Thermal load effects on fatigue life of a cracked railway wheel

Tehrani, Parisa Hosseini

doi:10.1590/1679-78251658

Cited by 15 publications

(8 citation statements)

References 20 publications

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“…The wheel and shoe contact surfaces are calculated according to Equations ( 11) and ( 12), in which R w is the wheel radius, H b is the block axial width, L b is the block length and N bw is the number of blocks per wheel as suggested by Haidari and Tehrani [41].…”

Section: Resultsmentioning

confidence: 99%

Simulation of the Thermal Behavior of Cast Iron Brake Block during Braking Maneuvers

2021

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In recent years, the interest in monitoring the operating conditions of freight wagons has grown significantly to improve the safety of railway vehicles. The railway research group of the Politecnico di Torino has been working for years on the development of solutions to effectively monitor the operating conditions of passenger and freight rail vehicles. As part of the national Cluster ITS Italy 2020 project funded by Italian ministry of education, university and research (MIUR), the Politecnico di Torino has collected a considerable amount of data thanks to the wired and wireless prototypes developed. The data obtained are used in this paper for the validation and calibration of a finite element (FE) model that simulates the temperature variation of a cast iron brake block due to braking operations of an intermodal freight wagon. The developed model can be a useful tool to predict the temperature at the wheel–shoe interface as a function of the current operating conditions since a direct measurement is not easy to perform.

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Section: Resultsmentioning

confidence: 99%

Simulation of the Thermal Behavior of Cast Iron Brake Block during Braking Maneuvers

2021

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“…For subsurface cracks in the rails and wheels, applied loads are non‐proportional, so the crack will be in the mixed mode conditions. The first failure mode can be effective in the fatigue crack growth when it can cause separation of the crack surfaces during the loading cycle 34 . In other words, the range of the changes of the first mode during a load cycle (

normalΔ K_{I}

) should be positive.…”

Section: Effective Ranges Of the Stress Intensity Factorsmentioning

confidence: 99%

Study of stress intensity factors in sliding and tearing modes for subsurface elliptical cracks in rolling train wheels

Seifi

Asadi

2023

Fatigue Fract Eng Mat Struct

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In the railway systems, induced contact between wheels and rails creates maximum shear stress around the contact surfaces. These shear stresses vary with the wheel's rolling and can initiate and extend subsurface cracks in the wheel and rail. The most common subsurface cracks in the rail systems have elliptical forms. Sliding and tearing modes of the fracture can be observed due to different components of the shear stresses around the contact area. Compressive normal stress has no considerable effects on in-plane and out-of-plane shear modes for subsurface cracks. In this research, by proper modeling of the wheel and rail, the effects of dimensions, position, and depth of the subsurface cracks on the stress intensity factors of the sliding (K II ) and tearing (K III ) modes have been investigated. Also, variations of the K II and K III values versus wheel rolling angles and frictions have been considered. The validity and accuracy of the cracked model created by sub-modeling technique have been verified by half-space modeling and weight function method.

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“…The use of the piece in question would be left to the specialists. Haidari and Tehrani [2015] seeks to identify fatigue with the aid of cracks in train wheels, in the case of the article, it presents a train wheel in a simulated environment to identify a period for its maintenance. Each wheel would have a set of two brakes for the analysis of the temperature effects in this scenario, and for that, two tests were performed, the temperature test and the mechanical test.…”

Section: Related Workmentioning

confidence: 99%

CNN-DFT Based Approach Applied to Image Inspection of Railcar Component: A Comparison with Machine Learning Methods

Rocha

Silva

Gomes

et al. 2021

jidm

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The railcar component inspection is one of the most critical tasks in railway maintenance. The use of image processing, coupled with machine learning has emerged as a solution for replacing current standard methodologies. The spectral analysis gives the frequency representation of a signal and has been largely used in signal processing tasks. In this sense, this work proposes the evaluation of the use of the discrete Fourier transform (DFT) in addition to the spatial representation image of railcar component for an automatic detector of defective parts performed by convolutional neural network (CNN) classification. The most appropriate combination of images of the spatial and frequency domains is compared to the histogram of oriented gradients (HOG) feature descriptor linked to the multilayer perceptron (MLP) and support vector machine (SVM) classification, where data augmentation is investigated to improve the classification performed by all approaches. A search is made for the parameters that best fit the MLP and SVM models for comparison with the proposed approach. The results are given in measure of accuracy in addition to accuracy boxplot, and it showed encouraging results in the combination of spatial image and DFT magnitude combined with data augmentation as CNN inputs, reaching an accuracy of 96.04% and demonstrating statistically to have a significant difference between the comparative methods.

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Thermal load effects on fatigue life of a cracked railway wheel

Cited by 15 publications

References 20 publications

Simulation of the Thermal Behavior of Cast Iron Brake Block during Braking Maneuvers

Simulation of the Thermal Behavior of Cast Iron Brake Block during Braking Maneuvers

Study of stress intensity factors in sliding and tearing modes for subsurface elliptical cracks in rolling train wheels

CNN-DFT Based Approach Applied to Image Inspection of Railcar Component: A Comparison with Machine Learning Methods

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