Characterization and Modelling of a New Heavy Axle Load Freight Wagon for Wheel Rail Wear Prediction

2014 ◽  
pp. 17-28 ◽  
Author(s):  
Guilherme Fabiano Mendonça dos Santos ◽  
Roberto Spinola Barbosa ◽  
Xinggao Shu ◽  
Curtis Urban ◽  
Richard Joy
Keyword(s):  
Wear Prediction ◽  
Rail Wear

ANALYTICAL METHODS FOR WHEEL AND RAIL WEAR PREDICTION

1986 ◽  
Vol 15 (sup1) ◽  
pp. 112-125 ◽  
Author(s):  
Robert H. Fries ◽  
Carlos G. Dávila
Keyword(s):  
Analytical Methods ◽  
Wear Prediction ◽  
Rail Wear

Criteria of bogie performance and wheel/rail wear prediction based on wayside measurements

Wear ◽  
2005 ◽  
Vol 258 (7-8) ◽  
pp. 1135-1141 ◽  
Author(s):  
Sergey M. Zakharov ◽  
Ilya A. Zharov
Keyword(s):  
Wear Prediction ◽  
Rail Wear

Rail Wear Simulation and Validation

2010 ◽  
Author(s):  
Xinggao Shu ◽  
Mark Dembosky ◽  
Curtis Urban ◽  
Nicholas Wilson
Keyword(s):  
Wear Test ◽  
Wear Prediction ◽  
Wear Process ◽  
Service Testing ◽  
Rail Wear ◽  
Calculation Methodology ◽  
Shape Effects ◽  
Test Zone ◽  
Wholly Owned Subsidiary ◽  
The Uk

Transportation Technology Center, Inc. (TTCI), a wholly owned subsidiary of the Association of American Railroads (AAR), has developed an iterative rail wear prediction model in the NUCARS® vehicle/track interaction multibody simulation program through internal research and development efforts and with funding from Network Rail (NR) in the UK. The rail wear model was built upon the NUCARS® penetration model1 to take advantage of the wheel/rail (W/R) contact calculation methodology for conformal W/R profiles. In addition to the advantages of NUCARS vehicle and track modeling capabilities, it modifies the rail profile online based on the Wear Indices (Tγ) and penetrated W/R profile shapes in the multipoint contact patches, and automatically updates the rail profile for the next run. The penetrated wheel profile segments or “wheel footprints” are blended into the modified rail profile. The worn rail shape eventually resembles the wheel shapes in the wheel database, and the wear process results in conformal W/R profile shapes. Rail wear prediction was validated using rail wear test results based on 515 million gross tons (MGT) of heavy axle load (39-ton (35-tonne) axle loads) freight traffic accumulated from 2003 to 2007 at the Facility for Accelerated Service Testing (FAST) on the nonground test zone (Section 25, 6-degree (291-meter (m)) curve with 5 inches (127 millimeter (mm)) superelevation). A wheel database, consisting of 50 measured new, mildly worn and heavily worn FAST train wheel profiles, was used to reflect the wheel shape effects during the wear process. This model has been used to predict rail relative wear trends of ground rail profiles for NR.2,3,4 A quantified W/R gap loss function has been implemented in NR’s Track-Ex© program5 for prioritizing rail grinding.

Analytical Methods for Wheel and Rail Wear Prediction

1985 ◽  
Vol 14 (1-3) ◽  
pp. 51-54 ◽  
Author(s):  
Robert H. FRIES ◽  
Carlos G. DÁVILA
Keyword(s):  
Analytical Methods ◽  
Wear Prediction ◽  
Rail Wear

Influence of rail flexibility in a wheel/rail wear prediction model

2016 ◽  
Vol 231 (1) ◽  
pp. 57-74 ◽  
Author(s):  
Javier F Aceituno ◽  
Pu Wang ◽  
Liang Wang ◽  
Ahmed A Shabana
Keyword(s):  
Prediction Model ◽  
Rigid Body ◽  
Contact Point ◽  
Three Dimensional ◽  
Contact Forces ◽  
Wear Model ◽  
Material Loss ◽  
Wear Prediction ◽  
Contact Points ◽  
Rail Wear

The aim of this paper is to study the influence of rail flexibility when a wheel/rail wear prediction model that computes the material loss based on an energy approach is used. The wheel/rail wear model used in this investigation is a simplified combined wear hypothesis that is based on the frictional energy loss in the contact patch. In order to account for wear and its distribution in a profiled wheel surface, the contact forces, creepages and location of the wheel/rail contact points are first calculated using a fully nonlinear multibody system (MBS) and three-dimensional contact formulations that account for the rail flexibility. The contact forces, creepages and contact point locations are defined as nonlinear functions of the rail deformations. These nonlinear expressions are used in the wear calculations. The wear distribution is considered to be proportional to the normal force in the contact area. Numerical simulations are first performed in order to compare between the results obtained using the simplified wheel/rail wear model and the results obtained using Archard’s wear model with a focus on sliding when the track is modeled as a rigid body. This simplified wear model is then used in the simulation of the MBS vehicle model in the case of a flexible body track, in which the rails are modeled using the finite element floating frame of reference approach and modal reduction techniques. The effect of the rail deformation on the wear results are examined by comparing these results with those obtained using the rigid-body track model.

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