A stochastic model for the estimation of renewal periods of sharply curved metro rails

Bai, Wenfei; Liu, Rengkui; Sun, Qiang; Wang, Futian; Xu, Peng

doi:10.1177/0954409716679449

Cited by 6 publications

(6 citation statements)

References 45 publications

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“…Given its low probability of contact, sample 3# was similar to the matrix. Rail wear is a prevalent issue, particularly in sharp curves, and these computational findings align well with the actual conditions [33].…”

Section: Relationship Between Contact Forces and Microstructuresupporting

confidence: 76%

“…The figur calculated wheel-rail contact probabilities for each sample, based on ra Sample 3# had a low likelihood of interacting with the wheel, in contrast and 2#. Given its low probability of contact, sample 3# was similar to the ma is a prevalent issue, particularly in sharp curves, and these computational well with the actual conditions [33]. Table 3 shows the mean values of wear and fatigue indexes for the wheel-rail contact points.…”

Section: Relationship Between Contact Forces and Microstructurementioning

confidence: 77%

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Effect of Cyclic Loading on the Surface Microstructure Evolution in the Pearlitic Rail

Shi,

Liu,

Yang

et al. 2023

Coatings

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The effects of cyclic loading on the surface microstructure evolution of different contact locations in a used pearlitic rail were studied. Microstructures were analyzed using Scanning Electron Microscopy (SEM). Meanwhile, grain boundaries and crystallographic orientations were explored via Electron Backscatter Diffraction (EBSD). At last, wheel–rail contact probabilities and forces were calculated using rail profiles. The results indicate that the side wear region located in the gauge face was 71.5% in the high-angle grain boundaries (HAGBs) fraction, 0.88 in the Kernel Average Misorientation (KAM) value, 36% in the recrystallization (REX) fraction, and had a predominant orientation in grains. The rolling contact fatigue (RCF) region situated at the gauge corner was 66.3% in the HAGBs fraction, 0.92 in the KAM value, 33% in the REX fraction, and was mis-orientated in grains. The region located at the edge of the running band was 60.7% in the low-angle grain boundaries (LAGBs) fraction, 0.97 in the KAM value, 12% in the REX fraction, and was mis-orientated in grains. Continuous dynamic recrystallization (cDRX) took place in wear and RCF regions during the cyclic rolling contact loading, creating ultra-fine grains with a transformation from LAGBs to HAGBs, lower KAM values, and more REX. Grains oriented along [111] parallel to the vertical direction in the wear region were influenced by the dominant normal force, while grains in the RCF region were non-oriented, which was attributed to large lateral and vertical forces of similar magnitudes.

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Section: Relationship Between Contact Forces and Microstructuresupporting

confidence: 76%

Section: Relationship Between Contact Forces and Microstructurementioning

confidence: 77%

Effect of Cyclic Loading on the Surface Microstructure Evolution in the Pearlitic Rail

Shi,

Liu,

Yang

et al. 2023

Coatings

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“…Khan et al [ 21 ] introduced the survival analysis parametric model into the Markov process model to predict the road deterioration process caused by flooding. In addition, Scheidegger [ 22 ], Bai [ 23 ], and Kobayashi [ 24 ] applied survival analysis and Markov process combined models to predict the remaining life or life cost analysis of lighting facilities in urban pipelines, subways and highway tunnels, respectively.…”

Section: Current Research Studies On the Prediction Approaches For Th...mentioning

confidence: 99%

An Innovation of the Markov Probability Model for Predicting the Remaining Service Life of Civil Airport Rigid Pavements

2022

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In view of the time series update of airport runway health status detection data, the Markov chain of stochastic process theory was adopted. Considering the influence of aircraft traffic load, age, and pavement structure surface-layer thickness on the performance deterioration process of airport runways, the method of survival analysis was used. The parameter model of survival analysis was used to establish the duration function model of the four condition states of the airport runway PCI (pavement condition index). The Markov transition matrix for the performance prediction of airport runways was constructed. In order to evaluate the ability of the Markov transition matrix method to predict the trend of deterioration for PCI of the airport runway under different conditions of aircraft traffic volume and thickness of the runway pavement surface, a data set was constructed with the actual inspection data of the airport runway, and the corresponding samples were selected for analysis. The results showed that a Markov transition matrix for airport runway performance prediction, constructed based on survival analysis theory, can combine discontinuous inspection data or monitoring data with Weibull function survival curves. The method proposed in this paper can quantitatively predict the remaining service life of airport runways and provide support for cost-effective decisions about airport pavement maintenance and rehabilitation.

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“…37 The changes in the rail condition states and the duration of each different condition state are uncertain, with different possible deterioration paths. 39 Figure 1 shows four examples of possible deterioration paths.…”

Section: Rail Deterioration Processesmentioning

confidence: 99%

“…The heterogeneities in the deterioration processes of rails are due to the fact that the deterioration progresses of different rails in different locations are affected by different heterogeneous factors occurring at different rates over different rail renewal periods. Figure 2 illustrates the heterogeneities in the deterioration processes of rails, 39 showing the variation in the rail side wear for four different sharp curves on the Beijing Metro, as measured over the last decade. The vertical lines superimposed on the plot indicate the times at which the rails were renewed.…”

Section: Rail Deterioration Processesmentioning

confidence: 99%

A segmental evaluation model for determining residual rail service life based on a discrete-state conditional probabilistic method

Bai

Sun

Wang

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part O:

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Because steel rail is one of the most fundamental components of railway operations, the accurate estimation of residual rail service life is of great significance in ensuring the safe operation of railways. In addition, maintenance expenses must be minimized in a manner that allows limited railroad resources to be optimally allotted. In this study, the typical types of continuous rail segments on a rail line are classified into non-sharply curved rail segments and sharply curved rail segments. Using these classifications, a model for estimating the residual service lives of rail segments using a discrete-state conditional probability method is proposed based on an analysis of rail deterioration characteristics. The model considers several heterogeneous factors to determine their influence on the deterioration process and is shown to be capable of estimating the residual service lives of rail segments. Finally, the model is validated through a case study of the Beijing Metro, using inspection records of rail defects in conjunction with heterogeneous factor data to predict the service life of the rail, which is then compared with its actual service life. The model is found to show good agreement with the rail inspection and maintenance records of the Beijing Metro, indicating its appropriateness for use by railroad management in allocating future rail maintenance resources.

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A stochastic model for the estimation of renewal periods of sharply curved metro rails

Cited by 6 publications

References 45 publications

Effect of Cyclic Loading on the Surface Microstructure Evolution in the Pearlitic Rail

Effect of Cyclic Loading on the Surface Microstructure Evolution in the Pearlitic Rail

An Innovation of the Markov Probability Model for Predicting the Remaining Service Life of Civil Airport Rigid Pavements

A segmental evaluation model for determining residual rail service life based on a discrete-state conditional probabilistic method

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