17th Annual AeSI CFD Symposium, 11th -12th August, 2015, Bangalore, India
Flow simulation around a helicopter
Konark Arora, K. Anandhanarayanan, R. Krishnamurthy and Debasis Chakraborty
Scientists, DOCD, DRDL, Hyderabad.
Email: konark.arora@gmail.com
Abstract: Numerical simulations have been performed to predict the flow field around the helicopter. In house
developed GEANS (Grid-free Euler and Navier Stokes) solver has been used to predict the pressure distribution and
forces on the fuselage of the NASA ROBIN geometry. The point distribution for the meshless solver has been
obtained from the unstructured grid generated around the ROBIN geometry. Comparison of the present results with
the experimental results and other CFD simulation results is presented. The results compare well with the experimental
results in the region of unseparated flows where the inviscid computations are valid.
Keywords: Helicopter, meshless, inviscid, validation, low speed
1. Introduction
CFD has been extensively used for simulating the flow field around the fixed winged aircrafts to predict the
aerodynamic characteristics. On the other hand, simulating the flow field around the rotary winged aircraft poses a
great challenge to CFD. Fixed wing aircrafts have a simple and stream lined structure as compared to rotary winged
aircrafts, which have a complex geometry with blunt edges that are very conducive to flow separation. Thus, viscous
simulations need to be performed in order to capture flow separation and predict the aerodynamic forces and moments
on the rotary winged aircrafts. In rotary winged aircrafts, unsteady flow prevails even for steady state flight conditions,
thus necessitating unsteady simulations to be performed for predicting various time dependent flow features. The
rotary winged aircrafts fly by pushing the air down through the rotor, impinging it on the fuselage. This is associated
with a strong vortical shedding from the blades of the rotor leading to massive flow separation regions over the
fuselage of the rotary winged aircrafts. The separated flow impinges on the tail rotor and other control surfaces. Even
in hover flight, the induced flow from the main rotor is a predominant factor, but as the forward air speed increases,
the unsteady separated flow from the fuselage influences the flow field around the helicopter. Thus it can also be said
that the rotary winged aircrafts fly in their own wake, which leads to severe complications in simulating the flow field
around them.
Accurate prediction of the forces, flow and its various features are extremely important for the design of the
rotary winged aircrafts from the point of view of its speed, performance, stealth and acoustic features desired by the
user. Apart from this, the large sized flexible wings and a number of moving parts in the helicopter not only cause
severe aeroelastic effects on the rotary winged aircrafts but also create large vibrations by aerodynamically induced
stresses leading to severe fatigue failure problems for these aircrafts. The flow through the main rotor may cause
changes in the vortex shedding, hence affecting the vibratory excitation and response of the helicopter rotor blades.
Several studies have been performed on the isolated rotor and fuselage of the rotary winged aircrafts [1,2,3,4]. Efforts
have also been made to predict the effect of the rotor field on the fuselage field by importing the rotor wake solution
on the isolated fuselage solution [5]. But it is not possible to predict the non linear effects of actual rotor wake fuselage
interaction by this method. Various experiments and numerical simulations have been performed on the NASA Rotor
Body Interaction (ROBIN) geometry by the researchers to predict the rotor fuselage interaction [6]. Mohagna et. al. [7]
have used the unstructured grid approach to simulate and predict the flows about the ROBIN geometry using inviscid
techniques. The pressure coefficients predicted by them showed a good match with the experimental results in the
unseparated regions of flow.
The scope of the current work is limited to prediction of the inviscid flow features and forces on the fuselage
of the ROBIN geometry without modeling the rotor blades. In-house developed meshless solver, GEANS (Grid free
Euler and Navier Stokes) [8] in the inviscid mode has been used to predict the flow field around the NASA ROBIN
geometry to demonstrate its ability to capture the various flow features in the unseparated regions of flow around the
rotary winged aircrafts. A brief description of the NASA ROBIN geometry and the meshless GEANS solver is given
followed by the results of validation of the meshless code for the rotary winged aircraft.
2. ROBIN Body
Rotor Body Interaction (ROBIN) fuselage geometry has been used to validate the predictive capability of the
in-house developed meshless solver. ROBIN rotorcraft fuselage geometry has been extensively tested in the wind
tunnels. A large number of experiments and computational studies have been performed on the ROBIN geometry for
predicting the rotor fuselage interaction effects. The ROBIN shape is mathematically derived from super-ellipse
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equation. For a given fuselage station of X, the cross-section (Y & Z) are defined by height (H), width (W), camber
line (Zo) and elliptic power (N) [9]. The super ellipse is defined by the elliptic equation:
 x  xo   y  yo 

 
 C
 A   B 
n
m
The above equation has been used to construct various sections of the ROBIN body by a computer program given in
the above reference. The ROBIN geometry is shown in Fig. 1.
Fig. 1 Robin Geometry
Fig. 2 Pressure taps along the fuselage of the ROBIN geometry.
3. Meshless solver and point generation
The grid free viscous solver GEANS has been used to simulate the inviscid flow field around the ROBIN
geometry. This solver operates on an arbitrary point distribution around the flight vehicle configuration. Second order
spatial accuracy (using entropy variables and defect correction approach) along with Barth’s min-max limiter is used
for simulation. Unstructured grids are generated around the ROBIN geometry and a preprocessor is used to generate
the data structure for the meshless solver [10]. This preprocessor uses the edge based data structure of the unstructured
grids to determine the connectivity points in the domain. The total number of points generated in the computational
domain around the ROBIN geometry is 374675.
4. Results and Discussion
The wind tunnel test was performed on the ROBIN geometry with 3.15 m diameter four bladed articulated rotors. The
pressure data for the experiment was collected without the rotor system. The wind tunnel data was acquired at a Mach
number of 0.062 and an effective Reynolds number of 4.46*10 6 [9]. However the simulations using the PUMA code
[9] is available in literature at Mach 0.30 at angles of attack 0o and -5o. The GEANS in inviscid mode has been applied
for the same flow conditions. The pressure taps located along the fuselage of the ROBIN geometry are shown in the
Fig. 2 and the pressure data was gathered at these locations. Since the flow simulations have been performed at a low
Mach number of 0.3 and without the use of a preconditioner, it is necessary to determine the convergence of the results
of the simulation. Fig. 3 shows the plot of the variation of L norm of the residue with iterations while the Fig. 4
shows the plot of the variation of side force with iterations. It is observed that variation of both the residue and the side
forces converge with iterations. Figs. 5 and 6 show the coefficient of pressure (Cp) contours along the length of the
ROBIN geometry obtained using the PUMA code and meshless GEANS code respectively. Qualitatively, a good
match has been obtained between the Cp contours obtained from both the codes. Fig. 7 shows the Mach contours
obtained over the nose region of the ROBIN geometry. Fig. 8 shows the streamlines over the ROBIN geometry using
Euler meshless code. The surface streamlines are observed to be parallel to each other. As expected, the Euler
computations are unable to capture the regions of separation over the fuselage of the ROBIN geometry.
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Fig. 3 Convergence history
Fig. 4 Convergence history of side force
Fig. 5 Cp contours along the length of ROBIN geometry using PUMA Code
Fig. 6 Cp contours along the length of ROBIN geometry using GEANS Meshless code
Figs. 9 (a-f) show the comparison of the Cp plot at various axial locations on the ROBIN geometry (Fig. 2) obtained
by experiments, PUMA code and Euler version of meshless GEANS code. It is observed that a very good match has
been obtained between the experiments and Euler computations of PUMA and GEANS code in the regions of
unseparated flow. However, the regions of separation exist beyond the axial location X/R=1.0008. It is observed that
in these regions of separated flow (Figs. 9 (d-f)), the results of the Euler computations of both PUMA and GEANS
code deviate from the experimental results. However, there is still a good match between the results of the two codes
even in the regions of the separated flows.
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Fig 7. Mach contours over nose of
Fig. 8 Stream lines over ROBIN geometry using meshless code
ROBIN geometry using meshless code
(a)
(b)
(c)
(d)
(e)
(f)
Fig. 9 Comparison of the Cp variation at various axial locations on the ROBIN geometry obtained from
experiments, PUMA code and meshless GEANS code.
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5. Conclusions
The inhouse developed meshless code has been used to simulate inviscid flow field around the ROBIN
geometry. The point distribution for the meshless solver was generated using the edge based data structure of the
unstructured grid for the ROBIN geometry. A good match has been obtained between the experimental results and the
Euler simulations of PUMA and GEANS code in the regions of unseparated flows. As expected, the regions of
separation over the fuselage geometry have not been captured by the inviscid flow simulations. Hence viscous
simulations need to be performed to capture the regions of separation over the ROBIN geometry and predict the
various flow features in these regions. Preconditioner needs to be implemented in the code to enable efficient flow
simulation at extremely low Mach numbers at which the rotary winged aircrafts operate.
Acknowledgment
The authors express their sincere gratitude to Director, DRDL for the continuous support, encouragement and
help provided during the course of this work.
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