The combination of selective laser melting (SLM) and shape memory effect (SME) of shape memory alloys (SMA) enables to design and manufacture reusable energy-absorbing structures with complex geometry. Meanwhile, the material properties of SMA result in a design constraint that the local strain in energy-absorbing structures cannot exceed the certain limit, so the problem of maximizing the overall structure's energy absorption while limitation of local recoverable strain needs to be addressed. This study proposes a non-concurrent honeycomb structure (NHS) with curved substructures. By effectively controlling the local material's strain level, NHS maximizes specific energy absorption (SEA) while utilizing SMA recoverability for reusable energy absorption. The quasi-static compression and impact tests were progressively tested and analyzed to investigate the energy absorption characteristics, shape recovery laws, and influence of failure strain of NHS. The experimental results combined with parametric analysis demonstrate that NHS can effectively control the local strain, and the shape recovery rate after five cycles of compression-heating recovery is above 90 %. Despite the presence of localized fractures, the impact sample can still exhibit a high level of shape recovery rate at a higher structural compression ratio. Furthermore, NHS demonstrate a 38.066 % higher SEA compared to conventional honeycomb (CH).

A thermomechanical model has been developed and implemented to couple temperature, thermal expansion, contact, and wear using the finite element method. This three-dimensional, transient, and nonlinear model is unconditionally stable because of the use of an implicit solver. The weak form of the nonlinear heat transfer and elasticity equations has been derived, incorporating penalty contact, conduction, convection, radiation, and deformation. Several boundary conditions, including Dirichlet, Neumann, and Robin conditions, have been applied. We focus on mechanical train brakes due to their strong thermomechanical coupling effect. The simulation results have been validated against full-scale experimental data. Additionally, mesh sensitivity and time step sensitivity analyses are conducted to further assess the model’s accuracy. Friction heat is calculated at each time step through contact conditions, enabling the identification of hot spots and thermal cracks. The results demonstrate that this thermomechanical model is both efficient and robust. This model has been open-sourced, providing a powerful tool for advanced research in thermomechanical multiphysics analysis.

Automating human-oriented tasks and complementing humans in their work with rail vehicles, may it be in relation to management, maintenance, or network operation, can be facilitated by the use of artificial intelligence (AI), which carries the promise to make human-oriented tasks more efficient and less error-prone. It is the firm belief of the authors, given the global lack of skilled rail expertise and the increased complexity and efficiency requirements of the operational environment that AI will become a complementary companion to humans in that work environment with the potential for making railways more efficient. The aim of this chapter is therefore to provide a backgrounding regarding some of the beneficial aspects of AI and, based on concrete examples, give recommendations on how to avoid typical pitfalls when using and implementing AI in your organization.

Different forms of curved beams, due to their superior load bearing capacity, are often preferred as essential components in engineering fields, such as vehicles, buildings, and even metamaterial. One of the challenges facing most curved beam design methods, especially those with fewer parameters, is how to obtain a configuration with good performance without increasing the design parameters. A curved beam configuration design method and a three-parameter logarithmic spiral (LS) definition curve are proposed, inspired by biological tip structures, i.e. the tusk shell (Shell), the elephant ivory (Ivory), and the snake fangs (Snake). This approach provides a route for improving stress homogeneity for a curved beam, which configuration is the depiction of biological shapes using definition curves controlled by the limited number of design parameters. The three-parameter straight-circular curve (StrC) and the two-parameter circular curve (CC) were compared with the LS definition curve. The influence of biological shapes and definition curve forms on the mechanical properties of the designed beams was analyzed using finite element (FE) simulation. The results reveal that the Shell-LS model achieves better stress homogeneity, leading to an up to 6.3 % reduction in surface stress variance compared to the Shell-StrC model and an up to 12.1 % reduction in equivalent stress compared to the Shell-CC model. To validate the accuracy of the FE modeling and stress distribution in the Shell-LS model, the full-field and path stress distributions under photoelastic experiment and FE simulation have been compared.

Active wheelset steering can improve the curving performance of railway vehicles and thus reduce wear. Several control strategies have been proposed to achieve a perfect steering condition which may require feedback signals that are difficult to measure. This study proposes a control strategy for an active wheelset steering system via wheelset angular velocity measurements aimed to minimise longitudinal creepages in curves. The desired wheelset angular velocity is derived from the relation of longitudinal creepages and the wheelset movement in curves. Co-simulations with a conventional railway vehicle with two two-axle bogies are carried out for 24 cases. First, the strategy based on actual wheel-rail geometry is used to evaluate the effectiveness of the proposed control strategy; in the second step, a simplified strategy is tested using the approximated equivalent rolling radius approach. Curving performance indicators, including wheelset movements and wheel-rail wear number, are used to evaluate the performance of the control system. The results indicate the effectiveness of the proposed control strategies. Challenges and practical considerations are also discussed.

This report contextualises Engineering models for the calculation of Differentiated Track Access Charges (D-TAC) with existing D-TAC schemes in UK and Switzwerland, and the Swedish proposed D-TAC model by Öberg. The focus is to review and critically assess Andersson’s proposed updates and simplifications to Öberg’s model. Two major focus areas are addressed:Marginal Cost Recalibration, where previous econometric model values are challenged, highlighting issues such as overestimated costs, improper inclusion of snowplough expenses, and maintenance inefficiencies. A revised cost structure is proposed: 0.0130 kr/ton-km + 2.35 kr/train-km, shifting some vehicle-dependent costs to train-dependent costs.Vehicle Classification Simplification, where the proposal is to simplify marginal costs dependent only on i) average axle load and ii) the vehicle’s steering ability, aiming for a system easier for Trafikverket (TRV) to use. The price would be first proportional to the average axle load of the train to the power of 2,5, plus a value from the steering-induced rail damage costs, where the vehicles would be categorized into classes (R1, R2, S) based on their steering performance. This second cost component directly introduces incentives for the adoption of track-friendly vehicles.The different models provide different levels of Precision, Simplicity and Incentives, with Andersson’s being the most promising option. An important conclusion is that, even if no single model is inherently superior from a daily operations standpoint, understanding how vehicle upgrades affect access charges (which depends on the Precision, Simplicity and Incentives of the model) is crucial for motivating fleet improvements and reducing track maintenance costs. A lack of clarity or visible link between vehicle features and charges undermines D-TAC’s purpose.The primary recommendation is to clearly define and implement Andersson’s Simplified model, including sensitivity analyses and simulation of fleet changes and their impact in the costing scheme, in order to demonstrate its capabilities as a simple yet incentivising model.

Rail corrugation is a typical rail cyclical disease which often occurs on heavy haul, urban transit, and high-speed railways. Rail corrugation has a significant impact on vehicle dynamic performance, especially on the axle box acceleration. It may cause the bolts of axle box to loosen or break the rail fastener, and even affect the operation of vehicle. Therefore, it is necessary to discover rail corrugation in time and to repair it by rail grinding, which is an important way to improve the safety of the vehicle. A numerical analysis method based on adaptive time-frequency feature extraction is proposed in this paper. First, acceleration sensors are installed on both the left and right side of the axle box. Then the vibration features of the axle box are extracted according to the line mileage segmentation based on the adaptive time-frequency feature extraction method proposed in this paper. Finally, the impact of different wavelength and different section length of rail corrugation is compared using field test data. The test results show that the method proposed in this paper can accurately extract the features of different wavelength and different section length of rail corrugation. Moreover, compared with traditional methods, this method is proven to be strongly adaptive and highly accurate.

A mechatronic two-axle rail vehicle with only one suspension step is introduced in the Shift2Rail project Pivot2. This vehicle design reduces the vehicle weight in comparison to standard bogie vehicles. However, having only one suspension step drastically decreases passenger comfort. Thus, hydraulic actuators are introduced instead of passive dampers and active modal sky-hook control is applied. Due to the strong interaction between the running gear frame and the carbody, a blended modal solution is applied where a percentage of the acceleration of the frame is used in the feedback loop in addition to the acceleration of the carbody. To assess the performance of the controllers, simulations are carried out with the vehicle running at constant speeds from 10 km/h to 120 km/h on tangent track with high level of track irregularities. First, multiplicative dimensional reduction method (M-DRM) sensitivity analysis is applied to determine the importance of the control variables and subsequently a genetic algorithm (GA) optimization is performed to identify the control gains for each speed. The blended control proposed here can improve passenger comfort with respect to a standard modal control while maintaining similar energy and force usage.

Hunting stability is a critical factor affecting high-speed locomotives dynamic performance, inherently connected to wheel-rail contact geometry. Tread wear typically increases the nonlinearities in the contact geometry, causing stability disparities. Previous studies on stability have often overlooked these nonlinear aspects, which can be captured by the equivalent conicity function. In this study, the equivalent conicity functions of worn wheel treads are systematically categorized into six distinct classes. This classification allows for a comprehensive evaluation of their respective influence on hunting stability failure, enabling the analysis of stability characteristics of typical worn wheel treads. The limited research available on three-axle bogies motivate the selection of a locomotive equipped with such bogies as the basis for framework, aiming to bridge the gap in existing literature. Based on different stability evaluation methods, theoretical, small-amplitude hunting, and engineering critical speeds have been determined. The observed differences in different critical speeds from the perspective of equivalent conicity function are elucidated. The results show that a high equivalent conicity at small displacement can significantly reduce the theoretical critical speed, and therefore, the engineering critical speed is recommended as a criterion for stability assessment and optimization. Moreover, the Driving Energy Loss Ratio (DELR), a metric assessing both primary and secondary hunting stability, is developed to evaluate the stability of self-excited vibrations. This research provides guidance for the evaluation and optimization of railway vehicle stability.

Negotiation of turnouts imposes challenges for an active wheelset steering system due to lack of smooth transition curves and existence of rail discontinuities. These affect the performance of both the vehicle and control system in turnouts, which is investigated in this paper. The simulation is carried out with a conventional railway vehicle with two two-axle bogies passing through a crossover onto a parallel track. The Swedish 60E1-R760-1:5 turnout is used in this study. The results reveal that an active wheelset steering system can decrease the wheel-rail wear index. However, peaks in wear number take place in the switch toe and the crossing nose and they are considerably higher than other regions. A control scheme with preview is proposed by considering wheelset lateral positions on discontinuous rail profiles to avoid flange contact. The proposed control system with preview results in a further reduction of the maximum wear number by 66%.