Document
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NASA Technical Memorandum 105977
AIAA-93-0398
Icing Effects on Aircraft Stability
and Control Determined From
Flight Data
Preliminary Results
T.P. Ratvasky and R.J. Ranaudo
Lewis Research Center
Cleveland, Ohio
Prepared for the
31st Aerospace Sciences Meeting and Exhibit
sponsored by the American Institute of Aeronautics and Astronautics
Reno, Nevada, January 11-14, 1993
NASA
ICING EFFECTS ON AIRCRAFT STABILITY AND CONTROL DETERMINED FROM FLIGHT DATA. Preliminary Results.
T.P. Ratvasky, and R.J. Ranaudo National Aeronautics and Space Administration Lewis Research Center Cleveland, Ohio 44135 Abstract: The effects of airframe icing on the stability and control characteristics of the NASA DH-6 Twin Otter icing research aircraft were investigated by flight test. The flight program was developed to obtain the stability and control parameters of the DH -6 in a baseline ("united") configuration and an "artificially iced" configuration for specified thrust conditions. Stability and control parameter identification maneuvers were performed over a wide range of angles of attack for wing flaps retracted (0°) and wing flaps partially deflected (10°). Engine power was adjusted to hold thrust constant at one of three thrust coefficients ( C r =0.14, C r =0.07, C, =0.00).
This paper presents only the pitching- and yawing-moment results from the flight test program. Stability and control parameters were estimated for the uniced and artificially iced configurations using a modified stepwise regression algorithm. Comparisons of the uniced and iced stability and control parameters are presented for the majority of the flight envelope. The artificial ice reduced the elevator and rudder control effectiveness by 12% and 8% respectively for the 0° flap setting. The longitudinal static stability was also decreased substantially (approximately 10%) because of the tail ice. Further discussion is provided to explain some of the effects of ice on the stability and control parameters.
List of Symbols and Abbreviations: A,,A,,,A Z longitudinal, lateral, and vertical p,q,r roll pitch and yaw rate, rate, rate, accelerations, respectively, g units respectively, rad/s or deg/s b wing span, m R'- squared multiple correlation coefficient C. I q pitching-, yawing-moment coefficients, S wing area, of respectively V total airspeed, m/s or knots C,,C,,, initial conditions of pitching-, yawing- (t) measured aircraft response or control moment coefficients, respectively surface input C r thrust coefficient y(t) computed aerodynamic coefficients T mean aerodynamic chord, m a angle of attack, rad or deg cg aircraft center of gravity angle of sideslip, rad or deg g acceleration due to gravity, m/s 4 change in parameter due to ice shape l lz klk moments of inertia about roll, pitch, 6 ,6,,5, elevator, aileron, and rudder and yaw axes, respectively, kg-mZ deflection, respectively, rad or deg T„Z product of inertia, kg-mz 6, flap deflection, rad or deg cost function for modified stepwise JMSR regression algorithm aerodynamic stability and control AMI A Analytical Methods, Inc.
parameters LeRC NASA Lewis Research Center constant offset term MSR modified stepwise regression derivative with respect to jth response or PID 6i parameter identification control surface input WFF NASA Wallops Flight Facility pitch and roll angles, respectively, rad or 0,0 deg standard deviation estimate of measure- C ment noise Pitching moment derivatives: ,^ = ac.
c c =.
c = ac qc ' aa^ as ' a- 2V Yawing moment derivatives: c = ac c _ ac^ c ac" n' ac _ C = ny aar a p ' a pb ' a rb ^o 2V 2V Introduction: effects from icing effects on the derivative estimates. Previous experience indicated that A principal objective of the NASA Lewis power had a measurable effect on certain Research Center's (LeRC) icing research program stability and control parameters °.
is to develop and validate computational methods for predicting the effects of airframe icing on This report is organized in sections which aircraft flight characteristics. Recently a multi-year describe the research aircraft, instrumentation contract was awarded to Analytical Methods, Inc. systems, flight test procedures, data analysis methods, a discussion of the derivative estimates, (AMI) to develop a three -dimensional flow code and conclusions drawn from the work. Because of to predict the stability effects and performance losses of a complete aircraft with known ice the volume of data acquired in the flight program, contamination. The code will be validated with and the need for brevity in this particular report wind tunnel data supplied by a large commercial format, only the pitching- and yawing-moment aircraft company and full-scale flight data from results are presented. A complete data report will NASA LeRC's icing research aircraft. be written at a later time.
NASA's DeHavilland DH-6 Twin Otter icing research aircraft was utilized in an extensive Research Aircraft: flight test program to acquire the needed flight data base. Although the DH-6 does not represent the The NASA Lewis icing research aircraft is geometry of a modern swept wing transport, it does a modified DeHavilland DH-6 Twin Otter (figure provide numerous advantages in terms of it's low 1). It is powered by two 550 SHP Pratt and operating cost, simplicity, adaptability for the Whitney PT6A-20A turbine engines driving intended experiment, and known flight three-bladed Hartzell constant speed propellers.
characteristics from previous stability and control The flight controls are mechanically operated flight experiments'. Also, a digitized panel model through a system of cables and pulleys. Control of the DH-6 that was previously developed', was surfaces consist of elevator, ailerons, rudder, and available for performing the AMI code validation. wing flaps. Physical characteristics of the aircraft are in Table 1.
Relying on extensive past experience in measuring icing effects on aircraft performance, The DH -6 was tested in a baseline stability and control ', NASA developed a com- configuration (clean airfoils), and an artificially iced prehensive flight program to generate the required configuration (figure 2). Artificial glaze ice shapes aerodynamic data base. The key elements of the were attached to the leading edges of the horizontal flight program include: and vertical stabilizers only. No other surfaces were contaminated. The ice shapes were determined by 1. A high-fidelity, onboard instrumentation system combining the geometry from actual tail ice with complete system characteristics known photographs with a well-known ice area calculation from comprehensive ground and flight procedure '. The ice shapes were cut from calibration tests.
Styrofoam blocks, and attached to the leading edges of the tail with double sided tape. The ice shapes 2. Use of measured aircraft weights, center of did not incorporate surface roughness or 3D effects gravity, and moments of inertia for data (scalloping).
reduction and analysis programs.
Extensive ground tests were conducted on 3.
Flight testing at specific thrust settings (C r = the DH-6 to obtain the center of gravity (cg) and 0. 14, Cr = 0.07, Cr = 0.00) to distinguish power moments of inertia along the longitudinal, lateral and vertical axes. These characteristics varied with Extensive calibrations were conducted on fuel and crew loading and any modifications that all components of the data system. Individual were made. Aircraft configuration was closely calibrations were conducted for all sensors, and monitored to account for any changes in center of through-put calibrations (sensor-filter-data gravity and moments of inertia. acquisition-recording) were run where possible.
Calibrations were checked periodically during the For that phase of testing when the DH-6 research program.
engines were shut down while in flight, an auxiliary power unit (APU) was installed to supply the research equipment with electrical power. The Flight Test Procedures: aircraft was modified structurally and electrically to accommodate the APU. Aircraft weight and balance were determined before each flight by weighing the fully fueled aircraft less crew. In flight, fuel totalizers Instrumentation System: provided an accurate measure of fuel burned.
These readings were used for cg and moment of The stability and control data system flown inertia calculations in the post flight data processing.
on the Twin Otter incorporated the following components: inertial data, air data, control surface Flight testing in the two configurations deflection data, signal conditioning, data acquisition (baseline, artificially iced) was performed with wing and recording systems. The inertial sensors flaps retracted (6 F =0°), and with wing flaps partially consisted of three orthogonally mounted linear extended (6, =10°). Test point airspeeds were accelerometers, three orthogonally mounted angular selected to cover the range of angles of attack in rate gyros, and a vertical gyro to provide pitch and each configuration from maximum cruise airspeed roll angle data. These sensors were near the to near aerodynamic stall. Parameter identification aircraft center of gravity. Yaw angle data was (PID) maneuvers consisting of elevator doublets provided by the ship's directional gyro. Air data (figure 3) and rudder-aileron doublets (figure 4) consisted of airspeed, angle of attack, angle of were used to excite the required aircraft response.
sideslip, pressure altitude, and outside air temperature. All air data parameters (except OAT) were sensed by a Rosemount 858 probe head To determine the power effects, each PID extended from the aircraft on a 9 foot noseboom. maneuver was flown at three target thrust The control surface deflections, (6., 6,, 6,), were coefficients (Cr ): Cr =0.14 (high thrust), q=0.07 measured using linear control position transducers (low thrust), and C,=0.00 (engines off and (CPT's) located near the control horns which propellers feathered). To attain the target thrust eliminated cable stretching errors. Transducer coefficients in the powered cases, a simple flight signals were amplified and filtered by a Precision procedure was developed. Initially, an altitude Filters System 6000 unit and then digitized with a would be selected where flight conditions were Keithley series 500 data acquisition system. A total smooth. This became the reference pressure of 26 channels of data were digitized at an altitude for all flight maneuvers. The outside air acquisition rate of 100 samples/second and a 12 bit temperature was also recorded. Based on the resolution. A ruggedized AT-class microcomputer pre-planned indicated test airspeeds, and a constant was used to control the data acquisition system, and 1800 propeller rpm, the required engine torque a removable hard drive in the computer provided pressure settings were calculated from known relationships between thrust coefficient, engine data storage. See table II for instrumentation specifications. power coefficient, propeller advance ratio, and propeller efficiency. Normally, the target thrust coefficients did not provide level flight conditions at The stability and control derivatives were the trimmed test airspeeds. Consequently, the PID estimated using a Modified Stepwise Regression maneuvers were usually performed in shallow (MSR) technique'. MSR is a version of linear climbs or descents as the aircraft reached the regression which can determine the structure of the reference pressure altitude. Generally, all PID aerodynamic model, and estimate the values of the maneuvers were accomplished within ±200 feet of model parameters. The general form of the the reference altitude. aerodynamic model is as follows: +0 MO + 9 2 x 2 (r) + ... + Oj.(I) (1) r ) = Y( e0 1 The tests at C,. =0.00 were performed at the NASA Wallops Flight Facility (WFF), where a y(t) represents the aerodynamic force or restricted test area, tracking support, and a moment coefficient and is known from dedicated landing site were employed for flight measurement.
safety reasons. In performing these tests, the DH-6 eo is a constant corresponding to the initial departed WFF and climbed to a pre-planned flight condition.
altitude and position which was within safe gliding distance to the landing field. While being tracked 1 to O on radar, the engines were shut down and the n are constant coefficients known as stability and control derivatives.
propellers feathered. Test airspeeds were attained by establishing the proper flight path. PID x, (t) to Y,(t) terms represent the measured maneuvers were then executed while the onboard input and output variables, or their data system, powered by the auxiliary power unit, combinations (regressors).
recorded the flight data. The glide was terminated and the engines re-started when a specified MSR determines the model structure one minimum altitude was reached.
term at a time. Each new term enters into the regression equation based on the largest correlation with the dependent variable, y(t), after adjusting for Data Analysis: the effect of the previously selected terms on y(t).
Essentially, the first regressor ) (t) is selected based Measured data were recorded with the on the highest correlation with the dependent onboard data acquisition system in a binary format.
variable y(t). A constant value, 8., is determined to Data were post-test processed into engineering units minimize the squared difference in the measured and corrected for instrument offsets from the aerodynamic coefficient y(t), and the model aircraft center of gravity, position errors in airspeed prediction 80 + 8J- ) (t). It means that at each step and altitude, and upwash effects in the angle of of the MSR, the parameters are obtained by attack measurements.
minimizing the following least squares cost function: Each flight contained a series of data compatibility maneuvers designed to verify sensor N 2 (2) and data system integrity. These maneuvers were ly(1) - e0 - E e,Xi ( 1)1 .)MSR = =t i-1 analyzed using a maximum likelihood algorithm' to estimate bias and scale factor errors in the data N is the number of data points system. The analysis indicated a small sidewash correction was required in the sideslip 1+1 is the number of parameters in the measurement. This correction was made prior to regression equation.
the stability and control parameter estimation.
In addition, at each regression step the provide an ensemble of data. From the ensemble, influence of individual derivative/regressor pairs on a better measure of the variance of the derivatives the model is re-evaluated. The estimated was made.
parameters, 6'., may be retained, or removed from the model due to their statistical significance. The The stability and control derivatives are plotted with respect to trim angle of attack in process of adding and deleting terms to the model continues until no further significant terms can be figures 5-14. For each parameter estimate, error admitted to the model, and no further insignificant bars representing 2a variance determined by MSR terms can be removed. are included. To clarify trends between the baseline and iced configurations, a third order polynomial Models based solely on significance of regression with respect to angle of attack was performed for each ensemble of data. Along with individual parameters has proven to contain too the regression line, a 95% confidence bound on the many terms for good predictability'. Criteria for mean was included to evaluate the statistical electing adequate models are the squared multiple correlation coefficient (W), and the F-statistic value. significance of configuration change due to icing.
Che W value indicates the percent of variation explained by the model. An W close to 100% '<nggests the model perfectly fits the measured data. Longitudinal Model: The F-statistic value is the ratio of regression mean The pitching moment coefficient was <quare to residual mean square. The model with adequately modeled with the following equation: the maximum F-value has been recommended as i he 'best' one for a given set of data. Both C. no C ,' '7c C. 6e criteria were used in this analysis. = C + C.. a + + (3) 2V Results: The suitability of the model was determined chiefly by the R= value and the F statistic value from The analysis performed for this report was the MSR program. For all data analyzed here, the limited to the pitching and yawing moment W >_ 90 %, which indicates that over 90%v of the coefficients. Ice on the horizontal and vertical variation of Cm was described by this model.
stabilizers strongly affects these moment coefficients because the moments are predominantly created by The bias term C,,,o ^ 0 for all data runs the lift generated from these tail surfaces. Ice because the elevator doublet inputs were initiated contamination may reduce the maximum lift and from trimmed conditions.
lift-curve slopes of the stabilizers, which could result in lower stability of the aircraft. Separated flows The derivative, CC„., is known as the static behind the ice shape may decrease the effectiveness longitudinal stability derivative. A statically stable of control surfaces, which results in reduced aircraft will have a negative C,. indicating that a controllability of the aircraft.
nose down moment is produced with a positive change in angle of attack. A more negative C,.
The effect of ice on the pitching and yawing implies greater static longitudinal stability.
moment coefficients is evaluated by comparing the values of stability and control derivatives for both Figure 5 presents the effect of the tail ice the baseline (uniced) and iced cases. Each stability on the static stability derivative with flaps retracted and control derivative and its standard error was (br =0°) for three thrust coefficients. Static stability estimated using the MSR technique described was reduced by approximately 10% for each Cr.
above. Each flight condition was repeated to Because of the exceptional repeatability in these overlap occurred in the low thrust case. For the data sets, the reduction in static stability due to tail zero thrust case, pitch damping was unaffected by ice was determined with high accuracy.
the tail ice. The confidence bounds overlap for the entire angle of attack range tested, indicating that The effect of ice on with the flaps no change in can be attributed to tail ice.
Cn.
Cn, deflected to 10 degrees (6 F =10°) is shown in figure 6. Similar to the S r =0°case, a reduction in static The derivative, C,,,,, is the elevator stability occurred because of the ice. However, the effectiveness control derivative. It is usually a effect of ice varied with the thrust setting. Static negative value so that a positive elevator deflection stability was reduced by approximately 8% in the results in a nose-down (i.e. negative) pitching thrust cases, and 17% in the zero thrust case. moment. The more negative value for Cn, Because of scatter in the derivative estimates, the indicates a more effective elevator.
reduction in for the low thrust case (C F =0.07) Cna was not statistically significant (i.e. the confidence In figure 9, the effects of tail ice on Cm, bounds overlapped for most the range tested). are shown for flaps retracted and three thrust Note that the least statically stable condition coefficients. Because of the linearity in this data appeared at low angles of attack with flaps extended set, a first order regression was performed to and a high thrust coefficient. indicate the trends. A clear separation exists between the baseline and iced cases for each thrust The derivative, C„ q , is known as the pitch coefficient. The tail ice caused an approximate 12% damping derivative. As the aircraft pitches, a loss in elevator effectiveness over the entire angle of moment is created usually countering the pitching attack range tested. Also, note that the slope of motion. The horizontal tailplane is the primary with angle of attack changes with thrust C , contributor to the pitch damping.
condition. Engine power is clearly a factor in the elevator effectiveness with or without ice on the tail.
Figure 7 shows the effects of the ice on C.1, with flaps retracted for three thrust coefficients. In Figure 10 shows the effect of ice on C,,,, the cases with thrust, the trends indicated a slightly with the flaps deflected to 10 degrees (6, =10°). As lower pitch damping occurred due to the ice with the 6 F =0° cases, the ice decreased elevator (A =5%). This reduction was statistically significant effectiveness for all thrust settings (A : 16%). Also, except at the low angles of attack where the the flaps appear to further decrease the dependence confidence bounds intersected. For the zero thrust of elevator effectiveness with angle of attack.
case, the pitch damping was virtually unaffected by the ice except at low angles of attack. The confidence bounds overlap for nearly the entire Lateral Model: range of angles of attack tested. This result seemed inconsistent with the results because a loss in The yawing moment coefficient was Cma static longitudinal stability should also result in a adequately modeled with the following equation: reduction of pitch damping. Further discussion on + Cn pb + Cn p this point will follow. C. = C rb + C^ 8r (4) + Cn n o /2V 2V Figure 8 presents the effect of ice on C„, with the flaps deflected to 10 degrees =10°). As OF The suitability of the model was determined with the 6 F =0° cases, pitch damping was reduced by chiefly by the W value and the F statistic value from 5% to 9% in the high and low thrust cases.
the MSR program. For all data analyzed here, the Overlap in the confidence bounds occurred in the high thrust case at low angles of attack, but no RZ >_ 90 %, which indicates that over 90 % of the In figure 13, the effect of ice on C,,, are variation of C, was described by this model. shown for flaps retracted (8, =0°) and three thrust conditions. Although the data are fairly repeatable, The bias term C, - 0 for all data runs the effects of ice on this derivative are negligible in because the rudder and aileron doublet inputs were each thrust case.
initiated from trimmed conditions.
The derivative, q,,, is the rudder The derivative, C,, a , is the directional effectiveness control derivative. It is usually a stability derivative ('weathercock" stability). A negative value so that a positive rudder deflection directionally stable aircraft will have positive C,e results in a negative yawing moment. A more indicating a positive yawing moment is produced negative value for q, means a more effective with a positive change in sideslip angle. The yawing rudder control.
moment will rotate the aircraft so as to decrease the sideslip. A more positive C,, b implies a greater Figure 14 presents the effect of ice on Crt,,, directional stability. with flaps retracted at three thrust conditions. Tail ice substantially reduced rudder effectiveness Figure 11 presents the effect of the vertical (A=8%) in all thrust cases except for the higher tail ice on C, a with flaps retracted (6, =0°). For angles of attack in the zero thrust case. This may high and low thrust cases, the trends indicate that be a result of low dynamic pressure at the rudder is ice slightly decreased directional stability. However, the zero thrust condition.
the decrease is insignificant since the confidence limits overlap for most of the tested angle of attack range. For the zero thrust case, the ice decreased Discussion: the directional stability (A=20%) for all but the lowest and highest angles of attack. Also note that From the results presented, it is clear that directional stability is greater with zero thrust than the ice on the tail surfaces considerably affect some with power on. of the aircraft stability and control parameters.
Aircraft longitudinal static stability was reduced.
The derivative, C„r , is the directional Ice contamination reduced the horizontal tail's cross-derivative. It indicates the rate of change in maximum-lift and lift-curve slope which resulted in the yawing moment due to roll rate. For most a decreased pitching moment capability. Elevator aircraft, C^ is usually negative and of low value.
and rudder control effectiveness decreased. Flow Figure 12 shows the effect of ice on C,P disturbances caused by the ice may have resulted in with flaps retracted (8,=O') for three thrust lower dynamic pressure at the control surfaces conditions. For the zero thrust case, C,, was not a which decreased the effectiveness.
significant term in the MSR model except at higher angles of attack. Regardless of the thrust condition, Other parameters indicated no change due to ice. The directional cross derivative, Cam , the effects of ice are negligible on Cam. and directional damping derivative, C,,,, showed virtually The derivative, C,,,, is the yaw damping no difference in the iced configuration. This derivative. It indicates the rate of change in the indicates that these derivative were not sensitive to yawing moment due to yaw rate. The vertical icing on this aircraft.
tailplane is the primary contributor to the yaw damping. A larger vertical tail will likely increase Two parameters, C,,„q and C,, a , had mixed yaw damping characteristics. results. Ice caused the pitch damping, C", to slightly decrease with engine power on, but was unaffected by ice in the C, =0 cases. Ice on the horizontal tail decreased the tail lift coefficient to a neutrally stable condition (C; . =0). It is which should have caused a change in both the pitch important to note that a high thrust condition with damping and longitudinal stability, C,.. The tail ice large flap deflections at low angles of attack may clearly affected the C,, in each thrust case, so cause serious stability problems.
similar changes were expected in C4rq . On further was found to be much more Finally, it also should be noted that the examination, Cam , sensitive to changes in the tail lift coefficient than DH-6 is a short takeoff and landing (STOL) airplane. The tail surfaces are designed for low C,,,. As a result, C, may appear unaffected by the ice when Cm , was affected by the ice as was speed operations and tend to be oversized for the configurations and flight conditions that were tested.
demonstrated in the Cr = 0 cases. The second parameter which showed mixed results was the The changes in stability and control derivatives due directional stability derivative, q,. It showed to tail ice were sometimes small, but measurable.
negligible changes due to tail ice with engine power These changes were expected to be small because on, but as much as 20% change in the zero thrust the DH-6 STOL capabilities make it more robust to case. Also, C, p was greater in the zero thrust case ice. Other airplanes may show greater losses in for both baseline and iced configurations. One stability and control for the conditions tested.
possible explanation is that the propeller wash had a more destablizing effect than the ice.
Consequently, the effect of ice with engine power on appeared insignificant. Another possibility may be a shortcoming in the analysis technique. The effects of the vertical tail ice may not be apparent on q, until P > 6°, but in these tests each q, was evaluated about a P^0°. Analysis techniques are available to separate the data that was collected into small bins of fi so that C s,p can be evaluated specifically at higher sideslip angles. These techniques will be applied for a future report.
Another interesting observation was the effect of aircraft configuration and flight condition on static longitudinal stability, C,.. Ice was shown to destablize the aircraft by 10% in the S F =0° cases and as much as 17% in the S F =10° cases. But the addition of flaps alone destablized the aircraft in the high thrust cases at lower angles of attack (see figures 5 and 6). For the uniced Cr =0.14 cases, at an a =0*, C,, = -1.5 for 6, =0*, and C,. = -0.9 for S F =10°. This example illustrates a 40% reduction in static longitudinal stability with flaps deflected only 10°. Tail ice in conjunction with the 10° flap deflection decreased static longitudinal stability by 50% for the same condition. It may be inferred that if flap deflection was increased beyond 10° and the aircraft flown at a =0°, the static longitudinal stability would be lowered even more. The effect of tail ice with flaps deflected could drive the aircraft Conclusions: Based on the analysis and results presented, the following conclusions are made: The test techniques and analysis methods 3. It was shown that ice on the tail surfaces did 1.
not significantly affect some stability and employed permitted an accurate evaluation of the effects of moderate glaze tail ice on aircraft control parameters. The following parameters stability and control characteristics. were unaffected: 2. It was shown that ice on the horizontal and • yaw damping was not affected by the ice vertical tail surfaces significantly affect some shapes on the tail surfaces.
aircraft stability and control parameters. The following parameters were affected: • Pitch damping was reduced because of tail ice for the Cr = (0.14, 0.07) cases, but not at • elevator and rudder control effectiveness the Cr =0 case. Further investigation needs was reduced by approximately 10% because to be made to understand this result.
of ice on the horizontal and vertical stabilizers • directional stability was shown to be unaffected by ice for the powered cases, • static longitudinal stability was reduced by but further investigation needs to be made approximately 10% because of ice on before this is conclusive.
horizontal stabilizer.
• directional stability was reduced by approximately 20% because of ice on the vertical tail for the zero thrust case.
References: Determination of Longitudinal Aerodynamic Derivatives Using Flight 1. Ranaudo, R.J., Batterson, J.G., et.al ., Data From an Icing Research Aircraft. AIAA Paper 89-0754, NASA TM 101427, 1989.
Two Drop Sizing Lutrunents: PMS OAP and PMS Norment, H.G., Three-Dimensional Trajectory Analyses of 2.
FSSP. NASA CR 4113, 1988.
Flight Test Report of the NASA Icing Research Airplane. KSR 3. Jordan, J.L., Platz, S.J., Schinstock, W.C., 86-01, Kohlman Systems Research, Inc., Lawrence, KS, NASA CR-179515, 1986.
4. Ranaudo, R.J., et.al ., The Measurement of Aircraft Performance and Stability and Control After Flight Through AIAA Paper 86-9758, NASA TM-87265, 1986.
Natural Icing Conditions.
Engineering Summary of Airframe Icing Technical Data.
5. Bowden, D.T., Gensemer, A.E., Skeen, C.A., General Dynamics /Convair, San Diego, CA, Technical Report ADS-4, 1964.
Klein, V., Morgan, D.R., Estimation of Bias Errors in Measured Airplane Responses Using Mavinuun 6.
Likelihood Method. NASA TM-89059, 1987.
STEP and STEPSPL - Computer Programs for Aerodynamic Model Structure Detennination 7. Batterson, J.G., and Parameter Estimation. NASA TM-86410, 1986.
Detennination Airplane Model Structure From Flight Data by 8. Klein, V., Batterson, J.G., Murphy, P.C., of NASA TP-1916, 1981.
Using Modified Stepwise Regression.
Klein, V., Estimation of Aircraft Aerodynamic Parameters Front Flight Data. Prog. Aerospace Sci. Vol 26, 9.
pp.1-77, 1989.
Physical Characteristics of Research Aircraft Table 1: CHARAYrE1xJSYYC LOW ...........
HYGN Mass, kg 4510 4970 INERTIA: &, kg-nF 26190 26660 1,, kg-m2 33460 34650 L L , kg-m2 47920 51650 k,, kg-n^ 1490 1560 WING: Area, m Z 39.02 Aspect ratio 10.06 Span, m 19.81 Mean geometric chord, m 1.98 Airfoil section (17% thickness) "Dellavilland High Lift" HORIZONTAL TAIL: Area, mZ 9.10 Aspect ratio 4.35 Span, m 6.30 Mean geometric chord, m 1.45 Airfoil section (inverted) NACA 63A213 Table 11: Instrument Specifications PARAMETERISFNSOR ::» RANGE,. :I:RMb M.0N A, & A, , Sundstrand QA-700 1g .0002g A \ , Sundstrand QA-700 +3g, -1g .00098 p, Humphrey RG02-2324-1 ±60°/s 0.0167°/s q, Humphrey RG02-2324-1 ±60°/s 0.0167°/s r, Humphrey RG02-2324-1 ±120°/s 0.0138°/s 9, Humphrey VG24-0636-1 ±60° 0.0293° 0, Humphrey VG24-0636-1 ±901 0.0439° a, Rosemount 858 +15°, -10° 0.003° 8, Rosemount 858 ±15° 0.003° V, Rosemount 542K 0 to 190 knot 0.076 knot Alt., Rosemount 542K 0 to 15K ft 8.2 ft OAT, Rosemount 102AUIP -201 to 30° F 0.041°F . & 6.. SAC series 160 +19°, -16° 0.0091° S. L R I 8^, SAC series 160 +14°, -26° 0.0128° d,, SAC series 160 ±16° 0.0080° 6.30 (20.67) 1.98 (6.5) ^ lO v DIAM 2.59(8.5) ^.
—.^ 3.81 (12.5) 19.81(65.0)
--F
5.66 18.58) 4.5 (14.75) 15.77(51.75) Figure 1: NASA Lewis Research Center Icing Research Aircraft: all dimensions are in meters (ft).
Figure 2: Artificial moderate glaze ice attached to horizontal and vertical stabilizers of the icing research aircraft U.3 0.2 A (g units) x 0.1 O 5 10 15 —0.4 —0.6 —0.8 A Z (g units) —1.0 —1.2 —1.4 -- -- 5 10 15 q (deg/s) o - -10
-zo
5 10 15 O 90 - V (i<ta S) 5 10 15 14 -- a (deg) $ 6 -
—\/V
O 5 10 15 - 8 - 0 (deg) 6 - O O 5 10 15 -
-s
S (deg) e -10 -15 -20-- O 5 10 15 Time (s) Figure 3: Longitudinal Parameter Identification Maneuver 0.15
A y
(g units) 0.00 -0.15 -0 30 O 5 10 15 P ( deg / s ) 0 -10 -20 O 5 10 15 r (deg/s) 0 -10 -20 O 5 10 15 a (3 (deg) -4 -8 O 5 10 15 ^P (deg) 0 -5 -10 O 5 10 15 5.0 2.5 0.0
d a (deg)
-2.5 -5.0 O 5 10 15 5.0 2.5 0.0 d (deg) r -5.0 O 5 10 15 Time (s) Figure 4: Lateral Parameter Identification Maneuver -0.5 • UNICED CT=0.14 ICED —1.0 Cm CK —1.5 -2.0 ' ' -2 0 4 2 6 8 10 12 -0.5 CT=0.07 -1.0 C m a —1.5 N11, —2 0 —2 0 4 2 6 8 10 12 —0.5 CT=0.00 —1.0 ______________ ------- Cm -1.5 V.
-2 0 -2 0 2 4 6 8 10 12 Angle of Attack (deg) Figure 5: Static longitudinal stability derivative with 95% confidence limits. S F =0° -0.6 • UNICED CT=0.14 ICED -0.8 -1.0 C m —1.2 a —1.4 —1.6 —18 —4 —2 0 2 4 6 8 10 12 —0.6 CT 0.07 —0.8 —1.0 C m —1.2 a —1.4 —1.6 —1 8 —4 —2 0 2 4 6 8 10 12 —0.6 —0.8 C T=0.
—1.0 C —1.2 m —1.4 —1.6 —1 8 —4 0 2 4 6 8 12 —2 10 Angle of Attack (deg) Figure 6: Static longitudinal stability derivative with 95% confidence bounds. S F =10° -25 • UNICED CT=O. 14 ICED -30 C m T, -35 q -40 -45 -2 0 2 4 6 8 10 12 -G0 CT=0.07 -30 C -35 m q -40 -45 —2 0 2 4 6 8 10 12 —25 CT=0.00 —30 -------- --- C —35 M q —40 —45 —2 0 2 4 6 8 10 12 Angle of Attack (deg) Figure 7: Pitch damping derivative with 95% confidence bounds. S F =0° -25 • UNICED CT=O. 14 ICED —30 —35 Cm q —40 —45 —4 —2 0 2 —25 CTI 0.07 —30 ---------- \^.
—35
Cm
q —40 —45 —4 —2 0 2 4 6 8 10 12 —25 —30 —35 C M q —40 —45 —4 4 —2 0 2 6 8 10 12
Angle of Attack (deg)
Figure 8: Pitch damping derivative with 95% confidence bounds. S F =10° • UNICEM CT=o.1-t ICV1) —1.5 C77Ibe —^ 0 2 4 (7 10 12 —1.0 CT 0.O7
C
I716e —2.0 1 1 — 2 .5 —2 0 2 4 6 8 10 11 —1.0 ^ I I I I I CT=0.00 — ^_____ --- •--- _______
C -^___
In 6e —2.0 1 1 1 1 1 1 1 —2.5 1 —2 0 2 4 6 8 10 12 Angle of Attack (deg) Figure 9: Elevator effectiveness derivative with 95% confidence bounds. S F. =0° -1.0 i • UNICED C 0. 14 T ICED —1.5 Cm de —2.0 .- ------ A_ -^- —25' —4 —2 0 2 4 6 8 10 12 —1.0 CT 0.07 —1.5 - ------- — — - Cmde —2.0 -------.
—2.5 —4 —2 4 0 2 6 8 10 12 —1.0 CT=0.00 -------------- : --------------------_- — -- — -- —1.5 ---------rte_--_ ^^----- -------------------- C m —2.0 I I I I I I I I — 2.5 ' —4 —2 0 2 4 6 8 10 12 Angle of Attack (deg) Figure 10: Elevator effectiveness derivative with 95% confidence bounds. 6F=100 0.15 • UNICED ICED CT=0.14 0.10 CnR 0.05 ' ' ' —2 2 4 6 8 10 12 0.15 CT=0.07 C 0.10
n
0.05 ' 1'
—2 O 2 4 6 8 10 12 0.15 I CT=0.00 w -"----------------- ---f----------- ----- 0.10 C - -----°^---- ----------- ---------------- --------------------------^ i- — — --- 0 . 05 1 1 1 1 1 1 1 —2 0 2 4 6 8 10 12
Angle of Attack (deg)
Figure 11: Directional stability derivative with 95% confidence bounds.
SF =0° o.00 • UNICED ICED CT=0.14 —0.03 —0.06 C P —0.09 —0 12 —2 0 2 4 6 8 10 12 U.UU CT=0.07 —0.03 —0.06 C P —0.09 —0 12 —2 0 2 4 6 8 10 12 0.00 CT=0.00 —0.03 —0.06 C n P —0.09 I I I —0 12 —2 0 2 6 8 10 12
Angle of Attack (deg)
Figure 12: Directional cross-derivative with 95 % confidence bounds.
6F= 00 -0.10 • UNICED ICED CT=0.14 -0.15
Cn
r _ --- -0.20 i _L - I i -0 25 -2 0 2 4 6 8 10 12 -0.10 CT=0.07 -0.15 C.
nr -0.20 -0.25 ' ' -2 0 2 4 6 8 10 12 -0.10 1 T CT=0.00 -0.15 ----_ ----^ = T ^_ -------- C n r -0.20 1 1 1 1 1 1 1 1 -0.25 —2 0 2 4 6 8 10
Angle of Attack (deg)
Figure 13: Directional damping derivative with 95% confidence bounds. S F =00 -0.10 • UNICED ICED CT=O. 14 —0.11 Cndr —0.12 —0.13
-T --J
^. i —0 14 —2 0 2 4 6 8 10 12 —0.10 CT=0.07 —0.11
T
—0.12 C
dr %--- ------ ----- I'^
--- ---- __ T
—0.13 —0 14 —2 0 2 4 6 8 10 12 —0.1 0 CT=0.00 T —0.11 ------ — —0.12 Cndr _- ---- -- ------------ —0.13 —0 14 —2 0 2 4 6 8 10 12 Angle of Attack (deg) Figure 14: Rudder effectiveness derivative with 95% confidence bounds. 6,=O' Form Approved
REPORT DOCUMENTATION PAGE
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2. REPORT DATE 1. AGENCY USE ONLY (Leave blank) 3. REPORT TYPE AND DATES COVERED January 1993 Technical Memorandum 4. TITLE AND SUBTITLE 5. FUNDING NUMBERS Icing Effects on Aircraft Stability and Control Determined From Flight Data Preliminary Results WU-505-68-10 6. AUTHOR(S) T.P. Ratvasky and R.J. Ranaudo 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION REPORT NUMBER National Aeronautics and Space Administration Lewis Research Center E-7500 Cleveland, Ohio 44135-3191 9. SPONSORING/MONITORING AGENCY NAMES(S) AND ADDRESS(ES) 10. SPONSORING/MONITORING AGENCY REPORT NUMBER National Aeronautics and Space Administration NASA TM-105977 Washington, D.C. 20546-0001 AIAA-9341398 11. SUPPLEMENTARY NOTES Prepared for the 31st Aerospace Sciences Meeting and Exhibit sponsored by the American Institute of Aeronautics and Astronautics, Reno, Nevada, January 11-14, 1993. T.P. Ratvasky and R.J. Ranaudo, Lewis Research Center. Responsible person, T.P. Ratvasky, (216) 433-3905.
12a. DISTRIBUTION/AVAILABILITY STATEMENT 12b. DISTRIBUTION CODE Unclassified - Unlimited Subject Categories 08 13. ABSTRACT (Maximum 200 words) The effects of airframe icing on the stability and control characteristics of the NASA DH-6 Twin Otter icing research aircraft were investigated by flight test. The flight program was developed to obtain the stability and control param- eters of the DH-6 in a baseline ("uniced") configuration and an "artificially iced" configuration for specified thrust conditions. Stability and control parameter identification maneuvers were performed over a wide range of angles of attack for wing flaps retracted (0°) and wing flaps partially deflected (10°). Engine power was adjusted to hold thrust constant at one of three thrust coefficients (C T =0.14, C T =0.07, C T =0.00). This paper presents only the pitching- and yawing-moment results from the flight test program. Stability and control parameters were estimated for the uniced and artificially iced configurations using a modified stepwise regression algorithm. Comparisons of the uniced and iced stability and control parameters are presented for the majority of the flight envelope. The artificial ice reduced the elevator and rudder control effectiveness by 12% and 8% respectively for the 0 0 flap setting. The longitudinal static stability was also decreased substantially (approximately 10%) because of the tail ice. Further discussion is provided to explain some of the effects of ice on the stability and control parameters.
14. SUBJECT TERMS 15. NUMBER OF PAGES Aircraft icing; Stability and control; Flight data; Power effects 16. PRICE CODE A03 17. SECURITY CLASSIFICATION 18. SECURITY CLASSIFICATION 19. SECURITY CLASSIFICATION 20. LIMITATION OF ABSTRACT OF REPORT OF THIS PAGE OF ABSTRACT Unclassified Unclassified Unclassified NSN 7540-01-280-5500 Form 298 (Rev. 2-89) Standard Prescribed by ANSI Std. Z39-18 298-102 FOURTH CLASS MAIL National Aeronautics and Space Administration Lewis Research Center ADDRESS CORRECTION REQUESTED
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