Prediction Model for the Environmental Noise Distribution of High-Speed Maglev Trains Using a Segmented Line Source Approach
Source abstract
Abstract
Based on the theory of uniform finite-length incoherent line source radiation and real vehicle online test data of Shanghai Maglev trains, a prediction model for environmental noise is established using an equivalent segmented line sound source approach. The noise produced by Shanghai high-speed Maglev trains running at speeds of 235, 300, and 430 km/h is tested and analyzed using microphones. The test data are combined with computational fluid dynamics simulations to divide the train’s sound sources equally into five sections. Theoretical calculations are carried out on the noise test data collected as the train passes by, and the source strength of each individual sub-sound source during the train operation is determined using the least-squares method. As a result, a prediction model for the environmental noise of high-speed Maglev trains, represented as a combination of multiple sources, is developed. The predicted results are compared with the measured values to validate the accuracy of the model. The proposed model can be used for environmental assessments before new train lines are launched, allowing for appropriate mitigation measures to be taken in advance to reduce the impact of Maglev noise on the surrounding residential and ecological environments.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Aerodynamics and Fluid Dynamics Research · Vehicle Noise and Vibration Control · Acoustic Wave Phenomena Research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Institute of Acoustics, School of Physics Science and Engineering, Tongji University, Shanghai 200092, China
School of Urban Railway Transportation, Shanghai University of Engineering Science, Shanghai 201620, China
CRRC Zhuzhou Times New Material Technology Co., Ltd., Zhuzhou 412007, China
Funding
Major Strategic Projects of The Chinese Academy of Engineering · CRRC Academy
References (23)
Show source-provided references
1. Prascevic, M., Gajicki, A., Mihajlov, D., Zivkovic, N., and Zivkovic, L. (, January Timişoara,). Application of the prediction model “SCHALL 03” for railway noise calculation in Serbia. Proceedings of the 12th International Symposium Acoustics and Vibration of Mechanical Structures, 23–24 May 2013.10.4028/www.scientific.net/AMM.430.237 ↗
2. Bundesbahn, D. (1990). Richtlinie zur Berechnung der Schallimmissionen von Schienewegen, Schall03/Akustik03.
3. The New German Prediction Model for Railway Noise “Schall 03 2006”—Potentials of the New Calculation Method for Noise Mitigation of Planned Rail Traffic10.1007/978-3-540-74893-9_26 ↗
4. Monitoring, modeling, and mapping of rail-induced noise at selected stations in megacity Delhi10.1007/s13762-022-04529-6 ↗
5. Projected multifunctional hotel complex noise level prediction from railway trains passing (JSC ‘Russian Railways’ connecting branch section) with sound insulation measures development10.1088/1757-899X/753/2/022078 ↗
6. The problem of high-speed railway noise prediction and reduction10.1016/j.proeng.2017.05.086 ↗
7. A study on predicting shinkansen noise levels using the sound intensity method10.1299/jsmec.47.508 ↗
8. Kawahara, M., Hotta, H., Hiroe, M., and Kaku, J. (1997, January 25–27). Source Identification and Prediction of Shinkansen Noise by Sound Intensity. Proceedings of the 1997 International Congress on Noise Control Engineering, InterNoise97, Budapest, Hungary.
9. Schulte-Werning, B., Thompson, D., Gautier, P.E., Hanson, C., Hemsworth, B., Nelson, J., Maeda, T., and Vos, P. (2008). Environmental noise reduction of Tokaido Shinkansen and future prospect. Noise and Vibration Mitigation for Rail Transportation Systems, Springer.10.1007/978-3-540-74893-9 ↗
10. Hanson, C.E., Ross, J.C., and Towers, D.A. (2012). High-Speed Ground Transportation Noise and Vibration Impact Assessment.
11. (2018). Technical Guidelines for Environmental Impact Assessment of Urban Rail Transit (Standard No. HJ 453-2018).
12. Model of high-speed railway noise prediction based on multi-source mode
13. Brecher, A., Disk, D.R., Fugate, D., Jacobs, W., Joshi, A., Kupferman, A., Mauri, R., and Valihur, P. (2025, April 01). Noise Characteristics of the Transrapid TR08 Maglev System, Available online: https://rosap.ntl.bts.gov/view/dot/8507.
14. Research on Prediction of Noises of High Speed Railway Bridge
15. Mathematical, statistical and neural models capable of predicting LA,max for the Tehran–Karaj express train10.1016/j.apacoust.2008.11.003 ↗
16. Separation of turbulent pressure and acoustic pressure on a maglev train window and the contribution of interior noise at high speeds10.1016/j.apacoust.2024.110465 ↗
17. Two-equation eddy-viscosity turbulence models for engineering applications10.2514/3.12149 ↗
18. (2013). Acoustics-Railway Applications—Measurement of Noise Emitted by Railbound Vehicles (Standard No. ISO 3095:2013).
19. Sound generation by turbulence and surfaces in arbitrary motion
20. Acoustic perturbation equations based on flow decomposition via source filtering10.1016/S0021-9991(03)00168-2 ↗
21. (2012). Acoustics—Determination of Sound Power Levels and Sound Energy Levels of Noise Sources Using Sound Pressure—Precision Methods for Anechoic Rooms and Hemi-anechoic Room (Standard No. ISO 3745:2012).
22. (1993). Acoustics, Outdoor Sound Propagation Attenuation Part I: Atmosphere Sound Absorption Calculation (Standard No. ISO 9613-1:1993).
23. Mao, D., and Hong, Z. (2010). Environmental Noise Control Engineering, Higher Education Press.