Production and propagation of a modulated optical vortex through atmospheric turbulence

2009 ◽  
Author(s):  
Robert K. Tyson ◽  
Marco Scipioni ◽  
Greg Gbur ◽  
Jaime Viegas
Keyword(s):  
Atmospheric Turbulence ◽  
Optical Vortex

Propagation characteristics of optical vortex pulse in atmospheric turbulence

Optik ◽  
2019 ◽  
Vol 180 ◽  
pp. 27-33 ◽  
Author(s):  
Kangle Yong ◽  
Jiawei Yan ◽  
Shiming Huang ◽  
Rongzhu Zhang
Keyword(s):  
Atmospheric Turbulence ◽  
Optical Vortex ◽  
Propagation Characteristics

Trajectory of an optical vortex in atmospheric turbulence

2009 ◽  
Vol 80 (4) ◽  
Author(s):  
A. Dipankar ◽  
R. Marchiano ◽  
P. Sagaut
Keyword(s):  
Atmospheric Turbulence ◽  
Optical Vortex

Beam-holding property analysis of the perfect optical vortex beam transmitting in atmospheric turbulence

2020 ◽  
Vol 472 ◽  
pp. 125879 ◽  
Author(s):  
Chunyong Yang ◽  
Yue Lan ◽  
Xiaoyu Jiang ◽  
Hao Long ◽  
Jin Hou ◽  
...  
Keyword(s):  
Atmospheric Turbulence ◽  
Optical Vortex ◽  
Vortex Beam ◽  
Property Analysis

Prediction of Atmospheric Turbulence Characteristics for Surface Boundary Layer using Empirical Spectral Methods

2020 ◽  
Author(s):  
Yagya Dutta Dwivedi ◽  
Vasishta Bhargava Nukala ◽  
Satya Prasad Maddula ◽  
Kiran Nair
Keyword(s):  
Boundary Layer ◽  
Time Series ◽  
Surface Roughness ◽  
Wind Speed ◽  
Atmospheric Turbulence ◽  
Surface Boundary ◽  
Low Frequencies ◽  
Surface Boundary Layer ◽  
Power Spectral ◽  
Mean Wind Speed

Abstract Atmospheric turbulence is an unsteady phenomenon found in nature and plays significance role in predicting natural events and life prediction of structures. In this work, turbulence in surface boundary layer has been studied through empirical methods. Computer simulation of Von Karman, Kaimal methods were evaluated for different surface roughness and for low (1%), medium (10%) and high (50%) turbulence intensities. Instantaneous values of one minute time series for longitudinal turbulent wind at mean wind speed of 12 m/s using both spectra showed strong correlation in validation trends. Influence of integral length scales on turbulence kinetic energy production at different heights is illustrated. Time series for mean wind speed of 12 m/s with surface roughness value of 0.05 m have shown that variance for longitudinal, lateral and vertical velocity components were different and found to be anisotropic. Wind speed power spectral density from Davenport and Simiu profiles have also been calculated at surface roughness of 0.05 m and compared with k−1 and k−3 slopes for Kolmogorov k−5/3 law in inertial sub-range and k−7 in viscous dissipation range. At high frequencies, logarithmic slope of Kolmogorov −5/3rd law agreed well with Davenport, Harris, Simiu and Solari spectra than at low frequencies.

Estimating Atmospheric Turbulence Parameters from the Envelopes of Radio Acoustic Signals

2001 ◽  
Vol 55 (8) ◽  
pp. 5
Author(s):  
V. M. Kartashov ◽  
V. A. Petrov ◽  
Ye. G. Proshkin ◽  
G. I. Sidorov
Keyword(s):  
Atmospheric Turbulence ◽  
Acoustic Signals ◽  
Turbulence Parameters
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