on the meshing step of the panels into point sources. A regular meshing of the whole volume (by projecting regular grids on the geometry) or a meshing of each panel independently can be imagined. The latter Figure: 13: Interior SPL convergence versus panelinto-sources-meshing step Reflection depth: considering the average absorption of a car it has been hinted that including too many reflections in the model does not give more precision and increases computational time. Sources on wall tuning: In a case with a lot of point sources on walls (up to thousands) and few receivers, the beam-tracing computation is done backward from the receivers to the sources. Since the sources are exactly on the walls they are oriented to gather paths only from the inside of the car. A link is kept from the geometry (the panels) to the sources. It means that when a beam hits a panel it knows which sources are on the panel and potentially inside the beam. As a consequence the process is much faster than classical beam-tracing and has the same speed advantages as using area sources like in GRIM method. For instance for a car with 494 panels (meshed into 744 points sources) and 9 receivers, with 3 reflections, calculation time fall from 59 mn to 5 mn 38 sec from the basic software to the dedicated one (for about 200,000 paths), the speed increase being about 90%. This link between the panel and the sources also allows to handle the reflection coefficient more precisely using the incident angle if needed. Prediction of Acoustic Comfort of a Trainset using Ray-Tracing Technology Page 5/8

6 4.5 Full process integration The computation of the impulse response between speakers and passengers ears inside a train car can be directly done using the ICARE software with its statistical reverberation extension [7]. The background noise is generated from the previously computed noise level spectrum. A narrow band white noise is generated then normalized to fit the noise level in octave thirds. Its impulse response is then computed and added to the speaker-to-ear IR (see figure 14). This complete IR can be used to compute room acoustics criteria such as reverberation time (RT), speech transmission index (STI) or rapid speech transmission index (RASTI) [8]. These criteria are useful for the qualification of the intelligibility in the car. Figure 15: Photo of Athens Metro 5.1 Preliminary measurements Some preliminary measurements on the metro were compulsory in order to have good inputs to set in OSCAR, so as to be sure that the only influent parameters is OSCAR s calculation. Room absorption Figure 14: echogram from a speaker to a passenger ear : without (green, RASTI = 0.67) and with background noise (red, RASTI = 0.56) All the process has been fully automated. As a result the only user time consuming step is the panel to parietal pressure levels / transmission losses / internal absorption coefficients assignments. 5. Validation of OSCAR in full scale Paragraph 4.3 explains the numerical model that was used by CSTB to validate the model implemented in OSCAR. Further validation, performed by Vibratec, was done on a full scale train which was Athens metro. Room absorption of the train was estimated using Sabine formula from reverberation time measurement, and from longitudinal acoustic waves decay. Panels Transparency Losses Transparency losses are measured directly on the train with an intensity probe. External Wall Pressures Some sets of microphones were placed on various sections of the trains to get the real external load. 5.2 OSCAR model The geometry is representative of the car, and internal elements are not included (seats ). Figure 16: Geometric model Prediction of Acoustic Comfort of a Trainset using Ray-Tracing Technology Page 6/8

7 5 db All inputs are set (room absorption, transparency losses, wall pressures). The calculation case correspond to a speed of 65 km/h inside a tunnel. 5.3 Results for internal noise The above figure shows the pressure level measured (in blue) and simulated by OSCAR (in red and green, corresponding to reflection depths of 8 and 6) in the train. 5.4 Discussion The results are very satisfactory. At a given frequency, the mean difference between experiment and computational results is about 1 db. At low frequencies (below 200 Hz), greater errors appear. They can be explained by two phenomena: OSCAR does not take into account structure borne noise The hypothesis of diffuse acoustic field below 200 Hz is not valid. The modal behaviour of the car is neglected. 5.5 Validation for internal source 5 db To validate internal sources, the acoustic power of one HVAC was directly measured under the equipment. To do so, an intensity probe and the guidelines of ISO 9614 are used to get the power of the bottom part (supply air ducts) of the unit. This part is the roof of the cab. A mesh of 6 elements was used during the intensity measurements, and the spectra of those 6 grid elements were declared as being internal sources on the roof in OSCAR. The results are compared with measurements done in the cab. 5 db Lp (db) 10 db Oscar Measurement Figure 18: Noise spectrum (OSCAR vs. Experiment) in a tramway cab 800 F (Hz) Figure 17: Noise spectrum at three locations inside the train (front, middle and back of the car) The global pressure level is exactly the same, the mean difference at a given frequency being about 3 dba. The results are satisfactory, with greater difference between 200 and 315 Hz. A possible explanation for differences is the way the HVAC was mounted: rigid on the test bench, and on resilient mountings in the train. Prediction of Acoustic Comfort of a Trainset using Ray-Tracing Technology Page 7/8

8 6. Comparison SEA / Ray-tracing The last stage of the present paper is a comparison between SEA method and ray-tracing (OSCAR) that was done during the validation stage of OSCAR is presented for a tramway application. The same inputs were used for both cases. Lp (db) 10 db Oscar AutoSEA F (Hz) Figure 19: Cab noise under the HVAC of a tramway, experimental and measured The global pressure level is found to be the same. The external pressure load shows a pure tone at 630 Hz which is more audible with SEA method (adjacent octave thirds are lower). There are no experimental results available for this case, but comparisons with SEA results obtained for Athens metro shows that OSCAR is closer to the experiment than SEA. 7. Future work Further validation remains to be done for internal noise predictions, on various materials (metros inside tunnels, very high speed trains, such as AGV ). Moreover, intelligibility predictions are not yet validated. Comparison between measurement of the audio system of a train and OSCAR calculations will be performed. People to people talk will also be checked (RASTI calculations). 8. Conclusion Nowadays, OSCAR is fully operative and is a good alternative to SEA. Its main advantages are its fastness for building new models (2 days are enough for a full model, one week for SEA), its interactivity and its accuracy. It is dedicated to Alstom s needs, and therefore, doing parametrical studies is really easy and fast, for instance choosing the best absorption for the roof of a train, or the insulation of a gangway tunnel to reach noise targets. Its validation took place first numerically by CSTB, and then experimentally by Vibratec and Alstom Transport. Results proved to be very satisfactory. 9. Acknowledgement The authors acknowledge the contribution of the Vibratec society for its testing and advising during the development stage of the operational tool 10. References [1] F. Gaudaire, N. Noé, J. Martin, P. Jean, D. van Maercke: "Une méthode de tirs de rayon pour caractériser la propagation sonore dans les volumes complexes", in proceedings of Confort Automobile et Ferroviaire, Le Mans, France, [2] P. Jean, N. Noé, F. Gaudaire: "Calculation of Tyre Noise Radiation with a Mixed Approach", Acta Acustica united with Acustica, Volume 94, [3] P. Jean: "Coupling integral and geometrical representations for vibro-acoustical problems", Journal of Sound and Vibration, Volume 224, pp , 1999 [4] A. Duval, J.F. Rondeau, R. Bossart, G. Deshayes, F. Lhuillier: "Vehicle Acoustic Synthesis Method 2 nd Generation: an effective hybrid simulation tool to implement acoustic lightweight strategies", in proceedings of SAE Noise and Vibration Conference and Exhibition, St Charles, IL, USA, May 2007 [5] P. Jean: "A variational approach for the study of outdoor sound propagation and application to railway noise", Journal of Sound and Vibration, Volume 226(2), pp , 1998 [6] P. Jean, J.F. Rondeau, "A simple decoupled modal calculation of sound transmission between volumes", Acta Acustica, Volume 88, pp [7] J. Martin and al: "Binaural simulation of concert halls: a new approach for the binaural reverberation process", JASA, Volume 96, pp , 1993 [8] T. Houtgast, H.J.M. Steeneken: "A review of the MTF concept in room acoustics and its use for estimating speech intelligibility in auditoria", JASA, Volume 77, pp , March 1985 [9] D.J. Thompson, "TWINS: a comprehensive theoretical model for railway rolling noise, Proceedings of the Dutch Acoustical Society (NAG), 139, 1997, AGV: BEM: FRF: IR: 11. Glossary Automotrice Grande Vitesse Beam Element Method Frequency Response Function Impulse Response RASTI: RApid Speech Transmission Index SEA: SPL: STI: TL: Statistical Energy Analysis Sound Pressure Level Sound Transmission Index Transmission Loss Prediction of Acoustic Comfort of a Trainset using Ray-Tracing Technology Page 8/8