Research on Optimization of Structural Parameters of Equipment Cabin Bottom Cover

Abstract

Since the railway vehicle structure has lots of parameters and several complex constraints, this study establishes a method for structural parameter optimization based on sensitivity analysis and surrogate models. Fatigue crack problem of the equipment cabin bottom cover of the EMU is taken as an example to optimize its structural parameters. First, establish the finite element (FE) model of the bottom cover and compare it with the bench test results to verify the accuracy of the load and restraint conditions. The sensitivity analysis method is used to determine the main parameters. The input samples are obtained by Latin hypercube sampling method, and the output samples are obtained by the method jointly developed by ABAQUS+Python and the surrogate model between the input and output samples is obtained by fitting, and its accuracy is verified. According to the design requirements, the optimization objective function and constraint conditions are established, and the optimization result is obtained by optimization algorithm. The results were substituted into the FE model for verification. The results show that the maximum equivalent stress of the bottom cover is reduced from 126.7 MPa to 78.9 MPa under a cyclic aerodynamic load of ±4 kPa, which is 37.7% optimized, and the effect is significant. This method avoids the iterative optimization of the FE model and improves the optimization efficiency.

Aerodynamic fatigue evaluation of the equipment cabin of high‐speed trains based on sub‐zone loading method

“…The EMU vehicle body is designed to withstand an aerodynamic load of 4 kPa when running at 250 km/h. 25 Moreover, since the measured aerodynamic load is smaller than the design standard, [7][8][9][10] it can be inferred that the stress range generated by the aerodynamic load is within the elastic limit of cabin material, resulting in linear dynamic stress. Consequently, the dynamic stress of the equipment cabin can be decomposed into distinct sub-zones, enabling the application of the superposition principle to more precisely evaluate the stress characteristics of each individual sub-zone.…”

“…Previous studies demonstrated that upon entering a tunnel, the surrounding air density was altered, inducing pressure waves that propagated along the tunnel. 8 The abrupt changes in pressure differentials within the equipment compartment stemmed from the transmission of compression and rarefaction waves. 4,32 These waves triggered a cycle of fluctuating peaks and troughs until the train emerged from the tunnel.…”

“…On one hand, the aerodynamic pressure spectrum was used to directly account for remaining fatigue life. To cite a few examples, Zou et al 8 optimized the equipment cabin bottom cover of the EMU on account of fatigue crack problem using design static aerodynamic loads. Lu et al 9 converted the transient pressure waves on the side wall of the car body as the train passes, into aerodynamic load to obtain the car body fatigue strength.…”

Thermal Parameters Inversion Method for Concrete Dam Based on Optimal Temperature Measuring Point Selecting

“…Whether the inversion can achieve good results or not mainly depends on the performance of the surrogate model. Over the past few decades, several surrogate models have been most widely used, including support vector regression (SVR) [31], kriging (KRG) [32], and radial basis function (RBF) [33]. By comparing diferent models, the results show that SVR has some advantages in terms of sparsity, accuracy, and fexibility, especially in dealing with small samples and nonlinear problems.…”