Master of Philosophy
School of Mechanical, Materials, Mechatronic and Biomedical Engineering
Wang, Chao, Wheel rail curve squeal modeling & rolling stock based mitigation measures, Master of Philosophy thesis, School of Mechanical, Materials, Mechatronic and Biomedical Engineering, University of Wollongong, 2015. http://ro.uow.edu.au/theses/4953
Railway curve squeal, on one hand, has long been held as an annoying environmental problem to the local community which increasingly demands effective technical countermeasure to alleviate its impact; on the other hand, it is a complex theoretical question involving nonlinear wheel-rail contact mechanics, rail vehicle curving dynamics, and vibration instability of the wheel-rail structure. Many factors affect the transient phenomena of curve squeal and a large amount of field monitoring data have been collected in the rail noise CRC projects in NSW. Due to the intrinsic perplexity of curve squeal, field data analysis leads to ambivalent conclusions regarding the influence of wheelset angle of attack (AOA), wheel-rail contact state, wheel-rail structure and mechanical properties on curve squeal. This ambivalence demands theoretical investigation and clarification since it is possible to analyse individual parameters and their combination on curve squeal through efficient computation methods. This thesis addresses part of this mystery through investigation of the causes of large wheelset AOA based on railway vehicle curving dynamics and investigation of wheel-rail parameters on curve squeal based on finite element method and complex eigenvalue analysis.
For the sensitivity analysis of key bogie parameters on wheelset AOA, a detailed freight wagon model has been built on the multi-body dynamics software, VAMPIRE®. Bogie parameters and their ranges in operating life have been collected through close industrial connection and carefully calibrated in terms of accuracy and availability. Individual bogie parameters and combination of major influencing factors on wheelset AOA have been simulated, analysed and ranked in terms of their relative importance. To be more specific, these important parameters include equivalent friction coefficient of the centre bowl, friction coefficient of the CCSB metal cap, warp stiffness between side frames and bolster, and setup height of CCSB. The worst case scenario of bogie parameters in regards to wheelset AOA is also identified and compared with field test wheelset AOA results. It would provide assistance for future rolling stock based curve squeal mitigation measures.
For the curve squeal prediction, a three dimensional wheel-rail contact and complex eigenvalue analysis model is built on the finite element software, ABAQUS. In the model, firstly, non-friction static contact is established under full axle load, then friction is introduced and a new contact state is searched under the constant sliding state. With this contact state as boundary condition, the friction induced damping effect on the vibration instability is evaluated during the subsequent complex eigenvalue analysis using the positive real part and negative effective damping ratio to indicate instability. Meanwhile, the wheel and rail mode shapes are visually checked to classify them into different categories and more importantly to identify the major vibration components in these unstable cases. The influence of individual parameters, such as wheel-rail friction coefficient, wheel rim thickness, lateral shift, rail support stiffness and damping, is discussed at first, and then combinations of wheel influencing factors, and different sliding directions between wheel and rail are incorporated. Together, this part of the study provides insight into the squeal mechanism under constant friction coefficient and constant sliding state, in contrast to the conventional analysis based on stick/slip and negative friction slope mechanism.