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Research Papers

Scaling Three-Dimensional Low-Pressure Turbine Blades for Low-Speed Testing

[+] Author and Article Information
Matteo Giovannini

Department of Industrial Engineering,
University of Florence,
Via di S.Marta, 3,
Florence 50139, Italy
e-mail: matteo.giovannini@tgroup.unifi.it

Michele Marconcini, Filippo Rubechini, Andrea Arnone

Department of Industrial Engineering,
University of Florence,
Via di S.Marta, 3,
Florence 50139, Italy

Francesco Bertini

GE Avio,
Viale I Maggio, 56,
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 January 8, 2016; final manuscript received March 18, 2016; published online May 10, 2016. Assoc. Editor: John Clark.

J. Turbomach 138(11), 111001 (May 10, 2016) (9 pages) Paper No: TURBO-16-1009; doi: 10.1115/1.4033259 History: Received January 08, 2016; Revised March 18, 2016

The present activity was carried out in the framework of the Clean Sky European Research Project ITURB (optimal high-lift turbine blade aeromechanical design), aimed at designing and validating a turbine blade for a geared open-rotor engine. A cold-flow, large-scale, low-speed (LS) rig was built in order to investigate and validate new design criteria, providing reliable and detailed results while containing costs. This paper presents the design of an LS stage and describes a general procedure that allows to scale three-dimensional (3D) blades for LS testing. The design of the stator row was aimed at matching the test-rig inlet conditions and at providing the proper inlet flow field to the blade row. The rotor row was redesigned in order to match the performance of the high-speed (HS) configuration, compensating for both the compressibility effects and different turbine flow paths. The proposed scaling procedure is based on the matching of the 3D blade loading distribution between the real engine environment and the LS facility one, which leads to a comparable behavior of the boundary layer and hence to comparable profile losses. To this end, the datum blade is parameterized, and a neural-network-based methodology is exploited to guide an optimization process based on 3D Reynolds-averaged Navier–Stokes (RANS) computations. The LS stage performance was investigated over a range of Reynolds numbers characteristic of modern low-pressure turbines (LPTs) by using a multi-equation, transition-sensitive, turbulence model. Some comparisons with experimental data available within the project finally proved the effectiveness of the proposed scaling procedure.

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Figures

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Fig. 1

HS (a) and LS (b) turbine flow path

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Fig. 2

Scaling procedure validation for the T106C cascade [15]. (a) Pressure coefficient distribution (Re2s = 1.6 × 105). (b) Kinetic energy loss coefficient as a function of streamwise distance Reynolds number.

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Fig. 3

Pressure coefficient distributions at HS and LS conditions: (a) 10% span, (b) 50% span, and (c) 90% span

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Fig. 4

Blade parameterization

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Fig. 5

LS rotor redesign: pressure coefficient distributions at midspan and near endwalls for the optimum of OPT-02 campaign: (a) 10% span, (b) 50% span, and (c) 90% span

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Fig. 7

Pressure coefficient distributions at different sections along the span for the LS blade. Local shape refinements allow to match HS distributions near endwalls (OPT-03 campaign results). (a) 10% span, (b) 50% span, and (c) 90% span.

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Fig. 8

LS blade geometry: (a) three-dimensional LS blade, (b) 30% span, (c) 50% span, and (d) 70% span

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Fig. 9

Kinetic energy loss coefficient for the HS and the LS blade as a function of the isentropic exit Reynolds number

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Fig. 10

Skin friction coefficient distribution for the HS and the LS blade for Re2s = 0.15 × 10−5 at rotor midspan

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Fig. 11

Spanwise distribution of the total pressure coefficient at stator inlet

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Fig. 12

Pressure coefficient distributions for the LS rotor blade: Re2s = 0.8 × 105. (a) 25% span, (b) 50% span, and (c) 75% span.

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Fig. 13

Pitchwise mass-averaged radial distributions of the relative flow angle at the rotor inlet and outlet

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Fig. 14

Rotor pressure losses as a function of the exit Reynolds number

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