Wake Width: Discussion of Several Methods How to Estimate It by Using Measured Experimental Data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61388998%3A_____%2F21%3A00545828" target="_blank" >RIV/61388998:_____/21:00545828 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/49777513:23210/21:43962487

Výsledek na webu

<a href="https://www.mdpi.com/1996-1073/14/15/4712/htm" target="_blank" >https://www.mdpi.com/1996-1073/14/15/4712/htm</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/en14154712" target="_blank" >10.3390/en14154712</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Wake Width: Discussion of Several Methods How to Estimate It by Using Measured Experimental Data

Popis výsledku v původním jazyce

Several methods of defining and estimating the width of a turbulent wake are presented and tested on the experimental data obtained in the wake past an asymmetric prismatic airfoil NACA 64(3)‐618, which is often used as tip profile of the wind turbines. Instantaneous velocities are measured by using the Particle Image Velocimetry (PIV) technique. All suggested methods of wake width estimation are based on the statistics of a stream‐wise velocity component. First, the expansion of boundary layer (BL) thickness is tested, showing that both displacement BL thickness and momentum BL thickness do not represent the width of the wake. The equivalent of 99% BL thickness is used in the literature, but with different threshold value. It is shown that a lower threshold of 50% gives more stable results. The ensemble average velocity profile is fitted by Gauss function and its σ‐parameter is used as another definition of wake width. The profiles of stream‐wise velocity standard deviation display a two‐peak shape, the distance of those peaks serves as wake width for Norberg, while another tested option is to include the widths of such peaks. Skewness (the third statistical moment) of stream‐wise velocity displays a pair of sharp peaks in the wake boundary, but their position is heavily affected by the statistical quality of the data. Flatness (the fourth statistical moment) of the stream‐wise velocity refers to the occurrence of rare events, and therefore the distance, where turbulent events ejected from the wake become rare and can be considered as another definition of wake width. The repeatability of the mentioned methods and their sensitivity to Reynolds’ number and model quality are discussed as well.

Název v anglickém jazyce

Wake Width: Discussion of Several Methods How to Estimate It by Using Measured Experimental Data

Popis výsledku anglicky

Several methods of defining and estimating the width of a turbulent wake are presented and tested on the experimental data obtained in the wake past an asymmetric prismatic airfoil NACA 64(3)‐618, which is often used as tip profile of the wind turbines. Instantaneous velocities are measured by using the Particle Image Velocimetry (PIV) technique. All suggested methods of wake width estimation are based on the statistics of a stream‐wise velocity component. First, the expansion of boundary layer (BL) thickness is tested, showing that both displacement BL thickness and momentum BL thickness do not represent the width of the wake. The equivalent of 99% BL thickness is used in the literature, but with different threshold value. It is shown that a lower threshold of 50% gives more stable results. The ensemble average velocity profile is fitted by Gauss function and its σ‐parameter is used as another definition of wake width. The profiles of stream‐wise velocity standard deviation display a two‐peak shape, the distance of those peaks serves as wake width for Norberg, while another tested option is to include the widths of such peaks. Skewness (the third statistical moment) of stream‐wise velocity displays a pair of sharp peaks in the wake boundary, but their position is heavily affected by the statistical quality of the data. Flatness (the fourth statistical moment) of the stream‐wise velocity refers to the occurrence of rare events, and therefore the distance, where turbulent events ejected from the wake become rare and can be considered as another definition of wake width. The repeatability of the mentioned methods and their sensitivity to Reynolds’ number and model quality are discussed as well.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20302 - Applied mechanics

Projekt

<a href="/cs/project/EF16_026%2F0008389" target="_blank" >EF16_026/0008389: Výzkumná spolupráce pro dosažení vyšší účinnosti a spolehlivosti lopatkových strojů</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Energies

ISSN

1996-1073

e-ISSN

1996-1073

Svazek periodika

14

Číslo periodika v rámci svazku

15

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

19

Strana od-do

4712

Kód UT WoS článku

000681885600001

EID výsledku v databázi Scopus

2-s2.0-85112097747