Fatigue life prediction of a railway hollow axle with a tapered bore surface

Son, Seungwan; Jung, Hyunseung; Kwon, Taesoo; Kim, Jin-Sung

doi:10.1016/j.engfailanal.2015.08.031

Cited by 15 publications

(5 citation statements)

References 10 publications

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“…Parametric research on the composite railway axle lightweight design concept has been reported, revealing a potential 75% reduction in unsprung mass compared to a conventional hollow steel axle [11]. Son et al [12] proposed a new material and taper bore axle geometry to predict fatigue life under various service conditions as a novel design approach. Hirakawa and Kubota [13] explored a fatigue design method comparing Japanese and European design philosophies and examined fretting fatigue damage of press-fitted parts.…”

Section: Introductionmentioning

confidence: 99%

Multiaxial Fatigue-Life Prediction of Railway Axles with Consideration of Braking Effects

Nwe¹,

Pimsarn²

2023

MMEP

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Ensuring safety in the design of railway infrastructure and rolling stock is a critical aspect of railway operations. Railway axles are subjected to fluctuating bending and torsion loads, which often lead to the development of plastic stresses in the vicinity of fillets and notches, even though they are designed to withstand nominal elastic loads. This study aims to provide an accurate fatigue-life prediction for a motor bogie axle, taking into account the braking effects in conjunction with press fitting and the influence of masses in motion on the axle. Initially, the stress and deflection of the axle under combined loadings are calculated in accordance with the EN 13104 standard. Subsequently, a comparative simulation analysis is conducted using ABAQUS commercial software, with particular emphasis on specific loading conditions. A strainbased approach is employed to estimate fatigue life under multiaxial loading and variable amplitude overloading scenarios, utilizing fe-safe commercial fatigue analysis software. The results reveal a strong correlation between the theoretical and finite element analyses. The braking effects are found to reduce fatigue life by 50% compared to the influences of press fitting combined with masses in motion. This research highlights the significance of considering braking effects in fatigue-life predictions of railway axles to ensure safe and robust design.

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Section: Introductionmentioning

confidence: 99%

Multiaxial Fatigue-Life Prediction of Railway Axles with Consideration of Braking Effects

Nwe¹,

Pimsarn²

2023

MMEP

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“…Son et al 16 evaluated the fatigue life of hollow railway axles with tapered bore surfaces in accordance with the European Standards EN13103 and EN13261. The fatigue strength was also evaluated by finite element analysis of a full-scale axle test piece.…”

Section: Introductionmentioning

confidence: 99%

An analysis method for fatigue life of rail vehicle axles considering rotation effect of wheelset

Guo

Liu

2022

Advances in Mechanical Engineering

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In this paper, the discrepancy between the calculated and actual fatigue life distribution trend of the axles of railway vehicle structures is corrected. The calculations were made using the traditional fixed-axle model in which the wheelset rotation is neglected in random vibration analysis. A correction method is proposed, which is based on the original methods of fatigue life analysis of the axle structure of railway vehicles (i.e. the pseudo-excitation method and finite element model) and according to the characteristics of the symmetrical axle structure and the actual rotational operation state of the railway vehicle wheelset. Taking a locomotive system as an example, the minimum fatigue life calculated by the fixed-axle model is only 0.81 million km. In contrast, the minimum fatigue life calculated by the proposed method is 5.85 million km, which is consistent with the actual fatigue life of the axle. The position of the minimum fatigue life is also consistent with the actual position. The reliability of the proposed method for calculating the random fatigue life of the axle structure is illustrated. The influence and contribution of the prestress generated by axle press-fitting and vehicle serving weight of the railway vehicle acting on the axle on the axle fatigue life were studied. The results show that the prestress has a different influence on the fatigue life reduction of the wheelset. The minimum fatigue life reduction can reach 16.68% when all the prestresses are considered. Therefore, the influence of prestress should be considered in the design of railway vehicle axle structures. The idea of considering prestress should be proposed when revising axle standards.

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“…Then, the numerical simulation analysis of the train wheel wear profile information is carried out. [4][5][6][7] The other is to analyze and predict the historical wear profile information obtained from the statistics and calculate the remaining service life of the wheel-set to propose a maintenance strategy, such as the time series model, 8 support vector machine, 9 gray prediction algorithm, 10 and Bayesian algorithm. 11 With the advent of the era of data explosion, big data technology and numerical analysis methods have gradually been applied to various device security predictions.…”

Section: Introductionmentioning

confidence: 99%

Optimization of LMBP high-speed railway wheel size prediction algorithm based on improved adaptive differential evolution algorithm

Zhang

Luo

Gao

2019

International Journal of Distributed Sensor Networks

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It is beneficial for maintenance department to make maintenance strategy and reduce maintenance cost to forecast the hidden danger index value. Based on the analysis of the research status of wheel-to-life prediction at home and abroad and the repair of wheel-set wear and tear, this article designs and implements an adaptive differential evolution algorithm Levenberg–Marquardt back propagation wheel-set size prediction model. Aiming at the shortcomings of back propagation neural network, it is easy to fall into local extreme value. The back propagation algorithm is improved by Levenberg–Marquardt numerical optimization algorithm. Aiming at the shortcomings of back propagation neural network algorithm for randomly initializing connection weights and thresholds to fall into local extreme value, the differential evolution algorithm is used to optimize the initial connection weights and thresholds between the layers of the neural network. In order to speed up the search of the optimal initial weights and thresholds of the differential evolution algorithm Levenberg–Marquardt back propagation neural network, the initial values are further optimized, and an adaptive differential evolution algorithm Levenberg–Marquardt back propagation wheel-set size prediction model is designed and implemented. Compared with the proposed combine adaptive differential evolution algorithm with LMBP optimization (ADE-LMBP) is effective and significantly improves the prediction accuracy.

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Fatigue life prediction of a railway hollow axle with a tapered bore surface

Cited by 15 publications

References 10 publications

Multiaxial Fatigue-Life Prediction of Railway Axles with Consideration of Braking Effects

Multiaxial Fatigue-Life Prediction of Railway Axles with Consideration of Braking Effects

An analysis method for fatigue life of rail vehicle axles considering rotation effect of wheelset

Optimization of LMBP high-speed railway wheel size prediction algorithm based on improved adaptive differential evolution algorithm

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