CURRENT PROSPECTS FOR ASTROD INERTIAL SENSOR

2008 ◽  
Vol 17 (07) ◽  
pp. 941-963 ◽  
Author(s):  
A. PULIDO PATÓN
Keyword(s):  
Solar System ◽  
Gravitational Waves ◽  
Inertial Sensor ◽  
Low Frequency ◽  
Optical Devices ◽  
Noise Levels ◽  
Noise Sources ◽  
System Parameters ◽  
Relativity Mission

The Astrodynamical Space Test of Relativity using Optical Devices (ASTROD) is a multi-purpose relativity mission concept. ASTROD's scientific goals are the measurement of relativistic and solar system parameters to unprecedented precision, and the detection and observation of low-frequency gravitational waves to frequencies down to 5 × 10-6 Hz. To accomplish its goals, ASTROD will employ a constellation of drag-free satellites, aiming for a residual acceleration noise of (0.3-1) × 10-15 m s-2 Hz-1/2 at 0.1 mHz. Noise sources and strategies for improving present acceleration noise levels are reported.

Preliminary Model Analysis of Acoustic Noise Levels for Space Station

2014 ◽  
Vol 1016 ◽  
pp. 287-291
Author(s):  
Yao Qi Feng ◽  
Jiang Yang ◽  
Guo Song Feng ◽  
Yao Wu
Keyword(s):  
Acoustic Analysis ◽  
Acoustic Noise ◽  
Spectral Characteristics ◽  
Space Station ◽  
Low Frequency ◽  
Frequency Range ◽  
Analysis Model ◽  
Noise Levels ◽  
Noise Sources ◽  
Modeling And Analysis

This paper presents the modeling and analysis method of acoustic noise levels of whole audible frequency range for Chinese Space Station (CSS) module. UsingBoundaryElementModeling(BEM), the acoustic analysis model of low frequency range for CSS module was established. The analysis model of high frequency range was created by usingStatistical EnergyAnalysis(SEA) method. Based on the established models, the acoustic noise levels in all areas of CSS module were analyzed and the results for some typical areas are provided. Finally, the acoustic contribution of noise sources according to their spectral characteristics is analyzed and the implementation of noise control methods to reduce acoustic levels in CSS module is discussed.

Noise source location and scaling of subsonic upper-surface blowing

2020 ◽  
Vol 19 (3-5) ◽  
pp. 191-206
Author(s):  
Trae L Jennette ◽  
Krish K Ahuja
Keyword(s):  
Strouhal Number ◽  
Noise Source ◽  
Low Frequency ◽  
Directivity Pattern ◽  
Source Location ◽  
Dipole Source ◽  
Frequency Noise ◽  
Noise Sources ◽  
Trailing Edge ◽  
Trailing Edge Noise

This paper deals with the topic of upper surface blowing noise. Using a model-scale rectangular nozzle of an aspect ratio of 10 and a sharp trailing edge, detailed noise contours were acquired with and without a subsonic jet blowing over a flat surface to determine the noise source location as a function of frequency. Additionally, velocity scaling of the upper surface blowing noise was carried out. It was found that the upper surface blowing increases the noise significantly. This is a result of both the trailing edge noise and turbulence downstream of the trailing edge, referred to as wake noise in the paper. It was found that low-frequency noise with a peak Strouhal number of 0.02 originates from the trailing edge whereas the high-frequency noise with the peak in the vicinity of Strouhal number of 0.2 originates near the nozzle exit. Low frequency (low Strouhal number) follows a velocity scaling corresponding to a dipole source where as the high Strouhal numbers as quadrupole sources. The culmination of these two effects is a cardioid-shaped directivity pattern. On the shielded side, the most dominant noise sources were at the trailing edge and in the near wake. The trailing edge mounting geometry also created anomalous acoustic diffraction indicating that not only is the geometry of the edge itself important, but also all geometry near the trailing edge.

scholarly journals Characterization of Noise Level Inside a Vehicle under Different Conditions

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2471 ◽  
Author(s):  
Daniel Flor ◽  
Danilo Pena ◽  
Luan Pena ◽  
Vicente A. de Sousa ◽  
Allan Martins
Keyword(s):  
Regression Analysis ◽  
Noise Level ◽  
Acoustic Noise ◽  
Experimental Setup ◽  
Strongly Correlated ◽  
Noise Levels ◽  
Noise Sources ◽  
Statistical Tools ◽  
Window Position

Vehicular acoustic noise evaluations are a concern of researchers due to health and comfort effects on humans and are fundamental for anyone interested in mitigating audio noise. This paper focuses on the evaluation of the noise level inside a vehicle by using statistical tools. First, an experimental setup was developed with microphones and a microcomputer located strategically on the car’s panel, and measurements were carried out with different conditions such as car window position, rain, traffic, and car speed. Regression analysis was performed to evaluate the similarity of the noise level from those conditions. Thus, we were able to discuss the relevance of the variables that contribute to the noise level inside a car. Finally, our results revealed that the car speed is strongly correlated to interior noise levels, suggesting the most relevant noise sources are in the vehicle itself.

Incubator Noise

PEDIATRICS ◽  
1975 ◽  
Vol 56 (4) ◽  
pp. 617-617
Author(s):  
Gōsta Blennow ◽  
Nils W. Svenningsen ◽  
Bengt Almquist
Keyword(s):  
Low Frequency ◽  
Sound Level ◽  
Noise Levels ◽  
Frequency Sound ◽  
Mechanical Noise ◽  
Sound Levels ◽  
Infant Incubator ◽  
Improved Model ◽  
Model C

Recently we reported results from studies of incubator noise levels.1 It was found that in certain types of incubators the noise was considerable, and attention was called to the sound level in the construction of new incubators. Recently we had the opportunity to study an improved model of Isolette Infant Incubator Model C-86 where the mechanical noise from the electrically powered motor has been partially eliminated. With this modification it has been possible to lower the low-frequency sound levels to a certain degree in comparison to the levels registered in our study.

Low frequency noise sources in AlGaN/GaN HEMTs

1999 ◽  
Author(s):  
J. A. Garrido ◽  
F. Calle ◽  
E. Muñoz ◽  
I. Izpura ◽  
J. L. Sánchez-Rojas ◽  
...  
Keyword(s):  
Low Frequency ◽  
Frequency Noise ◽  
Low Frequency Noise ◽  
Noise Sources ◽  
Gan Hemts

scholarly journals First low-frequency Einstein@Home all-sky search for continuous gravitational waves in Advanced LIGO data

2017 ◽  
Vol 96 (12) ◽  
Author(s):  
B. P. Abbott ◽  
R. Abbott ◽  
T. D. Abbott ◽  
F. Acernese ◽  
K. Ackley ◽  
...  
Keyword(s):  
Gravitational Waves ◽  
Low Frequency

scholarly journals In search for the most optimal EEG method: A practical evaluation of a water-based electrode EEG system

2021 ◽  
Vol 5 ◽  
pp. 239821282110536
Author(s):  
Marta Topor ◽  
Bertram Opitz ◽  
Philip J. A. Dean
Keyword(s):  
Signal To Noise Ratio ◽  
Flanker Task ◽  
Low Frequency ◽  
Noise Levels ◽  
Slow Drift ◽  
Practical Evaluation ◽  
Beta Power ◽  
Water Based ◽  
High Beta ◽  
Frequency Power

The study assessed a mobile electroencephalography system with water-based electrodes for its applicability in cognitive and behavioural neuroscience. It was compared to a standard gel-based wired system. Electroencephalography was recorded on two occasions (first with gel-based, then water-based system) as participants completed the flanker task. Technical and practical considerations for the application of the water-based system are reported based on participant and experimenter experiences. Empirical comparisons focused on electroencephalography data noise levels, frequency power across four bands (theta, alpha, low beta and high beta) and event-related components (P300 and ERN). The water-based system registered more noise compared to the gel-based system which resulted in increased loss of data during artefact rejection. Signal-to-noise ratio was significantly lower for the water-based system in the parietal channels which affected the observed parietal beta power. It also led to a shift in topography of the maximal P300 activity from parietal to frontal regions. The water-based system may be prone to slow drift noise which may affect the reliability and consistency of low-frequency band analyses. Practical considerations for the use of water-based electrode electroencephalography systems are provided.

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