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On the modelling turbulent transition in turbine cascades with flow separation

SYSNO ASEP	0503135
Document Type	J - Journal Article
R&D Document Type	Journal Article
Subsidiary J	Článek ve WOS
Title	On the modelling turbulent transition in turbine cascades with flow separation
Author(s)	Louda, Petr (UT-L)_{RID, ORCID} Příhoda, Jaromír (UT-L)_{RID, ORCID}
Source Title	Computers & Fluids. - : Elsevier - ISSN 0045-7930 Roč. 181, March (2019), s. 160-172
Number of pages	13 s.
Publication form	Print - P
Language	eng - English
Country	GB - United Kingdom
Keywords	turbine cascade ; transition model ; separation bubble ; shock wave-boundary layer interaction
Subject RIV	BK - Fluid Dynamics
OECD category	Applied mechanics
R&D Projects	TH02020057 GA TA ČR - Technology Agency of the Czech Republic (TA ČR)
Method of publishing	Limited access
Institutional support	UT-L - RVO:61388998
UT WOS	000466824800012
EID SCOPUS	85060326345
DOI	10.1016/j.compfluid.2019.01.008
Annotation	The work discusses performance, modification and implementation details of three intermittency based transition models. The intermittency is applied in the SST eddy viscosity turbulence model and in an explicit algebraic Reynolds stress model (EARSM). Experimental results of transonic flows through turbine cascades at different Reynolds numbers are used as test cases, where the interaction of shock wave with laminar or turbulent boundary layer can be distinguished and reproduced in simulations. Of the transition models tested, only the criteria based (gamma-zeta model captures well the influence of Reynolds number on the transition. The criterion for transition on separation bubble has been re-formulated so that the model is local in stream-wise direction and applicable also in 3D flows. The model is still non-local in wall- normal direction but this is found acceptable considering its performance and the fact that its evaluation is made fully automatic in the framework of structured multi-block solver.
Workplace	Institute of Thermomechanics
Contact	Marie Kajprová, kajprova@it.cas.cz, Tel.: 266 053 154 ; Jana Lahovská, jaja@it.cas.cz, Tel.: 266 053 823
Year of Publishing	2020
Electronic address	https://www.sciencedirect.com/science/article/pii/S0045793019300064?via%3Dihub

Number of the records: 1