Increased equivalent conicity of wheels because of hollow wear during long-term operation influences the ride comfort performance of Chinese high-speed trains. To investigate the evolution of wheel wear, a high-speed train operating on the Beijing-Shanghai Railway line at maximum operational speed of 350 km/h is monitored over a time of 1.5 years. An MBS based wear calculation software tool of KTH using stochastic simulation inputs has been used for wear prediction, where the vehicle suspension parameters and global structural modes of car-body and bogie frame have been identified using roller rig measurements and dynamic track measurements as well to validate the simulation models. The calculated wear is then validated against measurements by calibrating the wear rate coefficients. The influence of initial conicity on the lateral wear distribution is analyzed. Wheel profiles with lower initial conicities result in significantly less wear but more vibrations which possibly worsen the ride comfort. Increasing the roll-stiffness shows to be an effective way to damp the low frequency vibrations for the low conicity wheel while resulting in low wear. The suspension parameters and initial conicity which give the most stable equivalent conicity evolution and best ride comfort are selected for field tests.

Thermo-mechanical coupled systems are typically complex, however, the demand for analyses of this kind of multi-physics system is increasing, for example, accurately predicting the temperature and thermal stress of the railway disc brakes. However, many models ignore the phenomenon of thermal expansion and wear on brake pads. Therefore, their influence on the result is unclear. This research aims to investigate the effect of these two phenomena on the temperatures and stresses. These influences represent different heat flux input methods. Based on the finite element method (FEM), a three-dimensional (3D) transient thermo-mechanical model is built up. Three cases with or without thermal expansion and wear are conducted. The model is validated against measurement data. Simulation results show that thermal expansion and wear on the brake pads cause a 10% difference in the average temperatures of the brake discs, while a 257% difference in the maximum temperatures. As for the equivalent stresses (Von Mises stress), the difference can reach 3500%. Overall, this research builds a thermo-mechanical model and quantifies the effects of thermal expansion and wear on the temperatures and stresses of railway brake discs. The model can be transferred to other thermo-mechanical coupled multi-physics systems.

The trend in recent years to build longer and slender bridges has created new challenges in terms of safety and structural integrity. This study focuses on the effects of windinduced vibrations on the hangers of the Bomarsund Bridge in Åland, Finland. Those close to the mid-span have exhibited significant vibrations, requiring a thorough investigation to understand the response of the bridge to wind action. Computational Fluid Dynamics (CFD) simulations were performed using ANSYS Fluent to calculate the aerodynamic coefficients characterizing the given section (i.e. Strouhal number, drag, shedding frequencies, etc.) and to investigate the vortex-induced vibration (VIV) phenomena at different wind speeds. The results showed inconsistent drag coefficients at varying wind speeds and lower drag for geometries with rounded edges. The study highlighted the significant dependence of the Strouhal number on wind speed, challenging traditional geometry-based estimations. These findings can be used to implement effective measures to mitigate wind-induced vibrations.

The quantification of the influence of the weather conditions has a great importance in the field of Structural Heath Monitoring (SHM). In this work, the KTH two-span post-tensioned concrete bridge is studied. A shell based Finite Element (FE) model and a 3D solid FE-model are made. A sensitivity analysis of the dynamic properties of the system, i.e. natural frequencies and mode shapes is performed considering the influence of the boundary conditions, the elastic modulus of concrete, the material properties of the asphalt layer, the expansion joints of the bridge and the interaction between the deck and the abutments of the system. Furthermore, an experimental campaign was performed during winter weather conditions and compared to a previously developed study of the same system during autumn weather conditions. The results show the great influence the weather conditions on the dynamic properties of the system as well as the limitation, uncertainties and the problem of the unicity of the solution for the calibration of the developed FE-models. The case study shows the importance of SHM not only for tracking the dynamic properties of the studied system and early detection of global changes of the system but also how performing measurements can help to reduce the inherent uncertainties associated to a FE-model to improve the current engineering practice.

This paper presents a literature review of scientific publications on the topic of resilience of the transport system against antagonistic threats based on emerging technologies. The selected papers are discussed and publication trends are analysed.

In conventional vehicle design approaches, there is typically little understanding of the consequences of early stage design choices. This may be attributed to the conventional approach’s limitation in capturing complex interactions, further leading to increased design iterations. To overcome this, holistic multidisciplinary models were developed. However, they introduce the burden of complexity and costs because of their intricate nature. Furthermore, it is challenging to gain meaningful insights without a deeper understanding of the model’s nature and structure. Therefore, in this article, an alternative form of model representation was proposed to address these shortcomings. This was achieved by integrating two concepts: network theory and sensitivity analysis. A detailed and robust framework that represents complex multidisciplinary models as network models, reduce their complexity, and navigate insights from them, was provided. This is further demonstrated by a case study of a rail vehicle traction system including a traction motor and an inverter coupled with operational drive cycle. Among the identified 246 factors in the traction system network model, the three most influential inputs were identified for the chosen output factor of interest. Subsequently, the knock-on effects of these inputs were determined. The results indicate a significant reduction in the network graph size compared with the complete network graph of the traction system model. This indicated a significant reduction in the number of factors to consider in the analysis. This demonstrates the capability of the proposed framework to reduce the complexity of the analysis while retaining the ability to analyze intricate interaction effects.

Statiskt plattbelastningsförsök är en av de mest tillförlitliga metoderna för packningskontroll men styvheten som erhålls – även kallad bärighet – ska ses som en empirisk parameter som inte direkt kan översättas till jordmaterialets egenskaper i driftskedet. Detta eftersom plattbelastning utförs vid en betydligt högre spänningsnivå och med en mindre belastningsyta än för de flesta konstruktioner. Ofta används Ev2-modulen som ett direkt mått på E-modulen i beräkningar utan att ta hänsyn till jordens spännings- och töjningsberoende egenskaper. I denna artikel utforskas vad Ev2-modulen egentligen motsvarar och hur den kan användas till att beräkna deformationer. Med hjälp av mätresultat och FEM-simuleringar har en förenklad semi-empirisk metod utvecklats för att beräkna elastiska deformationer i driftskedet utifrån de resultat som erhålls i ett plattbelastningsförsök

The railway sector’s reliability, availability, maintainability, and safety (RAMS) can significantly improve by adopting condition based maintenance (CBM). In the CBM regime, maintenance decisions are driven by condition monitoring (CM) of the asset. This thesis proposes machine learning (ML) based onboard CM (OCM) algorithms for CM of vehicle-track dynamic interaction via vehicle response (VR). More specifically, the algorithms are developed to monitor track irregularities (TI) and vehicle running instability incidences (VRII) via VR.

CM of TI from onboard accelerations is a cost-effective method for daily surveillance of tracks. Most of the latest research is focused on monitoring vertical irregularity via vertical accelerations. Less attention is given to monitoring alignment level (AL) and cross level (CL) track irregularities. The PhD thesis proposes an ML based OCM algorithm to identify track sections with AL and CL  track irregularities exceeding maintenance thresholds via bogie frame accelerations (BFAs). In this thesis, the OCM algorithm’s supervised ML models are trained on BFAs’ datasets synthesized with multibody simulation (MBS) of a high-speed diagnostic vehicle. Furthermore, the trained ML models and OCM algorithm are validated with measurements acquired by the same high-speed vehicle. The proposed OCM algorithm shows excellent performance in track quality surveillance only from BFAs. 

OCM of vehicle running instability (VRI) is important to ensure safety and onboard ride comfort. The latest research focuses on designing OCM algorithms for detecting VRI, but these OCM algorithms lack fault diagnosis (FD) of detected VRII. The PhD thesis proposes various OCM algorithms under an "intelligent vehicle running instability detection algorithm" (iVRIDA) umbrella to detect VRII and diagnose corresponding root causes via carbody accelerations. The occurrence of VRI during regular operation across a whole train fleet is an anomaly. Thus, an unsupervised anomaly detection (AD) based iVRIDA algorithm is proposed and later extended as iVRIDA-fleet for vehicle fleetwide application. The proposed OCM algorithms iVRIDA and iVRIDA-fleet are verified by onboard measurements of a European high-speed vehicle and the Swedish X2000 vehicle fleet.

The thesis contributes towards the digitalization of vehicle and track maintenance by enabling adaptation of the CBM regime.

Intelligently identifying rail vehicle faults instigating running instability from carbody floor acceleration is essential to ensure operational safety and reduce maintenance costs. However, the vehicle-track interaction's nonlinearities and scarcity of running instability occurrences complicate the task. The running instability is an anomaly in the vehicle-track interaction. Thus, we propose unsupervised anomaly detection and clustering algorithms based iVRIDA framework to detect and identify running instability and corresponding root cause. We deploy and compare the performance of the PCA-AD (baseline), Sparse Autoencoder (SAE-AD), and LSTM-Encoder-Decoder (LSTMEncDec-AD) model to detect the running instability occurrences.

Furthermore, we deploy a k-means algorithm on latent space to identify clusters associated with root causes instigating instability. We deployed the iVRIDA framework on simulated and measured accelerations of European high-speed rail vehicles where SAE-AD and LSTMEncDec-AD models showed 97% accuracy. The proposed method contributes to smart maintenance by intelligently identifying anomalous vehicle-track interaction events.

In winter, some freight trains with composite brake blocks experience unexpected long braking distances, which seriously jeopardizes running safety. The reasons for the long braking distances are still not completely understood, and therefore it is difficult to suggest preventive measures. Up to now, it has not really been studied how a layer of ice that is often found between the brake block and the wheel influences the braking process. To investigate whether ice influences the braking distance, a numerical model is built. Ice thickness, ambient temperature, initial speed, and axle load/brake pressure are parameters that can be varied in the model. Results are checked against available on-track tests. The simulation results show that ice significantly influences the braking distance. The impact of ice on the braking distance increases when the ambient temperature, initial speed, and brake pressure are low, which is consistent with available field test reports. The results also show that a conditioning brake, a high brake pressure and a small clearance between the wheel and brake block can efficiently reduce the impact of ice on the braking distance of freight trains with composite brake blocks in winter.

Currently, the challenges of driverless or unattended train operation have not been described in detail and are often grouped into one category. This paper contributes to filling a knowledge gap regarding the roles of the train driver about the potential use of automatic train operation (ATO) on high grade of automation (GoA) levels. The results contribute to a better understanding of the challenges with driverless or unattended train operation to support strategies on how to utilize ATO on a wider range of trains than is presently the case. We use the Swedish railway network as a case study and delay logs written by train dispatchers for 2019. Our research quantifies how often unplanned events occur in which the train driver is needed, and the role of the train driver in solving these problems. In addition to this we elaborate on existing GoA levels definitions and propose a revised model that highlights more aspects of the train drivers’ roles. We have identified six categories in which an action by the driver is required: Detect, Report, Inspect, Adjust, Manage passengers, and Respond to train orders. The study illustrates some of the challenges with driverless or unattended train operation, and points to the need to develop strategies not only for the driving aspects of ATO but also for the more general technical operational management of rolling stock in high GoA levels.

Punctuality is a key factor in railway operations and is affected by both primary and secondary delays to differing degrees. Being able to separate these two types of delays is very important when simulating operations, and when conducting punctuality improvement efforts. However, it is not easy to estimate the relative proportions of primary versus secondary delays using historical data. In this paper, we demonstrate a method that uses repeated runs of a macroscopic simulation tool to estimate what share of delays has been primary or secondary. Using the Swedish region of Skåne as a case study, we estimate that about 36% of delays in 2019 were primary, leaving 64% as secondary. We further show that in order for operations to reach the targeted level of punctuality, 95% instead of the observed 87%, primary delays would have had to be cut by half. Using a draft timetable for 2025, we also simulate what the punctuality would be given different assumptions of primary delays. Assuming the same level of primary delays in 2025 as in 2019, we estimate that the punctuality would drop by a further 5 percentage points due to increased density of operations. In order to reach the punctuality target of 95% in 2025, primary delays would instead need to be reduced by two-thirds. At the request of the infrastructure manager, we also show the predicted geographical distribution of secondary delays in this future timetable. Our results highlight the need for drastic delay reduction measures to reach set targets.

Rail damage prediction is a complex task because it depends on numerous tribological parameters and the dynamic conditions produced by the vehicles operating at different speeds and configurations. Shakedown maps and Whole-Life-Rail-Model/T-Gamma have been used to predict rail damage, but they involve assumptions that may reduce their accuracy. This paper proposes a simulation modelling method to predict rail surface damage based on a locomotive digital twin, calibrated shakedown maps and friction measurements. The method improves the accuracy of rail damage predictions by including slip-dependent friction characteristics, co-simulation of locomotive traction mechatronic system and the mechanical properties of the wheel and rail materials measured through tensile tests. A set of operating conditions are simulated on a high-performance computing cluster, with stress results being post processed into calibrated shakedown heatmaps. The method clearly indicated the influences of the different operating conditions on rail damage for specific combinations of wheel-rail materials and vehicle-track configurations.

Track damage due to progressively increasing tonnage, especially due to longer and heavier freight trains, is one of the major problems faced in the European rail sector. In this context, to stay competitive, optimal track maintenance practices, track-friendly vehicles and safe operations of long freight trains assume prominence.

This PhD thesis studies long freight train operations and the long-term rail surface damage that they cause, to build a computer simulation-based framework for maintenance planning and assessment of running safety. 

The framework is formulated with four parts: long freight train operations, vehicle dynamics, rail surface damage and track maintenance. This is followed by a literature survey on each of the subtopics and how they are linked to each other.Safe operation of long freight trains in infrastructure bottlenecks such as S-curves is studied using three-dimensional multi-body simulations. Based on this, guidelines to build long freight trains and driving scenarios that can keep longitudinal in-train forces within acceptable limits have been provided. 

Multi-body simulation models of various freight bogies, including a novel design, are built and their dynamic running behaviour studied according to EN standards. The key focus is on track-loading and to this effect, methodologies for simulations-based assessment of `track-friendliness' of various bogie designs are studied. Various approaches to quantify rail surface damage using multi-body simulations in the form of wear and Rolling Contact Fatigue (RCF) are studied. Based on this, measures to ascertain similarities and differences in results from different approaches have been put forward. 

The impact of track maintenance, in the form of periodic rail reprofiling activities in different networks, on the evolution of rail surface damage is studied. It is found that optimal maintenance planning can be tailored depending on the type of traffic on the network.

Finally, various parts of the framework have been brought together to form a `train-track interaction' approach to facilitate optimal maintenance planning.

In this work, the authors present a detailed ’train-track’ interaction model of a long freight train operation topredict long-term rail surface damage. In addition to vehicles and track, intermediate maintenance actions inthe form of cyclic grinding passes have also been modelled according to EN standards to effectively representthe evolving wheel-rail interface. The influence of longitudinal train dynamics in the form of traction, braking,gradients, etc are also accounted in the method to reflect their effect on damage evolution. The two-stepmethodology consists of modules each modelling longitudinal train dynamics and long-term rail surface damagerespectively. The multi-disciplinary integrated numerical framework comprising of train, real operational casesand track attributes has been built based on principles of vehicle dynamics, tribology, and fatigue analysis. Themodel has been demonstrated for a heavy haul freight train operation on a 120 km long track section in thenorth of Sweden for which the results have been presented. Also, additional scenarios that can be expected ina real time operation with varying traction/braking, gradients etc have been considered. In the end, thisintegrated numerical framework comprising of 4 T’s namely train, track, tractive strategies, and trackmaintenance can be tuned into a digital twin to guide infrastructure managers regarding the condition of railassets as a function of tonnage passage. This can in turn facilitate predictive maintenance of track depending ontraffic and operation.

Trackside equipment and signalling devices are controlled by wayside object controllers (OC). Radio communication systems enable the wireless transmission of command control and signalling (CCS) data, which can help to reduce the cost of cabling and installation. However, for regional lines with low traffic volumes in rural areas, most of them are non-electrified, so a special cable for powering the wayside object controller system is still needed to be installed along the track, which would significantly increase the construction cost and maintenance work. A smart wayside object controller (SWOC) is suggested, which would be autonomous, self-sufficient, remotely-monitorized and locally-powered to ensure its proper operation, so the cabling and installation work can be totally removed. In order to demonstrate its viability and benefits over the existing systems, this work studies the possibility to use different renewable energy sources to power the system and then estimates the life cycle cost (LCC) of the SWOC in long-term operation. This study shows that in most places, it is sufficient to use 100% renewable energy sources to power the SWOC, trackside equipment and signalling devices. Compared with the existing system, the SWOC shows a significant cost saving in long-term operation by removing cabling and installation, reducing trackside maintenance and replacing the power supply with renewable energy power sources. Therefore, the SWOC shows its benefits over the existing system in both economical and environmental aspects. In the end, some suggestions on future development and implementation of SWOC are given.

The dynamic interaction of pantograph and catenary in electrified railway systems has considerable research attention, both in terms of simulation and of measurements. The simulation benchmark of 2015 proved a good base of agreement between established models, but also showed that deviations between the different models increase when the simulated system approaches critical speeds. From these deviations it can be concluded that some of the models in the benchmark better depict the system behaviour around critical speed than others. Therefore, this paper analyses and compares measurement data from the Green Train project in Sweden, which includes speed at and over critical level, to simulations performed with one of the participating models, the finite element (FE) based CaPaSIM model. Based on this comparison,modelling alternatives are implemented and tested in CaPaSIM, to examine if they improve the accuracy of the model in the speed range around critical speeds. These alternative modelling approaches are to a large extent based on previous studies in thefield, such as other models that  participated in the benchmark. The varied aspects include choice of element type for single components of the catenary and element mesh resolution. On the pantograph side, the effect of separately modelling independent flexible collector strips is studied. The modelling choices that prove to be most promising during the initial variation tests are presented and recommendations are given for further investigations of possible improvements.

Fastening failures have frequently been found on China high-speed railway curved tracks in recent years. Thus the influence of fastening failures on high-speed train-track interaction in curved track needs to be analyzed. A train-curved slab track interaction model is built, in which the real shape of the curved rail is considered and modeled with reduced beam model (RBM) and curved beam theory, and the slabs are modeled with four-nodes Kirchhoff-Love plate elements. The present model is validated at first with different traditional models. Then the influence of fastening failure in curved slab track on train-track interaction dynamics is studied. A different number of failed fastenings is assumed to occur at the curved track, and different types of fastening failure including the fatigue fracture of the clip structure and failure of the rail pad are considered. Based on the calculation results, the fatigue fracture of the clip structure has little influence on train-track interaction dynamics. But when rail pad failure happens and its equivalent vertical stiffness and damping are less than one-tenth of its original, the fastening failure seriously affects the high-speed train operation safety, and it must be prevented

Condition Monitoring (CM) of dynamic vehicle track interaction is an important research topic in rail vehicle dynamics. The most cost-effective method for CM is through carbody floor mounted accelerometers because this is most safe and reliable location for onboard accelerometers onboard inservice train. However, the dynamic response of carbody is influenced not only by excitations coming from track but also by various nonlinearities such as wheel-rail interface and vehicle suspension elements. Thus, it is very challenging to accurately monitor track subsystems via carbody floor accelerations. In this article, two feature extraction algorithms are proposed with the objective of obtaining crucial information on the stability of vehicle using carbody floor accelerations. The first algorithm is based on spectral analysis and the latter is on adaptive signal processing technique. The first algorithm calculates transfer function between track irregularities and carbody floor acceleration using Multiple Input Multiple Output (MIMO) system identification method. The later method analyses the carbody floor accelerations with Empirical Mode Decomposition followed by Singular Value Decomposition (EMD+SVD). These algorithms are evaluated on simulated carbody floor accelerations obtained with vehicle dynamic simulations. In this investigation, it is observed that the first method extracts more crucial information from carbody floor acceleration in comparison to EMD+SVD method. These features are planned to be used in future research to develop machine learning based intelligent fault identification algorithm for identification of root cause of vehicle running instability occurrence.

Syftet med föreliggande rapport är att följa upp utvecklingen av utbud och priser inom persontrafik på järnväg med ett urval sträckor i Sverige och till grannländerna som en del av Transportstyrelsens marknadsövervakning.

För de flesta järnvägslinjerna med persontrafik har utbud och biljettpriser studerats för en relation mellan två orter. På några viktigare relationer har insamlingen utökats med även kommersiella flyg- och busslinjer som konkurrerar med tåg för att få en helhetsbild av resemarknaden. Data om utbudet har samlats in en helgfri onsdag i mars eller oktober, beroende på förutsättningarna respektive år. 2022 var den planerade resdagen, eller huvudmätdagen, onsdagen den 5 oktober och priserna motsvarar bokning en vecka innan avresa. Målet har varit att representera en typisk vardag utan störning av helger eller semesterperioder som kan påverka resandet.

Persontrafiken på järnväg har trendmässigt ökat sedan 1990 och har mer än dubblerats på 30 år. Efterfrågan har växt i takt med utbudsförbättringar genom snabbare tåg, tätare turer och attraktiva priser. Coronapandemin 2020 innebar dock ett kraftigt avbräck i utvecklingen. Under 2022 har en återhämtning skett och fritidsresandet med tåg blev i ungefär samma storleksordning som det tidigare toppåret 2019, medan tjänsteresorna ligger lägre.

Den uppåtgående trenden i biljettpriser 2022 kan förklaras av den ökade efterfrågan på framför allt fritidsresor som gör det möjligt för järnvägsföretagen att ta igen förlorade intäkter från coronapandemiåren 2020-2021. Den begränsade tillgången till billiga biljetter kan dock ha medfört att flera resenärer får betala mer för sina tågresor. Det ger en större effekt för resenärerna, särskilt vid senare bokningar, än prishöjningar inom respektive biljettpriskategori som ingår i undersökningen.

Flygutbudet har inte återhämtat sig lika väl som tåget sedan coronapandemin, och ligger 2022 generellt på ungefär halva antalet avgångar jämfört med 2019. Däremot sker en priskonkurrens med tåg på de största reserelationerna Göteborg−Stockholm, Malmö−Stockholm och Umeå−Stockholm, med billiga flygbiljetter som beroende på avgång kan vara lägre än tillgängliga biljetter för tågresa. Inte heller bussutbudet har återhämtat sig och det är svårt för buss att konkurrera såväl i restid som i pris med lågprisbiljetter för tåg och flyg på de större relationerna.

Sammanfattningsvis har 2022 präglats av sviter av coronapandemin, särskilt personalbrist, men även andra problem inom järnvägen som försenad tidtabellsplanering. Efterfrågan är relativt svag på tjänsteresor men stark på privatresor, i nivå med det tidigare toppåret 2019. Ett flertal biljettpriser har stigit men annars ligger utbudet nästan i nivå med det tidigare toppåret 2019.

Most railways use fixed block technology, which could be replaced with moving block technology with associated high cost. It is therefore interesting to gradually upgrade the signalling system exploiting hybrid technologies. This paper aims to investigate the impact on capacity of various signalling systems (including fixed block technology and hybrid technology) using a microscopic simulation tool under scheduled (static) conditions without considering probability functions. To perform comparative analysis between European Train Control System (ETCS) Hybrid Level 3, ETCS Level 2, and the Swedish ATC2 legacy system, three signalling system scenarios are designed and capacity consumption is considered as a performance indicator. The study was performed on the central section of Stockholm’s commuter train network with peak hour conditions from the 2020 timetable. The results show that ETCS L2 delivers lower capacity consumption in total compared to the ATC2 legacy system. ETCS Hybrid Level 3 with existing trackside train detection and partially shortened block sections delivers lower capacity consumption compared to ETCS L2 and ATC2. The implementation of hybrid solutions such as ETCS Hybrid Level 3 in addition to allowing for gradual upgrading of signalling systems to the next generation (moving block system) can improve capacity of high-density commuter lines.

Locomotive multibody simulations are commonly used as a cost-effective tool to study, energy efficiency, wheel-rail wear, rolling contact fatigue, etc. The accuracy of the wheel-rail contact forces from multibody simulations depends on the correct modelling of the friction conditions. The friction coefficient is a function of the slip velocity, and it is influenced by several tribological parameters including, for example, material mechanical properties, environmental conditions and the presence of third body layers that vary spatially and temporally along the track. In most cases, generic friction-slip curves obtained from publications and public reports are used as inputs to the wheel-rail contact model in the locomotive simulations, as direct friction measurements using full-scale experimental set-ups are generally cost-prohibitive. A pathway to produce friction-slip curves from tribo-machine friction measurements is proposed in this paper. The pathway involves manufacturing discs from actual wheel and rail material samples to measure the traction coefficient at a spectrum of slip set points using a twin-disc tribo-machine. The tribo-machine results are scaled to be used in a locomotive multibody model that uses the modified Fastsim and a traction system co-simulation approach. Two friction curves for wet and dry conditions are processed and exemplified in a dynamic model.

In engineering education, as well as in the society at large, there is an increasing focus on sustainability and sustainable development. The CDIO Standards and the CDIO Syllabus has been substantially updated to meet and drive these changes. Progressive engineering programs have by now made substantial progress in integrating environmental aspects of sustainability and sustainable development into the curriculum. However, the integration of social aspects is generally considered to be more difficult and is therefore lagging behind. This explorative research paper provides insights in efforts to integrate elements of gender equality, diversity and equal conditions (GDE) in three courses on bachelor’s, master’s, and doctoral level. The focus is on the development and implementation of reflective assignments, where a theoretical framework is used for characterizing different levels of reflection. The work has been performed by use of an action research approach that has involved close dialogue and collaboration between researchers, pedagogic developers, teachers, students, and education leaders. The paper hereby contributes with multiple perspectives on GDE integration, and significant challenges are discussed. The paper also contributes with concrete examples of reflective assignments, learning activities, and literature that can be useful also in other contexts.

Generally, the equivalent conicity function (ECF) is denoted by equivalent conicity at 3mm (λ_3mm) and a Nonlinearity Parameter (NP). NP describes the nonlinearity of the ECF and its influence on a vehicle design is explored thoroughly, however, NP’s role in vehicle and track maintenance is not researched yet. This paper investigates the influence of track maintenance actions on vehicle dynamics with help of NP vs λ_3mm scatter plots of ECF database. The ECF database is constructed by combining measured worn wheel and rail profile pairs of the Swedish high-speed vehicle and rail network, respectively. The ECF database revealed an inverse relationship between λ_3mm and NP, i.e., NP is negative for larger λ_3mm values. The combination of negative NP and high λ_3mm causes reduction in the vehicle’s nonlinear critical speed and vehicle often exhibit the unstable running on the Swedish rail network. Thus, the occurrence of ECF with negative NP and high λ_3mm is undersirable and the undesirable ECF can be converted into desirable ECF by grinding the rail, which converts ECF’s into positive NP and low λ_3mm combinations. Thus, the NP parameter along with the λ3mm must be considered in track maintenance decisions.

Railway traffic usually adheres to a timetable, but in Sweden, around two-thirds of the freight trains depart before they are scheduled, often by hours. Even though they occur in real operations, early departures have rarely been included in simulation studies and the effects on punctuality are not fully investigated. With a macroscopic simulation tool such as PROTON, large networks can be simulated in a short time, which makes the simulation process easier. This paper uses the tool PROTON to perform a macroscopic simulation case study on the Swedish Western mainline to investigate how early departures of freight trains affect punctuality. The resulting output is a marginal overall punctuality improvement of about +0.5 percentage points. In addition, different levels of primary run time and dwell time delays have been used as simulation input, based on empirical data. The resulting ratio between primary and secondary delays appears to vary greatly between different train types, but overall about 30% were primary and 70% secondary. Future work includes modelling and calibration of departure deviations, which vary more between different train types, and where it is more difficult to separate between primary and secondary delays. Separating distributions based on train type or location will also be considered.

In recent years, significant research transpired on onboard monitoring of various phenomena arising in dynamic vehicle-track interaction. One key issue being monitoring of vehicle hunting instability. Current hunting detection standards are appropriate for certification tests of vehicles, but incapable to monitor the health of the vehicle and track subsystems influencing the hunting instability. This paper proposes a signal based procedure for accurately triggering Hunting/No-Hunting alarm by conforming to requirements of onboard monitoring. A new method is conceived to reveal coherence among lateral and longitudinal accelerations during vehicle hunting. Furthermore, an index which amalgamates phase and amplitude information of lateral and longitudinal axlebox accelerations is introduced to detect coupled modes in lateral and yaw directions, i.e. hunting modes. Several simulations based pragmatic case studies are performed to assess the efficacy of the proposed procedure. The proposed method outperforms traditional hunting detection procedures by detecting more Hunting/No-Hunting occurrences. The proposed method contributes towards digitalization of rail vehicles through condition-based and predictive maintenance.

Bearings of rail vehicles bear various dynamic forces. Any fault of the bearing seriouslythreatens running safety. For fault diagnosis, vibration and temperature measured from the bogieand acoustic signals measured from trackside are often used. However, installing additional sensingdevices on the bogie increases manufacturing cost while trackside monitoring is susceptible toambient noise. For other application, structural displacement based on computer vision is widelyapplied for deflection measurement and damage identification of bridges. This article proposesto monitor the health condition of the rail vehicle bearings by detecting the displacement of boltson the end cap of the bearing box. This study is performed based on an experimental platform ofbearing systems. The displacement is monitored by computer vision, which can image real-timedisplacement of the bolts. The health condition of bearings is reflected by the amplitude of thedetected displacement by phase correlation method which is separately studied by simulation. Toimprove the calculation rate, the computer vision only locally focuses on three bolts rather thanthe whole image. The displacement amplitudes of the bearing system in the vertical direction arederived by comparing the correlations of the image’s gray-level co-occurrence matrix (GLCM). Forverification, the measured displacement is checked against the measurement from laser displacementsensors, which shows that the displacement accuracy is 0.05 mm while improving calculation rate by68%. This study also found that the displacement of the bearing system increases with the increase inrotational speed while decreasing with static load

In order to improve current rail timetabling processes, the suitability of train departure times for passengers should be included in timetable assessment. To achieve this, one possibility is to calculate the change in consumer and producer surplus (i.e., the economic welfare) resulting from departure time shifts in rail timetables. However, existing methods for this calculation are quite limited. To fill this gap, we propose a new method in the current paper. This method enables comparing most scenarios involved in interregional rail timetabling in terms of economic welfare. To this end, our method takes advantage of schedule-based models that allow assessing the impact of departure time shifts on the demand and valuation of each possible route using the timetable. As a proof of concept, we illustrate this method on a case study on the busiest Swedish interregional line. This case study shows the potential of the method to deliver detailed calculations with analysis of equity effects. To conclude, the method presented in this paper improves on the current literature, and it can be used to improve timetable optimisation algorithms or to better resolve conflicts between train path requests.

The demand for road and rail freight transport continues to grow with the expanding economy, while the climate crisis requires reduction in greenhouse gas emissions. Therefore, tools and solutions for reducing fossil fuel use and enabling more efficient use of infrastructure are needed. This thesis utilises microscopic and macroscopic traffic simulation as tools to improve certain aspects of road and rail transport planning in the operational, tactical, and strategic planning time horizons.

For road freight transports conducted with heavy-duty vehicles, fuel consumption can be reduced by smarter driving. Strategic planning concerning introduction of intelligent and connected vehicles is needed, along with planning of actual vehicle operations. Microscopic road traffic simulation is utilised to show that heavy-duty vehicle platooning, which lowers the fuel consumption through reduced aerodynamic drag, can be conducted on two-lane highway stretches without disturbing surrounding traffic. Further, substantial reduction of the fuel consumption can be achieved by applying fuel-optimal deceleration trajectories, assuming available information about the traffic situation ahead.

Shifting freight transports from roads to railways is another possible measure to reduce emissions. Previous simulation studies of railway traffic has mainly focused on passenger trains, combined with not including freight train departures before the scheduled timetable, even though it commonly occurs in Sweden. Therefore, both microscopic and macroscopic railway traffic simulation, with and without allowing early freight train departures, is conducted in a case study. The resulting freight train punctuality is closer to empirical punctuality when early departures are included.

A modal shift from road to rail transport increases capacity utilisation of railway networks, and is only possible within available capacity. Therefore, reliable methods for capacity analysis are needed. A method for capacity analysis is introduced and evaluated, with particular focus on railway station analysis. An advantage of this method is it can be used in tactical and strategic planning of future timetables and infrastructure.

This paper is an outcome of an international collaborative research initiative. Researchers from 24 institutions across 12 countries were invited to discuss the state-of-the-art in railway train air brake modelling with an emphasis on freight rains. Discussed models are classified as empirical, fluid dynamics and fluid-empirical dynamics models. Empirical models are widely used, and advanced versions have been used for train dynamics simulations. Fluid dynamics models are better models to study brake system behaviour but are more complex and slower in computation. Fluid-empirical dynamics models combine fluid dynamics brake pipe models and empirical brake valve models. They are a balance of model fidelity and computational speeds. Depending on research objectives, detailed models of brake rigging, friction blocks and wheel-rail adhesion are also available. To spark new ideas and more research in this field, the challenges and research gaps in air brake modelling are discussed.

Running gears form a significant part of the weight of a railway vehicle, and if the weight of these could be reduced, this would affect the vehicle’s energy consumption, especially for services with many stops. In the project RUN2Rail, a part of the EU-funded initiative Shift2Rail, a single axle running gear was proposed for metro vehicles. Active suspensions were suggested to overcome deficiencies in terms of ride comfort and wheelset steering, which are well known for such vehicles. The concept has been further developed in the project NextGear, also part of Shift2Rail, where the material of the running gear frame has been changed from steel to composite to further reduce the weightand the wheelset guidance updated to decrease the running resistance in curves. Prototypes of frame and wheelset steering actuator will be built and tested in the laboratory to validate the performance.The present study is comparing a reference vehicle from Metro Madrid with the proposed vehicle in terms of energy consumption for simulated service on Metro Madrid Line 10 with curvature, gradients, stops and speed profiles considered. Only parameters with relation to the weight, curving performance and auxiliary energy consumption for the active system are assumed different for the vehicles. The vehicles are further assumed to use regenerative braking, hence the energy needed to accelerate the vehicle will be regenerated when braking, but there will be transformation losses with relation to the weight. The simulation results show that the very innovative NextGear vehicles will reduce energy consumption by 8% compared to the reference vehicles. The lower weight and the decreased running resistance in curves contribute about as much to the savings.

Condition monitoring of track geometry irregularities from onboard measurements of vehicle response is a cost-effective method for surveilling qual-ity of track irregularities on daily basis. The monitoring of Alignment Level (AL)and Cross Level (CL) track irregularities is challenging due to the nonline-arities of the contact between wheels and rails. Recently, the authors proposed a signal-based method in combination with a machine learning (ML) fault classi-fier to monitor AL and CL track irregularities based on bogie frame accelerations. The authors concluded that the Support Vector Machine (SVM) fault classifier outperformed other traditional ML classifiers. Thus, an important question arises: Is the previously reported decision boundary an optimal boundary? The objective of this research investigation is to obtain an optimal decision boundary according to theory of probabilistic classification and compare the same against the SVM decision boundary. In this investigation, the classifiers are trained with results of numerical simulations and validated with measurements acquired by a diagnostic vehicle on straight track sections of a high-speed line (300 km/h). A fault classi-fier based on Maximum A Posterior Naïve Bayes (MAP-NB) classification is developed. It is shown that the MAP-NB classifier generates an optimal decision boundary and outperforms other classifiers in the validation phase with classifi-cation accuracy of 95.9±0.2% and kappa value of 80.4±0.6%. Moreover, the Lin-ear SVM (L SVM) and Gaussian-SVM (G SVM) classifiers give similar perfor-mance with slightly lower accuracy and kappa value. The decision boundaries of previously reported SVM based fault classifiers are very close to the optimal MAP-NB decision boundary. Thus, this further strengthens the idea of imple-menting statistical fault classifiers to monitor the track irregularities based on dynamics in the lateral plane via in-service vehicles. The proposed method con-tributes towards digitalization of rail networks through condition-based and pre-dictive maintenance.

Within the Shift2Rail projects Pivot2 and NEXTGEAR, an innovative Metro vehicle with single axle running gear and only one suspension step is proposed. A composite material running gear frame is developed to be used both as structural and as suspension element. The design with only one suspension step can significantly degrade the passengers ride comfort. Thus, active modal control is implemented both in lateral and vertical direction to increase the performance of the system. The running gear frame is modelled in Abaqus® as well as the carbody. Structural modes of both elements are implemented in SIMPACK®. A hydraulic actuator model is developed in Simscape®, where two pressure-controlled valves are used to control the pressure inside the chambers of a double acting hydraulic cylinder. A co-simulation environment is then established between SIMPACK® and Simulink®. The vehicle is running with speeds between 10 and 120 km/h. Active modal control makes it possible to maintain ride comfort levels of conventional bogie vehicles with this innovative single axle and single suspension step running gear, promising substantial weight savings of about 400 kg/m. The single axle running gear solution with active comfort control developed here can be an attractive alternative to bogies, providing reduced Life Cycle Costs.

The aim of this paper is to assess how the introduction of technological innovations into a capacity constrained rail corridor may increase its ability to capture market share from road transport. The Montpellier-Perpignan section, a bottle-neck in the Mediterranean corridor, is used as a case study for the effects of implementing new rolling stock that allows for freight trains up to 1500 m, a new ballastless track replacing existing one, resilient switches and crossings, and monitoring systems that allow for a reduction in maintenance costs and closure times. The results of a cost-benefit analysis show positive net impacts, however, the increases in capacity are only enough to maintain current rail freight market shares. Evidence suggests that a heavy investment in technology in existing lines is not the most effective way to increase rail market share.

Pitting and micropitting are the two main gear rolling contact fatigue modes. It is widely accepted that micropitting will lead to pitting; however, the relationship between pitting and micropitting life needs further investigation. In this work, micropitting and pitting tests were performed on an FZG back-to-back test rig using standard FZG PT-C and GF-C gears. The gear tooth profile change due to micropitting and pitting damage was measured in situ in the gearbox using a profilometer after each test. The gear surface roughness parameters were calculated from the measured tooth profile. A Gaussian low pass filter with cut off length (Formula presented.) mm was applied to the measured tooth profile to obtain the waviness. The calculated roughness parameters and the obtained tooth profile with waviness for each test were imported into the KISSsoft software to calculate the contact stress and specific film thickness at the corresponding load stage. Experimental results show that smooth gear surface can reduce or even avoid micropitting damage, but could lead to a reduction in pitting life.

The use of high strength steel has the potential to reduce the amount of steel used in bridges and thereby, facilitate a more sustainable construction. In this study, an optimization of a composite steel and concrete bridge is presented. The study aimed at identifying the potential benefits of using high strength steel, compared to conventional steel, in terms of weight, material cost and environmental impact. The optimization routine followed what is outlined in the Eurocode and satisfied both ultimate and serviceability limit state conditions, with exception of fatigue. To study the influence of fatigue a separate verification was performed on the solutions found from the optimization. The study showed that substantial savings in weight, environmental impact and material cost could be made by implementing high strength steel. However, when the fatigue verification according to Eurocode was considered, the potential benefits of using steels of higher grade vanished completely.

A new methodology to estimate costs for wear and Rolling Contact Fatigue (RCF) on rails that cause a major portion of track maintenance costs is presented. It is demonstrated for a standard UIC-Y25 bogie and the FR8RAIL bogie, a softer and cross-braced iteration of the former, based on running conditions for the Swedish iron-ore line. Various non-linearities in the vehicle and track models have been considered. The rail profile evolution and the surface-initiated fatigue on the rail surface for different track radii with progressive tonnage are calculated using iterative multibody simulations. Additionally, the impact of maintenance measures on the long-term rail profile evolution has been considered with optimal preventive rail grinding actions implemented at fixed tonnage intervals based on the recommendations from EN13231-5. The rail profile attributes after 100 Mega Gross Tonnes passage are presented and discussed for both running gears. In doing so, the methodology addresses the long-term ‘track-friendliness’ of running gears considering wear, RCF and the intermediate track maintenance strategies.

With the need for increasing length of freight trains, Longitudinal Train Dynamics (LTD) and its influence on the running safety becomes a key issue. LTD is a complex issue with contributions from both the vehicles and the operating conditions such as infrastructure design, braking regimes, etc. Standards such as the UIC Code 530-2 and EN-15839 detail the procedure for on-track propelling tests that should be conducted to determine the running safety of a single wagon. Also, it only considers a single S-curve and specifies neighbouring wagons and buffers. The resulting LTD would hence not be able to judge the effects of various heterogeneities in the train formation such as the adjacent wagons, buffer types, carbody torsional stiffnesses, curvatures, etc. Here, there is a potential of using three-dimensional multi-body simulations to develop a methodology to judge the running safety of a train with regards to its longitudinal dynamic behaviour, subjected to various heterogeneities. A tool based on three-dimensional multi-body simulations has been developed to provide Longitudinal Compressive Force (LCF) limits, tolerable LCF for wagon combinations passing through S-curves of varying curvatures and assess the sensitivities of the various heterogeneities present in the train. The methodology is applied to open wagons of the ‘Falns’ type on tight S-curves by calculating the corresponding tolerable LCF and the effect of various parameters on the same is discussed.

Long freight trains up to 1500 m in length are currently not in regular operation in Europe. One of the important reasons for the same is high inter-wagon forces generated during the operation, especially when pneumatic (P-type) brake systems are used. For long trains with multiple locomotives at different positions along the train, radio communication with necessary fail-safe mechanisms can be used to apply the brakes. Long freight train operation on a given line is subjected to various attributes such as braking/traction scenarios, loading patterns, wagon geometries, brake-block materials, buffer types, track design geometries, etc., which are referred to as heterogeneities. The complex longitudinal train dynamics arising in the train due to various heterogeneities play a major role in determining its running safety. In this context, the maximum in-train force refers to the maximum force developed between any two wagons along the train during operation. The tolerable longitudinal compressive force is the maximum compressive force that can be exerted on a wagon without resulting in its derailment. Here, the authors adopt a bottom-up approach to model pneumatic braking systems and inter-wagon interactions in multibody simulation environments to study the complex longitudinal train dynamics behavior and estimate maximum in-train forces and tolerable longitudinal compressive forces, subjected to various heterogeneities. These two force quantities intend to facilitate a given freight train operation by providing guidelines regarding the critical heterogeneities, that currently limit its safe operation. In doing so, the authors propose the notion to have an operation-based approval for long freight trains using the simulations-based tool.

Compaction by vertically or horizontal oscillating probes increases not only the soil stiffness but also the horizontal effective stress. An important, but often neglected, consequence is that compaction also causes preloading of the soil. The change in horizontal stress following vibratory compaction can be measured independently by two in situ methods - a cone penetration test (CPT) and a flat dilatometer test (DMT). Values of sleeve resistance (CPT) and horizontal stress index (DMT) can be determined prior and after compaction. In this work, five case histories reported in the literature where different vibratory compaction methods were used (dynamic compaction, vibroflotation, VibroWing, TriStar and resonance compaction) were re-analysed. For each test site, the change in CPT cone resistance and sleeve resistance was determined and compared with the increase in horizontal stress index from DMTs. The preloading effect due to vibratory compaction was estimated using empirical correlations.

A new methodology to estimate costs for wear and Rolling Contact Fatigue (RCF) on rails that cause a major portion of track maintenance costs is presented. It is demonstrated for a standard UIC-Y25 bogie and a FR8RAIL bogie, a softer and cross-braced iteration of the former. The rail profile evolution and the surface-initiated fatigue on the rail surface for different track radii with progressive tonnage are calculated using multi-body simulations. ‘Fastrip’ is used to calculate tangential stresses on the contact patch. Various non-linearities in the vehicle and track models have been considered, based on running conditions on the Swedish Iron-ore line. A cyclic rail grinding procedure at fixed tonnage intervals based on recommendations from EN13231-5 is implemented, to also account for the effect of track maintenance on the rate of rail surface damage. The wear depths (W), worn cross-sectional areas (A) and the number of axle passes that carry a risk for RCF initiation (Nr) are presented and discussed for 100 Mega Gross Tonnes passage. In doing so, the methodology addresses ‘track-friendliness’ of the running gear considering both its design and the track maintenance strategies.

This paper reports on a novel project to develop a fully active, two axle railway vehicle which could provide reduced track forces and noise and improved ride comfort compared with existing vehicles. Computer simulations have been used to tune the suspension components and control systems to ensure good passenger comfort and safe operation even in failed control cases. A prototype of the vehicle has been constructed and tested on a full size roller rig. The test results confirm the computer simulations and demonstrate that for speeds up to 200 km/h and in all failure modes the vehicle was stable and with low track forces and high stability and passenger comfort.

This paper deals with the dynamic response of railway bridges traversed by articulated trains, specifically the interaction effect between the coach length D and bogie distance dBA. Current design code EN 1991-2 stipulate that the ratio D/dBA should not be close to an integer value, but no further guidance is given. By using train signatures and a so-called bogie factor, the combined effect is illustrated in a non-dimensional domain. The results are also presented by realistic examples which show that integer ratios of D/dBA are not necessarily worse than non-integer ratios. This is further confirmed by a parametric study of simply supported beams and ranges of train parameters according to EN 1991-2 Annex E. 

Since the concept of active suspensions appeared, its large possible benefits has attracted continuous exploration in the field of railway engineering. With new demands of higher speed, better ride comfort and lower maintenance cost for railway vehicles, active suspensions are very promising technologies. Being the starting point of commercial application of active suspensions in rail vehicles, tilting trains have become a great success in some countries. With increased technical maturity of sensors and actuators, active suspension has unprecedented development opportunities. In this work, the basic concepts are summarized with new theories and solutions that have appeared over the last decade. Experimental studies and the implementation status of different active suspension technologies are described as well. Firstly, tilting trains are briefly described. Thereafter, an in-depth study for active secondary and primary suspensions is performed. For both topics, after an introductory section an explanation of possible solutions existing in the literature is given. The implementation status is reported. Active secondary suspensions are categorized into active and semi-active suspensions. Primary suspensions are instead divided between acting on solid-axle wheelsets and independently rotating wheels. Lastly, a brief summary and outlook is presented in terms of benefits, research status and challenges. The potential for active suspensions in railway applications is outlined.

A mechatronic rail vehicle with reduced tare weight, two axles and only one level of suspension is proposed with the objective of reducing investment and maintenance costs. A wheelset to carbody connection frame in composite material will be used both as structural and as suspension element. Active control is introduced to steer the wheelsets and improve the curving performance. A feedforward control approach for active curve steering based on non-compensated lateral acceleration and curvature is proposed to overcome stability issues of a feedback approach. The feedforward approach is synthesised starting from the best achievable results of selected feedback approaches in terms of wheel energy dissipation and required actuation force. A set of 357 running cases (embracing 7 curves, 17 speeds per curve and 3 conicities) is used to design the controller. The controller is shown to perform well for conicity and track geometry variations and under the presence of track irregularities.