Результаты исследований: Научные публикации в периодических изданиях › статья по материалам конференции › Рецензирование
Prediction of vortex precession in the draft tube of a model hydro turbine using mean field stability theory and stochastic modelling. / Müller, Jens S.; Sieber, Moritz; Litvinov, Ivan и др.
в: IOP Conference Series: Earth and Environmental Science, Том 774, № 1, 012003, 15.06.2021.Результаты исследований: Научные публикации в периодических изданиях › статья по материалам конференции › Рецензирование
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TY - JOUR
T1 - Prediction of vortex precession in the draft tube of a model hydro turbine using mean field stability theory and stochastic modelling
AU - Müller, Jens S.
AU - Sieber, Moritz
AU - Litvinov, Ivan
AU - Shtork, Sergey
AU - Alekseenko, Sergey
AU - Oberleithner, Kilian
N1 - Funding Information: The funding from the RFBR under project number 20-58-12012 and the DFG under number 429772199 is gratefully acknowledged. Publisher Copyright: © Published under licence by IOP Publishing Ltd. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/6/15
Y1 - 2021/6/15
N2 - In this work we employ mean field stability theory (MFST) to predict the onset of the precessing vortex core (PVC) in the draft tube of Francis turbines. MFST is based on the linear stability analysis of the mean field of turbulent flows. Recent work shows that MFST very accurately predicts the formation of coherent structures in turbulent shear flows, such as the PVC. MFST may further reveal the flow regions that are most susceptible to flow actuation to suppress the PVC, which is of great practical relevance. In this work, MFST is accompanied by a data-driven approach to predict the linear growth rate of the PVC based on pointwise wall pressure measurements. The method is based on statistical evaluation of the probability density function of the PVC amplitude at limit cycle. It makes use of the intense noise induced by the background turbulence, which is expected to be a major driver of hydrodynamic instabilities. The empirical and analytic results are compared to phase-locked LDV measurements conducted inside the draft tube at various operating conditions, to assess the quantitative accuracy of the approach. The methodologies outlined in this work will be of relevance for future design of hydro turbines to run stable over a wide range of operating conditions.
AB - In this work we employ mean field stability theory (MFST) to predict the onset of the precessing vortex core (PVC) in the draft tube of Francis turbines. MFST is based on the linear stability analysis of the mean field of turbulent flows. Recent work shows that MFST very accurately predicts the formation of coherent structures in turbulent shear flows, such as the PVC. MFST may further reveal the flow regions that are most susceptible to flow actuation to suppress the PVC, which is of great practical relevance. In this work, MFST is accompanied by a data-driven approach to predict the linear growth rate of the PVC based on pointwise wall pressure measurements. The method is based on statistical evaluation of the probability density function of the PVC amplitude at limit cycle. It makes use of the intense noise induced by the background turbulence, which is expected to be a major driver of hydrodynamic instabilities. The empirical and analytic results are compared to phase-locked LDV measurements conducted inside the draft tube at various operating conditions, to assess the quantitative accuracy of the approach. The methodologies outlined in this work will be of relevance for future design of hydro turbines to run stable over a wide range of operating conditions.
UR - http://www.scopus.com/inward/record.url?scp=85108651399&partnerID=8YFLogxK
U2 - 10.1088/1755-1315/774/1/012003
DO - 10.1088/1755-1315/774/1/012003
M3 - Conference article
AN - SCOPUS:85108651399
VL - 774
JO - IOP Conference Series: Earth and Environmental Science
JF - IOP Conference Series: Earth and Environmental Science
SN - 1755-1307
IS - 1
M1 - 012003
T2 - 30th IAHR Symposium on Hydraulic Machinery and Systems, IAHR 2020
Y2 - 21 March 2021 through 26 March 2021
ER -
ID: 28874767