Development of differential image motion LiDAR for profiling optical turbulence

Yinjie, 周颖捷 Zhou; Anran, 周安然 Zhou; Dongsong, 孙东松 Sun; Xiwen, 强希文 Qiang; shuanglian, 封双连 Feng

doi:10.3788/irla20164511.1130001

Cited by 2 publications

(3 citation statements)

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“…This turbulence exhibits distinct large-scale energy aggregation regions, inertial ranges, and viscous dissipation ranges. This phenomenon is effectively described by the Kolmogorov-5/3 [45] formula, which is applicable over a range of about one to two orders of magnitude. The character of the power spectral densities changes significantly as the flow field moves downstream, with a consequent increase in the span of the inertial range.…”

Section: Power Spectrum Densitymentioning

confidence: 99%

“…The observation of power spectral density characteristics at different locations re that the wind passing through the rotor generates a dynamic turbulence phenome This turbulence exhibits distinct large-scale energy aggregation regions, inertial ra and viscous dissipation ranges. This phenomenon is effectively described by the Ko gorov-5/3 [45] formula, which is applicable over a range of about one to two orde magnitude. The character of the power spectral densities changes significantly as the field moves downstream, with a consequent increase in the span of the inertial rang the hub center height within the nacelle, as shown in Figure 9d-f, there are signifi differences in power spectral density under different conditions.…”

Section: Power Spectrum Densitymentioning

confidence: 99%

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Experimental Study of Wake Evolution under Vertical Staggered Arrangement of Wind Turbines of Different Sizes

Zhang,

Feng,

Zhao

et al. 2024

JMSE

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During the expansion of a wind farm, the strategic placement of wind turbines can significantly improve wind energy utilization. This study investigates the evolution of wake turbulence in a wind farm after introducing smaller wind turbines within the gaps between larger ones, focusing on aspects such as wind speed, turbulence intensity, and turbulence integral length scale. The flow field conditions are described using parameters like turbulence critical length and power spectral density, as determined through wind tunnel experiments. In these experiments, a single large wind turbine model and nine smaller wind turbine models were used to create a small wind farm unit, and pressure distribution behind the wind turbines was measured under various operating conditions. The results indicate that downstream wind speed deficits intensify as the number of small wind turbines in operation increases. The impact of these smaller turbines varies with height, with a relatively minor effect on the upper blade tip and increasingly adverse effects as you move from the upper blade tip to the lower blade tip. Through an analysis of power spectral density, the contribution of vortex motion to wake turbulence kinetic energy is further quantified. In the far wake region, the number of small wind turbines has a relatively small impact on wind speed fluctuations.

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Section: Power Spectrum Densitymentioning

confidence: 99%

Section: Power Spectrum Densitymentioning

confidence: 99%

Experimental Study of Wake Evolution under Vertical Staggered Arrangement of Wind Turbines of Different Sizes

Zhang,

Feng,

Zhao

et al. 2024

JMSE

View full text Add to dashboard Cite

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“…The atmospheric coherence length

is obtained by receiving the dither variance of the centroid of the spot on the aperture. In 2016, Zhou et al developed an atmospheric turbulence profile lidar based on differential image motion and conducted some experiments, but its resolution was limited [ 15 ]. In recent years, the S-DIMM+ method was proposed on the basis of DIMM, and the Shack–Hartmann wavefront sensor with a wide field of view was used to detect the atmospheric turbulence profile [ 16 , 17 ].…”

Section: Introductionmentioning

confidence: 99%

Novel Detection of Atmospheric Turbulence Profile Using Mie-Scattering Lidar Based on Non-Kolmogorov Turbulence Theory

Mao

Zhang

et al. 2023

Entropy

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Turbulence can cause effects such as light intensity fluctuations and phase fluctuations when a laser is transmitted in the atmosphere, which has serious impacts on a number of optical engineering application effects and on climate improvement. Therefore, accurately obtaining real-time turbulence intensity information using lidar-active remote sensing technology is of great significance. In this paper, based on residual turbulent scintillation theory, a Mie-scattering lidar method was developed to detect atmospheric turbulence intensity. By extracting light intensity fluctuation information from a Mie-scattering lidar return signal, the atmospheric refractive index structure constant, Cn2, representing the atmospheric turbulence intensity, could be obtained. Specifically, the scintillation effect on the detection path was analyzed, and the probability density distribution of the light intensity of the Mie-scattering lidar return signal was studied. It was verified that the probability density of logarithmic light intensity basically follows a normal distribution under weak fluctuation conditions. The Cn2 profile based on Kolmogorov turbulence theory was retrieved using a layered, iterative method through the scintillation index. The method for detecting Kolmogorov turbulence intensity was applied to the detection of the non-Kolmogorov turbulence intensity. Through detection using the scintillation index, the corresponding C˜n2 profile could be calculated. The detection of the C˜n2 and Cn2 profiles were compared with the Hufnagel–Valley (HV) night model in the Yinchuan area. The results show that the detection results are consistent with the overall change trend of the model. In general, it is feasible to detect a non-Kolmogorov turbulence profile using Mie-scattering lidar.

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Development of differential image motion LiDAR for profiling optical turbulence

Cited by 2 publications

References 0 publications

Experimental Study of Wake Evolution under Vertical Staggered Arrangement of Wind Turbines of Different Sizes

Experimental Study of Wake Evolution under Vertical Staggered Arrangement of Wind Turbines of Different Sizes

Novel Detection of Atmospheric Turbulence Profile Using Mie-Scattering Lidar Based on Non-Kolmogorov Turbulence Theory

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