Investigation and MASH Full-Scale Crash Testing of the Practice of Raising Blockouts on W-Beam Rail Systems

The Federal Highway Administration (FHWA) clarifies appropriate height measures for W-beam guardrails. Identification of existing locations where rail height is lower than recommended by FHWA is common. A research study was conducted to investigate the crashworthiness of raising blockouts on posts to restore barrier height and provide clarification on implementation of such methodology. The researchers evaluated the crashworthiness of raising blockouts by conducting a full-scale Manual for Assessing Safety Hardware (MASH) Crash Test 3-11 of a 28-in. W-beam guardrail system with composite blockouts raised 4 in. on posts. The 28-in. W-beam guardrail system with raised composite blockouts contained and redirected the 2270P vehicle, and it performed acceptably for MASH Test 3-11. The results of this study include guidance on the procedure for raising blockout mounting height on steel posts to achieve recommended rail height for a W-beam guardrail.

Comparison of Cabin Noise of Airport Express Rail Systems

In this paper, the cabin noise of four airport express rail systems, namely the Taiwan Taoyuan International Airport MRT, the Hong Kong Airport Express, RER B service from Paris Gare du Nord to Paris Charles de Gaulle Airport, and the Shanghai Maglev, have been measured. These four airport express rail systems have different specifications and maximum speeds, ranging from 100 to 300 km/h. The results show a significant low-frequency noise content below 100 Hz, which would not be captured if the measurements were conducted in dB(A). The difference between Leq in terms of dB(C) and dB(A) ranges from 11.3 to 17.0 dB. The maximum speed of the Taoyuan Airport MRT was found to be the lowest at 100 km/h and with the lowest Leq in terms of 66.4 dB(A) and 81.4 dB(C). The Shanghai Maglev has a maximum speed of 300 km/h but a relatively low Leq of 69.7 dB(A), although its top speed is almost three times the maximum of the other airport rail systems. It also has the lowest Lmax of 73.1 dB(A) among the four rail systems. Moreover, the Paris RER B railway system, with its top speed of 120 km/h, was measured to have the highest Leq and Lmax values of 72.8 dB(A) and 83.8 dB(A), respectively.

A Novelty Energy Storage Algorithm for High Speed Trains: Economical and Energy Saving Evaluation

Increasing the utilization rate of regenerative braking energy in rail systems is one of the ongoing applications increasing in significance in recent years. This study develops a novelty algorithm within the scope of this objective and provides the calculation of the regenerative braking energy recovery rate and then making a decision for storage or back to grid of this energy. Afterwards, the regenerative braking energy was calculated with the help of this algorithm for Eskisehir-Ankara and Ankara-Eskisehir trips in two different passengers (load) scenarios, using the YHT 65000 high-speed train, which was chosen as a case study. Then, with a decision maker added to this classical regenerative braking energy algorithm, it will be decided whether this energy will be stored or forward back into the grid for the purpose of providing non-harmonic energy to the grid.

Calibration of On-Board Energy Measurement Systems Installed in Locomotives for AC Distorted Current and High Voltage Waveforms and Determination of Its Uncertainty Budget

Periodic calibrations of Energy Measurement Systems (EMS) installed in locomotives must be carried out to demonstrate the required accuracy established in the EN 50463-2 standard according to European Parliament and Council Directive 2008/57/EC on the interoperability of rail systems within the Community. As a result of the work performed in the “MyRailS” EURAMET project an AC calibration facility was developed consisting of a fictive power source was developed. This fictive power source can generate distorted sinusoidal voltages up to 25 kV-50 Hz and 15 kV-16.7 Hz as well as distorted sinusoidal currents up to 500 A with harmonic content up to 5 kHz or phase-fired current waveform stated in EN50463-2 standard. These waveforms are representative of those that appear during periods of acceleration and breaking of the train. Reference measuring systems have been designed and built consisting of high voltage and high current transducers adapted to multimeters, which function as digital recorders to acquire synchronized voltage and current signals. An approved procedure has been developed and an in-depth uncertainty analysis has been performed to achieve a set of uncertainty formulas considering the influence parameters. Different influence parameters have been analyzed to evaluate uncertainty contributions for each quantity to be measured: rms voltage, rms current, active power, apparent power and non-active power of distorted voltage and current waveforms. The resulting calculated global expanded uncertainty for the developed Energy Measuring Function calibration set up has been better than 0.5% for distorted waveforms. This paper is focused on presenting the complete set of expressions and formulas developed for the different influence parameters, necessary for uncertainty budget calculation of an Energy Measuring Function calibration.

Linking Incidents to Customers (LINC): An Algorithm for Linking Incidents to Rail Customer Delays Inspired by Traffic Flow Theory

Rail transit agencies have greatly advanced the ability to measure delays to rail system customers and have developed key performance indicators for rail systems based on customer travel time. The ability for operators to link these customer delay metrics to root causes would provide great benefit to agencies, from incident response improvement to capital program prioritization. This paper describes a method for linking late train arrivals to both late customers and incident tickets. Inspired by traffic flow theory, the method identifies impact zones in time and space that can then be linked to a potential root cause by way of incident tickets. This algorithm is currently under development by the Washington Metropolitan Area Transit Authority’s Office of Planning, and its outputs are being integrated into a variety of operations- and capital-related business processes.

Multi-Source Coupling Based Analysis of the Acoustic Radiation Characteristics of the Wheel–Rail Region of High-Speed Railways

Based on elastic mechanics, the fluid–structure coupling theory and the finite element method, a high-speed railway wheel-rail rolling-aerodynamic noise model is established to realize the combined simulation and prediction of the vibrations, rolling noise and aerodynamic noise in wheel-rail systems. The field test data of the Beijing–Shenyang line are considered to verify the model reliability. In addition, the directivity of each sound source at different frequencies is analyzed. Based on this analysis, noise reduction measures are proposed. At a low frequency of 300 Hz, the wheel-rail area mainly contributes to the aerodynamic noise, and as the frequency increases, the wheel-rail rolling noise becomes dominant. When the frequency is less than 1000 Hz, the radiated noise fluctuates around the cylindrical surface, and the directivity of the sound is ambiguous. When the frequency is in the middle- and high-frequency bands, exceeding 1000 Hz, both the rolling and total noise exhibit a notable directivity in the directions of 20–30° and 70–90°, and thus, noise reduction measures can be implemented in these directions.

Identification of High-Risk Driving Behavior and Sections for Rail Systems

Risk assessment is an important process for railway safety. Current practices for assessing the risks of driving behaviors aim to inspect the driving record generated by automatic train protection systems. This paper proposes an automatic process to access detailed data contained in driving data, and identifies six high-risk driving behaviors. The modules can assess the competency of drivers and evaluate the frequency of high-risk behaviors in each section. Moreover, an integrated risk index for driving behaviors is proposed to compare each driver and section. An empirical study for drivers and sections is performed to demonstrate the feasibility of applying the proposed modules in practice. Results reveal that 20% of high-risk drivers contribute to 74% of the total risk, while 15% of high-risk sections contribute to 80% of the total risk. The proposed modules identify the drivers and sections with high risk. By enabling the operators of railway systems to take countermeasures, this methodology could enable them to improve the safety of railway systems more efficiently.