Xuedong Liu

The gear transmission system is a safety-critical component in rail transit, typically designed for a service life exceeding 20 years. Failure analysis of such systems remains a key focus for railway engineers. This study systematically investigates four representative cases of premature gear failure in high-speed trains using a standardized analytical procedure that includes visual inspection, chemical analysis, metallographic examination, scanning electron microscopy, and hardness testing. The results identify four primary root causes: subsurface slag inclusions in raw materials, inadequate heat treatment leading to a non-martensitic layer (∼60 μm) at the tooth root, grinding-induced temper burns (crescent-shaped "black spots") accompanied by a hardness drop of ∼100–150 HV, and insufficient lubrication. The interdependencies between these factors and failure mechanisms, e.g., fatigue cracking, spalling, and thermal scuffing, are analyzed. This work provides an evidence-based framework for improving gear reliability and proposes targeted countermeasures, such as ultrasonic inclusion screening and real-time grinding temperature control, to extend operational lifespans.

This study investigates premature fatigue failures in three EA1N steel axles from permanent magnet direct-drive locomotives during wheel-seat bending tests. Complete fracture occurred in one axle at 3 million cycles, and in the other two axles, cracks appeared and were observed through magnetic particle detection at 3.5 million and 1.6 million cycles, respectively. A comprehensive failure analysis was conducted through metallurgical examination, fractography, mechanical testing, residual stress measurement, and finite element analysis. The fractographic results revealed fractures consistently initiated at the wheel-seat to axle-body transition arc, exhibiting characteristic ratchet marks and beach patterns. The premature fracture mechanism was identified as a high-stress fatigue fracture. The residual stress measurements showed detrimental tensile stresses at the surface. Coupled with the operating stress, the stress on the axle exceeds fatigue strength, which accelerates the initiation and propagation of fatigue cracks. Based on these observations, the failure mechanism was identified, and preventive methods were proposed to reduce the risk of recurrence of the in-service axles.

The utilization of micro-sample testing has demonstrated its effectiveness in conducting quantitative research on mechanical properties, damage evolutions and fracture features. For in-service equipment, millimicron sampling allows for non-destructive testing and analysis of mechanical performance evolution during operation. This paper presents a comparative study of the miniature uniaxial tensile test (MUTT) and small punch test (SPT) by experimental and finite element methods. As a comparison, the standard conventional-size tensile tests were also carried out. Detailed analyses of the elastoplastic behaviors and damage evolutions of MUTT and SPT were presented, followed by an application case illustrating the characterization of hydrogen embrittlement sensitivity based on MUTT and SPT. An inverse finite element modeling method of load–displacement curve reproduction was used to calibrate the variations of damage parameters of hydrogen-charged MUTT and SPT specimens. Hydrogen embrittlement (HE) indexes were determined by using different calculation methods. The results reveal that the HE sensitivity estimated by MUTT is higher than that measured by SPT, which is related to the different deformation processes and strain rates of the two testing methods.

In this study, a combined experimental and finite element modeling methodology (FEM) for a nanoindentation study is presented to quantitatively investigate the influence of hydrogen on the mechanical properties of ferrite and austenite in 2205 duplex stainless steel. The experimental results showed that, during hydrogen charging, the nano-hardness of ferrite and austenite gradually increased with time, showing a hydrogen-induced hardening phenomenon. After 3 h of hydrogen charging, the nano-hardness of both ferrite and austenite reached a saturation state, and the values of the nano-hardness of ferrite and austenite increased by 17.5% and 46.1%, respectively. FEM is employed by using a dual-phase microstructure-based model to reproduce nanoindentation load–displacement curves. To minimize the indentation size effect, an analytical correction model considering geometrically necessary dislocations (GNDs) was proposed. By considering GNDs, the errors between numerical predictions and experimental data reduced from about 50% to less than 5%.

Hypergolic ignition of H₂O₂ and MEA-NaBH₄ by off-center collision of their droplets was experimentally studied, focusing on the characteristics and mechanism of droplet mixing, droplet heating and evaporation, and gas-phase ignition. The whole collision ignition process was divided into five stages, which were compared, respectively, with that of head-on collision. Under the condition of a slightly off-center collision (for cases where B < 0.35), H₂O₂ droplets penetrate MEA-NaBH₄ droplets after the collision and coalesce with it, but the internal H₂O₂ drop inside the MEA-NaBH₄ droplet does not form a stable sphere. Instead, it rotates and expands inside the mixed droplet. With B increasing to 0.59, the droplets no longer coalesce after collision but separate away, forming satellite droplets. In such cases, multi-ignition mode is observed. When B increases to a certain extent, specifically, 0.85, a grazing collision is observed such that no mass transfer exists during the interaction of droplets, which leads to ignition failure. A theoretical model quantifying droplet swelling rate was established to calculate the volume change of the droplet. It was found that the swelling can be attributed to the flash boiling of superheated internal H₂O₂ fluid. Meanwhile, the ignition delay time was found to linearly decrease with B at various Wes until the extent where the chemical reaction takes over control, leading to an almost constant time delay defined as RDT. Additionally, the regime of ignition modes corresponding to different droplet mixing features is summarized in the We-B parametric space.

The process of superhard particle breakage in the grinding zone of the fluidized bed opposed jet mill is investigated using the CFD-DEM (computational fluid dynamics-discrete element method) coupling method with the Tavares UFRJ Breakage Model in the present study. The effects of structural and operational parameters, such as target plate structure, nozzle position, air inlet velocity, and feed rate, on the equipment stress distribution, airflow velocity, pressure field, particle velocity, and cumulative particle size distribution are thoroughly studied to determine the optimal structural and operational parameters. Experimental validation is conducted, including scanning electron microscope (SEM) observation of particle morphology and analysis of particle size distribution of ground product particles. The simulation results indicate that the wear rate of the structure without a target plate is lower than that of the structure with a target plate in the grinding central zone. Therefore, the structure without a target plate is chosen for further investigation. The cumulative particle size distribution after grinding is influenced by nozzle position, air inlet velocity, and feed rate. The particle D₅₀ is positively correlated with nozzle spacing and feed rate, while it is negatively correlated with air inlet velocity. The optimal grinding effect is achieved when the distance between the nozzle and the center of the grinding zone ranges from 52.5 mm to 72.55 mm, the air inlet velocity is 950 m/s, and the feed rate is 10.5 g/s. Through experimental investigation, it has been observed that when the feed rate is 10 g/s, the particle size distribution becomes more uniform. Furthermore, consistent trends in the cumulative particle size distribution in the experiment and simulation results can be found, which validates the present numerical model. It was observed that particles at low feed rates retain certain angular edges, while particle roundness increases at high feed rates.

As the crucial part of a transmission assembly, the monitoring of the status of the crankshaft is essential for the normal working of a reciprocating machinery system. In consideration of the interaction between crankshaft system components, the fault vibration feature is typically non-stationary and nonlinear, and the single-scale feature extraction method cannot adequately assess the fault features, therefore a novel impact feature extraction method based on genetic algorithms to optimize multi-scale permutation entropy is proposed. Compared with other traditional feature extraction methods, the proposed method illustrates good robustness and high adaptability in the signal processing of crankshaft vibrations. Firstly, the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) method is developed on the signal to obtain several intrinsic mode function (IMF) components, and the IMF components with a large kurtosis are selected for array reorganization. Then, the parameters of multi-scale permutation entropy (MPE) are optimized based on genetic algorithm (GA), the multi-scale permutation entropy is calculated and the feature vector set is constructed. The feature vector set is input into the support vector machine (SVM) and optimized by a particle swarm optimization (PSO) model for training and final pattern recognition, where the Variational Mode Decomposition(VMD)-GA-MPE with a PSO-SVM recognition model and the ICEEMDAN-MPE with PSO-SVM recognition model without GA optimization are constructed for a comparison with the proposed method. The research result illustrates that the proposed method, which inputs the genetic algorithm optimized multi-scale permutation entropy extracted from the ICEEMDAN decomposition into the PSO-SVM, performs well in impact feature extraction and the pattern recognition of crankshaft vibrations.