Failure analysis in railway wheels

Zucarelli, T.; Vieira, Marisa; Filho, L. A. Moreira; Reis, Diogo; Reis, Luisa Fernanda Ribeiro

doi:10.1016/j.prostr.2016.02.029

Cited by 14 publications

(6 citation statements)

References 2 publications

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“…Rails serve as a path of rail transportation. Railroad rails have various types that are adjusted based on the type of train [1]. Coal transport type trains pass through the UIC 54 type railroad [2].…”

Section: Introductionmentioning

confidence: 99%

Simulation of Stress Intensity Factor and J-Integral on UIC 54 Railway Failure Using A Fracture Mechanics Approach

Kurniawan,

Darto,

Iswantoko

et al. 2024

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Repeated loading on the railroad tracks will result in fatigue failure. Fatigue failure combined with a defect in the form of a crack in the railroad track will result in a decrease in strength. Defects in the form of cracks are formed due to improper manufacturing and treatment processes. One treatment that can cause the formation of defects in the form of cracks is thermite welding. Improper and non-standard thermite welding techniques can trigger the formation of defects in the form of cracks in the railroad joints. Based on these problems, this simulation aims to obtain information about the value of maximum stress, SIF, J-Intergal, number of cycles, and crack extension from variations in crack size to repeated loading. The method consists of preprocessing, processing and postprocessing. Preprocessing begins with the design of the UIC 54 railroad crack which consists of 3 variations of crack length, namely 10 mm, 15 mm, and 20 mm. The design was tested through static structural simulation using the ANSYS 2021 R2 application. Meshing is configured using an element size of 5 mm and uses curvature capture. The results of the simulation obtained maximum stress values, SIF, J-Integral, number of cycles, and crack extension. Based on the simulation of SIF 1 and J-Integral values on the specimen design with a crack length of 10 mm it shows 362.03 Mpa.mm1/2 of 0.5708 mJ/mm2, for an initial crack length of 15 mm that is equal to 482.81 Mpa.mm1/2 and 0.91738 mJ/mm2, and for an initial crack length of 20 mm, it is 600.54 Mpa.mm1/2 and 1.4465 mJ/mm2. The results show that the increase in SIF 1 and J-Integral will be proportional to the increase in the initial crack length value. .

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Section: Introductionmentioning

confidence: 99%

Simulation of Stress Intensity Factor and J-Integral on UIC 54 Railway Failure Using A Fracture Mechanics Approach

Kurniawan,

Darto,

Iswantoko

et al. 2024

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“…Wheels degrade due to various environmental and operational reasons. Rough environments and operating conditions cause various faults such as cracks, fatigue, shelling, spalls, flats, cavities, and indentations [1], [2]. The continuous wheel degradation in the shape of different faults ultimately leads to major damages and accidents.…”

Section: Introductionmentioning

confidence: 99%

State-of-the-Art Wayside Condition Monitoring Systems for Railway Wheels: A Comprehensive Review

et al. 2023

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In recent decades, there has been a constant demand for faster, longer, and safer railway networks. This also brings challenges for condition monitoring systems in modern railway vehicles. More specifically, critical parts of railway vehicles like wheels degrade over time due to various operational and environmental reasons. Different dynamic effects such as skidding/sliding over the track and the presence of contamination between wheel-rail cause various wheel defects. Faulty wheels ultimately lead to the derailment of railway vehicles. To avoid worst situations like railway derailments, various research has been conducted for developing efficient condition monitoring systems for railway wheels. In addition, there have been some commercial condition monitoring products that can be deployed with railway vehicles. These systems incorporate various sensors such as strain gauges and vision sensors to collect data for diagnosis and prognosis. Various methods have been explored but yet there is a broad research gap in terms of developing advanced onboard condition monitoring systems. With the progress in technology, advanced systems with Machine Learning/Deep Learning methods can provide more efficient and robust condition monitoring of dynamic railway systems. Considering the need for advancement in condition monitoring systems for railway vehicles, a comprehensive review of existing condition monitoring systems for railway wheels is conducted in this paper. The review is aimed at understanding the feasibility and potential of new methods for modern railways. This paper provides a detailed overview of studies on the existing wayside systems and reports their advantages and disadvantages concerning its recently emerging counterpart on-board monitoring systems. Data acquisition systems and analysis methods are critically reviewed which could assist in developing more efficient and reliable condition monitoring systems for railway wheels. This article also reviews the current progress of wayside systems and their limitations. The article is targeted at the researchers and engineers working in this domain, who can pave the way for developing advanced and cost-effective condition monitoring systems for railway wheels using modern technologies.

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“…[1][2][3][4][5][6] Besides continuous wear leading to the degradation of the rail wheel material, crack initiation within the near-surface SPD microstructure can lead to fatigue crack growth at certain conditions. [7][8][9][10][11] Furthermore, corrosion occurring due to the environmental influences on the rail wheels in service can also act as crack initiation sites. [12][13][14] Initiated at non-metallic inclusions or pits creating spalling along the tread surface, 15 the formation of oxides changes mechanical properties such as strength, plasticity, and wear resistance.…”

Section: Introductionmentioning

confidence: 99%

Influence of the evolution of near-surface rail wheel microstructure on crack initiation by micro-bending investigations

Freisinger

Trausmuth

Hahn

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part F:

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Severe mechanical and thermal loadings, as well as the corrosive environment change the near-surface microstructure of rail wheels during service. Resulting severely plastically deformed (SPD) and corrosion affected microstructures are prone to influence crack initiation along the wheel tread. To evaluate the crack initiation and fracture behaviour, the in-situ micro-bending method is first applied on rail wheel samples from field within this work. Results reveal detailed insights in material behaviour of SPD microstructures, where the conducted micro-bending investigations point out predominant plastic behaviour without cracks initiated at the artificial notch of the micro-cantilevers during bending. In contrast, micro-bending investigations in microstructural regions with increased oxygen and silicon composition show crack initiation, fracture, and low maximum stress levels (approximately one seventh of the SPD microstructure). The presented study underlines the increased risk of crack initiation in corrosion affected regions by a novel testing method in this field with high spatial resolution and acknowledge the importance of periodic reprofiling of the rail wheels in service.

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Failure analysis in railway wheels

Cited by 14 publications

References 2 publications

Simulation of Stress Intensity Factor and J-Integral on UIC 54 Railway Failure Using A Fracture Mechanics Approach

Simulation of Stress Intensity Factor and J-Integral on UIC 54 Railway Failure Using A Fracture Mechanics Approach

State-of-the-Art Wayside Condition Monitoring Systems for Railway Wheels: A Comprehensive Review

Influence of the evolution of near-surface rail wheel microstructure on crack initiation by micro-bending investigations

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