Brillouin Frequency Shift Sensing Technology Used in Railway Strain and Temperature Measurement

This study and verification are based on the Brillouin frequency shift (BFS), which is related to the strain and temperature changes of a single-mode fiber, because such a shifted frequency can be quantitatively measured and converted to strain and temperature differences. We explain the installation of a Brillouin distributed fiber sensing system (DFOS) on an actual operating railway to measure the temperature and strain of the rail. In addition, the measured data were calculated and analyzed, revealing the geometric irregularity of the tested rail and the location of the abnormality. We obtained a temperature difference of 12.1 °C between the temperature distribution of the measured rail and the atmospheric temperature, and there was a 1.5 h delay between the two. We also obtained rail irregularities ranging from −0.3 to +0.4 mm by calculating the slight strain difference of the rail in this test.

Prediction of Theoretical Derailments Caused by Cross-Winds with Frequency

In this paper, theoretical derailment equations for cross-wind with frequency were derived to assess running safety. For a KTX (Korean high-speed train) unit, the wheel unloading ratios, which are the criteria for evaluating derailments in UIC (International union of railways) and TSI (Technical Specification for Interoperability) regulations, were calculated through the formula under the driving regulations according to cross-wind speeds, and the theoretical results were compared and evaluated through a multibody dynamics (MBD) simulation. In addition, the wheel unloading ratios were calculated for various frequencies of cross-winds. As a result of the formula and MBD, the wheel unloading ratios were shown to increase rapidly regardless of the dampers in suspension when the cross-wind frequency and the natural frequency of a vehicle were in agreement. Finally, we calculated the changes of wheel unloading ratio for different track gauges and found that these theoretical equations could calculate more accurate results than the existing Kunieda’s formula. The formula derived in this study has the advantage of considering various variables, such as fluctuant cross-winds, rail irregularities, and derailment behaviors, which were not considered in previous studies or Kunieda’s formula. It could be used for setting suspensions or railway vehicle specifications in the initial design stage.

Earthquake Influence on the Rail Irregularity on High-Speed Railway Bridge

Rail irregularity is the leading cause of enhancing train-track coupling vibration and, therefore, should be studied in detail for safety requirements. In this study, the differences between existing rail irregularities without being subjected to an earthquake between different countries were first studied. Results show that existing power spectrum density and time-domain displacement samples of rail irregularities in the American code are the largest, while the irregularities of the Germany railway are higher than those of China in a specific range of rail wavelengths. Afterward, the effects of earthquake intensity, soil site, and duration on the rail irregularity of a Chinese typical high-speed railway bridge were investigated. For this purpose, a finite element model was established and validated by the shaking table test of a 1/12-scaled high-speed railway bridge experimental specimen. The calculation results indicated that the influences of earthquakes on the rail alignment irregularity were evident.

Estimating Exceedance Probabilities of Railway Bridge Vibrations in the Presence of Random Rail Irregularities

This contribution addresses the estimation of exceedance probabilities of the dynamic random response of railway bridges subjected to high-speed trains in the presence of random rail irregularities. The random nature of the irregular rail track is described by a spatial ergodic stochastic process, and consequently the dynamic bridge response becomes a stochastic process in time with generally unknown distributions. Using numerical simulation methods, the response thresholds for bridge deflection and acceleration are estimated to obtain small exceedance probabilities. Combining these limits with the response at perfect rail geometry provides an estimate of the dynamic response amplification due to random rail irregularities. This is in line with the semi-probabilistic safety concept of modern civil engineering, where critical response thresholds for structures are associated with small exceedance probabilities. It is shown that modeling the maximum bridge deflection as a normally distributed random variable with parameters fitted to the results of a Monte Carlo simulation with small sample size is a computationally efficient approach for estimating the amplified deflection. In contrast, the random maximum bridge acceleration is better captured by a lognormal distribution. As an efficient alternative, the subset simulation method provides accurate predictions for very small exceedance probabilities. If the amplitudes of the rail irregularities at discrete spatial coordinates along the rail axis are considered as random variables, the stability of subset simulation increases.

Determination of wheel loading reduction in railway track with unsupported sleepers and rail irregularities

This study investigates the simultaneous effects of unsupported sleepers and rail random irregularities on track displacement and wheel load reduction, by means of numerical simulations with vehicle-track coupling. Vehicles are simulated as multibody systems comprising the major vehicle masses and suspension systems with nonlinear stiffness and damping. Flexible track with rail, sleeper and ballast components is considered using finite element and multibody programs. Numerical results of the simulations are in good agreement with field test measurements. Findings show that in tracks with less than four unsupported sleepers the vehicle is able to move at a speed of 110 km/h; with a higher number of unsupported sleepers the vehicle is vulnerable to derailment. The vehicle speed has no effect on the maximum rail displacement in tracks with less than four unsupported sleepers.

Random Characteristics of Vehicle-Bridge System Vibration by an Optimized Pseudo Excitation Method

The pseudo excitation method (PEM) is improved for its efficiency by incorporating the self-adaptive Gauss integration (SGI) technology as a new combining integration. The PEM can transform the random rail irregularities into some pseudo harmonic excitation, which is a mature approach to deal with the random excitation for vehicle–bridge systems. The SGI was used to distinguish the significant from the insignificant parts of an integral section for the random excitation frequency on the stochastic response of the system, thereby reducing the computational effort required for the random vibration analysis of the system. Also, the SGI can intelligently handle the recognized integral section, by subdividing the important sections into several necessary frequency points, making rough decomposition, and allowing the unimportant regions to be eliminated. Based on selected frequency points, the deterministic pseudo harmonic excitations were generated, and then the standard deviation (SD) of the time history for the system was calculated by the PEM. The vehicle subsystem was simulated as a 23-degree of freedom model, and the bridge subsystem as a three-dimensional finite element model. The time-varying power spectral density (PSD) plots of the system were presented. Besides, the cumulative distribution function (CDF) of the response was calculated using Poisson’s crossing assumption. The random characteristics for the vehicle–bridge vibrations for different speeds and rail irregularities were calculated.