14 research outputs found
Developing life cycle based startegies for track maintenance and renewal tools and rules from life cycle management plus project
Trai
Life cycle cost analysis for managing rail infrastructure
In the last decade managing railway infrastructure in Europe has changed compared to the century preceding it. Due to the restructuring of railways, which has resulted in separate Infrastructure Management and increasing performance demands from governments and Transport Operating Companies, infrastructure performance has become an important issue. Reliability requirements, budget limits, and operational conditions, such as the time available for maintenance, are becoming increasingly strict. As a response Infrastructure Managers (IMs) have started to develop computer-based tools for a quantitative analysis of the (long-term) impacts of design and maintenance decisions. These tools should enable IMs to systematically optimise and underpin their budget needs, minimise the total costs for a required performance level, and guarantee the infrastructure quality in the long run. Although progress has been made over the last years, these tools are still in an early phase of development, and have not yet been successfully implemented in the design and maintenance management processes. In this paper an approach based on Life Cycle Costing has been developed, which is able to support decision-making on design and maintenance quantitatively, even in absence of sophisticated maintenance planning tools, using expert judgement beside empirical data. Key to the approach is a decision support system (DSS) for analysing the long-term impacts of design and maintenance decisions on reliability, availability and cost of ownership. The DSS combines data from different management areas, such as construction, maintenance, financing and transport operations, in order to make estimates of the life cycle costs. Infrastructure availability and reliability are included in the analysis of life cycle costs, as they have an impact on the costs and revenues of transport operations. The DSS concept and its application during the tender for the Dutch High-Speed Line are presented. Both results and obstacles are discussed. Especially in a design phase a lot of uncertainty is involved in the analysis. The DSS proves to be a valuable tool for testing the robustness of design and maintenance decisions and for focusing the discussion on the important cost-driving factors
Railway design and maintenance from a life-cycle cost perspective: A decision-support approach
Technology, Policy and Managemen
Lessons learned from data analytics, applied to the track maintenance of the dutch high speed line
Life cycle performance and risk management are often mentioned as critical tasks for infrastructure managers. However, without proper data collection and analytics these tasks cannot be executed. This paper discusses lessons learned from a case where a data analytics approach was deployed when an unexpected phenomenon occurred on the Dutch High Speed Line (HSL-Zuid). In November 2014, it was found that large sections of the HSL-Zuid were affected by a severe type of rolling contact fatigue (RCF). The RCF resulted in deep cracks on top of the rail. These damages were unexpected as the rails were only 5 years in operation and these rails were expected to last about 20–25 years with proper maintenance. In this case, resulting in about 20 km of rail replacements and multiple additional grinding campaigns. As the causes of defects were unknown, the authors applied data analytics to evaluate the possible causes of the RCF. Several measurements of the infrastructure, maintenance and the rolling stock resulted in a set of parameters. Then, a bottom-up approach is proposed for evaluating the affected sections to find similar parameter values among these over the whole track. The idea was to look for parameter values which could explain why certain sections were affected by the defects while others were not. The outcomes of the analysis indicated that it is highly likely that one type of rolling stock was affecting the rails in the curves of the HSL-Zuid. As the track was designed at the high-speed sections for 220–300 km/h and this type of rolling stock was driving below design speed, different loading of the rails throughout the curves occurred. Lessons learned from this case do not only apply to the technical area of wheel/rail and vehicle/infrastructure interfacing, but also to the usage of data analytics itself and life cycle management. From this case study, it is discussed how data collection and analytics can be better embedded by (rail) infrastructure managers from an early stage of development and use of infrastructure. Further scientific development for infrastructure data analytics are also discussed.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Integral Design and ManagementRailway Engineerin
Dynamic Axle Loads as a Main Source of Railway Track Degradation
During train operation, geometrical irregularities develop in soil-supported ballasted railway tracks as a function of born tonnage. This form of degradation is combatted by periodic maintenance in the form of tamping by specially equipped trains in order to guarantee predefined levels of structural performance. The growth of irregular settlements depends on one hand on track properties (such as sleeper spacing, rail bending stiffness, subsoil geotechnical properties) and the intensity of longitudinal stiffness variations (variations in soil profile, switches and crossings, transitions etc.). The latter stiffness variations include both the static and the dynamic, frequency-dependent stiffness. On the other hand also the nature of the loading has an important influence. Running trains exert – depending on their velocity – quasistatic loads on the infrastructure due to the passing axles with a constant loading. Apart from this a dynamic loading component may occur with different frequencies as a result of non-perfect wheels, as a function of the speed. In general, the structural design of a railway line can be optimised with respect to its structural performance for the whole lifecycle. However, for existing lines this is difficult, and the only way to limit degradation and associated costs is to influence the condition of the rolling stock. The present study discusses theoretical backgrounds of track degradation in the form of differential settlements. It then shows results of an analysis of the loading conditions on Dutch railway lines, with both mixed passenger and freight transport and with dedicated freight traffic, based on actual measurements. Conclusions are drawn regarding deterioration and the effects of different loading types. Results show that especially on freight lines huge improvements are possible, with reductions in geometrical degradation up to 52% of actual values. The main driver of excessive degradation appears to be the low-frequency dynamic axle loading component.Structural EngineeringCivil Engineering and Geoscience
Railway track design & degradation
The long-term behaviour of railway track has attracted increasing attention in recent years. Improvements in long-term structural performance reduce demands for maintenance and increase the continuous availability of railway lines. The focus of this paper is on the prediction of the sensitivity of a track design to long-term deterioration in terms of track geometry. According to the state of the art literature, degradation is often investigated using empirical models based on field measurement data. Although a rough maintenance forecast may be made employing empirical models, the predictions are not generic, and the physical processes which govern track degradation under train operation remain unclear. The first aim of this study is to present a mathematical model to elucidate the underlying physics of long-term degradation of railway tracks. The model consists of an infinitely long beam which is periodically supported by equidistantly discrete sleepers and a moving unsprung mass which represents a travelling train. The mechanical energy dissipated in the substructure is proposed to serve as a measure of the track degradation rate. Secondly, parametric studies on energy dissipation are conducted to identify effects of various track design parameters on the susceptibility of the track to degradation, as well as the effect of the train speed. It has been shown that the track/subgrade stiffness is the most influential parameter on degradation whereas other system parameters do influence the degradation rate but at lower magnitudes. The conclusions can be used to optimise the track design in the early stage for better long-term structural performance of railway tracks.Railway Engineerin
Data Analytics for the of RCF Damages on the Dutch High Speed Line
During a typical measurement campaign, lots of temporal and spatial data can be gathered regarding the condition of the rail. This paper proposes two approaches that make use of data analytics techniques to find causes of rolling contact fatigue (RCF) damages. The first approach, named ‘bottom-up approach’, determines the influencing factors regarding RCF based on the worstaffected areas (hotspots). The second approach, called ‘top-down approach’, determines the influencing factors based on the condition of the whole track. The approaches use correlation analysis, clustering and similarity of parameters. To show the advantage of the approaches, they have been used for the study of the Dutch High Speed Line (HSL). The results indicates that severe RCF defectsoccurred only under two very specific conditions. First, in specific curves where one type of train was driving under high tractive efforts and large cant excess through curves. Second, at the entry zones of the HSL where voltage locks are present, the same type of trains’ low driving speeds result in driving without cant excess/deficiency (theoretical cant). The conditions suggest that structurally driving below design speed on a high-speed track can be a cause of rail damages.Railway EngineeringIntegral Design and ManagementMaterials and Environmen
Using data analytics to understand why certain rail sections at the Dutch high-speed line are affected by RCF
This paper describes the use of big data for analysing Rolling Contact Fatigue (RCF) phenomena at the High Speed Line (HSL Zuid) in The Netherlands. The authors developed a data model to investigate the impacting parameters in train-track interaction. This has been done to gain more insight in the circumstances where RCF occurs and to conclude why some track sections are severely affected and others not.To evaluate the worst affected areas by RCF, the methodology included a bottom-up approach which focuses at the worst affected areas by RCF, developing a set of characteristic parameter values regarding different types of hotspots. The methodology has been applied for the Dutch High-speed line, where certain sections had been heavily affected by RCF. Findings concluded that slow running traffic through curves on a high-speed line is likely to contribute to the appearance of RCF.Integral Design and ManagementRailway EngineeringMaterials and Environmen
Application of a bottom-up approach for the analysis of rolling contact fatigue in the Dutch high speed line
This paper describes the use of big data analytics for understanding the Rolling Contact Fatigue (RCF) phenomena at the High Speed Line (HSL Zuid) in The Netherlands. The authors developed a data model to investigate the impacting parameters in train-track interaction. This has been done to gain more insightabout the circumstances under which RCF occurs and to conclude why some track sections are severely affected and others not.To evaluate the worst affected areas by RCF, the methodology proposes a bottom-up approach. By focusing on the worst affected sections with RCF, a set of characteristic parameter values are defined to describe different types of hotspots. Then, a comparison between the hotspots is performed. Themethodology has been applied using real-life data of the Dutch High-speed line, where certain sections had been heavily affected by RCF. Findings concluded that slow running traffic through curves on a highspeed line is likely to contribute to the appearance of RCF.Integral Design and ManagementRailway EngineeringMaterials and Environmen
Evaluating railway track stiffness using axle box accelerations: A digital twin approach
While various train-borne techniques have been developed for measuring railway track stiffness, differentiating stiffness at different track layers remains a challenge. This study proposes a digital twin framework for the vehicle–track interaction system, which enables track stiffness evaluations based on axle box accelerations (ABA). The digital twin consists of a physics-based model, a model library and data-driven models. Compared to existing techniques, the proposed method simultaneously evaluates the stiffness of the railpad, sleeper and ballast layers at a sleeper spacing resolution, while being robust to varying track conditions, such as track irregularities and vehicle speeds. This is accomplished by employing a localized frequency-domain ABA feature capable of distinguishing between the characteristics of different track layers. Furthermore, track stiffness is evaluated in near real-time. This is achieved using a model library derived from physics-based simulations of a range of track conditions. Two data-driven models that can quickly select or interpolate model instances contained in the library are developed. During operation, the data-driven models use the measured ABA features as input and then infer the stiffness for the different track layers. The proposed method is applied to evaluate the track stiffness of a downscale test rig in a case study. The track stiffness evaluated by the proposed method is compared with that obtained through hammer tests and with the observations of the track component conditions. These comparisons show that the proposed method can capture the stiffness variations due to periodically fastened clamps and substructure misalignments at different speeds. In addition, the proposed method is demonstrated to be superior to the commonly used hammer test method for evaluating track stiffness under loaded conditions.Railway Engineerin