scholarly journals Survey and Analysis of Multiresolution Methods for Turbulence Data

2015 ◽  
Author(s):  
Jesus J. Pulido ◽  
Daniel Livescu ◽  
Jonathan Lee Woodring ◽  
James Paul Ahrens ◽  
Bernd Hamann
Keyword(s):  
Multiresolution Methods ◽  
Turbulence Data

scholarly journals Survey and analysis of multiresolution methods for turbulence data

2016 ◽  
Vol 125 ◽  
pp. 39-58 ◽  
Author(s):  
Jesus Pulido ◽  
Daniel Livescu ◽  
Jonathan Woodring ◽  
James Ahrens ◽  
Bernd Hamann
Keyword(s):  
Multiresolution Methods ◽  
Turbulence Data

Stochastic Models of Particle Trajectories in Turbulent Atmosphere Flows by Using the LANGEVIN Equations

Proceedings ◽  
2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Youssra El Qasemy ◽  
Abdelfatah Achahbar ◽  
Abdellatif Khamlichi
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Classical Method ◽  
Degradation Mechanism ◽  
Transformation Process ◽  
Langevin Equations ◽  
Turbulence Data ◽  
Power Curves ◽  
And Diffusion ◽  
Fluctuating Wind

The stochastic behavior of wind speed is a particular characteristic of wind energy production, which affects the degradation mechanism of the turbine, resulting in stochastic charging on the wind turbine. A model stochastic is used in this study to evaluate the efficiency of wind turbine power of whatever degree given fluctuating wind turbulence data. This model is based on the Langevin equations, which characterize, by two coefficients, drift and diffusion functions. These coefficients describe the behavior of the transformation process from the input wind speed to the output data that need to be determined. For this present work, the computation of drift and diffusion functions has been carried out by using the stochastic model to assess the output variables in terms of the torque and power curves as a function of time, and it is compared by the classical method. The results show that the model stochastic can define the efficiency of wind turbine generation more precisely.

scholarly journals Multiscale Sample Entropy of Two-Dimensional Decaying Turbulence

Entropy ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. 245
Author(s):  
Ildoo Kim
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Soap Film ◽  
Sample Entropy ◽  
Series Data ◽  
Entropy Analysis ◽  
Measured Time ◽  
Energetic Analysis ◽  
Turbulence Data ◽  
Decaying Turbulence

Multiscale sample entropy analysis has been developed to quantify the complexity and the predictability of a time series, originally developed for physiological time series. In this study, the analysis was applied to the turbulence data. We measured time series data for the velocity fluctuation, in either the longitudinal or transverse direction, of turbulent soap film flows at various locations. The research was to assess the feasibility of using the entropy analysis to qualitatively characterize turbulence, without using any conventional energetic analysis of turbulence. The study showed that the application of the entropy analysis to the turbulence data is promising. From the analysis, we successfully captured two important features of the turbulent soap films. It is indicated that the turbulence is anisotropic from the directional disparity. In addition, we observed that the most unpredictable time scale increases with the downstream distance, which is an indication of the decaying turbulence.

scholarly journals Description and Derived Climatologies of Automated In Situ Eddy-Dissipation-Rate Reports of Atmospheric Turbulence

2014 ◽  
Vol 53 (6) ◽  
pp. 1416-1432 ◽  
Author(s):  
R. D. Sharman ◽  
L. B. Cornman ◽  
G. Meymaris ◽  
J. Pearson ◽  
T. Farrar
Keyword(s):  
Atmospheric Turbulence ◽  
Dissipation Rate ◽  
Route Planning ◽  
Federal Aviation Administration ◽  
The United States ◽  
Commercial Aircraft ◽  
Upper Troposphere ◽  
Obvious Benefit ◽  
Turbulence Data

AbstractThe statistical properties of turbulence at upper levels in the atmosphere [upper troposphere and lower stratosphere (UTLS)] are still not well known, partly because of the lack of adequate routine observations. This is despite the obvious benefit that such observations would have for alerting aircraft of potentially hazardous conditions, either in real time or for route planning. To address this deficiency, a research project sponsored by the Federal Aviation Administration has developed a software package that automatically estimates and reports atmospheric turbulence intensity levels (as EDR ≡ ε1/3, where ε is the energy or eddy dissipation rate). The package has been tested and evaluated on commercial aircraft. The amount of turbulence data gathered from these in situ reports is unprecedented. As of January 2014, there are ~200 aircraft outfitted with this system, contributing to over 137 million archived records of EDR values through 2013, most of which were taken at cruise levels of commercial aircraft, that is, in the UTLS. In this paper, techniques used for estimating EDR are outlined and comparisons with pilot reports from the same or nearby aircraft are presented. These reports allow calibration of EDR in terms of traditionally reported intensity categories (“light,” “moderate,” or “severe”). The results of some statistical analyses of EDR values are also presented. These analyses are restricted to the United States for now, but, as this program is expanded to international carriers, such data will begin to become available over other areas of the globe.

Some Aspects of Wake-Wake Interactions Regarding Turbine Stator Clocking

2000 ◽  
Vol 123 (3) ◽  
pp. 526-533 ◽  
Author(s):  
Maik Tiedemann ◽  
Friedrich Kost
Keyword(s):  
Total Pressure ◽  
Guide Vane ◽  
Pressure Fluctuations ◽  
Fast Response ◽  
Turbine Stage ◽  
Flow Angle ◽  
Wake Interactions ◽  
Turbulence Data ◽  
Number Flow ◽  
Nozzle Guide

This investigation is aimed at an experimental determination of the unsteady flowfield downstream of a transonic high pressure turbine stage. The single stage measurements, which were part of a joined European project, were conducted in the windtunnel for rotating cascades of the DLR Go¨ttingen. Laser-2-focus (L2F) measurements were carried out in order to determine the Mach number, flow angle, and turbulence distributions. Furthermore, a fast response pitot probe was utilized to determine the total pressure distribution. The measurement position for both systems was 0.5 axial rotor chord downstream of the rotor trailing edge at midspan. While the measurement position remained fixed, the nozzle guide vane (NGV) was “clocked” to 12 positions covering one NGV pitch. The periodic fluctuations of the total pressure downstream of the turbine stage indicate that the NGV wake damps the total pressure fluctuations caused by the rotor wakes. Furthermore, the random fluctuations are significantly lower in the NGV wake affected region. Similar conclusions were drawn from the L2F turbulence data. Since the location of the interaction between NGV wake and rotor wake is determined by the NGV position, the described effects are potential causes for the benefits of “stator clocking” which have been observed by many researchers.

scholarly journals A Clustering Method to Characterize Intermittent Bursts of Turbulence and Interaction with Submesomotions in the Stable Boundary Layer

2015 ◽  
Vol 72 (4) ◽  
pp. 1504-1517 ◽  
Author(s):  
Nikki Vercauteren ◽  
Rupert Klein
Keyword(s):  
Thermal Stratification ◽  
Factor Model ◽  
Similarity Theory ◽  
Stable Stratification ◽  
Small Scale ◽  
Clustering Method ◽  
Atmospheric Boundary Layers ◽  
Optimal Sequence ◽  
Stable Conditions ◽  
Turbulence Data

Abstract Atmospheric boundary layers with stable stratification include a variety of small-scale nonturbulent motions such as waves, microfronts, and other complex structures. When the thermal stratification becomes strong, the presence of such motions could affect the turbulent mixing to a large extent, and common similarity theory that is used to describe weakly stable conditions may become unreliable. The authors apply a statistical clustering methodology based on a bounded variation, finite-element method (FEM-BV) to characterize the interaction between small-scale nonturbulent motions and turbulence. The clustering methodology achieves a multiscale representation of nonstationary turbulence data by approximating them through an optimal sequence of locally stationary multivariate autoregressive factor model (VARX) processes and some slow hidden process switching between them. The clustering method is used to separate periods with different influence of the nonturbulent motions on the vertical velocity fluctuations. The methodology can be used in a later stage to derive a stochastic parameterization for the interactions between nonturbulent and turbulent motions.

Observing the Dynamics of Wildland Grass Fires: FireFlux—A Field Validation Experiment

2007 ◽  
Vol 88 (9) ◽  
pp. 1369-1382 ◽  
Author(s):  
Craig B. Clements ◽  
Shiyuan Zhong ◽  
Scott Goodrick ◽  
Ju Li ◽  
Brian E. Potter ◽  
...  
Keyword(s):  
Great Plains ◽  
Forest Fires ◽  
Fire Behavior ◽  
The United States ◽  
Fire Season ◽  
Turbulent Structures ◽  
Tall Grass ◽  
Tall Grass Prairie ◽  
Validation Experiment ◽  
Turbulence Data

Grass fires, although not as intense as forest fires, present a major threat to life and property during periods of drought in the Great Plains of the United States. Recently, major wildland grass fires in Texas burned nearly 1.6 million acres and destroyed over 730 homes and 1320 other buildings. The fires resulted in the death of 19 people, an estimated loss of 10,000 head of livestock, and more than $628 million in damage, making the 2005/06 fire season the worst on record for the state of Texas. As an aid to fire management, various models have been developed to describe fire behavior. However, these models strongly emphasize fuels and fail to adequately consider the role of convective dynamics within the atmosphere and its interaction with the fire due to the lack of observational data. To fill this gap, an intensive field measurement campaign called FireFlux was conducted during February 2006 near Houston, Texas. The campaign employed a variety of instrument platforms to collect turbulence data at multiple levels within and immediately downwind of a 155 acre tall-grass prairie burn unit. This paper presents some first-time observations of atmospheric turbulent structures/fluxes associated with intense grass fires and provides a basis to further our understanding of the dynamics of grass fires and their interactions with the atmosphere.

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