Railway Systems

Quiroga, Lisandro M.; Schnieder, Eckehard

doi:10.1007/978-3-642-25850-3_26

Cited by 13 publications

(8 citation statements)

References 2 publications

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“…With reference to the maintenance limits explained in Section 2, Table 2 presents the different geometry states. Owing to the complexity of the degradation process and the maintenance process, predicting the effect of employing different inspection intervals on the track geometry condition is a difficult task (Andrews et al, 2014;Quiroga & Schnieder, 2012). Therefore, the Monte Carlo simulation technique is used to handle the variation of the various parameters within the proposed integrated model and to estimate the percentage of time spent in the different track geometry states.…”

Section: Proposed Methodologymentioning

confidence: 99%

Investigation of the effect of the inspection intervals on the track geometry condition

Soleimanmeigouni

Ahmadi

Khajehei

et al. 2019

Structure and Infrastructure Engineering

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In order to evaluate the railway track geometry condition and plan maintenance activities, track inspection cars run over the track at specific times to monitor it and record geometry measurements. Applying an adequate inspection interval is vital to ensure the availability, safety and quality of the railway track, at the lowest possible cost. The aim of this study has been to investigate the effect of different inspection intervals on the track geometry condition. To achieve this, an integrated statistical model was developed to predict the track geometry condition given different inspection intervals. In order to model the evolution of the track geometry condition, a piecewise exponential model was used which considers break points at the maintenance times. Ordinal logistic regression was applied to model the probability of the occurrence of severe isolated defects. The Monte Carlo technique was used to simulate the track geometry behaviour given different inspection intervals. The results of the proposed model support the decision-making process regarding the selection of the most adequate inspection interval. The applicability of the model was tested in a case study on the Main Western Line in Sweden.

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Section: Proposed Methodologymentioning

confidence: 99%

Investigation of the effect of the inspection intervals on the track geometry condition

Soleimanmeigouni

Ahmadi

Khajehei

et al. 2019

Structure and Infrastructure Engineering

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“…The required track condition data can be assessed using both statistical and stochastic track deterioration models. Statistical models based on simple linear (Corbin et al, 1981) and exponential regressions (Quiroga et al, 2011) have been researched widely over the last three decades (Andrade et al, 2016). Stochastic models have also been proposed within different academic literature (Andrews et al, 2013;Zhang et al, 2014), but unlike statistical models, they have not been adopted widely within the railway industry.…”

Section: Track Deteriorationmentioning

confidence: 99%

“…Stochastic models have also been proposed within different academic literature (Andrews et al, 2013;Zhang et al, 2014), but unlike statistical models, they have not been adopted widely within the railway industry. Monte Carlo simulation (MCS) was identified as an efficient method for such stochastic modelling (Quiroga et al, 2011), as it can be used to run hundreds of thousands of iterations before arriving at a track condition with the highest probability of occurrence for a given time. This paper adopts a stochastic track quality deterioration model using MCS suggested by Quiroga et al (2011) and assumes the track quality to be a linear function of cumulative tonnage or time and is given by Equation 1.…”

Section: Track Deteriorationmentioning

confidence: 99%

Risk-informed sustainable asset management of railway tracks

Sasidharan

Torbaghan

2021

Infrastructure Asset Management

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Railway track infrastructure asset management is a challenging problem with added values on safety, society and environment. With railways serving as a key sustainable mode of transportation for passengers and freight, the industry is facing an increasing demand to expand its capacity, availability and speed, resulting in faster deterioration of the ageing railway track infrastructure. Given the constrained maintenance budgets and the environmental challenges posed by climate change, railway asset managers have to identify economically and environmentally justifiable track maintenance strategies without compromising on safety. To this end, this paper proposes a risk-informed approach to arrive at sustainable railway track maintenance strategies while considering the associated track maintenance costs and impacts on train operation (environmental emissions and risk of derailments). Monte Carlo simulation is employed to address data uncertainties associated with track quality data, the costs and benefits of track maintenance and train operation. The proposed approach is successfully applied to the heavy-haul railway lines in Sweden and Australia to compare some alternative maintenance strategies and identify the sustainable one.

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“…The most relevant superstructure track failures can be sorted into two main groups [26], i.e., i) track-geometryrelated faults (cross-level, alignment, longitudinal levelling, twist, and gauge) and ii) rail-surface-related faults (surface, corrugation, long and short waves). It is worthy to notice that the above classes of failures are strictly dependent.…”

Section: Railway Ballast Decays and Their Estimationmentioning

confidence: 99%

Non-destructive technologies for sustainable assessment and monitoring of railway infrastructure: a focus on GPR and InSAR methods

et al. 2021

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Health monitoring of ballast in railway infrastructures is crucial to assure structural stability and efficiency of the operations. To this extent, an efficient and sustainable management of maintenance is fundamental for asset managers in setting up strategic and effective action plans.Amongst the available methods to assess the conditions of railway infrastructures, non-destructive technologies (NDT) are gaining popularity due to their capability to overcome main drawbacks of traditional routine methods, such as digging trenches and visually inspect locations assumed as critical along the track.The present paper presents an overview of the use of the Ground Penetrating Radar (GPR) and the Interferometric Synthetic Aperture (InSAR) technologies for a sustainable monitoring of railway infrastructures. Specifically, main traditional and non-destructive methods used for maintenance of railway ballast materials are presented with a special focus on their sustainability. A review about the research methods on the use of GPR and InSAR technologies for railway infrastructures also reported, including main investigations carried out in the laboratory and the real-life environments. Furthermore, a conceptual framework based on an integrated approach including satellite-based and ground-based investigations is proposed, where network and local level information can be merged for the detection of critical sections and the implementation of a more advanced predictive maintenance system.

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Railway Systems

Cited by 13 publications

References 2 publications

Investigation of the effect of the inspection intervals on the track geometry condition

Investigation of the effect of the inspection intervals on the track geometry condition

Risk-informed sustainable asset management of railway tracks

Non-destructive technologies for sustainable assessment and monitoring of railway infrastructure: a focus on GPR and InSAR methods

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