Measurement of axial phase difference of density fluctuations owing to spontaneously excited waves by using microwave reflectometer on GAMMA 10/PDX

2021 ◽  
Vol 92 (5) ◽  
pp. 053506
Author(s):  
R. Sekine ◽  
M. Hirata ◽  
R. Ikezoe ◽  
S. Jang ◽  
Y. Kubota ◽  
...  
Keyword(s):  
Phase Difference ◽  
Density Fluctuations

Study of Radial Particle Flux due to Phase Difference Between Potential and Density Fluctuations

2009 ◽  
Vol 55 (2T) ◽  
pp. 168-171 ◽  
Author(s):  
Yoshiaki Miyata ◽  
Masayuki Yoshikawa ◽  
Masanori Mizuguchi ◽  
Youhei Oono ◽  
Yousuke Nakashima ◽  
...  
Keyword(s):  
Phase Difference ◽  
Particle Flux ◽  
Density Fluctuations

What Is The Best Distance And Phase Difference Between The Elements Of Linear Antnna Array

2017 ◽  
pp. 1
Author(s):  
Asma M. N. El Ferjani ◽  
Ahmed S. El Barsha ◽  
AlZaroog Saleh Abdulali
Keyword(s):  
Phase Difference

Characterization of Flood Waves by Rating Curves

1997 ◽  
Vol 28 (1) ◽  
pp. 51-64 ◽  
Author(s):  
S.K. Mishra ◽  
M.K. Jain ◽  
S.M. Seth
Keyword(s):  
Phase Difference ◽  
Central India ◽  
Wave Number ◽  
Wave Characteristics ◽  
Travel Wave ◽  
Frame Work ◽  
Rating Curves ◽  
Exact Relationship ◽  
Flood Waves

The flood waves are characterized within the frame-work of loop (or hysteresis) of rating curves. The National Weather Service's Dam Break Flood Forecasting Model is used to generate the flood waves in the downstream valley of the Bargi dam located in Central India. The quantified hystereses, η, of non-dimensional rating curves are related with the corresponding flood wave characteristics, viz., speed of travel, wave number, phase difference, and attenuation. The analysis has led to the development of an exact relationship between η and phase difference. Using the concept of wave zoning, the better performance of the hysteresis based criteria compared with the available criteria is verified using Convex and Muskingum-Cunge routing in the wave zones. η limits are specified for the applicability of these simplified routing models. Furthermore, the envisaged applications of the based analysis are introduced.

Ballooning structure in density fluctuations observed with the 2 MeV heavy ion beam probe on the TEXT-U tokamak

1995 ◽  
Author(s):  
A. Fujisawa ◽  
A. Ouroua ◽  
J.W. Heard ◽  
T.P. Crowley ◽  
P.M. Schoch ◽  
...  
Keyword(s):  
Ion Beam ◽  
Heavy Ion ◽  
Density Fluctuations ◽  
Heavy Ion Beam ◽  
Heavy Ion Beam Probe

scholarly journals Looking for a proxy of the ionospheric turbulence with Swarm data

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Paola De Michelis ◽  
Giuseppe Consolini ◽  
Alessio Pignalberi ◽  
Roberta Tozzi ◽  
Igino Coco ◽  
...  
Keyword(s):  
Electron Density ◽  
Geomagnetic Activity ◽  
Density Fluctuations ◽  
Rate Of Change ◽  
Topside Ionosphere ◽  
Joint Probability Distribution ◽  
Activity Levels ◽  
Scaling Exponents ◽  
Electron Density Fluctuations ◽  
Scaling Features

AbstractThe present work focuses on the analysis of the scaling features of electron density fluctuations in the mid- and high-latitude topside ionosphere under different conditions of geomagnetic activity. The aim is to understand whether it is possible to identify a proxy that may provide information on the properties of electron density fluctuations and on the possible physical mechanisms at their origin, as for instance, turbulence phenomena. So, we selected about 4 years (April 2014–February 2018) of 1 Hz electron density measurements recorded on-board ESA Swarm A satellite. Using the Auroral Electrojet (AE) index, we identified two different geomagnetic conditions: quiet (AE < 50 nT) and active (AE > 300 nT). For both datasets, we evaluated the first- and second-order scaling exponents and an intermittency coefficient associated with the electron density fluctuations. Then, the joint probability distribution between each of these quantities and the rate of change of electron density index was also evaluated. We identified two families of plasma density fluctuations characterized by different mean values of both the scaling exponents and the considered ionospheric index, suggesting that different mechanisms (instabilities/turbulent processes) can be responsible for the observed scaling features. Furthermore, a clear different localization of the two families in the magnetic latitude—magnetic local time plane is found and its dependence on geomagnetic activity levels is analyzed. These results may well have a bearing about the capability of recognizing the turbulent character of irregularities using a typical ionospheric plasma irregularity index as a proxy.

UHF RFID Indoor Localization Based on Phase Difference

2021 ◽  
pp. 1-7
Author(s):  
Yanhan Zeng ◽  
Yuxing Liao ◽  
Xiheng Chen ◽  
Hong-zhou Tan
Keyword(s):  
Phase Difference ◽  
Indoor Localization ◽  
Uhf Rfid
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