A STATISTICAL APPROACH TO EVALUATING WHEEL-RAIL CONTACT DYNAMICS

被引:0
|
作者
Hosseini, SayedMohammad [1 ]
Ahangarnejad, Arash Hosseinian [1 ]
Radmehr, Ahmad [1 ]
Tajaddini, Ali [2 ]
Ahmadian, Mehdi [1 ]
机构
[1] Virginia Tech, Ctr Vehicle Syst & Safety CVeSS, Railway Technol Lab, Blacksburg, VA 24061 USA
[2] Fed Railroad Adm, Off Res Dev & Technol, Washington, DC USA
来源
PROCEEDINGS OF THE 2021 JOINT RAIL CONFERENCE (JRC2021) | 2021年
关键词
Statistical modeling; contact dynamics; parametric regression; longitudinal traction force; wheel load; angle of attack (AoA); creepage; ANGLE;
D O I
暂无
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
This paper provides a statistical analysis of the effects of wheel load, angle of attack (AoA), and creepage on longitudinal traction force at the wheel-rail contact using experimental data collected on the Virginia Tech-Federal Railroad Administration (VT-FRA) Roller Rig. The VT-FRA Roller Rig is a unique piece of equipment designed and built with the specific goal of evaluating the wheel-rail contact mechanics and dynamics with a high degree of precision. Longitudinal fraction forces are of great importance to the railroad industry since they provide the motive power needed to move a train. Various experiments are conducted in different settings to study the relationship between the aforementioned variables and the longitudinal traction force. The test data is split into "training" and "testing" sets, and the training sets (a total of four) are used to entertain statistical models in a standard parametric regression framework. The study carefully assesses whether the assumptions of the classical linear regression model hold by studying the empirical histogram and the normal Q-Q plot of the residuals. In the case of non-linearities, different transformations are applied to the explanatory variable to find the closest functional form that captures the relationship between the response and the explanatory variables. The developed models are then compared with their non parametric counterparts such as natural cubic splines in terms of goodness of fit, and prediction error on the testing set. The study develops regression models that are able to accurately explain the relationship between longitudinal traction and creepage and AoA. The models are intended to be used for predicting traction under various operating conditions.
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页数:9
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