Unsteady, Turbulent, Separated Flow Around Helicopter Fuselages

mustardarchaeologistMechanics

Feb 22, 2014 (2 years and 9 months ago)

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Project Number : PS 3.1

Unsteady, Turbulent, Separated Flow

Around Helicopter Fuselages

PI:


Prof. Lyle N. Long


tel : (814) 865
-
1172


Email: lnl@psu.edu


Web: http://www.personal.psu.edu/lnl/



Graduate Student:


Emre Alpman (PhD 2005)







2005 RCOE Program Review

May 3, 2005

Bell 214

Comanche

Technical Barriers

European Helifuse
investigation found that
turbulence models such as k
-

,
k
-

, Baldwin
-
Lomax were not
able to accurately predict lift
and drag on complex helicopter
geometries.


RANS
-
based CFD methods
cannot accurately predict the
unsteady turbulent flow around
rotorcraft fuselages.

Objectives:


Develop better numerical methods for flow around helicopter fuselages and for
drag prediction

Approach:


Unstructured grid CFD methods on inexpensive parallel computers


Validate code on simple shapes such as spheres and ellipsoids


Make detailed comparisons between experimental data and numerical predictions
for flow around helicopter fuselages

Expected Research Results or Products:



Better numerical algorithms and understanding of unsteady separated flows


Efficient parallel CFD codes

Very
Complex
Geometries

PUMA2 Flow Solver


Finite volume ANSI C++ parallel program


Message Passing Interface (MPI) used for inter
-
processor

communication


Unstructured grids to handle very complex geometries


Runge
-
Kutta for time
-
accurate runs


SSOR for steady
-
state runs


Turbulence:



Large Eddy Simulation (LES) with wall function



Reynolds Stress Model (RSM)


Runs on any Beowulf cluster or parallel computer

Turbulence Models

Approximate

Equations

Exact

Equations

DNS

Time

Average

Unsteady,

Spatially

Filter

LES

Use

Boussinesq

assumption

Do not use

Boussinesq

Reynolds Stress

Model

(7 new PDE’s)

Algebraic

Models

(e.g. Baldwin
-

Lomax)

1 Equation

Models

(Spalart
-

Allmaras)

2 Equation

Models

(K
-


& K
-

)

More

Physics

Less

CPU

Time

These are about as good as they are going to get
--
and they are not good enough for rotorcraft !!

DES

combines


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Reynolds
Transport
Equations

& RSM

Model

Exact

Modelled

12 nonlinear coupled PDE’s:

-

6
Re Stress

eqtns

-

1 Turb. Dissipation eqtn

-

5 Navier
-
Stokes Equations

Launder, B. E., Reece, G. J., Rodi W., Journal
of Fluid Mechanics, vol.68, part 3, 1975.

Wilcox, D. C., "Turbulence Modeling for
CFD", DCW Industries Inc.

RSM Solution for a 6:1 Prolate
Spheroid


Re = 6.5x10
6


M = 0.1322


α

= 30
°


Turbulence intensity: 0.03%


Grid is composed of 5.1
million tetrahedral cells


Solution took 7 days on 30
2.4 GHz Xeon processors

6:1 Prolate Spheroid (RSM)

Lateral Skin Friction Comparison at x/L = 0.738
Re = 6.5x10
6
, M = 0.1322,

= 30 deg
-0.0020
-0.0015
-0.0010
-0.0005
0.0000
0.0005
0.0010
0.0015
0.0020
0.0025
0.0030
90
100
110
120
130
140
150
160
170
180

[deg]
C
f
lat
Experiment
RSM Solution

Qualitative agreement
with experiment


Experimental data also
contain some uncertainties

Alpman, E., and Long, L. N., AIAA Paper 2005
-
1094, 2005

Experiment:

Kreplin, H. P., Volmers H., Meier H. U., DFVLR Rept, IB 222
-
84 A 33, 1985.

6:1 Prolate Spheroid (RSM)

RSM Solution

Measurement

Circumferential Location of Primary
Separation [degrees]

~ 105

~ 108

Circumferential Location of Secondary
Separation [degrees]

~ 159

~ 156



Vorticity contours with surface


skin friction lines




Asymptotic convergence of skin


friction lines means separation



At the upper lee side of the body


a second separation line is also


observed

RSM Solution for a 6:1 Sphere


Re = 1.14x10
6


M = 0.1763


Turbulence intensity:
0.45%


Grid is composed of 3.8
million tetrahedral cells


Solution took 6 days on
30 2.4 GHz Xeon
processors


RSM Solution & Experiment Sphere


Re = 1.14x10
6
M = 0.1763

Circumferential Pressure Distribution of a Sphere
Re = 1.14x10
6
-1.50
-1.00
-0.50
0.00
0.50
1.00
1.50
0
20
40
60
80
100
120
140
160
180

[deg]
Cp
Experiment
RSM
Midplane Skin Friction Coefficient Distribution
Re = 1.14x10
6
, M = 0.1763
-1.00
-0.50
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
0.00
30.00
60.00
90.00
120.00
150.00
180.00

[deg]
Cf*sqrt(Re)
Experiment
RSM Solution
Achenbach, E.,
Journal of Fluid Mechanics
, Vol. 54, No. 3, 1972, pp. 565


575.

Alpman, E., and Long, L. N., AIAA Paper 2005
-
1094, January, 2005

Sphere


Re = 1.14x10
6
M = 0.1763

Normalized τ
xx

contours

Normalized τ
xz

contours



In isotropic turbulence, normalized τ
xx

and τ
xz

take the values of 2/3 and 0


respectively



Flow is highly anisotropic



Anisotropic models (e.g. RSM) necessary for 3
-
D separated flows

Sphere Drag Prediction


Re = 1.14x10
6
M = 0.1763


Cd

Experiment

(Achenbach, JFM 1972)

0.13
±

0.01

LES

(Jindal & Long, 2004)

0.141

RSM

(Alpman & Long, 2005)

0.141

RSM Solution for a Bell 214ST
Fuselage


Re = 1.5x10
6
per ft


M = 0.3322


α

=
-
2.28
°
,
ψ
=0
°

(low angle of attack cruise condition)


α

= 17.04
°
,
ψ
=0
°

(high angle of attack condition)


α

=
-
1.6
°
,
ψ
=16.4
°

(high yaw angle condition)


α

=
-
2.28
°
,
ψ
=0
°

(low angle of attack cruise condition with rotors
modeled using momentum theory with linear loading)


Turbulence intensity: 1%


Grid is composed of 2.9 million tetrahedral cells


Solution took 7 days on 30 2.4 GHz Xeon processors

Computational Mesh

BELL 214ST

y+ ~ 40

Low Angle of attack Cruise Condition
Re = 1.5x10
6
per ft M = 0.3322 (without rotors)

Dorsal Centerline Pressure Distribution
Re = 1.5x10
6
ft
-1
, M = 0.2322,

= -2.28 deg.,

= 0 deg.
-1.50
-1.00
-0.50
0.00
0.50
1.00
1.50
0
2
4
6
8
10
12
14
x (m)
Cp
RSM Solution
Experimental Data
Surface Pressure Distribution

Good agreement with the measurements
.

Alpman, E., and Long, L. N., AHS International 61st Annual Forum and Display, June, 2005

Experiment
: Oldenbuttel, R. H., Report No. LSWT 554, Vought Corporation, 1978.

High Angle of Attack and High Yaw
Angle Conditions (without rotors)

Dorsal Centerline Pressure Distribution
Re = 1.5x10
6
ft
-1
, M = 0.2322,

= -17.0 deg.,

= 0 deg.
-2.00
-1.50
-1.00
-0.50
0.00
0.50
1.00
0
2
4
6
8
10
12
14
x (m)
Cp
RSM Solution
Experimental Data
High Angle of Attack Condition

High Yaw Angle Condition

Dorsal Centerline Pressure Distribution
Re = 1.5x10
6
ft
-1
, M = 0.2322,

= -1.6 deg.,

= 16.4 deg.
-1.50
-1.00
-0.50
0.00
0.50
1.00
1.50
0
2
4
6
8
10
12
14
x (m)
Cp
RSM Solution
Experimental Data
Good agreement even when the
expansions are quite abrupt

Good agreement with the measurements

except around the tail boom
.

Mainly due to differences between wind
tunnel and computational geometry

High Angle of Attack Condition

Normalized
τ
xz

contours

Computed Using RSM

Normalized
τ
xz

contours

Computed Using Boussinesq Hypothesis during post
processing

Reynolds stresses and mean strain rates are grossly misaligned.

Turbulence models based on the Boussinesq approximation might

perform poorly for this flow and warrants the use of RSM.

Simulation with Main and Tail Rotors

Vertical velocity contours

without rotors

Vertical velocity contours

T = 17500 lbs., Ttr = 1104 lbs



Induced downwash velocities



Tip vortices at the edge of rotor plane

Simulation with Main and Tail Rotors

Normalized
τ
yz

contours

without rotors

Normalized
τ
yz

contours

T = 17500 lbs., T
tr

= 1104 lbs


Vortices generated by the main rotor affects downstream
turbulence structure

Bell 214ST Total Drag Predictions


Re = 1.5x10
6
per ft M = 0.3322 (without rotors)



=
-
2.28 and


= 0



D/q (ft
2
)

% Error

Wind Tunnel Data

(
Oldenbuttel,1978)

4.596

?

LES prediction

(Souliez & Long, 2002)

6.225

35.4

RSM Simulation

(Alpman & Long, 2005)

5.405

17.6

RSM Simulation (with rotors)

(total drag)

5.547

N/A

Bell 214ST Drag Predictions

Re = 1.5x10
6
per ft M = 0.3322 (without rotors)



=
-
2.28 and


= 0



D/q
(ft
2
)

%
Err
or

Wind Tunnel Data

(
Oldenbuttel,1978)

(total drag)

4.596

?

Bell Simulations

(Narramore et.al. 1992) (pressure
drag)

5.466

18.9

RSM Simulation

(pressure drag)

4.356

5.22

RSM Simulation

(total drag)

5.405

17.6

90% of

Total

Drag

RANS

Solution

Inaccurate

Bell 214ST Drag Predictions

Re = 1.5x10
6
per ft M = 0.3322 (without rotors)

D/q (ft
2
)

% Error

wind tunnel data

(
Oldenbuttel,1978)
(total drag)

6.521

?

RSM Simulation

(total drag)

7.159

9.7

D/q (ft
2
)

% Error

wind tunnel data

(
Oldenbuttel,1978)
(total drag)

15.058

?

RSM Simulation

(total drag)

12.886

14.4



= 17 and


= 0



=
-
1.6 and


= 16.4

Accomplishments


CY 2002 Accomplishments:


Drag of Bell 214 compared to experiment


Unsteady tail loadings predicted on Bell 214 ST


Steady Comanche fan
-
in
-
fin simulations compared to experiment


CY 2003 Accomplishments


Comanche Fan
-
in
-
fin Simulations: Unsteady, rapid maneuvers


LES Wall function implemented on unstructured grids


RSM implemented on unstructured grids


LES & RSM Sphere Simulations:


LES & RSM Ellipsoid simulations:


CY 2004 Accomplishments


Detailed comparisons between LES & RSM


Bell 214ST RSM & LES simulations


French fuselage simulations ?

Tasks

2001

2002

2004

2005

Completed

Short Term

Long Term

2003

Comparisons to experimental data


-

Cone & 3
-
D Cylinder

Generic Fuselage Simulations


-

Robin Body w & w/o NLDE

R. Hansen Ph.D. Thesis


Bell 214ST grid & steady solution

Unsteady loads and drag

F. Souliez Ph.D. Thesis


Grid and viscous flow over ellipsoid

Re
-
Stress Model for turbulent flow
over ellipsoid

S. Jindal M.S. Thesis


Steady/unsteady Comanche flows

Detailed compare of RSM & LES

Re
-
Stress Model & LES for Bell 214

Helicopter drag and unsteady flows

E. Alpman Ph.D. Thesis





Schedule / Milestones





Publications & Theses


2005:


Alpman, Long, “Separated Flow Simulations,” AIAA
-
2005
-
1094, January, 2005


Alpman Long, “Bell 214ST RSM Simulations”, AHS Annual Forum, June 2005.


Lee, Sezer
-
Uzol, Horn, and Long, “Ship Airwakes,” Jnl of Aircraft, 2005


Sezer
-
Uzol, PhD Thesis, 2005


Alpman, PhD Thesis, 2005


2004:


Corfeld, Strawn, and Long, “Martian Rotor,” AHS Journal, 2004


Jindal, Long, Plassmann, and Sezer
-
Uzol, “LES,” AIAA 2004
-
2228, 2004


Modi, Sezer
-
Uzol, Long, Plassmann, “Visualization,” Jnl of Aircraft, 2004


Alpman, Long, and Kothmann, “Comanche (steady),” Jnl. of Aircraft, 2004


Alpman, Long, and Kothmann, “Comanche (unsteady),” Jnl. of Aircraft, 2004


Jindal, MS Thesis, 2004

Publications & Theses (cont.)


2003
:


Alpman, Long, and Kothmann, “Comanche,” AHS Forum, 2003


Lee, Sezer
-
Uzol, Horn, and Long, “Ship Airwakes,” AHS Forum, 2003


Alpman and Long, “Comanche,” AIAA
-
2003
-
4231, CFD Conf., June, 2003.


2002
:


Souliez, Long, Sharma, and Morris,
Intl. Jnl. of Aeroacoustics
,


Corfeld, Long and Strawn, AIAA Paper, St. Louis Mtg., June, 2002


Souliez, Long, Morris, and Sharma, AIAA 2002
-
0799, Reno, Jan., 2002


Hansen and Long, AIAA 2002
-
0982, Reno, Jan., 2002


Fred Souliez, Ph.D. Thesis (Unsteady CFD for Helicopter Fuselages) (at BMW)


Anirudh Modi, Ph.D. Thesis (Computational Steering and Wake Vortices) (at Intel)


Kelly Corfeld, M.S. Thesis (CFD for Martian Rotorcraft) (at Lockheed)


2001
:


L. Long, P. Plassmann, and A. Modi, “Airport Capacity,” London, Sept., 2001


Long and Modi, NCSA Linux Revolution Conference, Illinois, June, 2001.


LTC Bob Hansen, Ph.D. Thesis (Unsteady CFD using unstructured grids)


Nilay Sezer
-
Uzol, M.S. Thesis (CFD simulations of rotors)


Anupam Sharma, M.S. Thesis (ship airwake simulations)


Technology Transfer:


Worked with Bruce Kothmann at Boeing Helicopter on Comanche fan
-
in
-
fin


Got Bell 214ST data from Jim Narramore


Working with Georgia Tech (joint DARPA project)


Very good relationship with West Point (USMA)


Graduate student (Kelly Corfeld) was in Co
-
op program with NASA Ames
Rotorcraft worked on Martian Rotorcraft with Dr. Roger Strawn (she is now at
Lockheed)


Working with Dr. Earl Duque who is using different CFD approaches

Leveraging or Attracting Other
Resources or Programs



DARPA quiet helicopter project (joint Penn State, GATech, & NAU effort)


NSF Center for Particle Methods (Monte Carlo, Molecular Dynamics, & Vortices)


Army DURIP grant for computer hardware



120 processor Beowulf for RCOE center (with Prof. Brentner)


Institute for Computational Science and Engineering (2004), wide
-
spread
financial support across Penn State


Grant from National Renewable Energy Lab for Wind Turbine Aeroacoustics
(with Morris and Brentner)

2005 Recommendations:


The task work is excellent. It is suggested to compare various
turbulence modelings and to contact Langley for Comanche tail
buffett data.


Response:

Have compared LES and RSM for same geometry. Have
also post processed results to see what 2
-
equation model
might yield. With cancellation of Comanche we decided to
focus on Bell 214ST and simple shapes with good
experimental data.