Second-order moments of Schell-model beams with various correlation functions in atmospheric turbulence

2017 ◽  
Vol 42 (22) ◽  
pp. 4647 ◽  
Author(s):  
Guo Zheng ◽  
Jue Wang ◽  
Lin Wang ◽  
Muchun Zhou ◽  
Yu Xin ◽  
...  
Keyword(s):  
Atmospheric Turbulence ◽  
Correlation Functions ◽  
Second Order

scholarly journals Method for Measuring the Second-Order Moment of Atmospheric Turbulence

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 564
Author(s):  
Hong Shen ◽  
Longkun Yu ◽  
Xu Jing ◽  
Fengfu Tan
Keyword(s):  
Atmospheric Turbulence ◽  
Weighting Function ◽  
Structure Constant ◽  
Turbulence Models ◽  
Second Order ◽  
Index Structure ◽  
Order Moment ◽  
Site Testing ◽  
Optical Effects ◽  
Novel Method

The turbulence moment of order m (μm) is defined as the refractive index structure constant Cn2 integrated over the whole path z with path-weighting function zm. Optical effects of atmospheric turbulence are directly related to turbulence moments. To evaluate the optical effects of atmospheric turbulence, it is necessary to measure the turbulence moment. It is well known that zero-order moments of turbulence (μ0) and five-thirds-order moments of turbulence (μ5/3), which correspond to the seeing and the isoplanatic angles, respectively, have been monitored as routine parameters in astronomical site testing. However, the direct measurement of second-order moments of turbulence (μ2) of the whole layer atmosphere has not been reported. Using a star as the light source, it has been found that μ2 can be measured through the covariance of the irradiance in two receiver apertures with suitable aperture size and aperture separation. Numerical results show that the theoretical error of this novel method is negligible in all the typical turbulence models. This method enabled us to monitor μ2 as a routine parameter in astronomical site testing, which is helpful to understand the characteristics of atmospheric turbulence better combined with μ0 and μ5/3.

scholarly journals Wind Influence on Miro-launcher Dynamics Model

2019 ◽  
Vol 304 ◽  
pp. 07014
Author(s):  
Teodor-Viorel Chelaru ◽  
Valentin Pana ◽  
Alexandru Iulian Onel ◽  
Tudorel-Petronel Afilipoae ◽  
Andrei Filip Cojocaru ◽  
...  
Keyword(s):  
Atmospheric Turbulence ◽  
Correlation Functions ◽  
Degrees Of Freedom ◽  
Dynamics Model ◽  
Six Degrees Of Freedom ◽  
Body Model ◽  
Rigid Body Model ◽  
Wind Influence ◽  
Three Stages ◽  
Flight Parameters

The paper presents aspects regarding wind influence in dynamics of the three stages micro-launcher. The work is focus on atmospheric turbulence, with dedicated linear model based on characteristics correlation functions, that can be attached to the rigid body model with six degrees of freedom. The results analyzed will be the flight parameters of the launcher, with the wind influence. The novelty of the paper consists in dedicated wind models developed and their implementation in six degrees of freedom micro-launcher model.

ON THE GLOBAL SOLUTION TO THE DIFFERENTIAL EQUATION FOR THE N-POINT CONFORMAL CORRELATOR

1989 ◽  
Vol 04 (25) ◽  
pp. 2483-2486
Author(s):  
A. ROY CHOWDHURY ◽  
SWAPNA ROY
Keyword(s):  
Differential Equation ◽  
Differential Equations ◽  
Global Solution ◽  
Correlation Functions ◽  
Global Solutions ◽  
Second Order ◽  
Second Order Differential Equations

We have obtained compact expressions for the global solutions of the second order differential equations for the n-point conformal correlation functions. These equations were initially deduced by Belavin, Polyakov and Zamolodchikov. The monodromy property of such solutions can be ascertained from these expressions very easily.

scholarly journals Propagation of second-order moments of general truncated beams in atmospheric turbulence

2011 ◽  
Vol 13 (10) ◽  
pp. 103006 ◽  
Author(s):  
Xiaoling Ji ◽  
Xiaoqing Li ◽  
Guangming Ji
Keyword(s):  
Atmospheric Turbulence ◽  
Second Order

scholarly journals Characteristics of the Derived Energy Dissipation Rate using the 1-Hz Commercial Aircraft Quick Access Recorder (QAR) Data

2021 ◽  
Author(s):  
Soo-Hyun Kim ◽  
Jeonghoe Kim ◽  
Jung-Hoon Kim ◽  
Hye-Yeong Chun
Keyword(s):  
Energy Dissipation ◽  
Atmospheric Turbulence ◽  
Dissipation Rate ◽  
Energy Dissipation Rate ◽  
Second Order ◽  
Vertical Wind ◽  
Inertial Subrange ◽  
Order Structure ◽  
Von Karman ◽  
Von Kármán

Abstract. The cube root of the energy dissipation rate (EDR), as a standard reporting metric of atmospheric turbulence, is estimated using 1-Hz quick access recorder data from Korean-based national air carriers with two different types of aircraft [Boeing 737 (B737) and B777], archived for 12 months from January to December 2012. Various EDRs are estimated using zonal, meridional, and derived vertical wind components, and the derived equivalent vertical gust (DEVG). Wind-based EDRs are estimated by (i) second-order structure function (EDR1), (ii) power spectral density (PSD), considering the Kolmogorov’s -5/3 dependence (EDR2), and (iii) maximum-likelihood estimation using the von Kármán spectral model (EDR3). DEVG-based EDRs are obtained mainly by vertical acceleration with different conversions to EDR using (iv) the lognormal mapping technique (EDR4) and (v) the predefined parabolic relationship between the observed EDR and DEVG (EDR5). For the EDR1, second-order structure functions are computed for zonal, meridional, and vertical wind within the defined inertial subrange. For the EDR2 and EDR3, individual PSDs for each wind component are computed using the Fast Fourier Transform over every 2-minute time window. Then, two EDR estimates are computed separately by employing the Kolmogorov-scale slope (EDR2) or prescribed von Kármán wind model (EDR3) within the inertial subrange. The resultant EDR estimates from five different methods follow a lognormal distribution reasonably well, which satisfies the fundamental characteristics of atmospheric turbulence. Statistics (mean and standard deviation) of log-scale EDRs are somewhat different from those found in a previous study using a higher frequency (10 Hz) of in situ aircraft data in the United States, likely due to different sampling rates, aircraft types, and locations. Finally, five EDR estimates capture well the intensity and location of three strong turbulence cases that are relevant to clear-air turbulence (CAT), mountain wave turbulence (MWT), and convectively induced turbulence (CIT), with different characteristics of the observed EDRs: 1) zonal (vertical) wind-based EDRs are stronger in the CAT (CIT) case, while MWT has a peak of EDRs in both zonal and vertical wind-based EDRs, and 2) the CAT and MWT cases occurred by large-scale (synoptic-scale) forcing have more variations in EDRs before and after the incident, while the CIT case triggered by smaller mesoscale convective cell has an isolated peak of EDR.

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