Sand in wheel-rail contacts is successfully used for a long time to increase adhesion. However, the physical effects responsible for this adhesion increase remain unclear. To improve the understanding of these effects an approach combining experiments with Discrete Element Method (DEM) modeling is followed. Results from initial breakage and high loading experiments on single sand grains under purely normal loading conditions show that the spreading behavior and the forming of clusters of solidified sand fragments depend on the type of sand and the contact conditions, namely dry and wet. The experimental data were used to develop, calibrate and validate DEM models including particle breakage. These DEM models can describe the observed effects. Finally, a systematic classification is presented where tangential relative motion due to slip can occur in a sanded wheel-rail contact. This is seen as an important basis for future experimental and modelling work.
Due to the increased popularity of railway transportation, maximizing the availability of both vehicles and infrastructure is on high demand. To fulfill this requirement, the development of efficient maintenance strategies is in the focus of research in this area. Such strategies require a robust estimation and prediction of the vehicle’s component health states. In this chapter, a sliding-mode-based algorithm is proposed as a solution for the identification of suspension parameters, which are credible representatives of the operational status. The accuracy of the estimation, robustness to model uncertainties, and sensitivity to faults are shown through different test scenarios in a simulation environment.
Maintenance work on ballasted railway tracks due to the differential settlement along the track is a time-consuming and cost-intensive task.The mechanical properties of the sleeper, especially the sleeper's bending behaviour under load, influence how the wheel-rail contact forces are transferred through the ballast bed to the ground, which in turn significantly affects track settlement.A deeper physical understanding on the interaction between the railway sleepers and the ballast can therefore help to improve railway infrastructure and reduce maintenance work.To study the dynamic sleeperballast interaction numerically the discrete element method (DEM) is a commonly used tool to get insight into the physical effects inside the ballast bed.However, in recent DEM related research the sleeper was rarely considered as an elastically deformable body and a simple yet accurate sleeper model that considers proper mechanical properties of the sleeper is still missing.Therefore, a model was developed that uses the particle facet model (PFM) to implement a sleeper with a smooth surface into the DEM framework without the need of time-consuming coupling methods.This approach enables railway track simulations that consider the effects of sleeper elasticity on the discrete ballast realistically.Box-test simulations were carried out, in which the elastic sleeper model was placed on a compacted ballast bed and then cyclically loaded.The results obtained from the simulations are in qualitative agreement with the literature.Additionally, it was shown that the simulation outcome heavily depends on the initial (filling) configuration of the ballast bed.The modelling approach offers a realistic integration of elastic sleepers into railway track DEM simulations and is able to provide deeper insights into the underlying physics of the sleeper-ballast interaction.Studies of complex railway track phenomena, like hanging sleeper situations, are thus made possible.
Thermal runaway (TR) reactions of lithium ion cells pose a particular risk to the safety of battery systems. Beside the energy remaining in the cell body, particles and gases exiting the cell during the venting process cause major thermal load for adjacent cells and further system components [1]. In addition, high energy particles can act as an ignition source in the presence of ignitable venting gases and oxygen [2]. Therefore, measurements minimizing the risk of thermal propagation (TP) caused by venting ejecta material and the ignition of combustible gases are introduced on system level. For the dimensioning of the measures, the energy transported by venting particles and gases is identified as a crucial parameter. Depending on the amount of transported energy, the gas cooling distance as well as the complexity of the particle separation structure differ. Simulation methods are used to evaluate the effectiveness of such system measures. More information is needed regarding energy release to accurately predict the system behavior in simulations and to use them as a tool for design. Introducing a novel approach for TR tests enables the determination of the energy remaining in the cell body, separated from the energy transported by venting ejecta. The test setup combines a calorimeter combined with a cyclone separator placed inside an autoclave reactor. The TR energy release of 156 Ah prismatic lithium ion cells have been analyzed using the setup. Venting particles and gases transported a main part of the released energy out of the cell during the TR. Using an analytical approach, the energy transferred to the calorimeter is calculated. The obtained data can be used for validating simulation models for predicting the impact of venting reactions on TP. References [1] W. Walker, J. Darst, D. Finegan, G. Bayles, K. Johnson, E. Darcy, S. Rickman, J. Power Sources 2019, 415, 207-218 [2] H. Wang, H. Xu, Z. Zhao, Q. Wang, C. Jin, Y. Li, J. Sheng, K. Li, Z. Du, C. Xu, X. Feng, Appl. Therm. Eng. 2022, 211, 118418.
