Spectral moments for the analysis of frequency shift, broadening, and wavevector anisotropy in a turbulent flow

Narita, Yasuhito

doi:10.1186/s40623-017-0658-7

Cited by 6 publications

(7 citation statements)

References 24 publications

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“…The energy moment method is used to calculate the signal frequency [34] in this study. The energy moment balance method is shown in figure 2.…”

Section: Frequency Of Driving Signalmentioning

confidence: 99%

Measurement insights and error analysis of electronic parameters for ultrasonic transducers

Zhou,

Fan,

Tang

et al. 2024

Meas. Sci. Technol.

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Piezoelectric ultrasonic transducers with the function of energy conversation, as well as their numerous advantages, such as high-power density, quick response, flexible design, and service reliability, are involved in wide applications of industrial processing, precision driving, smart sensing, and medical services. The electromechanical equivalent circuit and Kirchhoff’s law indicate that mechatronics parameters are essential for performance evaluation, reliability analysis, and fault diagnosis of ultrasonic transducers. Importantly, the ultrasonic transducer is a time variant system, data of one single parameter collected from a certain test can’t match with the data of another single parameter acquired from a different test. So, a synchronous and precise online measurement of electronic parameters is encouraged for performance evaluation and optimization design of ultrasonic transducers. With the combination of virtual instrument technology, an asynchronous measurement system of electrical excitation parameters for the ultrasonic transducers of linear driving motors was established in this study. Furthermore, the systematic measurement methods and error theory, including the calculation methods and measuring circuits of electric signals, were illustrated. Experimental results proved that the proposed system and methods for measuring the input electronic power of ultrasonic transducer (e.g., effective value method for voltage and current, energy moment method for frequency, and spectrum analysis method for phase difference) are highly precise, quick responsive, robust, and reliable for ultrasonic transducers. The findings of this study provide valuable references and suggestions for efficient, accurate, and online performance evaluation of ultrasonic transducers, particularly for piezoelectric transducers utilizing ultrasonic high-voltage exciting signals.

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“…The energy moment method is used to calculate the signal frequency [34] in this study. The energy moment balance method is shown in figure 2.…”

Section: Frequency Of Driving Signalmentioning

confidence: 99%

Measurement insights and error analysis of electronic parameters for ultrasonic transducers

Zhou,

Fan,

Tang

et al. 2024

Meas. Sci. Technol.

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“…In the k-w domain, Taylor's hypothesis corresponds to a straight line, which contrasts with the continuous distributions observed in nature, as the energy density function (EDF) spreads in the vicinity of this linear prediction. The concept of spreading leads to the random sweeping hypothesis, which was exploited earlier in [47], and later, e.g., in [40,48,49]. A state-of-the-art review of these k-w spectrum models is presented in [49].…”

Section: Introductionmentioning

confidence: 99%

“…The concept of spreading leads to the random sweeping hypothesis, which was exploited earlier in [47], and later, e.g., in [40,48,49]. A state-of-the-art review of these k-w spectrum models is presented in [49].…”

Section: Introductionmentioning

confidence: 99%

Evidence of Ocean Waves Signature in the Space–Time Turbulent Spectra of the Lower Marine Atmosphere Measured by a Scanning LiDAR

et al. 2022

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To achieve more accurate weather and climate forecasting, and propose efficient engineering solutions for exploiting offshore renewable energies, it is imperative to accurately describe the atmospheric turbulent flow in the offshore environment. The ocean’s dynamics raise specific challenges for the aforementioned applications, as they significantly alter the atmospheric flow through complex wind–wave interactions. These interactions are important in fairly common situations and notably in old-sea conditions, where ocean waves travel fast, under comparatively slow wind velocities. In the present study, a scanning LiDAR (sLiDAR) was deployed on the shore to study micro-scale wind–wave interactions by performing horizontal scans 18 m above the ocean, and as far as 2 km from the coast. In the proposed configuration, and in the test cases presented in old seas, the sLiDAR captures wave-induced disturbances propagating into the lower part of the marine atmospheric boundary layer. Based on measurements of high-resolution space–time maps of the Radial Wind Speed, an original two-dimensional spectral analysis of the space–time auto-correlation functions was performed. Unlike more conventional data-processing techniques, and as long as the waves travel sufficiently (∼twofold) faster than the mean wind at the measurement height, the upward transfer of motions from the waves to the wind can be clearly distinguished from the atmospheric turbulence in the wave-number–angular-frequency (k–w) turbulent spectra. These are the first space–time auto-correlation functions of the wind velocity fluctuations obtained at micro-scales above the ocean. The analyses demonstrate sLiDAR systems’ applicability in measuring k–w-dependent turbulent spectra in the coastal environment. The findings present new perspectives for the study of micro-scale wind–wave interactions.

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“…Boldyrev in [ 25 ] also concluded that MHD turbulence is not completely described by either the

scales; the scales depend on the strength of the external magnetic field:

scale applies when the mean magnetic field is strong while

scale applies when the external magnetic field is weak. We refer to the review by Verma [ 19 ] for the several phenomenological theories on MHD turbulence, the book by Davidson et al [ 2 ] for the biographies and works of some of the prominent contributors to the area, and [ 26 , 27 , 28 , 29 ] and the references in there for interesting applications and recent developments.…”

Section: Introductionmentioning

confidence: 99%

On the Inertial Range Bounds of K-41-like Magnetohydrodynamics Turbulence

Tegegn

2022

Entropy

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The spectral slope of magnetohydrodynamic (MHD) turbulence varies depending on the spectral theory considered; −3/2 is the spectral slope in Kraichnan–Iroshnikov–Dobrowolny (KID) theory, −5/3 in Marsch–Matthaeus–Zhou and Goldreich–Sridhar theories, also called Kolmogorov-like (K-41-like) MHD theory, the combination of the −5/3 and −3/2 scales in Biskamp, and so on. A rigorous mathematical proof to any of these spectral theories is of great scientific interest. Motivated by the 2012 work of A. Biryuk and W. Craig (Physica D 241(2012) 426–438), we establish inertial range bounds for K-41-like phenomenon in MHD turbulent flow through a mathematical rigor; a range of wave numbers in which the spectral slope of MHD turbulence is proportional to −5/3 is established and the upper and lower bounds of this range are explicitly formulated. We also have shown that the Leray weak solution of the standard MHD model is bonded in the Fourier space, the spectral energy of the system is bounded and its average over time decreases in time.

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Spectral moments for the analysis of frequency shift, broadening, and wavevector anisotropy in a turbulent flow

Cited by 6 publications

References 24 publications

Measurement insights and error analysis of electronic parameters for ultrasonic transducers

Measurement insights and error analysis of electronic parameters for ultrasonic transducers

Evidence of Ocean Waves Signature in the Space–Time Turbulent Spectra of the Lower Marine Atmosphere Measured by a Scanning LiDAR

On the Inertial Range Bounds of K-41-like Magnetohydrodynamics Turbulence

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