To study the unsteady aerodynamic loads of high-speed trains in fluctuating crosswinds, the fluctuating winds of a moving point shifting with high-speed trains are calculated in this paper based on Cooper theory and h...To study the unsteady aerodynamic loads of high-speed trains in fluctuating crosswinds, the fluctuating winds of a moving point shifting with high-speed trains are calculated in this paper based on Cooper theory and harmonic superposition method. The computational fluid dynamics method is used to obtain the aerodynamic load coefficients at different mean yaw angles, and the aero- dynamic admittance function is introduced to calculate unsteady aerodynamic loads of high-speed trains in fluctuating winds. Using this method, the standard deviation and maximum value of the aerodynamic force （moment） are simulated. The results show that when the train speed is fixed, the varying mean wind speeds have large impact on the fluctuating value of the wind speeds and aerodynamic loads; in contrast, when the wind speed is fixed, the varying train speeds have little impact on the fluctuating value of the wind speeds or aerodynamic loads. The ratio of standard deviation to 0.SpKU2, or maximum value to 0.5pKU2, can be expressed as the function of mean yaw angle. The peak factors of the side force and roll moment are the same （ - 3.28）, the peak factor of the lift force is - 3.33, and the peak factors of the yaw moment and pitch moment are also the same （- 3.77）.展开更多
Pressure fluctuations signals of a lab-scale fiuidized bed （15 cm inner diameter and 2 m height） at different superficial gas velocities were measured. Recurrence plot （RP） and recurrence rate （RR）, and the simp...Pressure fluctuations signals of a lab-scale fiuidized bed （15 cm inner diameter and 2 m height） at different superficial gas velocities were measured. Recurrence plot （RP） and recurrence rate （RR）, and the simplest variable of recurrence quantification analysis （RQA） were used to analyze the pressure signals. Different patterns observed in RP reflect different dynamic behavior of the system under study. It was also found that the variance of RR （a2R） Could reveal the peak dominant frequencies （PDF） of different dynamic systems： completely periodic, completely stochastic, Lorenz system, and fluidized bed. The results were compared with power spectral density. Additionally, the diagram of σ^2RR provides a new technique for prediction of transition velocity from bubbling to turbulent fluidization regime.展开更多
基金supported by the 2013 Doctoral Innovation Funds of Southwest Jiaotong Universitythe Fundamental Research Funds for the Central Universities,the National Key Technology R&D Program of China (2009BAG12A01-C09)the High-Speed Railway Basic Research Fund Key Project (U1234208)
文摘To study the unsteady aerodynamic loads of high-speed trains in fluctuating crosswinds, the fluctuating winds of a moving point shifting with high-speed trains are calculated in this paper based on Cooper theory and harmonic superposition method. The computational fluid dynamics method is used to obtain the aerodynamic load coefficients at different mean yaw angles, and the aero- dynamic admittance function is introduced to calculate unsteady aerodynamic loads of high-speed trains in fluctuating winds. Using this method, the standard deviation and maximum value of the aerodynamic force （moment） are simulated. The results show that when the train speed is fixed, the varying mean wind speeds have large impact on the fluctuating value of the wind speeds and aerodynamic loads; in contrast, when the wind speed is fixed, the varying train speeds have little impact on the fluctuating value of the wind speeds or aerodynamic loads. The ratio of standard deviation to 0.SpKU2, or maximum value to 0.5pKU2, can be expressed as the function of mean yaw angle. The peak factors of the side force and roll moment are the same （ - 3.28）, the peak factor of the lift force is - 3.33, and the peak factors of the yaw moment and pitch moment are also the same （- 3.77）.
基金Supports from the Iran National Science Foundation(INSF) in lran(No.91001766)
文摘Pressure fluctuations signals of a lab-scale fiuidized bed （15 cm inner diameter and 2 m height） at different superficial gas velocities were measured. Recurrence plot （RP） and recurrence rate （RR）, and the simplest variable of recurrence quantification analysis （RQA） were used to analyze the pressure signals. Different patterns observed in RP reflect different dynamic behavior of the system under study. It was also found that the variance of RR （a2R） Could reveal the peak dominant frequencies （PDF） of different dynamic systems： completely periodic, completely stochastic, Lorenz system, and fluidized bed. The results were compared with power spectral density. Additionally, the diagram of σ^2RR provides a new technique for prediction of transition velocity from bubbling to turbulent fluidization regime.
