Results for “wind tunnel testing” — Page 48

NASA NTRS2012

Check-Standard Testing Across Multiple Transonic Wind Tunnels with the Modern Design of Experiments

This paper reports the result of an analysis of wind tunnel data acquired in support of the Facility Analysis Verification & Operational Reliability (FAVOR) project. The analysis uses methods referred to collectively at Langley Research Center as the Modern Design of Experiments (MDOE). These methods quantify the total variance in a sample of wind tunnel data and partition it into explained and unexplained components. The unexplained component is further partitioned in random and systematic components. This analysis was performed on data acquired in similar wind tunnel tests executed in four different U.S. transonic facilities. The measurement environment of each facility was quantified and compared.

Deloach, Richard↗

NASA NTRS2023

X-59 Sonic Boom Test Results from the NASA Glenn 8- by 6-Foot Supersonic Wind Tunnel

A wind tunnel test was conducted to investigate near-field sonic boom pressure signatures of the X-59 Low-Boom Flight Demonstrator aircraft. A 1.62%-scale model of the aircraft was fabricated for the wind tunnel test, which took place in the NASA Glenn 8- by 6-Foot Supersonic Wind Tunnel in September and October 2021. The model had provisions for being mounted by a swept blade strut that attached at top of model ahead of the inlet, or by a rear-entry sting that held the model at the location of the nacelle. The model had alternate parts for ±0.5° deflections of the flaps, ailerons, and stabilator, and ±1° deflections of the T-tail. Off-body static pressure measurements of the flow field below the model were made on a pressure rail which had 420 orifices along its tip. The model was positioned at various heights from the rail by vertical movement of the tunnel strut, and at various longitudinal stations relative to the rail by means of a linear actuator mounted between the wind tunnel strut and the balance. Spatial averaging of model pressure signatures acquired over a range of longitudinal positions reduced the effects of tunnel flow distortions and the interference of the rail flow field and shocks on the model pressure signatures. The test was run at approximate Mach numbers of 1.36, 1.4, and 1.47, and the model was set at various angles of attack and roll relative to the rail. Plots of the model signatures for representative variations of Mach number, model angles, control deflections, and height relative to the rail are provided throughout the report. Repeatability was generally very good and gave confidence in the quality of the measurements. The signatures measured at various heights from the rail provided insight into the aging of the model shocks as they propagated from 1.2 to 3 body lengths from the model. Off-track signatures up to 45° from centerline obtained by rolling the model gave indications of the shock flow fields across the width of the sonic boom carpet. The deflections of the various control surfaces allowed assessment of the boom sensitivity to the control surface movements.

Sonic boom↗

NASA NTRS2023

X-59 Sonic Boom Test Results from the NASA Glenn 8- by 6-Foot Supersonic Wind Tunnel

A wind tunnel test was conducted to investigate near-field sonic boom pressure signatures of the X-59 Low-Boom Flight Demonstrator aircraft. A 1.62%-scale model of the aircraft was fabricated for the wind tunnel test, which took place in the NASA Glenn 8- by 6-Foot Supersonic Wind Tunnel in September and October 2021. The model had provisions for being mounted by a swept blade strut that attached at top of model ahead of the inlet, or by a rear-entry sting that held the model at the location of the nacelle. The model had alternate parts for ±0.5° deflections of the flaps, ailerons, and stabilator, and ±1° deflections of the T-tail. Off-body static pressure measurements of the flow field below the model were made on a pressure rail which had 420 orifices along its tip. The model was positioned at various heights from the rail by vertical movement of the tunnel strut, and at various longitudinal stations relative to the rail by means of a linear actuator mounted between the wind tunnel strut and the balance. Spatial averaging of model pressure signatures acquired over a range of longitudinal positions reduced the effects of tunnel flow distortions and the interference of the rail flow field and shocks on the model pressure signatures. The test was run at approximate Mach numbers of 1.36, 1.4, and 1.47, and the model was set at various angles of attack and roll relative to the rail. Plots of the model signatures for representative variations of Mach number, model angles, control deflections, and height relative to the rail are provided throughout the report. Repeatability was generally very good and gave confidence in the quality of the measurements. The signatures measured at various heights from the rail provided insight into the aging of the model shocks as they propagated from 1.2 to 3 body lengths from the model. Off-track signatures up to 45° from centerline obtained by rolling the model gave indications of the shock flow fields across the width of the sonic boom carpet. The deflections of the various control surfaces allowed assessment of the boom sensitivity to the control surface movements.

Sonic boom↗

NASA NTRS2014

Computed and Experimental Flutter/LCO Onset for the Boeing Truss-Braced Wing Wind-Tunnel Model

This paper presents high fidelity Navier-Stokes simulations of the Boeing Subsonic Ultra Green Aircraft Research truss-braced wing wind-tunnel model and compares the results to linear MSC. Nastran flutter analysis and preliminary data from a recent wind-tunnel test of that model at the NASA Langley Research Center Transonic Dynamics Tunnel. The simulated conditions under consideration are zero angle of attack, so that structural nonlinearity can be neglected. It is found that, for Mach number greater than 0.78, the linear flutter analysis predicts flutter onset dynamic pressure below the wind-tunnel test and that predicted by the Navier-Stokes analysis. Furthermore, the wind-tunnel test revealed that the majority of the high structural dynamics cases were wing limit cycle oscillation (LCO) rather than flutter. Most Navier-Stokes simulated cases were also LCO rather than hard flutter. There is dip in the wind-tunnel test flutter/LCO onset in the Mach 0.76-0.80 range. Conditions tested above that Mach number exhibited no aeroelastic instability at the dynamic pressures reached in the tunnel. The linear flutter analyses do not show a flutter/LCO dip. The Navier-Stokes simulations also do not reveal a dip; however, the flutter/LCO onset is at a significantly higher dynamic pressure at Mach 0.90 than at lower Mach numbers. The Navier-Stokes simulations indicate a mild LCO onset at Mach 0.82, then a more rapidly growing instability at Mach 0.86 and 0.90. Finally, the modeling issues and their solution related to the use of a beam and pod finite element model to generate the Navier-Stokes structure mode shapes are discussed.

Bartels, Robert E.↗

NASA NTRS2022

X-59 Sonic Boom Test Results from the NASA Glenn 8- by 6-Foot Supersonic Wind Tunnel

A wind tunnel test was conducted to investigate near-field sonic boom pressure signatures from a model of the X-59 Low-Boom Flight Demonstrator aircraft. A 1.62%-scale model of the aircraft in the C612A configuration was fabricated for the wind tunnel test, which took place in the NASA Glenn 8- by 6-Foot Supersonic Wind Tunnel in September and October 2021. The model had provisions for two different mounting options: a swept blade strut that attached at the top of model ahead of the inlet, and rear-entry sting that was made as one piece with a dummy nacelle, and which had a 2”-long cylindrical segment aft of the nozzle exit before tapering up in size. The blade strut allowed for a clean aft end of the model for evaluation of the shocks from that region, while the sting avoided the significant distortions of the flow and shocks from the blade strut along the top of the model. Both the sting and the strut had adapters that attached to a force balance. The model had alternate parts for ±0.5° deflections of the flaps, ailerons, and stabilator, and ±1° deflections of the T-tail horizontal surface. Off-body static pressure measurements of the flow field below the model were made by use of a pressure rail which had 420 orifices along its tip. The model was positioned at various heights from the rail by vertical movement of the wind tunnel strut, and at various longitudinal stations relative to the rail by means of a linear actuator mounted between the tunnel strut and the balance. The longitudinal positioning allowed multiple pressure signatures to be obtained along different portions of the rail. These signatures were aligned by accounting for the model longitudinal movement and then averaged to take out the effects of tunnel flow distortions and the interference of the rail flow field and shocks on the model pressure signatures. The test was run at approximate Mach numbers of 1.36, 1.4, and 1.47, and the model was set at various angles of attack and roll relative to the rail. Plots of the model signatures for all the variations of Mach number, model angles, control deflections, and height relative to the rail are provided throughout the report. Repeatability was generally very good and gave confidence in the quality of the measurements. The signatures measured at various heights from the rail provided insight into the aging of the model shocks as they propagated from 1.2 to 3 body lengths from the model. Off-track signatures up to 45° from centerline obtained by rolling the model gave indications of the shock flow fields across the width of the sonic boom carpet. The deflections of the various control surfaces allowed assessment of the boom sensitivity to the control surface movements.

Sonic boom↗

NASA NTRS1983

Orbiter Entry Heating Lessons Learned from Development Flight Test Program

The Space Shuttle orbiter's thermal protection system (TPS), designed mainly on the basis of wind tunnel test data, has successfully completed its design, development, and flight test program. The flight test data provide an exceptional opportunity to evaluate the use of wind tunnel test data for the design of TPS for reentry vehicles. Comparisons of flight test data against wind tunnel data used to design the orbiter's TPS were developed. These flight data, though still in the preliminary analysis phases, generally support the use of wind tunnel test data in the design of TPS for hypersonic reentry vehicles.

Haney, J. W., Jr.↗

NASA NTRS2013

Pressure-Sensitive Paints Advance Rotorcraft Design Testing

The rotors of certain helicopters can spin at speeds as high as 500 revolutions per minute. As the blades slice through the air, they flex, moving into the wind and back out, experiencing pressure changes on the order of thousands of times a second and even higher. All of this makes acquiring a true understanding of rotorcraft aerodynamics a difficult task. A traditional means of acquiring aerodynamic data is to conduct wind tunnel tests using a vehicle model outfitted with pressure taps and other sensors. These sensors add significant costs to wind tunnel testing while only providing measurements at discrete locations on the model's surface. In addition, standard sensor solutions do not work for pulling data from a rotor in motion. "Typical static pressure instrumentation can't handle that," explains Neal Watkins, electronics engineer in Langley Research Center s Advanced Sensing and Optical Measurement Branch. "There are dynamic pressure taps, but your costs go up by a factor of five to ten if you use those. In addition, recovery of the pressure tap readings is accomplished through slip rings, which allow only a limited amount of sensors and can require significant maintenance throughout a typical rotor test." One alternative to sensor-based wind tunnel testing is pressure sensitive paint (PSP). A coating of a specialized paint containing luminescent material is applied to the model. When exposed to an LED or laser light source, the material glows. The glowing material tends to be reactive to oxygen, explains Watkins, which causes the glow to diminish. The more oxygen that is present (or the more air present, since oxygen exists in a fixed proportion in air), the less the painted surface glows. Imaged with a camera, the areas experiencing greater air pressure show up darker than areas of less pressure. "The paint allows for a global pressure map as opposed to specific points," says Watkins. With PSP, each pixel recorded by the camera becomes an optical pressure tap. "Instead of having 100 or 200 pressure taps, you can have in theory several million, up to whatever the resolution of your camera is." Watkins explains that typical wind tunnel testing requires two models: one with very little instrumentation, and a pressure model with a significant amount of sensors applied. "If you can make all of your measurements on one model with PSP, you've decreased your model costs by at least a factor of two and preferably your testing costs by about that much," he says. PSP technology has been around for almost 20 years, but a PSP solution for gathering instantaneous dynamic pressure data from surfaces moving at high speeds, such as rotor blades, was not available until a NASA partnership led to a game-changing innovation.

Source record↗

NASA NTRSDate not supplied

Low-Speed Testing of the 5.2% Semispan CRM-HL in the DNW-NWB Wind Tunnel

In this paper the wind tunnel test of the 5.2% CRM-HL in the DNW-NWB low speed wind tunnel is described. The tunnel test campaign is settled in the DLR project ADaMant, in which it is of interest to generate qualitative data for CFD validation to improve the predictive accuracy, efficiency, and usability of physical modeling in CFD codes at the borders of the flight envelope. Different configurations of the CRM-HL were tested in a closed as well as in an open test section of the wind tunnel. Several measurement techniques were used to generate validation data including forces and moments, pressures, flow visualization with tufts and oil painting, and infrared thermography for boundary layer transition detection. The evaluation of the results focuses on these techniques in the closed test section. The test comprises Mach numbers from 0.15 to 0.23 and Reynolds numbers from 1.2x10 6 to 1.2x10 6 . Some results are also compared to data from the NASA Langley Research Center 14x22 Foot wind tunnel to assess the repeatability of measurements of the same model in different wind tunnels.

DLR↗

NASA NTRS2023

Initial Characterization of the TiltRotor Aeroelastic Stability Testbed

This paper discusses the initial wind tunnel test of the TiltRotor Aeroelastic Stability Testbed (TRAST). TRAST is a generic tiltrotor testbed developed in collaboration between NASA and the Army. Ultimately, this test was a checkout of the model systems, functionality and familiarization, but also obtained subcritical whirl-flutter data in the terms of frequency and damping. Flutter data include two main configurations with different pitch spring stiffness, referred to as 4k and 8k, that were tested at various rotor speeds and airspeeds at the NASA Langley Transonic Dynamics Tunnel. The test included two modes of drivetrain operation: powered and windmilling. However, powered mode of operation was only conducted with the 8k pitch spring. This test reinforced the traditional knowledge of whirl-flutter trends such as flutter speed would decrease with an increase in rotor speed. The critical mode consistently being the wing vertical bending mode. The chord mode as expected was not affected by the pitch spring and was likely to go unstable at a tunnel airspeed slightly beyond the wing vertical bending mode. There were also test specific challenges such as the TRAST modal damping was more sensitive to temperature and amplitude motor than was expected. This test gathered valuable data on the baseline characterization of TRAST, how to improve the model and test practices for future wind tunnel testing. Additionally, a new more automated method for experimental subcritical damping determination based on the Stockwell transform has been demonstrated that may lead to more consistent whirl-flutter stability boundaries.

whirl flutter↗

NASA NTRSDate not supplied

Initial Whirl-Flutter Characterization of the TiltRotor Aeroelastic Stability Testbed

This paper discusses the initial wind tunnel test of the TiltRotor Aeroelastic Stability Testbed (TRAST). TRAST is a generic tiltrotor testbed developed in collaboration between NASA and the Army. Ultimately, this test was a checkout of the model systems, functionality and familiarization, but also obtained subcritical whirl-flutter data in the terms of frequency and damping. Flutter data include two main configurations with different pitch spring stiffness, referred to as 4k and 8k, that were tested at various rotor speeds and airspeeds at the NASA Langley Transonic Dynamics Tunnel. The test included two modes of drivetrain operation: powered and windmilling. However, powered mode of operation was only conducted with the 8k pitch spring. This test reinforced the traditional knowledge of whirl-flutter trends such as flutter speed would decrease with an increase in rotor speed. The critical mode consistently being the wing vertical bending mode. The chord mode as expected was not affected by the pitch spring and was likely to go unstable at a tunnel airspeed slightly beyond the wing vertical bending mode. There were also test specific challenges such as the TRAST modal damping was more sensitive to temperature and amplitude motor than was expected. This test gathered valuable data on the baseline characterization of TRAST, how to improve the model and test practices for future wind tunnel testing. Additionally, a new more automated method for experimental subcritical damping determination based on the Stockwell transform has been demonstrated that may lead to more consistent whirl-flutter stability boundaries.

whirl flutter↗

NASA NTRS2003

Neural Network Modeling of UH-60A Pilot Vibration

Full-scale flight-test pilot floor vibration is modeled using neural networks and full-scale wind tunnel test data for low speed level flight conditions. Neural network connections between the wind tunnel test data and the tlxee flight test pilot vibration components (vertical, lateral, and longitudinal) are studied. Two full-scale UH-60A Black Hawk databases are used. The first database is the NASMArmy UH-60A Airloads Program flight test database. The second database is the UH-60A rotor-only wind tunnel database that was acquired in the NASA Ames SO- by 120- Foot Wind Tunnel with the Large Rotor Test Apparatus (LRTA). Using neural networks, the flight-test pilot vibration is modeled using the wind tunnel rotating system hub accelerations, and separately, using the hub loads. The results show that the wind tunnel rotating system hub accelerations and the operating parameters can represent the flight test pilot vibration. The six components of the wind tunnel N/rev balance-system hub loads and the operating parameters can also represent the flight test pilot vibration. The present neural network connections can significandy increase the value of wind tunnel testing.

Kottapalli, Sesi↗

NASA NTRS1920

Gottingen Wind Tunnel for Testing Aircraft Models

Given here is a brief description of the Gottingen Wind Tunnel for the testing of aircraft models, preceded by a history of its development. Included are a number of diagrams illustrating, among other things, a sectional elevation of the wind tunnel, the pressure regulator, the entrance cone and method of supporting a model for simple drag tests, a three-component balance, and a propeller testing device, all of which are discussed in the text.

Prandtl, L↗

NASA NTRS2011

The Crucial Role of Error Correlation for Uncertainty Modeling of CFD-Based Aerodynamics Increments

The Ares I ascent aerodynamics database for Design Cycle 3 (DAC-3) was built from wind-tunnel test results and CFD solutions. The wind tunnel results were used to build the baseline response surfaces for wind-tunnel Reynolds numbers at power-off conditions. The CFD solutions were used to build increments to account for Reynolds number effects. We calculate the validation errors for the primary CFD code results at wind tunnel Reynolds number power-off conditions and would like to be able to use those errors to predict the validation errors for the CFD increments. However, the validation errors are large compared to the increments. We suggest a way forward that is consistent with common practice in wind tunnel testing which is to assume that systematic errors in the measurement process and/or the environment will subtract out when increments are calculated, thus making increments more reliable with smaller uncertainty than absolute values of the aerodynamic coefficients. A similar practice has arisen for the use of CFD to generate aerodynamic database increments. The basis of this practice is the assumption of strong correlation of the systematic errors inherent in each of the results used to generate an increment. The assumption of strong correlation is the inferential link between the observed validation uncertainties at wind-tunnel Reynolds numbers and the uncertainties to be predicted for flight. In this paper, we suggest a way to estimate the correlation coefficient and demonstrate the approach using code-to-code differences that were obtained for quality control purposes during the Ares I CFD campaign. Finally, since we can expect the increments to be relatively small compared to the baseline response surface and to be typically of the order of the baseline uncertainty, we find that it is necessary to be able to show that the correlation coefficients are close to unity to avoid overinflating the overall database uncertainty with the addition of the increments.

Hemsch, Michael J.↗

NASA NTRS2021

Characterization of the NASA Glenn Research Center 8- by 6-Foot Supersonic Wind Tunnel (2019 Test)

There were several major modifications made to the NASA Glenn Research Center 8- by 6-Foot Supersonic Wind Tunnel between 2016 and 2019, including the 9- by 15-Foot Low Speed Wind Tunnel Acoustic Improvement Modifications. Following completion of these facility modifications, a characterization test was conducted in the 8- by 6-Foot Supersonic Wind Tunnel test section. This test entry collected data for a single test section porosity configuration across the entire operating range of the facility. Flow field data were collected at a cross-sectional plane and axially along test section center-line for use in quantifying the test section flow quality. Off-nominal supersonic conditions were surveyed through variation of balance chamber pressure at each of the discrete flexible wall nozzle settings. Additionally, a baseline check calibration data set was acquired during this entry.

8x6 SWT↗

NASA NTRS2013

System-Level Experimental Validations for Supersonic Commercial Transport Aircraft Entering Service in the 2018-2020 Time Period

This report describes the work conducted by The Boeing Company under American Recovery and Reinvestment Act (ARRA) and NASA funding to experimentally validate the conceptual design of a supersonic airliner feasible for entry into service in the 2018 to 2020 timeframe (NASA N+2 generation). The report discusses the design, analysis and development of a low-boom concept that meets aggressive sonic boom and performance goals for a cruise Mach number of 1.8. The design is achieved through integrated multidisciplinary optimization tools. The report also describes the detailed design and fabrication of both sonic boom and performance wind tunnel models of the low-boom concept. Additionally, a description of the detailed validation wind tunnel testing that was performed with the wind tunnel models is provided along with validation comparisons with pretest Computational Fluid Dynamics (CFD). Finally, the report describes the evaluation of existing NASA sonic boom pressure rail measurement instrumentation and a detailed description of new sonic boom measurement instrumentation that was constructed for the validation wind tunnel testing.

Magee, Todd E.↗

NASA NTRS2017

Estimates for the Aerodynamic Coefficients of Ringsail and Disk-Gap-Band Parachutes Operating on Mars

Models are presented for the aerodynamic coefficients of Supersonic Ringsail and Disk-Gap-Band parachutes as functions of total porosity, Lambda(sub t), Mach number, M, and total angle of attack, Alpha(sub t) (when necessary). The source aerodynamic coefficients data used for creating these models were obtained from a wind tunnel test of subscale parachutes. In this wind tunnel test, subscale parachutes of both parachute types were fabricated from two different fabrics with very different permeabilities. By varying the fabric permeability, while maintaining the parachute geometry constant, it was possible to vary Alpha(sub t). The fabric permeability test data necessary for the calculation of Alpha(sub t) were obtained from samples of the same fabrics used to fabricate the subscale parachutes. Although the models for the aerodynamic coefficients are simple polynomial functions of Alpha(sub t) and M, they are capable of producing good reproductions of the source data. The (Alpha(sub t), M) domains over which these models are applicable are clearly defined. The models are applicable to flight operations on Mars.

Cruz, Juan R.↗

NASA NTRS2017

Estimates for the Aerodynamic Coefficients of Ringsail and Disk-Gap-Band Parachutes Operating on Mars

The creation of flight dynamics simulations is often part of the design, development, and flight operations of missions that include entry, descent, and landing (EDL) in their concept of operation. Such flight dynamics simulations include models for many of the EDL sub-systems. For EDL systems that include a parachute, models of the parachute’s aerodynamic characteristics must be created for inclusion in the flight dynamics simulations. Models are presented for the aerodynamic coefficients (i.e., C(D),C(Tot),C(T),C(N), and C(m,SLCP)) of Supersonic Ringsail (SSRS) and Disk-Gap-Band (DGB) parachutes as functions of total porosity, λ(T), Mach number, M, and total angle of attack, λ(T) (when necessary). The source aerodynamic coefficients data used for creating these models were obtained from a wind tunnel test of subscale parachutes. In this wind tunnel test, subscale parachutes of both parachute types were fabricated from two different fabrics with very different permeabilities. By varying the fabric permeability, while maintaining the parachute geometry constant, it was possible to vary λ(T). The fabric permeability test data necessary for the calculation of λ(T) were obtained from samples of the same fabrics used to fabricate the subscale parachutes. Although the models for the aerodynamic coefficients are simple polynomial functions of λ(T) and M, they are capable of producing good reproductions of the source data. The (λ(T), M) domains over which these models are applicable are clearly defined. The models and their domains are applicable to flight operations on Mars. The models presented in this report are not unique – other models could be created from the source data. To make the creation of alternative numerical models, the aerodynamic coefficients source data are included in this report.

Cruz, Juan R.↗

NASA NTRS1988

Space shuttle phase B wind tunnel model and test information. Volume 2: Orbiter configuration

Archived wind tunnel test data are available for flyback booster or other alternate recoverable configurations as well as reusable orbiters studied during initial development (Phase B) of the Space Shuttle. Considerable wind tunnel data was acquired by the competing contractors and the NASA centers for an extensive variety of configurations with an array of wing and body planforms. All contractor and NASA wind tunnel test data acquiredin the Phase B development have been compiled into a database and are available for applying to current winged flyback or recoverable booster aerodynamic studies. The Space Shuttle Phase B Wind Tunnel Database is structured by vehicle component and configuration type. Basic components include the booster, the orbiter, and the launch vehicle. Booster configuration types include straight and delta wings, canard, cylindrical, retroglide, and twin body. Orbiter configuration types include straight and delta wings, lifting body, drop tanks, and double delta wings. Launch configration types include booster and orbiter components in various stacked and tandom combinations. The digital database consists of 220 files of data containing basic tunnel recorded data.

Glynn, J. L.↗