Robert Narducci

The Boeing Company, Philadelphia, Pennsylvania

Richard E. Kreeger

Glenn Research Center, Cleveland, Ohio

Analysis of a Hovering Rotor in Icing Conditions

NASA/TM—2012-217126

January 2012
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Robert Narducci

The Boeing Company, Philadelphia, Pennsylvania

Richard E. Kreeger

Glenn Research Center, Cleveland, Ohio

Analysis of a Hovering Rotor in Icing Conditions

NASA/TM—2012-217126

January 2012

National Aeronautics and

Space Administration

Glenn Research Center

Cleveland, Ohio 44135

Prepared for the

66th Annual Forum and Technology Display (AHS Forum 66)

sponsored by the American Helicopter Society (AHS)

Phoenix, Arizona, May 11–13, 2010
Acknowledgments

This work represents a team effort at The Boeing Company and the authors wish to thank Stanley Orr, Peter Hartman, and Andy 

Peterson for their contributions. The authors would also like to thank Paul Tsao and Colin Bidwell for their support and many 

fruitful discussions. This projected was funded by NASA Contract NNC08CA88C through the NASA Glenn Research Center. 

Available from

NASA Center for Aerospace Information

7115 Standard Drive

Hanover, MD 21076–1320

National Technical Information Service

5301 Shawnee Road

Alexandria, VA 22312

Available electronically at http://www.sti.nasa.gov

Level of Review: This material has been technically reviewed by technical management. 
NASA/TM—2012-217126 1

Analysis of a Hovering Rotor in Icing Conditions

Robert Narducci

The Boeing Company 

Philadelphia, Pennsylvania 19078

Richard E. Kreeger

National Aeronautics and Space Administration

Glenn Research Center

Cleveland, Ohio 44135

Abstract

A high fidelity analysis method is proposed to evaluate the 

ice accumulation and the ensuing rotor performance 

degradation for a helicopter flying through an icing cloud. The 

process uses computational fluid dynamics (CFD) coupled to a 

rotorcraft comprehensive code to establish the aerodynamic 

environment of a trimmed rotor prior to icing. Based on local 

aerodynamic conditions along the rotor span and accounting 

for the azimuthal variation, an ice accumulation analysis using 

NASA’s Lewice3D code is made to establish the ice 

geometry. Degraded rotor performance is quantified by 

repeating the high fidelity rotor analysis with updates which 

account for ice shape and mass. The process is applied on a 

full-scale UH-1H helicopter in hover using data recorded 

during the Helicopter Icing Flight Test Program.

Introduction

Whether a helicopter is used for emergency rescue, military 

missions, or commercial business there are strong desires to 

operate them safely in all climate conditions. Operating 

helicopters in icing conditions is particularly dangerous 

because rotor blades are especially susceptible to ice growth 

due to their small chord. Quick accumulating ice on rotor 

systems leads to increased vibration, rapid loss of lift, and a 

large power increase to sustain flight. Shed ice from spinning 

rotors is common and creates hazardous projectiles. 

Ice protection systems can guard against adverse effects of

ice accumulation. These systems require certification for 

commercial use and qualification for military applications. 

Both involve extensive flight tests which are expensive and 

time consuming. Several icing seasons are usually required to 

cover the boundaries of the flight envelope. Model-scale and 

full-scale laboratory tests assist in the certification or 

qualification, but scaling effects can complicate the 

interpretation of results.

A highly accurate ice accumulation and rotor performance 

degradation prediction system can help in understanding 

rotorcraft behavior and limitations in adverse weather. 

Analytic results can guide flight test planning and add a layer 

of safety during icing trials. Furthermore the system can assist 

in reliably extrapolating model scale testing results to fullscale flight conditions. This could result in less flight tests for 

certification or qualification. 

The approach taken to develop an icing analysis system for 

rotors leverages methods developed for fixed-wing aircraft. 

Bidwell (Ref. 1) coupled ice accretion analysis with 

computational fluid dynamics (CFD) to evaluate ice on a highlift wing configuration. He used Lewice3D (Ref. 2) to evaluate 

droplet trajectories, heat transfer, and ice growth while relying 

on OVERFLOW (Ref. 3) or CFD++ (Ref. 4) for aerodynamic 

analysis. OVERFLOW is well suited for aerodynamic 

assessments of rotorcraft and therefore Bidwell’s approach is a 

natural point of departure for an icing analysis system for 

rotors.

A high-fidelity ice analysis system for helicopters is the 

subject of this paper. The paper begins with an overview of 

the analysis approach and then offers a description of the 

process to generate an aerodynamic solution for a trimmed 

rotor in forward flight. The process to predict ice on the rotor 

blades utilizes information from the rotor flow field and is 

described next. Analysis of the iced rotor concludes the rotor 

icing analysis process. The process is described for a 

helicopter in forward flight but is applied to a hover situation 

which represents the first step in validating the method. 

Following the results of the hover analysis are conclusions.

Analysis Approach

The high fidelity icing analysis approach developed for 

rotor systems follows four basic steps. These are:

• Establish rotor trim and clean rotor performance and the 

initial flow field environment using CFD or coupled 

CFD/CSD as appropriate;

• Extract representative 2D airfoil conditions for blade 

sections at radial and azimuthal locations;

• Predict ice buildup on the rotor accounting for the 

diverse operating environment of the rotor;

• Reestablish rotor performance for the iced blades. 

The approach is appropriate to address ice accumulation on 

rotors for all flight regimes from hover to high-speed forward 

flight. The process is shown pictorially in Figure 1.
NASA/TM—2012-217126 2

Figure 1.—High-fidelity ice accretion and performance 

degradation methodology.

Figure 2.—CFD/CSD coupling process.

The process begins with a CFD or coupled CFD/CSD 

(computational structural dynamics) analysis of the rotor in 

flight. In this scenario, atmospheric conditions of the icing 

event are modeled with the exception of water drops. Rotor 

performance for clean blades is obtained and serves as the 

baseline with which to compare iced rotor performance. The 

numerical solution provides flow details including pressure 

distributions and air loads that are useful for the ice accretion 

analysis. Coupling CFD with CSD means that the blade 

response to air loads (flapping, lead-lag motion, and 

aeroelastic bending) is represented in the solution and that 

control settings are trimmed to provide a balanced rotor. It is 

not always necessary to couple CFD with CSD for stiff rotors 

and prescribed controls or for rotors in hover. For these cases 

the analysis can be simplified by using a pure CFD solution.

Generally, rotary-wing aeromechanics is inherently 

multidisciplinary, where elastic deflections of the rotor blade 

interact strongly with aerodynamic forces. Aeromechanics 

predictions require a coupling of structural dynamic and 

aerodynamic analysis within an umbrella that solves both 

simultaneously and also provides a solution for aircraft or 

rotor trim. The rotorcraft industry has developed 

comprehensive analyses (Refs. 5 to 7) that apply modeling 

technologies that are well suited for this. They include nonlinear finite elements for structural dynamics analysis, lifting 

line theory for aerodynamics analysis, and trim algorithms to 

find rotor controls that balance forces. Finite-element analysis 

captures relatively large deflections and the tension field 

induced by rotation; lifting line theory is supplemented with 

corrections for unsteady aerodynamics including dynamic stall 

and airfoil section load coefficient lookup tables (so-called 

C81 format) that are functions of Mach and angle of attack.

Efforts to replace the lifting-line air loads models within 

comprehensive codes with CFD-based analysis have been 

ongoing (Refs. 8 and 9). Recent efforts with Navier-Stokes 

CFD coupled with comprehensive codes have demonstrated 

improved air loads predictions, particularly where large 

unsteady aerodynamic forces cause blade deflections that feed 

back into the aerodynamics. Empirical correction models have 

not been able to capture all aerodynamic phenomena of 

importance to blade loads and performance, but CFD has 

shown promise.

Comprehensive codes compute air loads as needed during 

the convergence process. Trim magnifies the number of times 

air loads must be computed, so the long run-time for CFD 

makes direct substitution of lifting-line impractical. A method 

of substitution has been developed called loose-coupling. This 

method allows trim to use lifting-line air loads during trim, 

while successively using the CFD solution. The method is 

outlined in Figure 2. At iteration n = 0, the comprehensive 

code trims and converges with only lifting-line air loads as 

usual. Blade motions for one rotor period are then passed to 

the CFD solver. These motions contain gross pitching motions 

from controls as well as the elastic response. It is not 

necessary to achieve a perfect periodically-converged solution 

from CFD at this point; successive iterations between the 

comprehensive code and the CFD code move the solution 

toward convergence. At iteration n ≥ 1, CFD-based air loads 

are passed back into the comprehensive code and used with 

lifting-line air loads from the previous solution. The 

comprehensive code continues to compute lifting-line air loads 

during trim and convergence and while adding the previous 

iteration CFD and lifting-line “delta” for the total air load to 

drive the aeromechanical solution. These iterations continue 

until there is no change in trim controls or air loads, at which 

point the lifting-line air loads from the previous iteration 

cancel the lifting-line air loads from the current iteration 

leaving only the CFD as the total air load. This process is 

fairly efficient with CFD, and usually requires simulation of 

between two and five rotor revolutions as trim and periodic 

convergence move together.

The solution is naturally time dependent, but periodic, as the 

blades rotate around the azimuth and respond to the air loads. 

Ice accretion is influenced by the local aerodynamics which 

changes over the course of a rotor revolution. To harvest the 

Series of

2-D Ice

Accretion

Iced 3-D Flow Field

From CFD/CSD Analysis

Initial 3-D Flow Field

From CFD/CSD Analysis

Data mine 

for 2D Air

conditions

Converged?

Done

CFD

yes

no

Comprehensive Rotor Analysis

n = n + 1

Air Loads

Blade Motions

( ) if ( 1)

if ( 0)

= + 1 − 1 ≥

= =

F F F − F − n

F F n

LL

n CFDn LL n n

LL

n n
NASA/TM—2012-217126 3

aerodynamic conditions, the CFD/CSD solution is saved for 

several blade positions in a rotor revolution providing 

snapshots of the flow field at several instances in time.

Accreting ice using a 2D strip approach is possible provided 

representative conditions can be data mined from these 

solutions. Specific required data include local angle of attack 

and relative velocity as a function of blade radial and 

azimuthal position. There are several ways to extract this 

information. Ideally, the extracted conditions should produce a 

2D pressure distribution on an airfoil that is identical to the 

instantaneous pressure distribution from the 3D solution.

Extracted pressure from the rotor solution is typically 

presented in coefficient form using the hover tip speed as the 

reference velocity, Vtip. Assuming mostly 2D flow along the 

blade and that the flow stagnates on the blade, the pressure 

coefficient can be renormalized by V2D such that Cpmax is 

equal to 2

2 1/ 1− M D . The 2D free stream Mach number that 

satisfies this requirement is

( ) 4 2 2 2 4

2

1 M D = A + A − A , (1)

where

max 2 A = M tipCp . (2)

The reference 2D velocity is then M2D a where a is the speed 

of sound.

A representative angle of attack for the 2D ice accretion 

strip approach can be determined a number of ways, for 

example, by utilizing a 2D aerodynamic database of Mach 

numbers, normal force, and angle of attack or using an airfoil 

aerodynamic analysis tool to find the angle of attack that best 

matches the 3D pressure distribution for V2D.

The extracted aerodynamic conditions along with the 

conditions of the icing environment allow for an ice accretion 

analysis. The process begins by considering one radial 

location at a time and segmenting the icing encounter into a 

number of smaller time steps. At a radial location, ice is 

accumulated over these small time increments using the 2D 

conditions which vary as a function of azimuth as illustrated in 

Figure 3. Each subsequent ice accretion is accumulated on top 

of the ice growth calculated from the previous time step. At 

the conclusion of the final time step, the ice accumulated over 

the length of the blade will represent ice growth influenced by 

the aerodynamic conditions encountered over all azimuthal 

positions.

The ice analysis follows a similar approach to Bidwell 

(Ref. 1) which involves a coupling between Lewice3D and 

CFD. Here, Lewice3D evaluates drop trajectories, 

thermodynamic equilibrium, and ice growth for a blade 

section using an airfoil aerodynamic solution from CFD. For 

consistency the airfoil aerodynamic solution is also computed 

Figure 3.—Ice build-up prediction process.

Figure 4.—The influence of accreted ice on drop 

trajectories.

with OVERFLOW. Depending on the extent and shape of the 

accreted ice, the ice growth may be computed in a multi-step 

approach. As the ice grows, blade aerodynamics, droplet 

trajectories, impingement limits, and collection efficiency can 

be significantly altered. This is illustrated in Figure 4. It may 

be necessary to update the airfoil geometry and airfoil 

aerodynamic solution to reflect intermediate ice growth. 

Generally for rotors in forward flight, the icing event can be 

segmented in small enough time increments to perform singlestep ice accretion. However, in the case of hover, where there 

are no azimuthal variations in the 2D aerodynamic conditions, 

a multi-step ice accretion could improve prediction fidelity.

Once the ice has been established on the blade, the 

CFD/CSD analysis process is repeated for the iced rotor. The 

3D rotor grid is modified to account for the ice shape on the 

blade. The input to the CSD analysis is modified to reflect the 

additional mass and change to the blade center of gravity. It is 

assumed that the effect on blade stiffness is small. Rotor 

performance degradation is obtained by comparing the 

forward flight performance characteristics of the iced rotor to 

t

0= 0

t

1= t0+∆t

t2= t1+∆t

α0, V0

α1, V1

α2, V2
NASA/TM—2012-217126 4

the baseline rotor. One important element of rotor 

performance degradation is the increase in power for the same 

thrust. In addition to this metric, the coupled CFD/CSD 

solutions will give insight to the change in blade loads and 

control positions for trim.

One important element of ice prediction of rotors is ice 

shedding. Rotor centripetal force and aerodynamic loads can 

cause segments of ice to leave the rotor, increasing vibration 

levels. The prediction of ice shedding events, though 

important, is not currently addressed in this process.

Hover Test Case

During the winter of 1982-83, the NASA Lewis Research 

Center and the U.S. Army conducted the Helicopter Icing 

Flight Test (HIFT) program to study the characteristics of a 

helicopter in near hover conditions subjected to icing 

conditions. As a part of this program, an attempt was made to 

document, as completely as possible, the ice formations on the 

main rotor blades and the resultant rotor performance 

degradation for the purpose of validating analytical 

techniques. These results are taken as reference to validate the 

simulation approaches presented in this paper. The helicopter 

used for the HIFT Program was a Bell UH-1H and it was 

tested at the Canadian National Research Council (NRC) 

spray rig facility at Uplands Airport, Ottawa, Canada. Figure 5

shows a photograph of the test.

Though it was desired to achieve near hover conditions, the 

spray rig required a wind speed of a least 6 knots to carry the 

icing cloud out over the helicopter. Due to the low speed, a 

hover flight condition is assumed for the analytic predictions. 

From the five flights tested, summarized in Table 1, condition 

‘E’ was selected to be reproduced with numerical computation 

due to the low gusts and the existence of the ice on the rotor 

up to 92 percent of the span. The median volumetric drop 

diameter for these flight conditions is 30 μm and the total 

accretion time is 3 min.

TABLE 1.—SUMMARY OF HOVER ICING FLIGHTS TEST 

CONDITIONS DURING THE HIFT PROGRAM

Flt

no.

Wind 

speed 

(m/s)

Gusts LWC

(g/m3)

T∞

(°C)

Time

(min)

Ice 

extent 

(r/R)

A 3.6 Medium 0.4 –12. 4.5 0.75

B 5.1 Medium 0.4 –9.5 4.25 0.65

C 3.0 Medium 0.4 –17. 4.0 -----

D 2.1 Low 0.4 –21. 6.0 -----

E 4.6 Low 0.7 –19. 3.0 0.92

The stereo photography tracing techniques was adopted, 

among others, to document rotor ice accretion shapes. Ice 

shape tracings were made for several sections along span-wise 

locations. An exhaustive description of the test and results of 

the HIFT Program can be found in References 10 and 11.

The rotor for the Bell UH-1H has a conventional NACA 

0012 airfoil with a constant chord of 21 in. The span is

Figure 5.—Photo of the Army UH-1H helicopter hovering in the 

NRC icing cloud.

Figure 6.—Isolated rotor grid for the UH-1H; every 

4th point shown for clarity.

288 in. and the main rotor area is equal to 1809.5 ft2

, with a 

rotational speed ω of 33.9 rad/sec and a resulting Mach 

number tip of about 0.79. The rotor blade has a linear 10.9° 

twist along the span. The maximum gross weight of the UH1H is about 9500 lb. This value is considered for the 

estimation of the thrust coefficient.

Results

The clean UH-1H hover performance is estimated using an 

isolated rotor model. A rotational source term is added to the 

governing equations of motion to obtain a steady state solution 

in a blade-fixed reference frame using the technique described 

in Reference 12. The grid system for the clean rotor is shown 

in Figure 6 and features a C-grid topology in the chord 

direction with 533 points. Along the span 275 points are used 

to define the geometry as ice will be predicted in 

1-in. increments across the radius. The hover model has a 

fictitious center body to prevent blade root vortices from 
NASA/TM—2012-217126 5

Figure 7.—Figure of merit convergence with 

OVERFLOW for the UH-1H rotor in hover, 

collective 7° and flight conditions ‘E’.

circulating. The blades are physically disconnected from the 

center body to easily adjust the blade collective pitch angle.

The solution was computed with OVERFLOW 2.1g using a 

central differencing scheme for the Euler terms. The Spalart 

Allmaras turbulence model was used assuming a fully 

turbulent boundary layer over the blade. The turbulence model 

was turned off in the off-body wake region as a simplistic 

engineering approach to maintain blade tip vortex strength 

which tends to prematurely dissipate in traditional RANS 

solutions. Typical hover solutions with this grid system 

require about 10,000 iterations to converge the figure of merit 

to within 0.002 (Figure 7).

The solution for a rotor thrusting at 9500 lb is data mined 

for representative 2D airfoil conditions to be used in the strip 

analysis for ice accumulation. The chordwise pressure 

distribution is extracted at several radial positions and 

normalized with a reference velocity according to 

Equation (1). Local angles of attack are found such that when 

applied in a 2D airfoil analysis with the reference velocity 

similar pressure distributions are obtained. The velocity and 

angle of attack distribution used to accrete ice on the UH-1H 

rotor is shown in Figure 8. Since this is a hover condition, 

there is no azimuthal variation.

The ice event time for flight condition E is 3 min which 

could produce significantly large ice shapes. To address the 

influence of accreting ice on the final ice shape, the icing 

analysis was performed in 1 and 3 steps for the airfoil 

condition at 62 percent R. In the 3-step analysis, ice is grown 

for 1 min before the geometry and aerodynamic solution is 

updated. The comparison of the 1-step and 3-step approach is 

shown in Figure 9. Though some differences exist, the shapes 

are close enough to believe that both will produce similar rotor 

performance degradation. Due to the additional computational 

expense of the 3-step approach, rotor ice across the blade is 

accreted in 1 step.

The accreted ice shape for the blade is shown in Figure 10. 

To generate this shape, icing analyses are performed in 1-in. 

increments from blade root to blade tip. Moderate amounts of 

ice are grown towards the root end where the Mach number is

generally low and the ram temperature is also relatively low. 

Figure 8.—Representative 2D aerodynamic 

conditions along the rotor radius.

Figure 9.—Ice accreted at 62 percent rotor radius computed in 

1 and 3 steps.

Figure 10.—Predicted ice along the span of the 

blade; ice analysis is performed in 1-in.

increments.

Further outboard, just beyond the mid-radius, the ice shapes 

are larger in size. Beyond 65 percent, the ice shapes begin to 

get smaller as the ram temperature increases.

The predicted ice shapes using the 1-step approach correlate 

well to measured data. Figure 11 shows a sample of the 

correlation at 4 radial stations: 45, 62, 70, and 79 percent.

0.0

0.2

0.4

0.6

0.8

0 4000 8000 12000

Iteration

Figure of Merit

0

200

400

600

800

1000

0.0 0.2 0.4 0.6 0.8 1.0 1.2

r/R

Reference Velocity (ft/s)

0

4

8

12

16

20

Angle of Attack (deg)

Angle of Attack

Velocity

-0.10

-0.05

0.00

0.05

0.10

-0.10 -0.05 0.00 0.05 0.10 0.15 0.20 0.25 0.30

X/C

Y/C

1 Step

3 Step
NASA/TM—2012-217126 6 r/R = 0.45 r/R = 0.62 r/R = 0.70 r/R = 0.79

Figure 11.—Comparison of predicted and measured ice 

shapes for Flight E of the HIFT program.

The iced rotor is analyzed in the same manner as the clean 

rotor. The grid density is unchanged between the clean and 

iced rotor because it is sufficient to capture the features of the 

ice. The predicted rotor power and the power increment

needed to maintain hover is shown in Figure 12. The HILT 

Figure 12.—Predicted and measured rotor 

performance degradation for Flight E of 

this HIFT program.

Figure 13.—Blade loads for the clean and 

iced rotor near zero-thrust.

program measured the increase in power required at two 

conditions: First, directly after ice accumulation in out-ofground-effect (OGE) hover, then while on the ground with flat 

pitch. The two data points are indicted as open symbols in 

Figure 12. The predicted power increase is roughly 50 percent 

of the experiment.

The air loads along the blade near the zero-thrust condition 

(Figure 13) and near the maximum gross weight (Figure 14) 

-0.10

-0.05

0.00

0.05

0.10

-0.10 -0.05 0.00 0.05 0.10 0.15 0.20 0.25 0.30

X/C

Y/C

-0.10

-0.05

0.00

0.05

0.10

-0.10 -0.05 0.00 0.05 0.10 0.15 0.20 0.25 0.30

X/C

Y/C

-0.10

-0.05

0.00

0.05

0.10

-0.10 -0.05 0.00 0.05 0.10 0.15 0.20 0.25 0.30

X/C

Y/C

-0.10

-0.05

0.00

0.05

0.10

-0.10 -0.05 0.00 0.05 0.10 0.15 0.20 0.25 0.30

X/C

Y/C

0

20

40

60

80

100

0 2000 4000 6000 8000 10000

Thrust (lbs)

∆ HPrequired

0

200

400

600

800

1000

Horsepower

Clean

Iced

-0.4

0.0

0.4

0.8

1.2

Lift Coefficient

Clean

Iced

0.00

0.02

0.04

0.06

0.08

0 50 100 150 200 250 300

Radius (in)

Drag Coefficient x (r/R)

Clean

Iced
NASA/TM—2012-217126 7

Figure 14.—Blade loads for the clean and 

iced rotor near the maximum gross 

weight hover condition.

shows that lift and drag are impacted the most near the 

50 percent span location for this icing condition. Intuitively, 

this is where the largest ice shape is grown. The blade loads 

outboard of 50 percent seem relatively unaffected by the ice 

shape which suggests that the hover analysis is not properly 

capturing the impact of the ice on rotor performance.

Comparisons of Mach contours at station 150 (Figure 15) 

and 227 (Figure 16) suggest the ice shape over the outboard 

section is more aligned with the flow and therefore is less 

detrimental. This stresses the importance of accurately 

capturing the ice shapes.

Conclusions

A high fidelity ice accretion and rotor performance 

degradation methodology was presented and applied to a 

rotorcraft in hover. The process uses computational fluid 

dynamics to establish clean and iced rotor performance. The 

ice growth assumes 2D flow along the radius of the blade and 

is accreted using a loose coupling between 2D CFD and 

Lewice3D. Application to the UH-1H in hover is the first step 

in the validation of the process as the problem is simplified 

because there is no azimuthal variation in flow conditions to 

consider during the ice analysis. The correlation in predicted 

ice shape is good however the ensuing rotor performance 

degradation is under-predicted by 50 percent. Follow-on work 

will include the application of this methodology to forward 

flight.

Figure 15.—Mach contours for the clean (bottom) and 

iced (top) rotor at station 150 near the maximum 

gross weight hover condition.

Figure 16.—Mach contours for the clean (bottom) and 

iced (top) rotor at station 227 near the maximum 

gross weight hover condition.

-0.4

0.0

0.4

0.8

1.2

Lift Coefficient

Clean

Iced

0.00

0.02

0.04

0.06

0.08

0 50 100 150 200 250 300

Radius (in)

Drag Coefficient x (r/R)

Clean

Iced
NASA/TM—2012-217126 8

References

1. Bidwell, C., “Icing Calculations for a 3D, High-Lift 

Wing Configuration,” AIAA-2005-1244, 43rd AIAA 

Aerospace Sciences Meeting and Exhibit, Reno, NV, 

Jan. 10-13, 2005.

2. Bidwell, C., “User’s Manual for the NASA Glenn Three 

Dimensional Grid Based Ice Accretion Code

(LEWI3DGR),” NASA Glenn Research Center, 

Cleveland, OH, 2003.

3. Buning, P.G., Jespersen, D.C., Pulliam, T.H., Chan, 

W.M., Slotnick, J.P., Krist, S.E., Renze, K.J., 

“OVERFLOW User’s Manual, Version 1.8b,” NASA 

Langley Research Center, Hampton, VA, 1998.

4. Peroomian, O., Chakravarthy, S., Palaniswamy, S.,

Goldberg, U., “Convergence acceleration for unifiedgrid formulation using preconditioned implicit 

relaxation”, AIAA Paper 98-0116, Aerospace Sciences 

Meeting and Exhibit, 36th, Reno, NV, Jan. 12-15, 1998.

5. Shultz, L., Panda, B., Tarzanin, F., Derham, R., Oh, B.,

Dadone, L., “Interdisciplinary Analysis for Advanced 

Rotors – Approach, Capabilities and Status,” American 

Helicopter Society Aeromechanics Specialists 

Conference, San Francisco, CA, 1994.

6. Johnson, W., “A Comprehensive Analytical Model of 

Rotorcraft Aerodynamics and Dynamics. Part 1: 

Analysis Development,” NASA TM 81182, 1980.

7. RCAS User’s Manual, Volume 1, Rotorcraft 

Comprehensive Analysis System Version 2.0. 2003, U.S.

Army Aviation and Missile Command.

8. Potsdam, M., Yeo, H., Johnson, W., “Rotor 

Aerodynamic Prediction using Loose Aerodynamic and 

Structural Coupling”, American Helicopter Society 60th 

Annual Forum, Baltimore, MD, June 2004.

9. Bhagwat, M., Dimanlig, A., Saberi, H., Meadowcroft, 

E., Panda, B., Strawn, R., “CFD/CSD Coupled Trim 

Solution for the Dual-Rotor CH-47 Helicopter Including 

Fuselage Modeling,” American Helicopter Society 

Specialist Conference on Aeromechanics, San Francisco, 

CA, January 2008.

10. Lee, J.D., “Aerodynamic Evaluation of a Helicopter 

Rotor Blade with Ice Accretion in Hover,” AIAA-84-

0608, 1984.

11. Lee, J.D., Harding, R., Palko, R.L. “Documentation of 

Ice Shapes on the Main Rotor of a UH-1H Helicopter in 

Hover,” NASA CR 168332, Lewis Research Center, 

1983.

12. Potsdam, M., Pulliam, T., “Turbulence Modeling 

Treatment for Rotorcraft Wakes,” American Helicopter 

Society Specialist Conference on Aeromechanics, San 

Francisco, CA, January 2008.

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01-01-2012 

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Technical Memorandum 

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4. TITLE AND SUBTITLE

Analysis of a Hovering Rotor in Icing Conditions 

5a. CONTRACT NUMBER

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5c. PROGRAM ELEMENT NUMBER

6. AUTHOR(S)

Narducci, Robert; Kreeger, Richard, E. 

5d. PROJECT NUMBER

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5f. WORK UNIT NUMBER

WBS 877868.02.07.03.03.01 

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National Aeronautics and Space Administration 

John H. Glenn Research Center at Lewis Field 

Cleveland, Ohio 44135-3191 

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E-17815 

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NASA 

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NASA/TM-2012-217126 

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Subject Category: 02 

Available electronically at http://www.sti.nasa.gov 

This publication is available from the NASA Center for AeroSpace Information, 443-757-5802

13. SUPPLEMENTARY NOTES

14. ABSTRACT

A high fidelity analysis method is proposed to evaluate the ice accumulation and the ensuing rotor performance degradation for a helicopter 

flying through an icing cloud. The process uses computational fluid dynamics (CFD) coupled to a rotorcraft comprehensive code to 

establish the aerodynamic environment of a trimmed rotor prior to icing. Based on local aerodynamic conditions along the rotor span and 

accounting for the azimuthal variation, an ice accumulation analysis using NASA’s Lewice3D code is made to establish the ice geometry. 

Degraded rotor performance is quantified by repeating the high fidelity rotor analysis with updates which account for ice shape and mass. 

The process is applied on a full-scale UH-1H helicopter in hover using data recorded during the Helicopter Icing Flight Test Program.

15. SUBJECT TERMS

Icing; Rotorcraft 

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