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In this paper, the authors follow the work done by Lei and Noda [1], concerning the vertical interaction between railway vehicle and track, where random irregularities of track vertical profile are considered. A Matlab/Simulink simulator has been developed to simulate the vehicle dynamic response. The vehicle (upper part) is modeled as a multi-body...
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Context 1
... [ M ] track , [ C ] track and [ K ] track are the mass matrix, the damping matrix and the stiffness matrix of the considered track portion. [ M ] track is a square matrix of dimension 4 × ( N elem +1), assembled using the 8 × 8 square mass matrix [ M ] elem for one element, as shown in Figure 3. The expression of [ M ] elem is given in [1] and can be obtained using d’Alembert’s principle. [ M ] elem is the sum between a mass matrix resulting from beam element and a mass matrix resulting from sleepers and ballast. It is function of ρ , A , l , m and m . The global stiffness matrix [ K ] track is assembled similarly to [ M ] track , but using [ K ] elem instead of [ M ] elem . [ K ] elem is function of K x1 , K y1 and K y2 , of I (moment of inertia of the rail with respect to z axis), E (module of elasticity), A s and l . The same for [ C ] track , assembled using the 8 × 8 square damping matrix [ C ] elem for one element, where [ C ] elem depends mainly of C x1 , C y1 and C y2 .The matrices [ K ] track and [ C ] track can be also found in ...
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Citations
... In 1992, Zhai Wan-ming [1] firstly explored the vehicle and track structure as a whole system and established the vertical vehicle-track unified model by adopting the system engineering approach, laying a foundation for the vehicle-track coupled system dynamics. Later, Popp [2] and Dumitriu [3] together with many other scholars conducted more in-depth studies on this model, contributing to its wide recognition and rapid development. Thus, the vehicle-track coupled system dynamics also became a new research field to be explored. ...
According to time-temperature superposition (TTS) and WLF formula, the temperature-dependent and frequency-dependent kinetic parameters of the railpads of WJ-7 fasteners were predicted based on the experimental results at a certain frequency and under the different temperatures. By combining the pseudo excitation method and symplectic mathematics scheme, the impact of railpads frequency-dependent and temperature-dependent stiffness on the random variation of the coupled vehicle-track system was investigated efficiently. The results suggest that, within the range of environment temperature and frequency-dependent extent of railpads in the railway, the PSD peak of the vertical random vibration acceleration of the wheelsets and rail gets the largest increase of 3.3 times at least, and the increment of their 1st dominant frequency also reaches up to 20.6 Hz or more. Therefore, in order to accurately analyze the random vibration responses of the vehicle-track coupled system, experiments must be conducted to obtain the accurate kinetic parameters of the polymer materials like railpads.
This research is intended to develop a FEM-based riding comfort optimization approach to the railway trains considering the coupling effect of vehicle-track system. To obtain its accurate dynamic response, the car body is modeled with finite elements, while the bogie frames and wheel-sets are idealized as rigid bodies. The differential equations of motion of the dynamic vehicle-track system are derived considering wheel-track interaction, in which the pseudo-excitation method and the symplectic mathematical method are effectively applied to simplify the calculation. Then, the min-max optimization approach is utilized to improve the train riding comfort with related parameters of the suspension structure adopted as design variables, in which 54 design points on the car floor are chosen as estimation locations. The K-S function is applied to fit the objective function to make it smooth, differentiable and have superior integrity. Analytical sensitivities of the K-S function are then derived to solve the optimization problem. Finally, the effectiveness of the proposed approach is demonstrated through numerical examples and some useful discussions are made.
