Comparison With Experimental Data

Vijay K. Garg

University of Toledo, Toledo, Ohio

July 2002
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Comparison With Experimental Data

Vijay K. Garg

University of Toledo, Toledo, Ohio

Prepared for the

Turbo Expo 2002

cosponsored by the American Society of Mechanical Engineers

and the International Gas Turbine Institute

Amsterdam, The Netherlands, June 3–6, 2002

Prepared under Contract NAS3–00180 and Cooperative Agreement NCC3–926

National Aeronautics and

Space Administration

Glenn Research Center

July 2002
gy gg pgy g

Available from

NASA Center for Aerospace Information

7121 Standard Drive

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National Technical Information Service

5285 Port Royal Road

Springfield, VA 22100

This report contains preliminary

findings, subject to revision as

analysis proceeds.

Available electronically at http://gltrs.grc.nasa.gov/GLTRS

Trade names or manufacturers’ names are used in this report for

identification only. This usage does not constitute an official

endorsement, either expressed or implied, by the National

Aeronautics and Space Administration.
ABSTRACT

The present work details a computational study, using the GlennHT code, that analyzes the use of vortex generator jets (VGJs) to

control separation on a low-pressure turbine (LPT) blade at low

Reynolds numbers. The computational results are also compared with

the experimental data of Bons et al. [1] for steady VGJs. It is found

that the code determines the proper location of the separation point on

the suction surface of the baseline blade (without any VGJ) for

Reynolds numbers of 50,000 or less. Also, the code finds that the

separated region on the suction surface of the blade vanishes with the

use of VGJs. However, the separated region and the wake

characteristics are not well predicted. The wake width is generally

over-predicted while the wake depth is under-predicted.

NOMENCLATURE

B jet blowing ratio = (ρu)jet/(ρu)local

Cp blade pressure coefficient = (po,in - ps)/0.5(ρu2)in

Cx axial chord of the blade

d injection hole diameter

k turbulence kinetic energy

turbulence length scale

p pressure

Pr Prandtl number

Re inlet Reynolds number = Cx(ρu/μ)in

Tu freestream turbulence intensity

u streamwise mean velocity

v* shear velocity

x,y Cartesian coordinate system with origin at the blade leading

edge

y+ distance in wall coordinates = ρyv*/μ

α thermal diffusivity

∆y distance (from the wall) of the first point off the wall

ε turbulence dissipation rate

γ wake loss coefficient = (po,in - po,ex)/(po,in - ps,in)

μ dynamic viscosity

ρ density

τ shear stress

ω specific turbulence dissipation rate = ε/k

Subscripts

ef effective value

ex value at cascade exit

in value at cascade inlet

jet vortex generator jet conditions

laminar value

local local blade mid-channel conditions

o stagnation value

s static value

t turbulent value

w value at the wall

INTRODUCTION

For the flow over an airfoil, there is an adverse pressure gradient

region over a large part of the suction surface. This can cause the flow

to separate on the suction surface, especially at low Reynolds numbers,

in which case the boundary layer over the blade may be laminar. It is

well known that a laminar boundary layer can withstand only a minor

adverse pressure gradient before separation while a turbulent boundary

layer can withstand a much stronger adverse pressure gradient region.

Flow separation reduces lift and increases drag. It is thus undesirable

and needs to be controlled.

Flow separation can be controlled by both passive and active

techniques. The former employs small vortex generators (rectangular

or delta shaped winglets) which are imbedded in a boundary layer

ahead of a line of flow separation [2]. Spanwise arrays of vortex

generators are often placed along a wing upstream of the flap hinge or

inside the lip of a jet engine inlet diffuser. The longitudinal vortices

generated in the boundary layer increase cross-stream mixing of

streamwise momentum and suppress or eliminate separation. These

fixed vortex generators have the advantages of simplicity, ruggedness

and low cost. However, they add parasitic drag in flow situations

where separation control is not needed, e.g., take-off and landing.

*NASA Resident Research Associate at Glenn Research Center.

Vijay K. Garg*

University of Toledo

Toledo, Ohio 43606

vijay.garg@grc.nasa.gov

1 NASA/CR—2002-211689
single, dominant vortex for a VGJ at high skew angles. It has been

shown by Johnston and Nishi [8] that this vortex energizes the

separating boundary layer by bringing high momentum freestream fluid

down to the wall. Experimental data on the beneficial effects of VGJs

are available in [9].

The flow requirements for the jets in the VGJ method is a very

small fraction of the total jet engine flow, and compressor bleed air is

sufficient to power the system. The jets can be turned on and off as

desired. With jets off, there is no parasitic drag. The potential

applications of the VGJ method are numerous for external flow over

aircraft and missiles. Internal flows in diffusers can also be improved

and pressure losses reduced. The VGJ method can be used with

appropriate flow direction sensors and a feedback control system to

suppress surge and rotating stall in compressors of jet engines.

The operating Reynolds number for the low-pressure turbine in an

aircraft gas turbine engine can drop below 25,000 during high altitude

cruise. At such low Reynolds numbers, the boundary layers on the

LPT blades are largely laminar, making them highly susceptible to

flow separation near the aft portion of the blade suction surface, with

associated increase in losses and drop in performance. Altering the

blade shape to avoid this low Reynolds number separation problem is

not feasible since such a modification will likely impair the engine

operation at higher (design) Reynolds numbers. As such, an active

flow control strategy, such as the use of VGJs, has been tested

experimentally at the Air Force Research Laboratory recently [1, 10].

This paper aims to use the Glenn-HT code in order to analyze the use

of VGJs at low Reynolds numbers, and to compare the computational

predictions with the experimental data of Bons et al. [1].

ANALYSIS

The numerical simulation has been performed using the NASA

Glenn Research Center General Multi-Block Navier-Stokes Convective

Heat Transfer code, Glenn-HT. Briefly, the code, formerly known as

TRAF3D.MB [11], is an explicit, multigrid, cell-centered, finite

volume code with a k-ω turbulence model without any wall functions.

This is a general purpose flow solver designed for simulations of flows

in complicated geometries. The Navier-Stokes equations in a rotating

Cartesian coordinate system are mapped onto a general body-fitted

coordinate system using standard techniques. The multistage RungeKutta scheme developed by Jameson et al. [12] is used to advance the

flow solution in time from an initial approximation to the steady state.

A spatially varying time step along with a CFL number of 4 is used to

speed convergence to the steady state. Eigenvalue-scaled artificial

dissipation and variable-coefficient implicit residual smoothing are used

along with a full-multigrid method. The overall accuracy of the code

is second order. No wall functions are used, thus avoiding any bias to

original k-ω model of Wilcox [13] activated in the near-wall region

and the standard k-ε model [17] activated in the outer wake region and

in free shear layers. Moreover, the definition of eddy viscosity is

modified to account for the transport of the principal turbulent shear

stress. The reader is referred to Menter [14] for an elucidating

discussion of the SST model. More details on the relevant equations

and their implementation are available in Garg and Ameri [16]. The

SST model was used for the present computations.

It is assumed that the effective viscosity for turbulent flows can

be written as

where the laminar viscosity μ is calculated using a power-law for its

(1)

dependence on temperature [18]. The turbulent viscosity μt is

computed using the SST model. The turbulent thermal diffusivity is

computed from

where a constant value of 0.9 is used for the turbulent Prandtl number,

(2)

Prt

.

Boundary Conditions

At the main flow inlet boundary located at an axial distance equal

to the blade axial chord upstream of the blade leading edge, the total

temperature, total pressure, whirl, and meridional flow angle are

specified, and the upstream-running Riemann invariant based on the

total absolute velocity is calculated at the first interior point and

extrapolated to the inlet. The velocity components are then decoupled

algebraically, and the density is found from total temperature, total

pressure and total velocity using an isentropic relation. For the

turbulence model, the value of k and ω is specified using the

experimental conditions, namely

where Tuin is the intensity of turbulence at the inlet (taken to be 0.01

(3)

as per experimental data for the PakB blade), uin is the absolute

velocity at inlet, and is the integral length scale representing the size

of the energy containing eddies. This length scale needs to be

assumed, if not reported as part of the experimental conditions, as in

the present case. It was assumed to be 5% of the blade axial chord.

At the main flow exit plane located at an axial distance equal to

80% of the blade axial chord downstream of the blade trailing edge,

2 NASA/CR—2002-211689
The grid around the blade extends to mid-way between two

(5)

adjacent blades with periodic flow conditions in terms of cylindrical

velocity components set on a dummy grid line outside this boundary.

For a linear cascade (which is true for the experimental data), it is

possible to consider only a slice of the real span for computational

purposes with a periodic boundary condition at both ends of the

computational span. For the basic blade with no VGJ, this slice can

be of any reasonable width, but with VGJs, the width of the slice is

one span-wise pitch of the holes.

The effect of VGJs has been incorporated in the form of

appropriate boundary conditions at the hole locations on the blade

surface. Each hole exit in its true oval shape is represented by 224

control volumes. Different velocity and temperature profiles for the

injected fluid can be specified at the hole exits. For the present study,

polynomial distribution [21] of velocity and temperature of the

injectant at the hole exit was specified. The injectant angle was taken

to be the same as the hole angle. Turbulent intensity at the hole exit

was assumed to be 1% (same as for the freestream), while the

turbulence length scale at the hole exit was taken to be the same as the

hole diameter d.

EXPERIMENTAL DETAILS

Measurements were made by Bons et al. [1] in an induction wind

tunnel at the U.S. Air Force Research Laboratory. The linear cascade

consisted of eight 0.88 m (34.5 in) span, 0.18 m (7 in) axial chord (Cx)

blades plus two partial blade endwalls. The blades were fabricated

from molded polyurethane resin. The 2-D blade shape studied is the

Pratt & Whitney "PakB" research design, which is a Mach number

scaled version of a typical highly loaded LPT blade design. The

cascade had a solidity (axial chord to blade spacing) of 1.13, an inlet

flow angle of 55° (measured from the plane of the cascade), and a

design exit angle of 30°. Blades 4 and 6 were instrumented around

both pressure and suction surfaces (in the center 0.2 m of their span)

with forty 1 mm diameter static pressure taps. Uncertainties in the

pressure measurement translated to an error of ± 0.18 in the Cp data at

Re = 100,000 [1].

Blade #5 of the cascade had the active separation control. It was

manufactured with a hollow cavity running the span of the blade and

covering the region from 40% to 90% axial chord. A needle valve

located upstream of the feed port allows fine control of the mass flow

rate into the blade cavity. Air exhausts from this valve into a 1.2 cm

diameter capped copper tube running the span of the blade inside the

cavity. Holes of 1.5 mm diameter and spaced every 2.54 cm along the

Standard pitot and hot-wire probes mounted on a large Dantec 3-

axis traverse located atop the tunnel facility were used to map a 0.6m

× 0.6m planar cross-section of the flow domain. Wake velocity

profiles were measured using a single 4μm diameter tungsten hot-wire.

A single TSI sub-miniature hot-film probe was used for boundary layer

profile measurements. The hot- film sensor diameter was 25μm and

the sensing element length was 0.25mm. The error in the hot-wire and

film probes was within ±2% at flow rates of interest. More details are

available in [1].

COMPUTATIONAL DETAILS

The computational span extended over a part of the blade span

with a periodic boundary condition at both ends. In the axial direction,

the computational domain extended from the inlet plane located one

axial chord upstream of the blade leading edge to the exit plane located

80% of the axial chord downstream of the blade trailing edge. Around

the blade, the grid extends to mid-way between two adjacent blades

with periodic boundary conditions. Figure 1 shows a spanwise section

of the multi-block viscous grid around the blade. The viscous grid is

obtained from an inviscid grid by clustering the grid near all the solid

walls (blade here). The clustering is done in such a way as to ensure

that in the viscous grid, the distance of any cell center adjacent to a

solid wall, measured in wall units (y+

), is less than half for the cases

studied here, following Boyle and Giel [22]. The inviscid grid was

generated using the commercial code GridPro/az3000 [23]. For

computational accuracy the ratio of two adjacent grid sizes in any

direction was kept within 0.8-1.25. As can be observed from Fig. 1,

the grid quality is very good especially near the blade surface. Figure

1 also shows the grid over the blade span near and within the injection

hole exits.

Initially, the grid for the blade with injection holes consists of 136

blocks but before the solver is used, it can be merged into just 10

blocks using the Method of Weakest Descent [24]. The final viscous

grid consists of 160128 cells, formed by clustering near the blade from

an inviscid grid with 92928 cells. There are 224 cells within the hole

exit on the blade surface. The inviscid grid has 144 cells around the

blade (for the O-grid around the blade), 28 cells in the blade-to-blade

direction from the blade to the periodic boundary in-between the two

blades, and 24 in the spanwise direction. After clustering, the number

of cells in the blade-to-blade direction increases to 48. Two more

grids were generated for a grid-independence study. One inviscid grid

had 1.5 times the number of cells in each direction as compared to the

basic grid described above. For the second grid, the basic inviscid grid

was clustered near the blade with a grid spacing half of that for the

basic viscous grid. All these variations of the basic grid yielded nearly

the same values for the skin friction coefficient on the entire blade

surface as the basic grid; any variations were within ±2%. The results

presented here correspond to the basic grid shown in Fig. 1.

3 NASA/CR—2002-211689
subsequent cases, results for this case served as the starting point.

RESULTS and DISCUSSION

Several experimental cases for the PakB blade, available in [1],

were analyzed for comparison. These cases cover three inlet Reynolds

number values, 25000, 50000 and 100000 for a freestream turbulent

intensity of 1%. Most of the data in [1] are for Tu = 1%. Values of

B for which computations were done are 0, 1 and 2. Figure 2 shows

the computed shear stress on the basic blade surface, without any VGJ,

for three values of the inlet Reynolds number. In this figure, the zero

shear stress line is shown for reference. Clearly, the shear stress is

negative beyond the separation point on the suction surface of the

blade. The separation point on the suction surface, corresponding to

τw = 0, is little affected by the Reynolds number; it is at 0.71 Cx for Re

= 50,000 and 100,000, but at 0.73 Cx for Re = 25,000. There appears

to be a small region on the pressure surface as well that has separated

flow for Reynolds numbers ≥ 50,000. The small separated region on

the pressure surface is over 0.22 ≤ x/Cx ≤ 0.25 for Re = 50,000, and

over 0.18 ≤ x/Cx ≤ 0.29 for Re = 100,000. There is no separated

region over the pressure surface for Re = 25,000. The location of

separation point on the suction surface matches very well with the

experimental data [25] for Reynolds numbers of 50,000 or less. Bons

et al. [1] give no indication whether they observed any separated

region over the pressure surface.

We may note that the boundary layer over the entire blade is

laminar, as evidenced in Fig. 3. This figure shows the dimensionless

turbulent viscosity, μt, within a narrow range from 0 to 1.0 in the flow

field for Re = 50,000 and B = 0 and 1. Noting that the dimensionless

laminar viscosity, μ , is nearly unity (dimensionless local temperature

is near unity), it is clear that the effective viscosity within the entire

boundary layer over the blade surface is essentially laminar. We may

note the presence of separation on the suction surface in Fig. 3(a),

while with the VGJs turned on, the flow gets attached (cf. Fig. 3(b)).

Similar results were obtained for Re of 25,000 and 100,000.

Figure 4 shows the velocity vectors, colored by static pressure, in

the flow field around the blade for inlet Reynolds number of 50,000,

and for B = 0 and 1. The thick separated region, with reverse flow, is

clearly visible in Fig. 4(a) for the uncontrolled blade, while there is

almost no separation on the suction surface for the controlled blade

(Fig. 4(b)) with B = 1. On the pressure surface, the velocity profiles

appear to be close to separation over a very small region, as discussed

above regarding the results in Fig. 2. Similar results were obtained for

Re of 25,000 and 100,000.

Figure 5 compares the present computations with the experimental

data [1] for the pressure coefficient on the baseline blade at two inlet

Bons et al. [1] to be unsteady in the region y < 3mm. That is why the

experimental data fall into a wide band in the near-wall region. At

73% and 79% axial chord, the flow is separated, with the computations

clearly showing reverse flow. For the experimental data, reverse flow

direction could not be resolved [1] since a single hot-film probe was

used. However, separate smoke visualization did confirm that flow

reversal was present inside the separation bubble at the 73% axial

chord measurement station. The comparison between the computed

and experimental data is not very good, specially at 79% axial chord

location, where the experimental data show much thicker boundary

layer compared to the computations. This implies that the separated

region is not well resolved by the computations.

A similar comparison is shown in Fig. 7 for inlet Reynolds

number = 100,000 and B = 0. Clearly at this high Reynolds number,

the boundary layer is thinner compared to that in Fig. 6. However, the

experimental data show a thinner boundary layer compared to that

from the computations at all three chordwise locations. While the

computations show separated (reverse) flow at both 73% and 79%

axial chord locations, Bons et al. [1] report that the flow was close to

separation at the 79% axial chord location but attached at the 73%

axial chord location. Figure 8 compares the computed velocity profiles

in the wake at 0.62 axial chord downstream from the blade trailing

edge for two inlet Reynolds numbers against the experimental data of

Bons et al. [1] with no VGJ. While the computations show little effect

of Re on the wake width and relatively small effect on the wake depth,

the experimental data show a larger effect of Re on both the wake

width and depth. At Re = 50,000, the computed and experimental

wake widths match but the computed wake depth is only about half of

the experimental value. At Re = 100,000, the computed wake depth

compares well with the experimental value but the computed wake

width is about twice that of the experimental value. Such problems

with computed wakes are well known, and point to the need for more

work in this area. Moreover, in the present case, these problems are

augmented by the large separation region over the suction surface of

the blade. Any unsteady effects owing to the flow separation and

wake shedding cannot be resolved by the steady code that was used for

the present computations.

Figure 9 shows a comparison between the presently computed loss

coefficient, γ, and the experimental values provided by Bons et al.

[10]. While the experimental data show a sudden drop in loss

coefficient around Re = 50,000, the computations show only a gradual

decrease in the loss coefficient from Re = 25,000 to 100,000. This is

again a reflection of the poor wake prediction noted above. Figure 10

compares the computed boundary layer profiles over the blade suction

surface at three chordwise locations with the experimental data from

Bons et al. [1] for Re = 50,000 and B = 2. Both the computations and

experiment show no separation (reverse flow). However, the

4 NASA/CR—2002-211689
VGJs on (B ≠ 0) is shallower and somewhat narrower than that without

any VGJ (B = 0), as one would expect since the separation region

vanishes when VGJs are on. However, the effect is not so dramatic,

specially for the wake width, as for the experimental data.

Experimentally the wake is very narrow when the VGJs are on

compared to the case when they are not. The wake depth recovery,

ratio of the wake depth for B ≠ 0 to that for B = 0, is about the same

for both the computational and experimental data. Also, there is little

difference between the profiles corresponding to B = 1 and B = 2 for

both the computational and experimental data.

CONCLUSIONS

The Glenn-HT code was used to compute the flow over a lowpressure turbine blade at very low Reynolds numbers with and without

the use of vortex generator jets. The results are compared with the

experimental data of Bons et al. [1] for steady VGJs. It is found that

the code determines the proper location of the separation point on the

suction surface of the baseline blade (without any VGJ) for Reynolds

numbers of 50,000 or less. Also, the code finds that the separated

region on the suction surface of the blade vanishes with the use of

VGJs. However, the separated region and the wake characteristics are

not well predicted. The wake width is generally over-predicted while

the wake depth is under-predicted. Thus, there is a need to improve

the prediction of wake characteristics, especially in situations where

large separated regions may exist upstream of the wake, as in the

present case. For resolution of the unsteady effects due to flow

separation and wake shedding, use of an unsteady code is

recommended.

REFERENCES

1. Bons, J.P., Sondergaard, R. and Rivir, R.B., 1999, Control of

Low-Pressure Turbine Separation Using Vortex Generator Jets,

AIAA Paper 99-0367.

2. Pearcey, H.H., 1961, Shock Induced Separation and its

Prevention, Boundary Layer & Flow Control, vol. 2, (Ed.) G.V.

Lachmann, Pergamon, NY, pp. 1170-1344.

3. Wallis, R.A., 1952, The Use of Air Jets for Boundary Layer

Control, Aerodynamics Research Laboratories, Australia, Aero

Note 110 (N-34736).

4. Wallis, R.A., 1960, A Preliminary Note on a Modified Type of

Air Jet for Boundary Layer Control, Aeronautical Research

Council, Australia, Current Paper No. 513.

Layer, AIAA J., vol. 30, pp. 640-647.

10. Bons, J.P., Sondergaard, R. and Rivir, R.B., 2001, The Fluid

Dynamics of LPT Blade Separation Control Using Pulsed Jets,

ASME Paper 2001-GT-190.

11. Steinthorsson, E., Ameri, A.A. and Rigby, D.L., 1997,

TRAF3D.MB A Multi-Block Flow Solver for Turbomachinery

Flows, AIAA Paper 97-0996.

12. Jameson, A., Schmidt, W. and Turkel, E., 1981, Numerical

Solutions of the Euler Equations by Finite Volume Methods

Using Runge-Kutta Time-Stepping Schemes, AIAA Paper 81-

1259.

13. Wilcox, D.C., 1988, Reassessment of the Scale-Determining

Equation for Advanced Turbulence Models, AIAA J., vol. 26, pp.

1299-1310.

14. Menter, F.R., 1994, Two-Equation Eddy-Viscosity Turbulence

Models for Engineering Applications, AIAA J., vol. 32, pp. 1598-

1605.

15. Wilcox, D.C., 1998, Turbulence Modeling for CFD, DCW

Industries, 2nd Edn.

16. Garg, V.K. and Ameri, A.A., 2001, Two-Equation Turbulence

Models for Prediction of Heat Transfer on a Transonic Turbine

Blade, Int. J. Heat & Fluid Flow, vol. 22, pp. 593-602.

17. Jones, W.P. and Launder, B.E., 1973, The Calculation of

Low-Reynolds-Number Phenomena with a Two Equation Model

of Turbulence, Int. J. Heat Mass Transfer, vol. 16, pp. 1119-1130.

18. Schlichting, H., 1979, Boundary Layer Theory, McGraw-Hill,

New York, 7th edition, pp. 312-313.

19. Menter, F.R., 1992, Improved Two-Equation k-ω Turbulence

Models for Aerodynamic Flows, NASA TM-103975.

20. Chima, R.V., 1996, A k-ω Turbulence Model for Quasi-ThreeDimensional Turbomachinery Flows, AIAA Paper 96-0248.

21. Garg, V.K. and Gaugler, R.E., 1997, Effect of Velocity and

Temperature Distribution at the Hole Exit on Film Cooling of

Turbine Blades, J. Turbomachinery, vol. 119, pp. 343-351.

22. Boyle, R.J. and Giel, P., 1992, Three-Dimensional Navier Stokes

Heat Transfer Predictions for Turbine Blade Rows, AIAA Paper

92-3068.

23. Program Development Corporation, 1997, "GridProTM/az3000 -

User’s Guide and Reference Manual," White Plains, NY.

24. Rigby, D.L., Steinthorsson, E. and Coirier, W.J., 1997, Automatic

Block Merging Using the Method of Weakest Descent, AIAA

Paper 97-0197.

25. Rivir, R.B., 2001, private communication.

5 NASA/CR—2002-211689
-25

0

255075

1.0 0.8 0.6 0.4 0.2 0

Re=100000Re=50000Re=25000

pressure

suction

x/cx

τ

w

Fig. 2 Computed shear stress on the blade surface at various inlet Reynolds numbers (Tu = 1%; B = 0)

(a)

Fig. 3 Dimensionless turbulent viscosity within 0  Re = 50,000; Tu = 1%. (a) B = 0; (b) B = 1.

Fig. 4 Computed velocity vectors, colored by static pressure, a

 (a) B = 0; (b) B = 1.

(a)

periodicboundary

periodicboundary

periodicboundary

012345

1.0 0.8 0.6 0.4 0.2 0

expt, Re=50000expt, Re=100000comp, Re=50000comp, Re=100000

x/cx

C

p

Fig. 5 Co ba nu

Fig. 1 Spanwise section of the multi−block viscous grid around the blade, with detail of grid over the blade span near

 and within the hole exits

0.91.0

p/po

6 NASA/CR—2002-211689
0

-0.2 0.2 0.6 1.0

u/mid-channel velocity

Fig. 6 Comparison of boundary layer profiles of streamline velocity

 normalized by mid−channel velocity at three chordwise stations:

 0.67, 0.73 and 0.79 axial chord on the suction side.

 Re = 50,000; Tu = 1%; B = 0

0

1.5

1.0

0.5

-0.2 0.2 0.6 1.0

expt 0.79

expt 0.73

expt 0.67

comp 0.79

comp 0.73

comp 0.67

u/mid-channel velocity

y (cm)

Fig. 7 Comparison of boundary layer profiles of streamline velocity

 normalized by mid−channel velocity at three chordwise stations:

 0.67, 0.73 and 0.79 axial chord on the suction side.

 Re = 100,000; Tu = 1%; B = 0

1.05

1.00

0.95

0.90

0.85

0.80

3.4 3.8

expt, Re=100000

comp, Re=100000

expt, Re=50000

comp, Re=50000

4.2 4.4

y/blade spacing

streamwise velocity/mid-channel velocity

Fig. 8 Comparison of wake velocity profile at 0.62 axial chord downstream

 from the blade trailing edge for two inlet Reynolds numbers. Tu = 1%

 and B = 0

0

0 0.4x105 0.8x105 1.2x105

Rein

Fig. 9 Comparison of loss coefficient vs. inlet Reynolds number for Tu = 1%

0

1.5

1.0

0.5

0 0.3 0.6 0.9 1.2

expt 0.79

expt 0.73

expt 0.67

comp 0.79

comp 0.73

comp 0.67

u/mid-channel velocity

y (cm)

Fig. 10 Comparison of boundary layer profiles of streamline velocity

 normalized by mid−channel velocity at three chordwise stations:

 0.67, 0.73 and 0.79 axial chord on the suction side.

 Re = 50,000; Tu = 1%; B = 2

1.05

1.00

0.95

0.90

0.85

0.80

3.4 3.8 4.2

expt, B=2

comp, B=2

expt, B=1

comp, B=1

expt, B=0

comp, B=0

4.4

y/blade spacing

streamwise velocity/mid-channel velocity

Fig. 11 Comparison of wake velocity profile at 0.62 axial chord downstream

 from the blade trailing edge for Re = 50,000; Tu = 1%; B = 0, 1, 2

7 NASA/CR—2002-211689
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13

Vijay K. Garg

Low-pressure turbine; Separation control; Vortex generator jets

Unclassified -Unlimited

Subject Categories: 07 and 34 Distribution: Nonstandard

University of Toledo

Toledo, Ohio 43606

Vijay K. Garg, University of Toledo, Toledo, Ohio and NASA Resident Research Associate at Glenn Research Center.

Prepared for the Turbo Expo 2002 cosponsored by the American Society of Mechanical Engineers and the International

Gas Turbine Institute, Amsterdam, The Netherlands, June 3–6, 2002. Project Manger, R.E. Gaugler, Turbomachinery and

Propulsion Systems Division, NASA Glenn Research Center, organization code 5820, 216–433–5882.

The present work details a computational study, using the Glenn HT code, that analyzes the use of vortex generator jets

(VGJs) to control separation on a low-pressure turbine (LPT) blade at low Reynolds numbers. The computational results

are also compared with the experimental data for steady VGJs. It is found that the code determines the proper location of

the separation point on the suction surface of the baseline blade (without any VGJ) for Reynolds numbers of 50,000 or

less. Also, the code finds that the separated region on the suction surface of the blade vanishes with the use of VGJs.

However, the separated region and the wake characteristics are not well predicted. The wake width is generally

over-predicted while the wake depth is under-predicted.