Recently, there has been a large demand for predicting, in real time, the performance of multiple railroad vehicle types traversing existing track as the geometry of the track is being measured. To accurately predict a railroad vehicle’s response over a specified track requires the solution of nonlinear equations of motion and extensive calculations based on the suspension characteristics of the vehicle. To realize the real time goal, codes are being implemented that use linear approximations to the fully nonlinear equations of motion to reduce computation time at the expense of accuracy. Alternatively, neural network technology has the ability to learn relationships between a mechanical system input and output, and, once learned, give quick outputs for given input. The training process can be done using measured data or using simulation data. In general, measured data is very expensive to gather due to the instrumentation requirements and is most often not available. In this paper, the use of multibody simulation code as a training tool for a neural network is presented. The example results estimate the vertical and lateral forces at the wheel-to-rail interface as a function of the geometry of the track and the suspension characteristics of the vehicle type by using a multibody code with neural network technique.
In recent decades, there has been a considerable effort in improving railroad vehicle dynamic performance. This involves high operational speed with stable behavior, better curving performance, better ride quality, and increased life of the wheel and rail profiles. To achieve this goal, the use of independently rotating wheels (IRW) is proposed as one potential option. Using IRW either partially or totally decouples the pitch rotation of the two wheels of the “wheelset”, thereby reducing or eliminating the longitudinal creepage and thus wheelset hunting motion. On the other hand, the longitudinal creepage is no longer available to provide steering assistance in curves, and continuous flange contact during curving is expected. However, by judicious choice of wheel profile and careful truck design, the lateral force between wheel and rail during curving can be reduced, decreasing the wear on both the wheel and rail profiles. Therefore, such solution is assumed to achieve higher stable operational speed and improved curving behavior. In this paper, the effect of using IRW on railroad vehicle performance is examined. The equations of motion of a single wheelset model and a suspended wheelset model that use IRW are presented and compared with those for similar models that use a rigid wheelset. Using a newly developed general multibody code, a complete vehicle model that uses IRW is examined and compared with one that uses rigid wheelsets. The effect of the IRW system on vehicle dynamic performance is quantitatively presented. In addition, the ability of the contact formulations used in this multibody code for modeling the IRW system is confirmed.
The dynamic response of a railroad vehicle traveling at speed over track deviations can be predicted by using multibody simulation codes. In this case, the solution of nonlinear equations of motion and extensive calculations based on the suspension characteristics of the vehicle are required. Recently, the Federal Railroad Administration, Office of Research and Development has sponsored a project to develop a general multibody simulation code that uses an online nonlinear three-dimensional wheel-rail contact element to simulate contact forces between wheel and rail. In this paper, several applications to examine such issues as critical speed, curving performance at varying cant deficiencies, and wheel load equalization are presented to demonstrate the use of the multibody code. In addition, the application of the multibody code can be extended to train a neural network system. Neural network technology has the ability to learn relationships between a mechanical system input and output, and, once learned, give quick outputs for given input. The neural network can be combined with the use of a nonlinear multibody code to predict the performance of multiple railroad vehicle types in real time. In this paper, this system is briefly presented to shed light on the optimum use of the multibody code to prevent derailment.
The Federal Railroad Administration has been directing engineering studies to support the development of high speed track geometry standards. These standards are intended to cover train operating speeds from 110 mph to 200 mph. The studies conducted include evaluation of the use of measuring track geometry with offsets from several chord lengths, computer simulations of vehicle response to track surface and alignment variations, application of the proposed specifications to previously measured track geometry, and comparison of proposed specifications to foreign practice. The proposed standards use multiple chords to control surface and alignment geometry. Single isolated geometry variations are allowed greater amplitudes than three or more repeated geometry variations. The results of the engineering studies indicate that use of multiple chords is effective in controlling a wide range of geometry variation wavelengths, from less than 30 feet to greater than 250 feet. The computer simulation studies show that at high speed, wheel/rail interaction dominates vehicle response to short wavelength (less than ∼100 feet) alignment variations, while carbody motions dominate vehicle response to long wavelength variations. Derailment and carbody accelerations are the principal concerns in vehicle response to track geometry variations. Application of the proposed specifications to previous measurements of high speed track on the Northeast Corridor indicates a relatively modest number of exception locations (∼1 location every 3 miles). Comparison of the proposed specification with foreign practice indicates that the proposed specification provides a generally similar level of control of track geometry.
To conduct the testing and evaluation of railway and railway vehicles, the Federal Railroad Administration (FRA) developed a portable system that consists of accelerometers oriented in the vertical and horizontal directions, a GlobalPositioning System (GPS) receiver, data collection and power systems, and a portable computer. Commercial software was used to collect and display the data, while software, developed by ENSCO, was used to analyze and display results. The GPS provided dynamic location to an accuracy of 30 meters or better, and vehicle speed to within one mile per hour. The system was used in the demonstration tests of several advanced high-speed trains on Amtrak's Northeast Corridor (NEC) and on other track in the U.S. The portable measurement system proved to be a simple and effective device to characterize the vibration environment of any transportation system. It is ideal for use in the assessment of the safe performance of high-speed trains operating at high cant deficiency. The system has also been used for other field tests, including braking performance and bridge monitoring. This report discusses the portable measurement system, the test applications that the system has been used for, the results of those tests, and the potential for improvements.
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