Low and High Broadband Spectral Models of Atmospheric Pressure Fluctuation

Author(s):  
Julien Marty ◽  
Benoit Doury ◽  
Alfred Kramer

AbstractThis paper presents new low and high power spectral density models for pressure fluctuations at the Earth’s surface over the frequency range of (10−5 – 8) Hz. Previously proposed models often included limitations, such as a much narrower frequency range, the inclusion of erroneous and non-calibrated data or recorded data not deconvolved from the measurement system responses. The progress recently made with response modeling and field calibration of pressure fluctuation measurement systems now allows to propose more realistic power spectral density models over an extremely large frequency band. This paper describes how the data were selected, processed, and analyzed to obtain the final global models. In addition, the intermediate results allow the characterization of several atmospheric mechanisms, such as gravity wave saturation, limits of the buoyancy and acoustic cut-off frequencies or wind turbulence modes. The two proposed low and high power spectral density models are planned to be used for a wide range of applications, including assessing the quality of measured pressure fluctuations, verifying the validity of modeled pressure fluctuations and supporting the design, testing and calibration of a new generation of measurement systems. The models presented in this paper are made available to the scientific community.

Author(s):  
Wenjie Bai ◽  
Quan Duan ◽  
Zaoxiao Zhang

Hydraulic tests for elongated orifice-induced wall pressure fluctuations and vibration in pipeline have been carried out. The regulating modes of test system consist of maintaining outlet pressure to increase flow rate and maintaining flow rate to decrease outlet pressure. Both regulating modes would increase the possibility of cavitation within elongated orifice, which has been confirmed by numerical simulation in present study. Statistical characteristics of the fluctuating pressure and structure vibration response have been studied. The standard deviation analyses indicate that the amplitude of fluctuating pressure is mainly determined by flow rate. The power spectral density analyses show that the energy of the fluctuating pressure behind elongated orifice is concentrated in lower frequency range and it can be divided into two parts in this test: the pressure pulsation excited by plunger pump and the random fluctuating pressure produced by elongated orifice’s disturbance. The power spectral density of pipe vibration response shows that the lower frequency of pipe vibration response can be ascribed to the fluctuating pressure behind elongated orifice and the characteristic frequencies corresponding to cavitation within elongated orifice are in the higher frequency range.


2021 ◽  
Vol 15 ◽  
Author(s):  
Yang Di ◽  
Xingwei An ◽  
Wenxiao Zhong ◽  
Shuang Liu ◽  
Dong Ming

An ongoing interest towards identification based on biosignals, such as electroencephalogram (EEG), magnetic resonance imaging (MRI), is growing in the past decades. Previous studies indicated that the inherent information about brain activity may be used to identify individual during resting-state of eyes open (REO) and eyes closed (REC). Electroencephalographic (EEG) records the data from the scalp, and it is believed that the noisy EEG signals can influence the accuracies of one experiment causing unreliable results. Therefore, the stability and time-robustness of inter-individual features can be investigated for the purpose of individual identification. In this work, we conducted three experiments with the time interval of at least 2 weeks, and used different types of measures (Power Spectral Density, Cross Spectrum, Channel Coherence and Phase Lags) to extract the individual features. The Pearson Correlation Coefficient (PCC) is calculated to measure the level of linear correlation for intra-individual, and Support Vector Machine (SVM) is used to obtain the related classification accuracy. Results show that the classification accuracies of four features were 85–100% for intra-experiment dataset, and were 80–100% for fusion experiments dataset. For inter-experiments classification of REO features, the optimized frequency range is 13–40 Hz for three features, Power Spectral Density, Channel Coherence and Cross Spectrum. For inter-experiments classification of REC, the optimized frequency range is 8–40 Hz for three features, Power Spectral Density, Channel Coherence and Cross Spectrum. The classification results of Phase Lags are much lower than the other three features. These results show the time-robustness of EEG, which can further use for individual identification system.


2017 ◽  
Vol 28 (02) ◽  
pp. 1750019 ◽  
Author(s):  
A. T. da Cunha Lima ◽  
I. C. da Cunha Lima ◽  
M. P. de Almeida

We calculate the power spectral density and velocity correlations for a turbulent flow of a fluid inside a duct. Turbulence is induced by obstructions placed near the entrance of the flow. The power spectral density is obtained for several points at cross-sections along the duct axis, and an analysis is made on the way the spectra changes according to the distance to the obstruction. We show that the differences on the power spectral density are important in the lower frequency range, while in the higher frequency range, the spectra are very similar to each other. Our results suggest the use of the changes on the low frequency power spectral density to identify the occurrence of obstructions in pipelines. Our results show some frequency regions where the power spectral density behaves according to the Kolmogorov hypothesis. At the same time, the calculation of the power spectral densities at increasing distances from the obstructions indicates an energy cascade where the spectra evolves in frequency space by spreading the frequency amplitude.


2013 ◽  
Vol 233 ◽  
pp. 215-226 ◽  
Author(s):  
Or-ampai Jaiboon ◽  
Benjapon Chalermsinsuwan ◽  
Lursuang Mekasut ◽  
Pornpote Piumsomboon

2015 ◽  
Author(s):  
Wan-Qing Huang ◽  
Ying Zhang ◽  
Wen-Yi Wang ◽  
Yuan-Chao Geng ◽  
Lan-Qin Liu

1996 ◽  
Author(s):  
Janice K. Lawson ◽  
David M. Aikens ◽  
R. Edward English, Jr. ◽  
C. Robert Wolfe

2022 ◽  
Vol 68 ◽  
pp. 102774
Author(s):  
Yusheng Huang ◽  
Ping Yan ◽  
Jingtao Xin ◽  
Dan Li ◽  
Yulun Wu ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document