Minimising rail lifecycle costs using Track-Ex damage and cost estimates Network Rail, Systems Engineering

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1 Minimising rail lifecycle costs using Track-Ex damage and cost estimates Network Rail, Systems Engineering M.A. Dembosky 1, S.P. Greenwood 1, A. Doherty 1 Network Rail, 40 Melton Street, London, UK 1 Abstract Network Rail, in conjunction with GB industry stakeholders, has developed an easy to use tool Track-Ex that predicts Rolling Contact Fatigue (RCF) cracks and Wear as well as loss of ground rail profile. Track-Ex bases these damage estimates upon the TGamma contact patch energy concept originally developed by British Rail research in the 1970s. A paper describing this approach was presented at the 2006 WCRR conference at Montreal [1] and a paper describing the technical basis of Track-Ex itself was presented at the 2008 WCRR conference [2]. Current users of Track-Ex include strategic planners, research analysts, maintenance engineers and track designers. The most powerful tool in Track-Ex is the Route/Fleet Analysis (RFA) function which provides a very quick means of analysing the effects of an entire fleet upon an entire route. In response to user requests, a Cost Model has been developed which uses the results of many RFA runs to allow different track designs or maintenance tactics to be quickly evaluated for damage potential as well as rail life costs. TGamma and Rail Damage estimates in Track-Ex Previous papers have described in some detail the TGamma concept and the Whole Life Rail Model (WLRM) that relates TGamma to actual rail head damage and wear [3, 4]. Wear RCF WLRM RCF/Wear Function TGamma Figure 1 depicts the leading axle RCF damage potential on the high rail of a curve for both GB standard (260) and GB premium (400) rails. Since TGamma increases as the wheel contact moves toward the gauge face, RCF damage grows as well. But it is limited by the onset of Wear which begins removing metal ever more aggressively as the contact approaches the gauge face. Eventually Wear dominates (negative RCF potential) as contact arrives at the gauge face itself. Most Likely 260 RCF Zone Most Likely 400 RCF Zone Figure 1: standard and premium rail WLRM damage functions Gauge Face The interplay between RCF and Wear results in a peak RCF potential on the gauge shoulder and gauge corner for 260 and 400 grade steel respectively. Track-Ex makes great use of the WLRM damage functions to predict both RCF and Wear. Track-Ex differs from most vehicle dynamics models in that it does not actually compute detailed vehicle motions and forces but uses Vehicle Damage Matrixes (VDMs) which tabulate TGamma for specific vehicle parameters, operating conditions and wheel/rail profile types as a function of curvature and cant deficiency. Since both curvature and cant deficiency can be derived from Track Geometry Measurement Files, Track-Ex can estimate the RCF and Wear potential for a vehicle over an entire route in fractions of a second using contemporary PCs. Figure 2 depicts a typical VDM table for the leading axle on the high (outside) rail of a curve. In all VDMs, negative TGamma values indicate a negative Longitudinal Creep force which means that RCF will not form Page 1 of 10

2 on the rail. Each trace depicts a cant deficiency state with negative values representing cant surplus and positive values deficiency. The Primary Yaw Stiffness (PYS), which governs the ability of the axles to deflect from parallel while curving, is fixed in this VDM at a value of 24MNm/rad and results in a broad range of curvature that will exhibit high rail RCF, particularly for non-cant deficiency states. (The RCF onset value for 260 grade steel is a TGamma of 15). Tgamma n-m/m VDM table pys: 24 W/R: mod Curve radius - m Cant Deficiency Figure 2: High rail leading axle VDM for PYS 24, 50 tonne vehicle and Moderate Wheel/rail This VDM is typical in that TGamma increases with curvature and cant surplus. The sudden decrease in TGamma that occurs in the 500m to 1000m range is caused by 2 point contact and the subsequent transferral of energy into the flange/gauge face interface. The table includes data for up to 300mm of cant deficiency to account for tilt body passenger stock in the GB system. The very low or negative TGamma values for these states corroborate experience to date on the West Coast Main Line which is dominated by tilt-body trains but has not seen the increase in high rail RCF that would be expected for a vehicle with such high PYS. The TGamma values in the VDM tables are averages formed by the execution of the Vampire high resolution vehicle dynamics model for each curve-cant deficiency pair. But previous studies have shown that the average TGamma in a curve can be significantly less than the dynamic TGamma caused by variations in track geometry, notably lateral alignment variations of 35m or less. The present version of Track-Ex estimates the dynamic TGamma by using the measured alignment variations as a proxy for actual axle motion. These estimates have the same general magnitude and wavelength as those produced by Vampire but often exhibit a phase shift due to the axle inertia. Vampire and Track-Ex Dynamic TGamma estimates Track-Ex Vampire Figure 3: Vampire TGamma and Track-Ex dynamic TGamma produced using the Alignment method Page 2 of 10

3 Figure 3 shows TGamma estimates produce by Vampire and Track-Ex. The general basis for the use of alignment as a substitute for actual axle motion is the finding that most variations in track geometry are dominated by wavelengths predicted by the Klingel axle motion concept [5]. Since axle lateral motion is dominated by the conicity of the wheel and rail pair, the energy generated tends to imbed the Klingel wavelength in the track as gauge and or alignment variations. Hence, alignment serves as a first order substitute for axle motion in Track-Ex dynamic TGamma estimates. Track-Ex axle motion estimates generally follow those of Vampire but do have some variations particularly when an axle approaches flange contact. For this reason, Track-Ex is described as an 80/20 tool i.e. 80% accuracy for 20% of the effort. This level of accuracy is deemed acceptable for most applications but efforts underway to increase accuracy are described later on in this paper. Route/Fleet Analysis: a system level tool The Route Fleet Analysis (RFA) function is extremely powerful and rather unique in that it forms the single axle damage for each vehicle type in a fleet and scales that damage value by the ACTRAFF derived number of such vehicles which may in fact vary over the route analysed. This automatic combination of fleet information, vehicle characteristics, track geometry and wheel/rail theory eliminates many time consuming operator data set manipulations and produces reports in a few seconds at most. Figure 4 shows typical Track-Ex inputs which can be easily varied to explore different system configurations. Thus the RFA function is a true system tool since both sides of the wheel/rail interface are taken into account. Figure 4: Track-Ex data sources and products Outputs of the RFA process include traditional distance history plots of each vehicle type s scaled damage as well as the aggregate damage of the entire fleet. In addition, RFA produce histograms of the aggregate damage estimates segregated by range of curvature. These Curvograms depict the vulnerability of curves to damage or wear on a route and can be used to compare a variety of scenarios. RCF Damage Indexes 260 un-ground 400 un-ground 400 ground 260 ground Figure 5: Predicted RFC damage Indexes for un-lubricated 260 grade rail ground/unground and 400 grade rail ground/un-ground for a busy main line terminus station Page 3 of 10

4 Figure 5 depicts the distribution of damage by curvature for both 260 and 400 grade rail steels in both the ground and un-ground condition. Grinding 260 grade steel with this particular route and fleet reduces the RCF to 12% of the un-ground 260 base case. Use of un-ground 400 steel reduces the RCF to 50% but grinding 400 grade decreases the RCF to 1% of the base case. The synergy of mixing anti-rcf tactics is clear. The large RCF index for the un-ground 400 grade in the 400m to 600m range is caused by very high TGamma values on the gauge corner. This is corroborates field observations that in GB, RCF on 260 grade is on the gauge shoulder area while 400 grade RCF appears on the gauge corner. Use of Track-Ex for both track design and maintenance implies a departure from the age old method of managing the track asset by track attributes alone. Vehicle behaviour is now taken into account and damage values themselves are often used as asset performance indexes. They are now an element in track access charge determination. The Track-Ex Cost Model Present users of Track-Ex include local maintenance engineers and track designers who are interested in specific locations of damage as well as corporate level analysts who focus upon company standards and route optimisation. Cost benefit analysis driven by estimated damage is required to translate change requests into business cases and justify potential increases in initial costs. For this reason, Track-Ex now includes a Cost Analysis function which exploits the RFA function by automatically generating a set of 20 RFA outputs which cover a range of grinding, lubrication and steel grade combinations. These results are annualised and summarised into segments of 50m. The segment RCF and Wear values are then divided into predefined intervention levels producing a rail life limited by RCF and a rail life limited by Wear. The shortest interval is then used to trigger the rail replacement and the annual costs for each segment are tallied. A similar approach is used to compute anti-rcf ground rail profile life using a Gap Loss index developed for Network Rail by TTCI-UK [6]. Figure 6 shows 50m RCF and Wear Cost Model input data for a high tonnage and highly curved portion of the main line starting at a terminus station in London. This area is difficult to maintain because of limited access and high train density and has historically had short rail life. Terminus Waterloo Station -Woking RCF A In Figure A, the base case un-ground and un-lubricated damage level of 11 is reduced to about 2 in the ground & un-lubricated case. RCF But Figure B shows that these changes cause the Wear index to soar from the base case level of 50 to about 250 due to the increased gauge-face contact caused by the ground rail profile. Wear Ground- No Lube Waterloo Terminus -Woking Station Wear Ground- Lube B In figure B, lubrication of the ground rail returns the Wear to the base case level. Unfortunately Figure A shows the corresponding RCF index almost returning to the original base case level of 11. This is caused by lubrication reducing flange steering forces resulting in an Page 4 of 10 Figure 6a & b: Terminus station approaches RCF and Wear summaries

5 increase in the axle angle-of-attack and subsequent tread TGamma. This conundrum (Wear vs. RCF) is not unusual in areas of tight curves and heavy traffic and illustrates why past British Rail policy called for premium rails in such areas. Such a uniform policy is not currently part of Network Rail current standards but premium rail can be used if cost justified. Review of cant and of grinding tight curve policies is currently underway. The Track-Ex Cost Model computes segment costs using the 20 RFA data sets in conjunction with user defined unit costs for rail replacement and rail grinding. The user can conduct route analysis by varying the rail grade, grinding and lubrication tactics and observing the resultant annual and accumulated costs for the entire route over a span of years. Cost Model results are in use at present but none the less considered preliminary for several reasons: Intervention levels used to compute rail life are notional and require study and validation Ground rail profiles are assumed to last until the next scheduled grind. But this is not always true with rail wear between grinding cycles removing the anti-rcf gauge shoulder/wheel gap. Gauge face wear is assumed to be linear over time which is not true, especially for extremely high initial values. Lubrication and rail inspection costs are not included. The latter can have significant impact where rail conditions require an enhanced inspection regime. Work is planned to address these issues and a more accurate model will be available in autumn Figure 7 shows the accumulated costs for the combinations of grinding and lubrication depicted in figure 6 for the Terminus station approach, a segment of track dominated by tight curves. The importance of lubrication is clear in the ground case and should serve as a reminder for all maintenance engineers that the return on investment for lubrication is extraordinarily high. Figure 7: Terminus station approaches Cumulative Costs The use of 400 grade steel has a clear benefit by reducing the base case costs by 60%. Other combinations of grinding and lubrication produce ambiguous results that are due to the preliminary nature of the Cost Model especially the present inability to reflect premature loss of ground rail profiles. Other outputs are available in spreadsheet and graphical form such as annual costs, total costs per 50m segment and rail life per 50m segment which is depicted in figure In effect, the cost Model is a route asset life optimiser in that the user may evaluate many maintenance and renewal tactics to maximise rail life and minimise costs. This is particularly useful when evaluating Whole Life costs where benefits are not immediately evident due to a tendency to focus on cheapest initial costs. 260 In addition, rail renewal, grinding and lubrication plans may be derived from the standard data outputs. Figure 8: Terminus station approaches Rail Life estimation 260 vs. 400 grade rail steel Page 5 of 10

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7 Track-Ex Vertical Energy Concept Many analysts have noted that rail damage, which is both a cost and safety issue, does not represent the majority of Network Rail costs. Other damage modes such as sleeper, joint, ballast and Switch & Crossing (S&C) degradation are major cost factors. Whereas Rail RCF and Wear can be described as a consequence of Horizontal or Track Plain energy, the other damage modes are essentially a function of Vertical Energy. Manchester Metropolitan University (MMU) has been tasked by Network Rail to explore the Vertical Energy concept. Although many industry studies have developed degradation models focused upon ballast or rail pads, none use Vertical Energy as such. Nonetheless, a simple Vertical Energy algorithm has been developed to allow Track-Ex users to evaluate in a relative sense changes in fleet composition, individual vehicle speeds or changes to vertical track geometry quality. The present algorithm is simple and is based upon the 2 nd derivative of top and vehicle un-sprung mass. The resultant force is then converted to an equivalent spring energy using a nominal track structural stiffness. These calculations are available in Track-Ex for individual vehicles or in a RFA context, analogous to the rail RCF and Wear RFA tool. Figure 9 shows the RFA cumulative Vertical Energy for the terminus station approaches example. Many of the localised high values are associated with bridges and S&C where changes in structural stiffness are inevitable. But some high values are plain track, suggesting weakness in the local formation or rapid changes in vertical alignment. Figure 9: Terminus station approaches RFA Total Vertical Energy for Left and Right rails. The Vertical Energy concept is a speculative enterprise. MMU has already demonstrated that the simple un-sprung mass concept produces forces that differ significantly from Vampire predictions. A simple massspring-damper does better but its accuracy is currently under review. Rail engineers are nonetheless interested in the development of the concept so that relative comparison of the vertical energy can identify specific sections of track where the stress on the rail and risk of failure is the greatest. Although many analysts have developed degradation models such as the ORE Committee D141 algorithms [5], they tend to be statistical and relevant to uniform stretches of track. Network Rail is pursuing Vertical Energy to find local damage of short duration, but of longer wavelength than the classic P1 or P2 forces [5] generated from dip angles. It is hoped that this will lead to the identification and prioritisation of maintenance activities at specific locations where benefits will be the greatest. Network Rail would certainly welcome any leads to Vertical Energy work already done or any suggestions regarding its further development. Page 7 of 10

8 Track-Ex: Accuracy issues The GB railway system has at its disposal a system level costing tool known as VTISM [7]. For RCF and Wear calculations, it currently uses TGamma estimates generated by Vampire. Some users wish to explore the use of Track-Ex generated TGamma estimates since their production is simpler and much faster. But, Track-Ex is an 80/20 tool whereas Vampire is the de facto GB high accuracy standard. Comparisons to date show that Track-Ex estimates definitely vary on a local basis and show a route based statistical error that is not sufficiently consistent. The heart of the error is the Track-Ex dynamic TGamma which uses the AL35 as a substitute for true axle motion. Track-Ex Vampire Figure 10: Vampire Hi-pass filtered Axle Lateral motion and the inverse of 35m lateral Alignment Figure 10 shows a fair correlation between the Vampire axle motion and the inverse of the measured Al35. The phase is quite good because the curvature in this case was shallow thereby avoiding the phase errors due to flange contact. The magnitude errors are largely due to axle inertial properties. Overall, the approach is sufficient for an 80/20 system but not good enough to replace the Vampire data in VTISM. Track-Ex has an experimental axle lateral motion simulator based upon a non-linear mass-spring-damper. This approach is similar to the Klingel motion 2 nd order system and the Gravitational Stiffness concept [8] which uses a non-linear stiffness. Figure 11 shows a comparison of Vampire axle motion and the Track-Ex experimental simulator. Left Rail Track-Ex Right Rail Phase Break Vampire Figure 11: Track-Ex developmental axle motion simulator & Vampire results for a 1000m curve Overall, the Vampire and Track-Ex axle motion computations are correlated but small differences in the point of flange contact cause breaks in phase that require many wavelengths to re-converge. Since this algorithm is not considered accurate enough for VTISM work, a second generation method using parameters directly related to the wheel/rail pairs used in the Vampire simulation is under development. In general, the sensitivity of the axle trajectory to flange contact may require a much more comprehensive model dubbed SimBogie that is essentially the simplest complete bogie model that can duplicate Vampire results within a 95% error band. This endeavour will not be undertaken in the near future due to resource constraints. As an alternative to SimBogie, Network Rail has contracted TTCI-UK to explore the use of Neural Networks to predict axle motion and preliminary results show a credible correlation especially for curved track. Page 8 of 10

9 Track-Ex: Present status and future expectations Within Network Rail there are approximately 130 staff currently trained in the use of Track-Ex, many of whom are Route Asset Managers who use Track-Ex to create maintenance & renewal plans as well as more justifiable and realistic budgets. Internal standards now require damage evaluation of curves that are subject to renewals where changes to standard construction such as the use of premium rail steel is of potential benefit. Track-Ex is the currently preferred tool. These users have a long list of usability issues that are focused primarily on simplifying execution of tasks or in the combination of several tasks into automatic processes. For example, the Cost Model currently does not allow for user variations in the installed cant of specific curves. Nor does it easily allow changes to specific vehicle speed at specific locations. Use of Track-Ex has increased by track design engineers engaged in Line Speed Improvement projects or actual design of new routes. In either case, Track-Ex damage estimates have become an integral part of the process. At the moment, the design process is viewed as cumbersome involving many software tools. As a result, a Network Rail study group has been created to explore the possibility of streamlining the process. First efforts will be modest and involve better data storage and format translations but eventually the process will lead to the integration of various software packages either by an in-house effort or by the software vendors themselves. Track-Ex users have long requested a curve optimiser function that would test each curve for better performance by varying the steel grade, cant, grinding, lubrication and alignment quality. It would feed the best results to the Cost Model and produce a route & fleet best matched for minimum damage and costs. At present, many of the software routines to support parts of the process exist but production of a Route Optimiser is not expected until late Summary Track-Ex with its Route Fleet Analysis and Cost Model is growing in usage within Network Rail and amongst the GB consultancy business. Analysis is conducted over entire routes as well as in specific curve complexes. Route analysis is usually done to evaluate the overall effects of fleet changes, evaluate changes in maintenance tactics and justify regional budgets. Analysis of individual curves tends to focus on adjustment of cant, track quality or rail steels with an aim of reducing local damage levels. Track-Ex has evolved in stages from analysis of a single axle to the Route Fleet Analysis (RFA) report which analyses many axles and finally the Cost Model that uses many RFA reports. Future developments will again escalate the level of automation by providing automatic route optimisation. Each curve in a route will be analysed (automatic parametric adjustments) to minimise damage and insure compliance with standards. The costs for each curve will be determined by the cost Model, resulting in a route with curves optimised for minimum damage and lowest whole life costs. Track-Ex is a practical tool in the GB rail industry for those with front line or strategic duties. It is also an example of a new generation of comprehensive tools that combine track and vehicle data to provide new value added information such as damage indexes that are directly used for system management. This is a departure from traditional methods of track management which focus mainly on track geometry quality and measured and/or observed wear to rail and other track components. Track-Ex has already become a factor in Network Rail s efforts to meet present performance goals of increasing system reliability and throughput whilst reducing system costs. A recent governmental review of the GB rail system has asserted that the industry at present needs better system level integration to meet future performance goals. Track-Ex is a practical example of a new generation of tools that will translate system integration aspirations into functional reality. Page 9 of 10

10 References [1] M. Dembosky, A. Doherty, C. Urban, R. Walker and S. Gurule. Management of rolling contact fatigue (RCF) in the UK system: a systems solution, Proceedings of the 7 th World Congress on Railway Research (WCRR 2006), Montreal, Canada. (2006). [2] M. C. Burstow, M. A. Dembosky, S. Gurule and C. Urban, Recent findings in the effect of vehicle/track interaction on track damage and rolling contact fatigue (RCF), Proceedings of the 8 th World Congress on Railway Research (WCRR 2008), Seoul Korea. (2008). [3] M. C. Burstow, S. Price and J. Stowe. A report on vehicle/track interaction on c2c route (2004). [4] M. C. Burstow. Whole life rail model application and development for RSSB- Development of an RCF damage parameter, AEA Technology Rail report AEATR-ES Issue 1, (2003). [5] C Esveld. Modern Railway Track Second Edition, 2001 MRT-Productions ISBN [6] X. Shu, M Dembosky, C. Urban and N. Wilson, Rail wear simulation and validation, Proceedings of the 2010 Joint Rail Conference, JRC2010, April 27-29, 2010, Urbana, Illinois, USA (2010) [7] VTISM Stage 2 summary Report, (2010) [8] A.H. Wickens, Fundamentals of rail vehicle dynamics and guidance, Swets & Zeitlinger, (2003) Page 10 of 10