Analysis of the Influence of Transmission Housing Elasticity on the Vibration Characteristics of Gear Shafting under Coupling Effect

The influences of transmission housing elastic deformations on the vibration gear shafting characteristics are studied. The vibration model of the vehicle transmission system in consideration of the dynamics coupling of the housing and the gear shafting is constructed. Aiming at a vehicle transmission, the mathematical model of the bending and torsional gear shafting vibrations is established based on the lumped mass method. Following the elastic treatment of the box, a comprehensive stiffness model at the bearing considering the housing deformation is proposed to achieve the dynamic coupling between the box and the gear shafting system. Furthermore, the gear shafting vibration characteristics considering housing deformations are obtained by integrating multisource dynamic excitation, which is solved using an iterative method. The results are verified through a bench test. And, it shows that the elastic deformation of the housing aggravates the gear shafting vibration (bending and torsional coupled vibration). The peak frequency mostly remains the same. The maximum speed changes amplitude and associated root mean square value (calculated at the gear position) increase by 55.5% and 59.6%, respectively. Next, the maximum bearing support force and its root mean square value are increased by 63.7% and 97.6%, respectively. Finally, the largest increase in maximum vibration acceleration at the measuring point and the simulated root mean square value are 90% and 63.1%, respectively. It is concluded that the research results provide a theoretical basis for the study of transmission dynamic reliability.

Stochastic Dynamic Response Analysis of the 3D Slopes of Rockfill Dams Based on the Coupling Randomness of Strength Parameters and Seismic Ground Motion

Because rockfill strength and seismic ground motion are dominant factors affecting the slope stability of rockfill dams, it is very important to accurately characterize the distribution of rockfill strength parameters, develop a stochastic ground motion model suitable for rockfill dam engineering, and effectively couple strength parameters and seismic ground motion to precisely evaluate the dynamic reliability of the three-dimensional (3D) slope stability of rockfill dams. In this study, a joint probability distribution model for rockfill strength based on the copula function and a stochastic ground motion model based on the improved Clough-Penzien spectral model were built; the strength parameters and the seismic ground motion were coupled using the GF-discrepancy method, a method for the analysis of dynamic reliability of the 3D slope stability of rockfill dams was proposed based on the generalized probability density evolution method (GPDEM), and the effectiveness of the proposed method was verified. Moreover, the effect of different joint distribution models on the dynamic reliability of the slope stability of rockfill dams was revealed, the effect of the copula function type on the dynamic reliability of the slope stability was analysed, and the differences in the dynamic reliability of the slope stability under parameter randomness, seismic ground motion randomness, and coupling randomness of parameters and seismic ground motion were systematically determined. The results were as follows: the traditional joint distribution models ignored related nonnormal distribution characteristics of rockfill strength parameters, which led to excessively low calculated failure probabilities and overestimations of the reliability of the slope stability; in practice, we found that the optimal copula function should be selected to build the joint probability distribution model, and seismic ground motion randomness must be addressed in addition to parameter randomness.

Dynamic Reliability Evaluation of Diesel Generator System of One Chinese 1000MWe NPP Considering Temporal Failure Effects

Loss of power supply from the diesel generator system (DGS) after loss of offsite power (LOOP) will pose great threat to the safety of GEN-II pressurized water reactors (PWR). Therefore, it is very desirable to evaluate the DGS’s reliability. The traditional analyzing tools are limited to static approaches neglecting the dynamic sequence failure behaviors, such as reliability block diagram (RBD), static fault tree (SFT). Static reliability modeling techniques are not capable of capturing the dynamic sequence-dependent failure behaviors typically existing in NPP safety systems such as DGS, and thus often overestimate the unreliability of systems. In this paper, motivated to study the effects of sequence failure behaviors, dynamic fault tree (DFT) is applied to evaluate the reliability of the DGS of one Chinese 1000MWe Nuclear Power Plant (NPP), and an integrated two-phased Markov Chain model is also developed, which can be considered as a contribution of this article. Comparative study of DGS reliability between DFT and SFT is carried out. The results indicate that compared with the result derived from the DFT model, the unreliability of DGS calculated by SFT is greatly overestimated by about one to two orders of magnitude. Therefore, DFT has a potential to improve the economy of NPP by relaxing the overestimated unreliability of nuclear power systems.

Probability Density Evolution Algorithm for Stochastic Dynamical Systems Based on Fractional Calculus

With the increasing load and speed of trains, the problems caused by various random excitations (such as safety and passenger comfort) have become more prominent and thus arises the necessity to analyze stochastic dynamical systems, which is important in both academic and engineering circles. The existing analysis methods are inadequate in terms of computational accuracy, computational efficiency, and applicability in solving complex problems. For that, a new efficient and accurate method is used in this paper, suitable for linear and nonlinear random vibration analysis of large structures as well as static and dynamic reliability assessment. It is the direct probability integration method, which is extended and applied to the random vibration reliability analysis of dynamical systems. Dynamical models of the dynamic system and coupled system “three-car vehicle-rail-bridge” are established, the time-varying differential equations of motion are derived in detail, and the dynamic response of the system is calculated using the explicit Newmark algorithm. The simulation results show the influence of the number of representative points on the smoothness of the image of the probability density function and the accuracy of the calculation results.