scholarly journals Stochastic Intermittency Fields in a von Kármán Experiment

Symmetry ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1752
Author(s):  
Jürgen Schmiegel ◽  
Flavio Pons
Keyword(s):  
Time Series ◽  
Energy Dissipation ◽  
Turbulent Flow ◽  
Turbulence Intensity ◽  
Statistical Properties ◽  
Close Resemblance ◽  
Von Karman ◽  
The One ◽  
Von Kármán

We discuss the application of stochastic intermittency fields to describe and analyse the statistical properties of time series of the generalised turbulence intensity in an anisotropic and inhomogeneous turbulent flow and provide a parsimonious description of the one-, two-, and three-point statistics. In particular, we show that the three-point correlations can be predicted from observed two-point statistics. Our analysis is motivated by observed stylised features of the energy dissipation in homogeneous and isotropic situations where these statistical properties are well represented within the framework of stochastic intermittency fields. We find a close resemblance and conclude that stochastic intermittency fields may be relevant in more general situations.

scholarly journals Evaluation of a Procedure to Correct Spatial Averaging in Turbulence Statistics from a Doppler Lidar by Comparing Time Series with an Ultrasonic Anemometer

2016 ◽  
Vol 33 (10) ◽  
pp. 2135-2144 ◽  
Author(s):  
Peter Brugger ◽  
Katja Träumner ◽  
Christina Jung
Keyword(s):  
Time Series ◽  
Pulse Length ◽  
Doppler Lidar ◽  
Spatial Averaging ◽  
Outer Scale ◽  
Turbulence Statistics ◽  
Von Karman ◽  
Velocity Variance ◽  
Ultrasonic Anemometer ◽  
Von Kármán

AbstractDoppler lidars are frequently used for wind measurements in the atmospheric boundary layer, but their data are subject to spatial averaging due to the pulse length of the laser and sampling frequency of the return signal. This spatial averaging also affects estimates of turbulence statistics like the velocity variance and outer scale of turbulence from Doppler lidar data. In this study a procedure from Frehlich and Cornman based on a von Kármán turbulence model was systematically applied to correct these effects of spatial averaging on turbulence statistics. The model was able to reduce the occurring bias of the velocity variance and outer scale of turbulence in a comparison of time series from a Doppler lidar and an ultrasonic anemometer. The measurements show that the bias of the velocity variance was reduced by 29% and that of the outer scale of turbulence by 43%. But both turbulence parameters had a remaining systematic error that could not be explained by the von Kármán model of the structure function.

On the Velocity Distribution of Turbulent Flow in Pipes and Channels of Constant Cross Section

1946 ◽  
Vol 13 (2) ◽  
pp. A85-A90
Author(s):  
Chi-Teh Wang
Keyword(s):  
Turbulent Flow ◽  
Velocity Distribution ◽  
Length Distribution ◽  
Critical Examination ◽  
Large Reynolds Number ◽  
Good Picture ◽  
Von Karman ◽  
Von Kármán ◽  
New Formula ◽  
Good Agreement

Abstract This paper follows the Prandtl conception of momentum transport and gives a critical examination of the so-called Prandtl-Nikuradse formula and the von Kármán formula for the velocity distribution of the turbulent flow in tubes or channels at large Reynolds number. It shows that both formulas would not give a good picture of the turbulent flow near the center of the conduit, and indeed they actually do not. A new formula for the velocity distribution is developed from a study of the mixing-length distribution across the section. This new formula checks quite well with the experiments and yields the same skin-friction formula as derived by von Kármán and Prandtl, which itself is in very good agreement with experiments.

scholarly journals Global vs local energy dissipation: The energy cycle of the turbulent von Kármán flow

2015 ◽  
Vol 27 (7) ◽  
pp. 075105 ◽  
Author(s):  
Denis Kuzzay ◽  
Davide Faranda ◽  
Bérengère Dubrulle
Keyword(s):  
Energy Dissipation ◽  
Local Energy ◽  
Von Karman ◽  
Energy Cycle ◽  
Von Kármán

Existence of a sharp transition in the peak propulsive efficiency of a low- pitching foil

2016 ◽  
Vol 800 ◽  
pp. 307-326 ◽  
Author(s):  
Anil Das ◽  
Ratnesh K. Shukla ◽  
Raghuraman N. Govardhan
Keyword(s):  
Power Coefficient ◽  
Energetic Cost ◽  
Mean Power ◽  
Thrust Coefficient ◽  
Propulsive Efficiency ◽  
Von Karman ◽  
Wide Range ◽  
The Mean ◽  
The One ◽  
Von Kármán

We perform a comprehensive characterization of the propulsive performance of a thrust generating pitching foil over a wide range of Reynolds ($10\leqslant Re\leqslant 2000$) and Strouhal ($St$) numbers using a high-resolution viscous vortex particle method. For a given $Re$, we show that the mean thrust coefficient $\overline{C_{T}}$ increases monotonically with $St$, exhibiting a sharp rise as the location of the inception of the wake asymmetry shifts towards the trailing edge. As a result, the propulsive efficiency too rises steeply before attaining a maximum and eventually declining at an asymptotic rate that is consistent with the inertial scalings of $St^{2}$ for $\overline{C_{T}}$ and $St^{3}$ for the mean power coefficient, with the latter scaling holding, quite remarkably, over the entire range of $Re$. We find the existence of a sharp increase in the peak propulsive efficiency ${\it\eta}_{max}$ (at a given $Re$) in the $Re$ range of 50 to approximately 1000, with ${\it\eta}_{max}$ increasing rapidly from about 1.7 % to the saturated asymptotic value of approximately $16\,\%$. The $St$ at which ${\it\eta}_{max}$ is attained decreases progressively with $Re$ towards an asymptotic limit of $0.45$ and always exceeds the one for transition from a reverse von Kármán to a deflected wake. Moreover, the drag-to-thrust transition occurs at a Strouhal number $St_{tr}$ that exceeds the one for von Kármán to reverse von Kármán transition. The $St_{tr}$ and the corresponding power coefficient $\overline{C_{p,}}_{tr}$ are found to be remarkably consistent with the simple scaling relationships $St_{tr}\sim Re^{-0.37}$ and $\overline{C_{p,}}_{tr}\sim Re^{-1.12}$ that are derived from a balance of the thrust generated from the pitching motion and the drag force arising out of viscous resistance to the foil motion. The fact that the peak propulsive efficiency degrades appreciably only below $Re\approx 10^{3}$ establishes a sharp lower threshold for energetically efficient thrust generation from a pitching foil. Our findings should be generalizable to other thrust-producing flapping foil configurations and should aid in establishing the link between wake patterns and energetic cost of thrust production in similar systems.

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.

On the Principle of Haar and von Karman in Statically Determinate Problems of Plasticity

1957 ◽  
Vol 24 (3) ◽  
pp. 461-463
Author(s):  
Leo Finzi
Keyword(s):  
Energy Density ◽  
Elastic Energy ◽  
Yield Condition ◽  
Variational Formula ◽  
Stress Strain ◽  
Von Karman ◽  
The One ◽  
Von Kármán

Abstract It is shown that a variational formula similar to the one expressing the principle of Haar and von Karman in the statically determinate problems of plasticity holds independently of the stress-strain relations and yield condition. In the variation of the elastic energy the part connected with the variation of the field must be distinguished from the part connected with the variation of the energy density. These points are illustrated by an example.

On von Karman modeling for turbulent flow near a wall

2019 ◽  
Vol 26 (3) ◽  
pp. 291-296
Author(s):  
Jacques Rappaz ◽  
Jonathan Rochat
Keyword(s):  
Turbulent Flow ◽  
Von Karman ◽  
Von Kármán

Correlation in the heart rate data

1998 ◽  
Vol 2 ◽  
pp. 141-148
Author(s):  
J. Ulbikas ◽  
A. Čenys ◽  
D. Žemaitytė ◽  
G. Varoneckas
Keyword(s):  
Nonlinear Dynamics ◽  
Experimental Data ◽  
Heart Rate ◽  
Time Series ◽  
Cardiovascular Function ◽  
Statistical Properties ◽  
Rate Data ◽  
Heart Rate Data ◽  
Dynamical Nature ◽  
Analysis Of Time Series

Variety of methods of nonlinear dynamics have been used for possibility of an analysis of time series in experimental physiology. Dynamical nature of experimental data was checked using specific methods. Statistical properties of the heart rate have been investigated. Correlation between of cardiovascular function and statistical properties of both, heart rate and stroke volume, have been analyzed. Possibility to use a data from correlations in heart rate for monitoring of cardiovascular function was discussed.

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