Research Papers

Predicting High-Lift Low-Pressure Turbine Cascades Flow Using Transition-Sensitive Turbulence Closures

[+] Author and Article Information
Roberto Pacciani

e-mail: roberto.pacciani@unifi.it

Andrea Arnone

Department of Industrial Engineering
University of Florence
via di Santa Marta,
3 Firenze 50139,Italy

Francesco Bertini

Avio S.p.A. via I Maggio, 99,
Rivalta di Torino (TO) 10040,Italy

Contributed by the International Gas Turbine Institute (IGTI) of ASME for publication in the JOURNAL OF TURBOMACHINERY. Manuscript received June 13, 2013; final manuscript received July 29, 2013; published online September 27, 2013. Editor: Ronald Bunker.

J. Turbomach 136(5), 051007 (Sep 27, 2013) (11 pages) Paper No: TURBO-13-1098; doi: 10.1115/1.4025224 History: Received June 13, 2013; Revised July 29, 2013

This paper discusses the application of different transition-sensitive turbulence closures to the prediction of low-Reynolds-number flows in high-lift cascades operating in low-pressure turbine (LPT) conditions. Different formulations of the well known γ-R˜eθt model are considered and compared to a recently developed transition model based on the laminar kinetic energy (LKE) concept. All those approaches have been coupled to the Wilcox k-ω turbulence model. The performance of the transition-sensitive closures has been assessed by analyzing three different high-lift cascades, recently tested experimentally in two European research projects (Unsteady Transition in Axial Turbomachines (UTAT) and Turbulence and Transition Modeling for Special Turbomachinery Applications (TATMo)). Such cascades (T106A, T106C, and T108) feature different loading distributions, different suction side diffusion factors, and they are characterized by suction side boundary layer separation when operated in steady inflow. Both steady and unsteady inflow conditions (induced by upstream passing wakes) have been studied. Particular attention has been devoted to the treatment of crucial boundary conditions like the freestream turbulence intensity and the turbulent length scale. A detailed comparison between measurements and computations, in terms of blade surface isentropic Mach number distributions and cascade lapse rates will be presented and discussed. Specific features of the computed wake-induced transition patterns will be discussed for selected Reynolds numbers. Finally, some guidelines concerning the computations of high-lift cascades for LPT applications using Reynolds-averaged Navier–Stokes (RANS)/unsteady RANS (URANS) approaches and transition-sensitive closures will be reported.

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Fig. 1

(a) Analyzed cascades configurations, (b) T106C – single-block O-type grid 641×101

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Fig. 2

Turbulence decay upstream of the T106C and T108 cascades (Re2,is = 1.6×105)

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Fig. 3

T108 cascade: experimental [16] and computed isentropic Mach number distributions along the blade suction side (a) Re2,is = 0.8×105 (b) Re2,is = 1.4×105 (c) Re2,is = 2×105

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Fig. 4

T108 cascade: wall shear stress distributions (a) Re2,is = 0.8×105 (b) Re2,is = 2×105

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Fig. 5

T108 cascade: experimental [16] and computed Reynolds number lapse rate

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Fig. 6

T106C cascade: experimental [34] and computed isentropic Mach number distributions along the blade suction side (Tu∞ = 0.8%) (a) Re2,is = 0.8×105 (b) Re2,is = 1.6×105 (c) Re2,is = 2.5×105

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Fig. 7

T106C cascade: experimental [34] and computed Reynolds number lapse (Tu∞ = 0.8%)

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Fig. 8

T106C cascade: experimental [34] and computed isentropic Mach number distributions for different freestream turbulence levels (Re2,is = 0.8×105)

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Fig. 9

T106C cascade: experimental [34] and computed cascade lapse rates for different freestream turbulence levels

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Fig. 10

T106C cascade: steady and unsteady isentropic Mach number distributions (a) Re2,is = 1×105, (b) Re2,is = 1.4×105, and (c) steady and unsteady cascade lapse rates

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Fig. 11

T106C cascade: space time diagrams (a) turbulence indicator function (b) laminar kinetic energy, Re2,is = 1.4×105, Tu∞=0.8%

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Fig. 12

T106A cascade: (a) experimental [6] and computed steady and unsteady pressure coefficient distributions, (b) steady boundary layer shape factor, (Re2,is = 1×105, Tu∞ = 4.0%)

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Fig. 13

T106A cascade: space time diagrams boundary layer shape factor (a) LKE-based model (b) γ-R˜eθt LM model, (c) measured [6]




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