Benchmarking railway vibrations – Track, vehicle, ground and building effects

This paper presents a multiphysics modeling of a switched reluctance motor (SRM) to simulate the acoustic radiation of the electrical machine. The proposed method uses a 2-D finite-element model of the motor to simulate its magnetic properties and a multiphysics mechatronic model of the motor and controls to simulate operating conditions. Magnetic forces on the stator are calculated using finite-element analysis and are used as the excitation on a forced response analysis that contains a finite-element model of the motor stator structure. Finally, sound power levels are calculated using the boundary element method. Simulation results of the model are shown and compared with experimental measurements for a four-phase 8/6 SRM.

Multiphysics NVH Modeling: Simulation of a Switched Reluctance Motor for an Electric Vehicle

SUMMARY Broad-band urban seismic noise (USN) must be considered as a temporally and spatially non-stationary random process. Due to the high variability of USN a single measure like the standard deviation of a seismic noise time-series or the power spectral density at a given frequency is not enough to characterize a sample (time-series) of USN comprehensively. Therefore, we use long-term spectrograms and propose an automated statistical classification in the time domain to quantify and characterize USN. Long-term spectrograms of up to 28 d duration are calculated from a broad-band seismic data set recorded in the metropolitan area of Bucharest, Romania, to identify the frequency-dependent behaviour of the timevariable processes contributing to USN. Based on the spectral analysis eight frequency ranges between 8 mHz and 45 Hz are selected for our proposed time domain classification. The classification scheme identifies deviations from the Gaussian distribution of 4-hr-long timeseries of USN. Our classification is capable to identify Gaussian distributed seismic noise timeseries as well as time-series dominated by transient or periodic signals using six noise classes. Four additional noise classes are introduced to identify corrupt time-series. The performance of the method is tested with a synthetic data set. We also apply the statistical classification for the data set from Bucharest in three time windows (0–4, 8–12 and 13–17 EET) at 11 d in the eight frequency ranges. Only 40 per cent of the analysed time-series are observed to be Gaussian distributed. Most common deviations from the Gaussian distribution (∼47 per cent) are due to the influence of large-amplitude transient signals. In all frequency ranges between 0.04 and 45 Hz significant variations of the statistical properties of USN are observed with daytime, indicating the broad-band human influence on USN. We observe the human activity as a dominant influence on the USN above and below the frequency band of ocean-generated microseism between 0.04 and 0.6 Hz. Our time domain classification and quantification is furthermore capable to resolve the influence of wind on seismic noise and a known site effect variation in the metropolitan area of Bucharest. The information about noise amplitudes and statistical properties derived automatically from broad-band seismic data can be used to select time windows containing adequate data for seismic noise utilization like H/V-studies or ambient noise tomography.

Time domain classification and quantification of seismic noise in an urban environment

Measurement and prediction of train-induced vibrations in a full-scale building

The aim of this paper is to provide a comprehensive overview of the state of the art on railway-induced ground vibration. The governing physical mechanisms, prediction methods, and mitigation measures of ground-borne vibration are discussed, with focus on low frequency feelable vibration and the case of railway traffic at grade. In order to clarify the importance of quasi-static and dynamic excitation, the basic problems of a moving load with constant magnitude and harmonic magnitude are discussed first. Dynamic excitation due to wheel and track unevenness and parametric excitation is shown to be the dominant source of environmental vibration in most cases. Next, an overview of prediction methods for ground-borne vibration is given. The advantages and limitations of numerical methods, based on physical or mechanical models, and empirical models, derived from measured data, are discussed. Finally, the mitigation of railway-induced ground vibration is considered, where the focus goes to mitigation measures at source (wheel and rail unevenness, rolling stock, track) and measures on the transmission path (trenches and barriers, wave impeding blocks, subgrade stiffening, and heavy masses next to the track). In conclusion, a number of open points requiring further research is given.

Ground-Borne Vibration due to Railway Traffic: A Review of Excitation Mechanisms, Prediction Methods and Mitigation Measures

Numerical modelling of ground-borne noise and vibration in buildings due to surface rail traffic

A numerical prediction model is developed to quantify vibrations and re-radiated noise due to underground railways. A coupled FE-BE model is used to compute the incident ground vibrations due to the passage of a train in the tunnel. This source model accounts for three-dimensional dynamic interaction between the track, tunnel and soil. The incident wave field is used to solve the dynamic soil-structure interaction problem on the receiver side and to determine the vibration levels along the essential structural elements of the building. The soil-structure interaction problem is solved by means of a 3D boundary element method for the soil coupled to a 3D finite element method for the structural part. An acoustic 3D spectral finite element method is used to predict the acoustic response. The Bakerloo line tunnel of London Underground has been modelled using the coupled periodic FE-BE approach. The free-field response and the re-radiated noise in a portal frame office building is predicted.

A Numerical Model for Re-radiated Noise in Buildings from Underground Railways

Numerical evaluation of source–receiver transfer functions with the Fast Multipole Boundary Element Method for predicting pass-by noise levels of automotive vehicles

Head related transfer functions (HRTF) are used in 3D auralization to synthesize binaural sound from a monaural source. In our paper, we present a Fast Multipole Boundary Element (FMBEM) method used to simulate the pressure field scattered from a dummy head and torso mesh illuminated by incident wave fields from different directions. The FMBEM implementation is based on the diagonal form of the acoustic Green’s function’s multipole expansion. This method is optimal for high frequencies, and reduces to a conventional BEM in the lower frequency range. For the case of scattering problems with complex sources, often several excitations need to be modeled which is computational demanding. In the paper we present an SVD based reduction method to reduce the number of independent RHS vectors and to adjust the tolerances for optimal performance. The modeled HRTFs are validated by comparison to conventional BEM results in the lower frequency range and to measurement data in the range up to 10 kHz.

Fast multipole BEM modeling of head releated transfer functions of a dummy head and torso

This paper studies the feasibility of acquiring the multiple source-receiver transfer functions for the prediction of pass-by noise Sound Pressure Level (SPL) of vehicles with the Fast Multipole Boundary Element Method (FMBEM). Employing measurements and simulations, the influence of frequency resolution, mesh density, mesh accuracy and solver accuracy on the computation time and on the overall SPL and the third octave band SPL is investigated. It is concluded that pass-by noise estimates with an accuracy of about 4 dB within a computation time of less than one day can be achieved in the near future.

peter fiala

Papers

Numerical modelling of ground-borne noise and vibration in buildings due to surface rail traffic

A Numerical Model for Re-radiated Noise in Buildings from Underground Railways

Numerical evaluation of source–receiver transfer functions with the Fast Multipole Boundary Element Method for predicting pass-by noise levels of automotive vehicles

Fast multipole BEM modeling of head releated transfer functions of a dummy head and torso

Simulation of pass-by noise of automotive vehicles in the mid-frequency range using Fast Multipole BEM