Shock and Vibration

Bridges situated on small-radius reverse curves play a pivotal role within some railway networks, exerting influence over project-wide design progress. Typically, assessing the safety of bridge design parameters necessitates laborious vehicle-bridge dynamic coupling vibration numerical analysis or model experiments. To streamline the design process and enhance efficiency during the preliminary design phase, we propose an efficient method to assess the dynamic performance of bridges on small-radius reverse curves. This approach enables direct prediction of bridge dynamic performance based on design parameters, eliminating the need for numerical simulations and model experiments. We first develop a vehicle-bridge coupling vibration program grounded in train-curve bridge coupling vibration theory, validated using on-site measured data. Subsequently, through numerical simulation experiments, we evaluate 80 simply supported beam bridges on small-radius reverse curves under various operating conditions, generating ample dynamic response data for bridge pier tops and girders. These data are then compared with regulatory thresholds to assign dynamic performance labels. After identifying essential design parameters as data features using Fisher scores, we proceed to input these features into a support vector machine (SVM). Through supervised training with dynamic performance labels, this process empowers the SVM model to predict the dynamic performance of the bridge. Our results demonstrate that this method circumvents the need for detailed vehicle-bridge interaction analysis, yielding an impressive 86.9% accuracy in predicting dynamic performance and significantly boosting computational efficiency. Besides, the top five design parameters that significantly influence the prediction of bridge dynamic performance are obtained. This novel approach has the potential to expedite design assessments and enhance safety in railway bridge construction.

It is crucial to comprehend the heat soak phenomenon, which may result in a significant temperature increase after the shutdown followed by a gradual decrease. This could bring potential risks for the engine including oil coking. The temperature change of engine components dictates the clearance after shutdown, while startup strategies are primarily based on this. A simulation strategy, utilizing computational fluid dynamics (CFD) and finite element analysis (FEA) coupled models, is suggested to investigate the transient temperature and clearance after shutdown. The maximum temperature deviation between the simulation result and experimental data are less than 6%. Flow parameters, including velocity and mass flow rate obtained from the CFD result, were applied as boundaries of the FEA model. Based on the FEA model, transient temperature calculations were also conducted for 20 hours after shutdown. The results indicate that the FEA model demonstrates good agreement with the CFD simulation, with a maximum deviation of less than 5% and at only 0.2% of the simulation time. After the engine shuts down, the stator’s temperature change rate is faster than that of the rotor due to better cooling conditions and relatively small heat capacity. Consequently, the seal clearance increases in the initial period after shutdown and then decreases to a minimum value. The nondimensional minimum clearance can be 0.8 times the cold state value at the location of the high-pressure turbine seal.

The rolling bearing is one of the commonly used mechanical components in rotating machinery, and its health directly affects the normal operation of equipment. However, the fault signal of rolling bearing is susceptible to noise interference, which makes it difficult to extract the fault characteristics of the rolling bearing and thus affects the accuracy of the diagnosis results. To address this problem, this paper proposes a method by using a snake optimization algorithm to optimize variational mode decomposition (SOA-VMD) and applies it to the extraction of the fault feature of rolling bearing. First, the minimum Shannon entropy to kurtosis ratio (EKR) is used as the fitness function of SOA to search for the best parameter combination of VMD. Second, the optimized VMD is used to decompose the vibration signal of rolling bearing to obtain K intrinsic mode functions (IMFs). Then, the IMF with the most fault information is selected for reconstruction through EKR. The Teager–Kaiser energy operator (TKEO) spectrum analysis is performed on the reconstructed signal. Finally, this method is used to analyze the simulation signal and rolling bearing vibration signal and compared with empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD), and complete ensemble empirical mode decomposition adaptive noise (CEEMDAN) algorithms to verify the feasibility and effectiveness of the SOA-VMD method.

Since the development of industry, sound absorption and noise reduction have gradually become an urgent problem to be solved. Lightweight polymer film materials are very effective in response to sound waves, and sound waves can easily cause vibration of the film, which can convert sound energy into vibration and film friction to achieve sound absorption. The application conditions of the film material are very harsh, that is, a support body is required to fix the film and the film needs to be tensioned. The film is very thin and easy to damage. The idea of this research is to transform the film into a bubble structure and use a large number of film bubbles to form a cavity structure material. As a unit of the sound absorption structure, bubbles can avoid damage to the film. In this paper, commercial polyvinyl chloride film bubble materials are used to prepare two kinds of film multicavity structure materials, and the sound absorption performance of this film multicavity structure material is studied. The research results show that this film multicavity structure material has very excellent broadband sound absorption performance, which changes the narrow band sound absorption properties of the usual film single cavity. The average sound absorption coefficient can reach 0.84 in frequency range from 500 Hz to 6400 Hz. This structural material has a single peak sound absorption curve at the middle and low frequency bands, which is the characteristic of resonance sound absorption. And at the middle and high frequency bands, it exhibits the characteristics of broadband sound absorption. The film multicavity structure material has both cavity sound absorption and broadband sound absorption characteristics.

To study the impact of cutting blasting on the surface, a vibration waveform prediction function was constructed, and a method of dividing the affected area was proposed. Based on the equivalent spherical charge theory, it is possible to establish a connection between the fitting coefficient and the engineering parameters in the equivalent source intensity function. Furthermore, a blasting vibration waveform function suitable for engineering can be constructed. Secondly, the reliability of the method introduced is verified through the data monitored on-site. Finally, the affected partitions of blasting vibration are divided based on the peak particle velocity and vibration displacement as standards. The results show that the vibration waveform prediction system introduced can restore the vibration waveform corresponding to cutting blasting. In addition, the zoning method can reasonably divide the scope of the affected area.

The use of earth-covered magazines (ECMs) is increasingly prevalent in protective engineering due to their concealment and cost-effectiveness. To explore the optimal thickness of earth covering for ECMs, scaled model tests were conducted under explosive charges equivalent to 30 kilograms of TNT. The resulting overpressure outside the model in the 180° direction was measured. Subsequently, computational analyses were conducted employing LS-DYNA software to examine these experimental findings. The findings indicate that increasing the thickness of the rear soil can mitigate peak overpressure, delay the air shock wave’s arrival time, and reduce the impulse of the positive phase. The numerical calculations closely align with experimental data, with peak overpressure deviation remaining under 10%. The shock wave initially impacts the top of the model before reaching the rear, with soil scattering more pronounced in the 90° direction compared to the 180° direction. Furthermore, an analysis of soil energy absorption rate variation was conducted based on energy conservation principles. These results provide valuable insights for optimizing the design and construction of ECMs.