Analysis on the Track Irregularity Power Spectral Density of the Beijing-Shanghai High Speed Railway

2014 ◽  
Author(s):  
X.B. Liu ◽  
H.Y. Li ◽  
W.D. Wang
Keyword(s):  
Spectral Density ◽  
Power Spectral Density ◽  
High Speed ◽  
High Speed Railway ◽  
Power Spectral ◽  
Track Irregularity

Method of Modeling the Excitation Spectrum of Train Based on Track Irregularity

2011 ◽  
Vol 97-98 ◽  
pp. 931-934
Author(s):  
En Wei Chen ◽  
Tie Ming Zhou ◽  
Zheng Shi Liu
Keyword(s):  
Spectral Density ◽  
Dynamic Model ◽  
Power Spectral Density ◽  
Excitation Spectrum ◽  
Excitation Power ◽  
Railway Track ◽  
Power Spectral ◽  
Left And Right ◽  
Track Irregularity ◽  
A New Technique

A new technique is present in this paper that transforms the railway track irregularity power spectral density of left and right rails into the excitation power spectral density of wheelset of train, compared with the railway track irregularity spectrums of left and right rails which are not the direct inputs of simulation dynamic model of trail. A parameter model is chosen as the model of excitation spectrum and parameters fitting result shows that this model is suitable for the excitation spectrums of traversing, floating and head shaking, and the method present in this paper is effective.

The Response of Rotating Machinery to External Random Vibration

1974 ◽  
Vol 96 (2) ◽  
pp. 477-489 ◽  
Author(s):  
J. M. Tessarzik ◽  
T. Chiang ◽  
R. H. Badgley
Keyword(s):  
Spectral Density ◽  
Power Spectral Density ◽  
High Speed ◽  
Thrust Bearing ◽  
Dynamic Environment ◽  
Amplitude Distribution ◽  
Random Vibrations ◽  
Mass Model ◽  
Power Spectral ◽  
Rotor Axis

A high-speed turbogenerator employing gas-lubricated hydrodynamic journal and thrust bearings was subjected to external random vibrations for the purpose of assessing bearing performance in a dynamic environment. The pivoted-pad type journal bearings and the step-sector thrust bearing supported a turbine-driven rotor weighing approximately twenty-one pounds at a nominal operating speed of 36,000 rpm. The response amplitudes of both the rigid-supported and flexible-supported bearing pads, the gimballed thrust bearing, and the rotor relative to the machine casing were measured with capacitance type displacement probes. Random vibrations were applied by means of a large electrodynamic shaker at input levels ranging between 0.5 g (rms) and 1.5 g (rms). Vibrations were applied both along and perpendicular to the rotor axis. Response measurements were analyzed for amplitude distribution and power spectral density. Experimental results compare well with calculations of amplitude power spectral density made for the case where the vibrations were applied along the rotor axis. In this case, the rotor-bearing system was treated as a linear, three-mass model.

Time-Domain Simulation of High-Speed Railway Track Irregularity

2014 ◽  
Vol 587-589 ◽  
pp. 1039-1042
Author(s):  
You Fu Du ◽  
Chu Yang Chen ◽  
Xiang Na Li
Keyword(s):  
Spectral Density ◽  
Density Function ◽  
Power Spectral Density ◽  
Time Domain ◽  
High Reliability ◽  
Spectral Density Function ◽  
Superposition Method ◽  
Power Spectral Density Function ◽  
Power Spectral ◽  
Track Irregularity

It was more convenient to describe track irregularity by the spatial frequency.The conventional frequency-domain transfer function can not effectively solve the vibration equation when anlysis of the vibration response to structure of vehicle-track dynamic coupling system, the time domain numerical integration must be used to solve it.The trigonometric series superposition method can be used to convert track irregularity spectrum into time domain frequency power spectral density function, and then turn the simulated irregularity samples into spectral density by the Inverse Fast Fourier Transform (IFFT), which compared with the theoretical spectral density to test the reliability of the sample. The results show that the simulated sample have the same characteristics with the given power spectral density function, which demonstrate the high reliability of this sample and it can be used as the external excitation of the locomotive vehicle system.

Direct numerical simulation of high-speed transition due to roughness elements

2019 ◽  
Vol 868 ◽  
pp. 762-788 ◽  
Author(s):  
Prakash Shrestha ◽  
Graham V. Candler
Keyword(s):  
Spectral Density ◽  
Power Spectral Density ◽  
High Speed ◽  
Shear Layers ◽  
Dynamic Mode Decomposition ◽  
Flow Structures ◽  
Dynamic Mode ◽  
Streamwise Vortices ◽  
Vortex System ◽  
Power Spectral

We study and compare instability mechanisms of a Mach 5.65 laminar boundary layer tripped by an isolated diamond-shaped trip and by an array of diamond-shaped trips using direct numerical simulations. A low-Reynolds-number experiment, consisting of the trip array (Semper & Bowersox, AIAA J., vol. 55 (3), 2017, pp. 808–817), is used to validate our simulations. Three dynamically prominent flow structures are observed in both trip configurations. These flow structures are the upstream vortex system, the shock system, and the downstream shear layers/counter-rotating streamwise vortices that originate from the top and sides of the trips. Analysis of the power spectral density of pressure reveals the source of instability to be an interaction between the shear layers and the counter-rotating streamwise vortices downstream of both trip configurations. The interaction leads to the formation of hairpin-like structures that eventually break down to turbulent flow. This finding contrasts with that of an isolated cylindrical trip (Subbareddy et al., J. Fluid Mech., vol. 748, 2014, pp. 848–878) where the upstream vortex system is found to be the source of instability. Therefore, the shape of a trip plays an important role in the instability mechanism. Furthermore, dynamic mode decomposition (Rowley et al., J. Fluid Mech., vol. 641, 2009, pp. 115–127; Schmid, J. Fluid Mech., vol. 656, 2010, pp. 5–28) of three-dimensional snapshots of pressure fluctuations unveil globally dominant modes consistent with the power spectral density analysis in both diamond-shaped trip configurations.

scholarly journals Ciphertext-only attacks on the double random-phase encryption based on redundancy vulnerability

2020 ◽  
Author(s):  
Xingzhi Wu ◽  
Haobo Chen ◽  
Liwei Zhang ◽  
Qiliang Ten ◽  
Wenqing Sun
Keyword(s):  
Spectral Density ◽  
Power Spectral Density ◽  
High Speed ◽  
Random Phase ◽  
Phase Encoding ◽  
Occlusion Test ◽  
Double Random Phase Encoding ◽  
Power Spectral ◽  
Random Phase Encoding ◽  
Simulation And Experiment

Abstract Background: The double random phase encoding techniques have received considerable attention from researchers in recent years because of its advantages of parallel and high speed processing capability. Meanwhile, the security of cryptosystem is also one of the major concerns. Methods : We experimentally demonstrated the ciphertext redundancy vulnerability of the coherent double random encryption system (DRPE). Based on the statistical ergodicity of speckles and the consistency of the power spectral density (ESD), we have proved that the most plaintext information can be retrieved from partial ciphertext alone. Results: In this paper, the simulation and experiment result were performed to verify whether the algorithm is effectiveness. The ciphertext redundancy of the DRPE system is analyzed from the results of ciphertext occlusion test. There is a risk of plaintext leakage of this scheme, as long as the average ESD can be estimated from the sub-images. The results will help to open up deeper understanding of limitation of current optical security techniques. Conclusions: The DRPE system has potential redundancy risk. Even one-time-pad manner is not secured in DRPE system. This vulnerability allows a cryptanalyst to estimate the plaintext information with only a half or less ciphertext.

Fuzzy Modeling of Multi-Degree-of-Freedom Power Spectral Density Systems

2009 ◽  
Vol 2 (1) ◽  
pp. 40-47
Author(s):  
Montasser Tahat ◽  
Hussien Al-Wedyan ◽  
Kudret Demirli ◽  
Saad Mutasher
Keyword(s):  
Spectral Density ◽  
Power Spectral Density ◽  
Fuzzy Modeling ◽  
Degree Of Freedom ◽  
Power Spectral
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