This paper studies the phenomenon of internal resonance in high-speed vehicle system under high frequency periodic excitations. A numerical model of the vehicle system, taking into consideration the dynamic effects of the primary suspension system and the flexibility of the car-body, is established for the study. An approximate approach incorporating the incremental harmonic balance method with frequency response function is adopted to solve the dynamic responses of the vehicle system in frequency domain. Numerical results show that internal resonance vibration in the vehicle system may occur with certain combinations of design parameters of the vehicle system. The vibration of the car-body and the primary suspension system are significantly amplified with energy transmitted between the natural modes of the car-body and the primary suspension system. Parametric studies on the internal resonance are further explored. Results show that the nonlinearity of the primary suspension spring and the modal damping ratio of the vehicle system play very important roles to the occurrence of internal resonance.

Abstract. The pipeline's stability is the key problem of submarine pipeline's design. In order to supply the theory basis for the pipeline's design, the ABAQUS software has been adopted to analyze the pipe/soil system. The Ramberg-Osgood model has been adopted to simulate the seabed; the contact pair also adopted to simulate the pipe/soil system, the dynamic boundary contact problem of pipe embedded into the seabed has been analyzed. The computation has been operated according to change pipe's subweight, environment load, pipe's diameter, yielding stress and so on. The computation results have shown that these parameters have effects on the pipe's penetration.

The Gabor wavelet is the important technique widely used in the areas of images recognition such as human face expression, it extract the more important grain features for face expression effective, but it does not take into account the relative changes in the important characteristics of each location of the point features. Aiming at recognizing the information of human face expression, fuse the geometry feature based on angle changes at key parts on face expression, and then a radial basis function (RBF) neural network is designed as the classifier to perform recognition. The results of the experiment in the human face expression database indicate that the recognition rate by the feature fusion is obviously superior to that of traditional method.