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).

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.

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%.

This work applies numerical simulations and a drive cycle perspective for the estimation of wear on rail vehicle collector strips using an existing heuristic wear model. As it is crucial to understand the origin of wear patterns to ensure long service life, the proposed analysis method allows to identify the contribution of each drive stage during operation to the wear pattern and to compare their wear rates against each other. Input data is created by numerically simulating the power intake of a rail vehicle during a drive cycle between two stations and extracting power-speed couples for characteristic drive stages. The dynamic interaction between pantograph and catenary is then simulated using a FE-representation of the catenary and a pantograph model with two individually suspended flexible collector strips. Using these transient time signals as input data to the heuristic wear model, the lateral wear distribution along both collector strips can be estimated for each drive stage. Here, a representative run of a Swedish X2 higher speed train is used as a case example. The results show that mechanical wear dominates on average, but that there is a considerable electrical wear intensity, especially during acceleration. This contribution is however relativised by the short distance covered in this stage, and the total wear pattern is dictated by the cruising stage. The wear patterns show high dependence on the evaluated frequency range in the force signal.

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.

This work presents an analysis of the sensitivity and impact of various vehicle parameters on the estimation of ballast settlement cost in passenger and freight systems in the Universal Cost Model (UCM). The study compares the vertical force obtained from multibody simulation results to analytical solutions for passenger and freight wagons. These results highlight the significance of considering unsprung mass, vehicle type, and vertical suspension parameters when estimating ballast settlement cost with the analytical representation of the P2 force. For passenger vehicles, the simulated P2 force is sensitive to all investigated parameters, with an average sensitivity of approximately 18%. The choice of method for determining vertical force for simulated track irregularities also influences the impact of these parameters. The simulated P2 force for the track section with track irregularities exhibits a higher percentile difference compared to other track cases, indicating that the parameters have a greater impact on the simulation of P2 force. In contrast, for freight vehicles, the simulated P2 force shows sensitivity only to two out of seven investigated parameters: the vertical stiffness of the outer and inner coil springs. The impact of these parameters is dependent on track irregularities and the chosen method for determining vertical force. The standard deviation measure has the highest impact on the outer coil spring, while the 99-percentile and mean value measure show a medium and minimal impact, respectively. The inner coil spring has an overall minimal impact across all track cases and comparison methods. These results show that the existing UCM methods can be improved by incorporating the identified parameters, thereby enhancing the accuracy of ballast maintenance cost estimation modules.