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Experimental processes, analytical methods, and numerical algorithms are described that may be used to predict the forces and moments of an internal strain–gage balance during a wind tunnel test. First, the control volume model of a strain–gage balance and the concepts of load state, load space, and output space are introduced. These important abstractions provide a better understanding of fundamental characteristics of different balance load prediction approaches. Then, the description of strain–gage balance data and the definition of the primary bridge sensitivity are discussed. Afterwards, basic elements of the calibration of a typical six–component balance are reviewed. Two fundamentally different balance load prediction methods, the processing of check loads, and related topics are also discussed. Three real–world balance data examples are reviewed in great detail to illustrate typical analysis results for a variety of strain–gage balance designs. Finally, important observations are summarized and recommendations are provided. – Additional information and detailed mathematical derivations can be found in the appendices of the document. They include the following topics: balance terminology, definitions of important statistical metrics, balance axis system conventions, balance load transformations, the combined load diagram, electrical output format options, bi–directional output characteristics, determination of the natural zeros, derivation of two balance load prediction methods, description of two tare load iteration algorithms, modeling of balance temperature effects, basics of three–component moment balances, definition of the percent contribution, detection of linear and near–linear dependencies in balance calibration data, a regression model search algorithm, balance interactions, and other related information.

This paper 1) documents findings and observations from the American Institute of Aeronautics and Astronautics (AIAA) Ground Test Technical Committee (GTTC) Future of Ground Test Working Group and the Applied Aeronautics Technical Committee (APATC) Collaborative Experiments & Computation Discussion Group, and 2) develops a more focused approach for sharing and advancing integrated development and use of physical experimental and computational capabilities for aerospace research and development. The GTTC and APATC are engaging with the larger AIAA technical community by creating a Focus Group on this topical area that will support working together on common interests in the public domain. This paper summarizes the knowledge capture from the last ten+ years and proposes a structure and scope going forward for the new, combined Focus Group.

Vinci is software that can be used to plan image-based measurements in wind tunnels. It allows the user to plan the placement of cameras and the choice of lenses well in advance of a test, thereby reducing the set-up time and cost when tunnel occupancy begins. It can also be used post-test to display data (pressure-sensitive paint, particle image velocimetry, model deformation) in context with the test article. Vinci is self-contained and runs on personal computers under Windows operating systems. No other software is required. Test articles are represented by CFD-like surface grids that may be read from an external file or created within the program as a combination of simple geometric shapes. The user controls the position and orientation of the test article through a Graphical User Interface (GUI) and may add many additional objects, including tunnel walls and windows, a wide variety of simple geometric shapes, mirrors, lamps, and laser sheets. The application computes simulated images from up to 40 cameras. Images are based on pinhole projection. Each camera is defined by the sensor size and the focal length of the lens. All camera parameters, including position and point angles, are controlled through the GUI. Simulated images are displayed in a window of the GUI and may be saved as bitmaps.

The objective of this work is to perform an uncertainty analysis of the deduced stagnation heat flux environment on a slug calorimeter for conditions that span the performance envelope of the Hypersonic Materials Environmental Test System arc-jet facility located at NASA Langley Research Center. Analytical solutions are developed for boundary-value problems on the slug element accounting for non-ideal effects, including spatial variation in the slug heat flux, multi-dimensional thermal conduction, and back-face losses, which departs from the state-of-the-art method derived from the American Society of Testing and Materials. Boundary-value problem definitions are informed by preliminary finite element thermal analysis of the slug calorimeter assembly (including both slug and housing) and just the slug element. The analytical solutions are presented in a general sense and in a truncated form from error analysis. Results are shown in optimizing and validating the analytical models against available slug back-face thermal data. The optimization results indicate that the appropriate epistemic uncertainty of the deduced stagnation heat flux on the slug calorimeter is at most±2.5% for both a high-and low-enthalpy test condition. In addition, a numerical approach is used to determine the aleatory (probabilistic) uncertainty component in the slug stagnation heat flux by applying a marching least-squares slope routine through the steady-state portion of the slug back-face thermal response. Results indicate a compromise between the number of samples and the filter frequency of slug back-face thermal data points when evaluating the standard deviation of the deduced stagnation heat flux statistics. When combining the mixed uncertainty, both aleatory and epistemic, the interval of uncertainty in the deduced stagnation heat flux is determined to be up to ±4%, which is at least a 60% reduction from the standard uncertainty used in the state-of-the-art method.

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.

This guide describes the Propulsion Systems Laboratory (PSL) at NASA Glenn Research Center (GRC) and was written to help customers utilizing the facility understand all the components of conducting a test program within the facility. The PSL complex supports two large engine test cells that simulate altitude flight conditions for a wide range of research and experimental tests. The test cells operate at altitudes up to 90,000 ft and speeds from subsonic to above supersonic. The way the facility sets test points at the engine or test article inlet, such as pressure, temperature, and Mach number is discussed. Support systems such as the heated and cooled combustion air system, the altitude exhaust system, the hydraulic system, the nitrogen, oxygen, and hydrogen systems, hydrogen burners, the engine exhaust gas-sampling system, and single- and multiple-axis thrust stands are addressed. Facility safety procedures, pre-test requirements, test operation standards are also stated in later sections. Past PSL tests and other capabilities are also discussed.

The aviation industry has long recognized the potential benefits of predictive maintenance, a maintenance strategy that leverages sensor and operational data to predict the future degradation of components. Prescriptive maintenance takes this a step further and considers the entire aviation ecosystem to schedule maintenance actions optimally. With the ability to reduce maintenance costs by up to 30%, as reported by the Department of Energy, these maintenance strategies have been identified to be an important investment to reduce a airline costs. However, despite great interest and technological advances in areas such as diagnostics, prognostics, sensing, computation, and machine learning, the adoption of predictive and prescriptive maintenance has not been widely applied in aviation. To shed light on this issue, we conducted an analysis of the barriers preventing or limiting the adoption of predictive and prescriptive maintenance in aviation. Through discussions with subject matter experts across industry, academia, standards bodies, and government, we identified five key challenges: complexity of prediction; validation, safety assurance, and regulatory challenges; cost of adoption; difficulty in quantifying impact and informing decisions; and data availability, quality, and ownership challenges. This study provides a detailed overview of these barriers and areas where stakeholders could invest to overcome them, aiming to support the scaled adoption of predictive and prescriptive maintenance in aviation.

This paper presents methods and results of a measurement uncertainty analysis that was performed for the 8- by 6-foot Supersonic Wind Tunnel located at the NASA Glenn Research Center. The uncertainty analysis is based on data collected during a characterization test following major structural modifications to the facility and upgrades to the facility’s data and control systems. The statistical methods and engineering judgments used to estimate elemental uncertainties are described in this report. The Monte Carlo method of propagating uncertainty was selected to determine the uncertainty of calculated variables of interest. A description of the Monte Carlo method as applied for this analysis is provided. The primary variable of interest (VOI) for this facility is free stream Mach number. In addition to determining the uncertainty in Mach number, the uncertainty in free stream values of static pressure, total pressure, dynamic pressure, total temperature, static temperature, Reynolds number, and air speed were also calculated. Uncertainty results are presented as random (unpredictable variation in repeated measurements), systematic (potential offset between observed and true value), and total (random and systematic combined) uncertainty for Mach number. Systematic uncertainty results are presented for the other VOIs. Individual uncertainty sources are presented both dimensionally and as percent contributions to uncertainty in all VOIs, to aid in the identification of primary uncertainty sources.

The National Aeronautics and Space Administration is supporting research to develop a prototype remote vehicle operations center at Langley Research Center to explore current and future advanced air mobility operations using small unmanned aerial systems vehicles as surrogates for future, larger-scale passenger carrying vehicles. Data collected within the Remote Operations for Autonomous Missions (ROAM) Unmanned Aerial Systems (UAS) Operations Center will be used to explore different roles and responsibilities of remote operators managing multiple autonomous vehicles, with the goal of exploring human-autonomy teaming concepts that enable m:N operations (i.e., m operators managing N vehicles). ROAM has developed into a world-class research, development, and technology (RD&T) environment that can support both the collection of human factors data and the command and control of remote vehicles in beyond visual line of sight conditions. Presented in this paper is an overview of ROAM, with a focus on the design components that support human factors data collection and a review of initial usability results of the facility.

The National Aeronautics and Space Administration is supporting research to develop a prototype remote vehicle operations center at Langley Research Center to explore current and future advanced air mobility operations using small unmanned aerial systems vehicles as surrogates for future, larger-scale passenger carrying vehicles. Data collected within the Remote Operations for Autonomous Missions (ROAM) Unmanned Aerial Systems (UAS) Operations Center will be used to explore different roles and responsibilities of remote operators managing multiple autonomous vehicles, with the goal of exploring human-autonomy teaming concepts that enable m:N operations (i.e., m operators managing N vehicles). ROAM has developed into a world-class research, development, and technology (RD&T) environment that can support both the collection of human factors data and the command and control of remote vehicles in beyond visual line of sight conditions. Presented in this paper is an overview of ROAM, with a focus on the design components that support human factors data collection and a review of initial usability results of the facility.

This technical memorandum describes the development of a new natural gas/oxygen (NG/O2) fueled burner rig to be used for high-temperature environmental durability studies of advanced materials and components at atmospheric pressure. The burner simulates the high-temperature, high-heat flux, and high-velocity thermal environments encountered in aerospace applications. It will be used to study environmental effects such as water vapor interactions relevant to advanced gas turbine engine materials such as ceramic matrix composites with protective environmental barrier coatings. The highest sample temperature achieved to date in a study of the oxidation and recession of monolithic silicon carbide is 3000 °F.

Welcome to the Eight by six foot Supersonic Wind Tunnel Research Facility located at the NASA Glenn Research Center in Cleveland, OH. This wind tunnel complex is part of NASA's Aerosciences Evaluation and Test Capabilities (AETC) portfolio of testing facilities. Complex hosts two wind tunnels 8 x 6 for supersonic testing and the 9 x 15 for low-speed acoustic testing. Explore the lobby and view the different objects within. Once you are looking at an object you can left click for additional information. All items in lobby are interactive, and can be viewed using the arrow keys and mouse as indicated on the bottom of the video.

Experimental processes, analytical methods, and numerical algorithms are described that may be used to predict the forces and moments of an internal strain-gage balance during a wind tunnel test. First, the control volume model of a strain-gage balance and the concepts of load state, load space, and output space are introduced. These important abstractions provide a better understanding of fundamental characteristics of different balance load prediction approaches. Then, the description of strain-gage balance data and the definition of the primary gage sensitivity is discussed. Afterwards, basic elements of the calibration of a typical six-component balance are reviewed. Two fundamentally different balance load prediction methods, the processing of check loads, and related topics are also discussed. Three real-world balance data examples are reviewed in great detail to illustrate typical analysis results for a variety of strain-gage balance designs. Finally, important observations are summarized and recommendations are provided. Additional information and detailed mathematical derivations can be found in the appendices of the document. They include the following topics: balance terminology, definitions of important statistical metrics, balance axis system conventions, balance load transformations, the combined load diagram, electrical output format options, bi-directional gage output characteristics, determination of the natural zeros, derivation of two balance load prediction methods, description of two tare load iteration algorithms, modeling of balance temperature effects, basics of three-component moment balances, definition of the percent contribution, detection of linear and near-linear dependencies in balance calibration data, a regression model term selection algorithm, and other related topics.

This paper presents the results of the measurement uncertainty analysis that was performed on the aero-thermal characteristics of the 6- by 9-Foot Icing Research Tunnel (IRT) at the NASA Glenn Research Center. The engineering judgments and statistical methods used to determine the elemental uncertainties are described. Instrumentation uncertainty was quanti�ed using MANTUS (Measurement Analysis Tool for Uncertainty in Systems) and instrument speci�cation sheets. The Monte Carlo method was used to propagate systematic components of uncertainty in order to quantify the uncertainty of the Variables of Interest (VOI). A detailed description of the Monte Carlo method and the MANTUS tool can be found in the Uncertainty Analysis of the NASA Glenn 8x6 Supersonic Wind Tunnel report [1]. Detailed uncertainty results for test section airspeed and temperature as well as other variables of interest are described within this document.

The NASA Glenn Research Center 2019 Icing Research Tunnel cloud calibration results are presented in this paper. The current status of the cloud uniformity, liquid water content, and drop-size calibration results will be discussed. The goals achieved in this calibration were to establish a uniform cloud and to generate transfer functions from the inputs of airspeed, spray bar atomizing air pressure, and spray bar water pressure to the outputs of median volumetric diameter (drop size distributions) and liquid water content. This was completed for both 14 CFR Parts 25 and 29, Appendix C (“typical” icing) and Appendix O (supercooled large drop) conditions. The cloud uniformity from the Standard nozzles has remained the same as what was reported for the 2014 full calibration. Changes were made to the Mod1 nozzle cloud, resulting in higher liquid water content values associated with the Mod1 cloud.

The C-5 Electrical Substation (C5ES) is a National Aeronautics and Space Administration (NASA) operated electrical power substation located at the John F. Kennedy Space Center (KSC), Florida. This facility has been designated Solid Waste Management Unit (SWMU) 066 under KSC’s Resource Conservation and Recovery Act (RCRA) Corrective Action program. This Performance Monitoring Report (PMR) presents the Interim Measure (IM) activities, including baseline sampling, air sparge system construction and operation, and performance monitoring, that were completed to remediate chlorinated volatile organic compounds (CVOC) in groundwater exceeding the Florida Department of Environmental Protection (FDEP) natural attenuation default concentrations (NADC).

Demonstrate 50% improvement in efficient operational capability using a Variable-Speed Power Turbine concept. To enable this improvement, thermodynamics mechanical challenges from operating across variable shaft speeds must be accommodated. Also, aerodynamics research for the engine high-efficiency turbine component design must be conducted over a wide range of incidence angle variation.

Following completion of the 9- by 15-Foot Low Speed Wind Tunnel acoustic improvement modification project, a characterization of the flow field throughout the 9- by 15-foot test section was conducted in 2019. The acoustic improvement modifications project included several large-scale tunnel loop modifications and reconstruction of the 9- by 15-Foot Low Speed Wind Tunnel test section and diffuser to decrease the noise floor in the test section. Data were collected at three cross-sectional planes in the 9- by 15-ft test section using a 15-foot traversing calibration rake and a set of eight boundary layer rakes. The data from the characterization test were used to generate calibration relationships for facility operation and understand the flow quality in the new test section, including uniformity, flow angularity, turbulence intensity, and boundary layer characteristics. Additionally, the subsonic quick check rake was used to baseline the check calibration data set for the new test section.

A full aerothermal characterization of the NASA Glenn Icing Research Tunnel (IRT) was completed in August 2019. A mandatory maintenance period required the test entry to be separated into two phases: the first occurring in April 2019 and the second in August 2019. The hardware used during this test entry consisted of the 6-foot quick-check rake, 6-foot traversing rake, RTD array, and hot-wire rake. The 6-foot quick check rake collects static pressure, total pressure, total temperature, and flow angularity data along the centerline of the test section. The data from the 6-foot quick-check rake were used to generate test section calibration relationships for total and static pressure as well as implement statistical process control. The 6-foot traversing rake collects flow uniformity data across the test section for various flow parameters, such as static pressure, total pressure, and flow angularity. Total temperature flow uniformity data is mapped by the RTD array and is used to generate the test section calibration relationship for total temperature. The hot-wire rake measures turbulence intensity at three lateral locations and characterizes airspeed unsteadiness in the test section. The test entry resulted in updated calibration relationships and a full characterization of test section flow quality and flow uniformity in the IRT.

Over the course of four years, a team of aerospace engineers at the National Aeronautics and Space Administration Armstrong Flight Research Center completed four projects, each with the objective to research sonic boom signatures from a ground and building level perspective. The relatively compressed timeline of these projects resulted in the team amassing a large number of lessons learned. With each successive project, these lessons have been more relied upon and referenced. This report serves as a written record of the teams tribal knowledge capturing the relevant lessons learned and their importance for future projects.

The document for review is a chapter for a new AGARD document on wind tunnel wall interference. The chapter describes NASA's current approach to wind tunnel wall interference assessment by using the implementation of the wall interference correction system of the NASA Ames 11-ft Transonic Wind Tunnel as an example.

Among all the ground test facilities that have been developed over the past 7 decades for testing TPS, arc jet ranks as the most flight relevant and extensively used test facility in the history of TPS development in the US. Arc Jet facilities played, and continue to play, a critical role not only in the early screening and selection of TPS materials, but more importantly, in the flight vehicle integrated development and in the flight qualification.

This paper presents an uncertainty analysis of the stagnation-point calibration probe surface predictions for conditions that span the performance envelope of the Hypersonic Materials Environmental Test System facility located at NASA Langley Research Center. A second-order stochastic expansion was constructed over 47 uncertain parameters to evaluate the sensitivities, identify the most significant uncertain variables, and quantify the uncertainty in the stagnation-point heat flux and pressure predictions of the calibration probe for a low- and high-enthalpy test condition. A sensitivity analysis showed that measurement bias uncertainty is the most significant contributor to the stagnation-point pressure and heat flux variance for the low-enthalpy condition. For the high-enthalpy condition, a paradigm shift in sensitivities revealed the computational fluid dynamics model input uncertainty as the main contributor. A comparison between the prediction and measurement of the stagnation-point conditions under uncertainty showed that there was evidence of statistical disagreement. A validation metric was proposed and applied to the prediction uncertainty to account for the statistical disagreement when compared to the possible stagnation-point heat flux and pressure measurements.

The Tiltrotor Test Rig (TTR) is a new NASA facility for testing full-scale proprotors. The first test campaign in the National Full-Scale Aerodynamics Facility (NFAC) concluded in November 2018. The wind-tunnel test included vertical climb conditions; that is, axial flow at low airspeeds (true hover is not possible in the NFAC). The rotor tested was the Bell Model 699, a 609 rotor modified specifically for wind-tunnel testing. The rotor was tested under a variety of NFAC configurations, some unprecedented and unique to vertical climb. Researchers must understand the differences in configuration if they are to make proper use of the data. This paper presents results for several different test configurations, including assessments of data quality. Comparisons with earlier tests of a similar rotor, the 0.656- scale Joint Vertical Experimental (JVX) rotor, are included to provide additional insights into rotor and wind tunnel behavior.

The X-56A Multi-Utility Technology Testbed (MUTT) is a subscale, fixed-wing aircraft designed for high-risk aeroelastic flight demonstration and research. Structural dynamics ground testing for model validation was especially important for this vehicle because the structural model was directly used in the development of a flight control system with active flutter suppression capabilities. Structural dynamics ground tests of the X-56A MUTT with coupled rigid-body and structural modes provided a unique set of challenges. An overview of the ground vibration test (GVT) and moment of inertia (MOI) test setup and execution is presented. The series of GVTs included the wing by itself attached to a strongback and complete vehicle at two mass conditions: empty and full fuel. Two boundary conditions for the complete-vehicle test were studied: on landing gear and suspended free-free. Pitch MOI tests were performed using a compound pendulum method and repeated with two different pendulum lengths for independent verification. The original soft-support test configuration for the GVT used multiple bungees, resulting in unforeseen coupling interactions between the soft-support bungees and the vehicle structural modes. To resolve this problem, the soft-support test setup underwent multiple iterations. The various GVT configurations and boundary-condition modifications are highlighted and explained. Lessons learned are captured for future consideration when performing structural dynamics testing with similar vehicles.

NASA has a significant maintenance challenge with the agency’s aging wind tunnel infrastructure. Wind tunnel blades, such as the ones in the National Transonic Facility at NASA Langley Research Center, have been subjected to damage from impacts and fatigue. Accurate analytical models of these blades are necessary to either recertify replacement blades to be built or for redesign of these blades. In this paper a process for generating structural finite element models of these wind tunnel blades is presented. The model developed in this paper was analyzed under loading conditions from tests conducted on the original blades and the results are compared with legacy strain gage data.

Infra-red thermography can visualize surface flow features including boundary layer transition, shock impingement, streamwise vortex impingement, flow separation, and buffet. The Infra-red thermography system at the NASA ARC Unitary Plan Wind Tunnel allows for continuous monitoring of wind tunnel models with up to four cameras simultaneously. For best results the models should be covered with a high emissivity coating, and the images processed to enhance contrast. However image processing algorithms allow some flow information to be recovered even from uncoated models.

Although there has been no physical change to the cloud drop diameters in the NASA Glenn Icing Research Tunnel (IRT), the IRT cloud calibration team now has an improved understanding of the facility’s drop-sizing instrumentation, which has resulted in a recent change to the drop-sizing equations. Only the calculated values given in the previous calibration report have changed. In 2017, IRT staff found reason to believe that since at least 2014, the sample area for its Cloud Droplet Probe (CDP) (Droplet Measurement Technologies, Inc.) has been closer to 0.289 mm2, rather than the user manual’s suggested value of 0.24 mm2. In September 2017, the probe’s sample area was measured both before and after the probe was realigned, and the end sample area was measured to be 0.248 mm2. Following the probe’s realignment, drop size measurements were made in the IRT using the CDP as well as optical array probes OAP–230X and OAP–230Y (Particle Measurement Systems, Inc.). These measurements suggested that 0.289 mm2 was the more accurate value for historical measurements. When the CDP sample area used for calculations was changed from 0.24 to 0.289 mm2, distributions previously reported to have a median volumetric diameter (MVD) between 30 and 100 μm were instead calculated to have MVD values 10 to 18 percent higher. The analyses that led to these conclusions are reported in this paper, as well as the new drop-sizing equations that have been developed for the corrected measurement values. This report contains updates to drop-sizing data for the IRT’s “normal” operating conditions (MVD < 50 μm) and discusses the effects on the IRT’s “large-drop” conditions (Mod1 nozzles, Pair < 10 psig), but it does not include updates to the drop-sizing equations for those large-drop conditions.

In December 2010, NASA deployed for the first time the Multiple Altimeter Beam Experimental Lidar (MABEL), an airborne simulator for Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) algorithm development. Between 2010 and 2013, engineering flights were conducted in the continental United States, to ready the instrument for deployments to Alaska and Iceland, where flight lines could be designed and flown over sea ice and grounded ice. Ultimately, MABEL engineering missions included: 1) flights based out of NASA Armstrong Flight Research Center (California, formerly Dryden Flight Research Center) in 2010, 2011, and 2012; flights based out of NASA Wallops Flight Facility (Virginia) in 2012; flights based out of NASA Langley Research Center (Virginia) in 2013; and flights based out of the Mojave Air and Space Port (California) in 2013.

The training of pilots at major US air carriers has changed little over the years. These courses often begin in learning each and every sub-system of the particular airplane to be flown. The training course culminates in a series of training sessions in a full-motion, full-mission flight simulator. Most US airlines now incorporate one final simulator training session known as LOFT, Line Oriented Flight Training, where rather than going through a series of disconnected, isolated, flight maneuvers, the session is conducted as a flight from a departure airport to a destination airport. Flying for an Air Line, one is a Line Pilot, flying the "line." And so the LOFT session in the simulator is supposed to represent the reality of line operations and thus prepare the trainee to fly the line. But if the ultimate goal of the training is to produce a pilot who is ready to safely and efficiently fly the line, shouldn't all training be "line oriented"? This paper describes an approach to structuring airline flight training such that all training is "line oriented." This approach represents an opportunity to translate many of the training principles offered by Healy and her colleagues into training specifications.

A prototype light extinction tomography system has been developed for acquiring real-time in-situ icing cloud uniformity and density measurements in the NASA Glenn Research Center's Icing Research Tunnel (IRT). These measurements are currently obtained through periodic manual calibrations of the IRT. These calibrations are time consuming and assume that cloud uniformity and density does not greatly vary between the periodic calibrations. It is envisioned that the new light extinction tomography system will provide the means to make these measurements in-situ in real-time and minimize the need for these manual calibrations. This new system uses the principle of light extinction tomography to measure the spray density and distribution in the test section. The prototype system was installed and successfully demonstrated in the Icing Research Tunnel in early 2018. Data sets were acquired for several standard spray and simulated fault conditions to assess system capability and sensitivity. This paper will describe the prototype light extinction system, the theory behind it, and the results of the demonstration test that was conducted in the IRT.

A fundamental improvement of a convergence test for wind tunnel strain-gage balance load iterations was developed. The improvement became necessary because incorrect test results were obtained whenever the original test was applied to multi-component balances with large load capacity differences. The original test was first published in NASA TN D-6860. It uses an upper bound of the Lipschitz constant to assess convergence characteristics of balance load predictions whenever the Iterative Method is applied. The Lipschitz constant is a function of the partial derivatives of each balance load component with respect to all other load components. Unfortunately, the original definition of the convergence test overlooked the fact that the Lipschitz constant is a dimensionless quantity and that the partial derivative of one load component with respect to another load component is not always dimensionless. Therefore, an improvement of the original test was successfully developed that uses load capacities to make all inputs for the calculation of the Lipschitz constant dimensionless before use. Results from the calibration data analysis of a six-component force balance and a five-component semi-span balance are used to illustrate the application of the improved load iteration convergence test.

Fundamental characteristics of design, calibration, and application of three-component moment balances are investigated in great detail. These balances are typically used to determine loads on control surfaces, canards, or other parts that are attached to a wind tunnel model. First, three different descriptions of the load state of a moment balance are reviewed. Then, load transformations between different load formats and the combined load diagram for two of the three load components are discussed. An error analysis showed that it is critical to maximize the product of the distance between the bending moment gages and their sensitivities in order to minimize the overall error in the normal force prediction. In addition, it is important to apply a sufficient number of calibration loadings near the first bending moment gage. Then, unwanted near-linear dependencies between the two bending moment gage outputs can be avoided. The error in the bending moment prediction is also investigated that results from the elastic deformation of the metric part of the balance under load. Finally, the application of the Non-Iterative Method to three-component moment balance calibration data is described in order to obtain regression models that can be used to predict loads from measured outputs during a wind tunnel test.

Fundamental characteristics of three gage output formats are discussed that may be used to both interpret and analyze wind tunnel strain-gage balance data. The first output format uses raw outputs, i.e., absolute voltage measurements, for the analysis. This choice requires an intercept term in the regression model of the outputs if the Iterative Method is chosen for the load prediction. Raw outputs can be used for the analysis of all known output characteristics as long as the Iterative Method is applied. However, raw outputs cannot be used to analyze data of a balance with bi-directional outputs if the Non-Iterative Method is chosen for the analysis. The second output format, i.e., difference type 1, uses the difference between raw outputs and the natural zeros of the balance gages for the analysis. In this case, the use of the intercept term becomes optional. Analysis results for difference type 1 will exactly match analysis results obtained by using raw outputs as long as identical math models are used for the regression analysis. In addition, difference type 1 may be used to analyze data of a balance with bi directional outputs if an analyst prefers to process data using the Non-Iterative Method. The third output format, i.e., difference type 2, uses the difference between raw outputs and the outputs of the zero load point of a load series for the data analysis. The application of this format is only recommended if the maximum magnitude of all tare loads of a given balance calibration data set is less than two percent of capacity. Data from the calibration of a force balance is used to illustrate the application of the three gage output formats.

The 14-by 22-Foot Subsonic Tunnel has the capability to simulate propulsion and augmented lift using high pressure air supplied by a variety of air stations. During a customer test in 2018, the chosen air station did not provide the necessary air flow required for the test, so an effort was made to revive a decommissioned air station in a brief time window. This presentation summarizes the high pressure air capabilities of the 14x22 and the challenges of reactivating an air station.

This document provides a description of equations used to calculate test section dynamic pressure in the 14- by 22-Foot Subsonic Tunnel. The equation used to calculate dynamic pressure is dependent on the test section configuration.

The ANCF test article was relocated to the University of Notre Dame. A sample of the farfield acoustic data is shown, comparing the AAPL to the White Sands facility results.

A study of the Weber Number effects on droplets in the NASA Icing Research Tunnel is described. The work focuses on examining the droplet Weber Number effects observed for droplets accelerated by air flow in the contraction section of the Icing Research Tunnel to the test section. These results will aid in Supercooled Large Drop facility design studies. Measurements acquired with the Phase Doppler Interferometer and High Speed Imaging Dual Range Flight Probes at a series of locations through the contraction are presented alongside a 1D numerical model developed during this study to aid interpretation of the experimental results. An estimate of the maximum Weber Number observed in the Icing Research Tunnel for varying drop sizes up to 1000 μm is presented and provided for incorporation into future design studies. Finally, experimental results coupled with a numerical model indicate that breakup of drops up to 1000 μm is not occurring in the NASA Icing Research Tunnel up to 129 m/s.

A flow quality survey (FQS) was conducted in December 2015 and January 2016 to characterize the flow quality of the 9- by 15-Foot Low-Speed Wind Tunnel (9×15 LSWT) test section prior to the start of significant structural and acoustic modifications. The data from this FQS will be compared with data collected during a replicated FQS after completion of the acoustic improvement modifications. This document contains only the FQS data collected in December 2015 and January 2016 using the 15-ft survey rake and the 18-in. boundary layer rakes in the 9×15 LSWT. The spatial variation at one axial test section station (TSTA), nominally TSTA 198, and five vertical heights of the 15-ft survey rake was computed for Mach number, velocity, total and static pressure, total temperature, and flow angularity (pitch and yaw). Three hot-wire probes mounted to the 15-ft survey rake were used to measure turbulence intensity; however, data from a previous test entry were used as the mean turbulence intensity baseline value, as there were issues with the hot-wire performance. The boundary layer pressure profiles around the perimeter of the test section at TSTA 199 were also measured and the boundary layer heights computed. All calculated results are tabulated for each facility condition set point.

The supersonic/hypersonic ground testing serves a multitude of purposes and objectives. From structural and material integrity, to force and moment models; from pressure mapping, thermal imaging, shock structure to scramjet/ramjet engine operability and ignition studies. Hypersonics has become more of a high profile area of late. Compared to flight testing, ground testing typically it is less expensive and usually is not a one single-test test program. It is more forgiving in the fact that a test program can utilize a single test article and get data from a number of tests. Ground test data is the input to the formation of research databases, as well as, validation of CFD models/tools. To understand the output, one must first understand the inputs. To achieve supersonic/hypersonic speeds the use of compressors or compressed air storage along with converging-diverging nozzles are needed. Flight temperatures also need to be achieved for the ground test to truly simulate flight conditions. At NASA Langley's 8' High Temperature Tunnel (HTT), compressed natural gas (methane) is burned to heat the air. To validate that the desired test condition is met, test instrumentation is used and data is collected from the combustor all the way through the nozzle exit plane. In this talk, NASA Langley's 8' HTT will be the basis for what kind of test capabilities hypersonic ground testing offers. It certainly does not offer every capability within ground testing, nor will the discussion cover all types. Specific test techniques used and data collection methods will be discussed and how these confirm certain flight conditions have been achieved. There will be subsequent thoughts on experimental methods that aid test articles such as thrust stands, model actuation, etc.

A review is provided of recent aerothermodynamic ground-test contributions by NASA Langley Research Center (LaRC) to the BOLT flight test program. Several test entries into the Langley Aerothermodynamic Laboratory 20-Inch Mach 6 Air Tunnel are discussed. These entries were intended to support the development and design of flight hardware and instrumentation. Some trends and observations from these entries are provided. Also, a comparison of two different global heat transfer test techniques is included and discussed.

A recent experiment at NASA Ames Research Center’s Vertical Motion Simulator (VMS) successfully combined a real-time, human in-the-loop architecture with the flexibility of operating in the Simulink® graphical model-based engineering environment. The VMS is a large amplitude flight simulator designed to be adaptable to provide rapid integration and development of a wide variety of vehicles and support diverse aeronautical investigations. Math models are often programmed in Simulink. Typically, to run Simulink models in real time, they are converted to C code. However, the conversion and integration process can be time consuming and cumbersome. Thus, the VMS facility capabilities were expanded to allow a Simulink vehicle math model to run in the MathWorks’ MATLAB environment during a piloted full-motion simulation experiment. The MATLAB Simulink based approach to driving the VMS was found to decrease development time by allowing quick integration of math model changes and providing the ability to run the same version of the model on researcher’s desktop computers. This accomplishment demonstrated that the development ease of the graphical Simulink environment could be retained, while working within the real-time environment of the VMS architecture and maintaining the unique flexibility of the VMS.

A recent experiment at NASA Ames Research Center’s Vertical Motion Simulator (VMS) successfully combined a real-time, human in-the-loop architecture with the flexibility of operating in the Simulink® graphical model-based engineering environment. The VMS is a large amplitude flight simulator designed to be adaptable to provide rapid integration and development of a wide variety of vehicles and support diverse aeronautical investigations. Math models are often programmed in Simulink. Typically, to run Simulink models in real time, they are converted to C code. However, the conversion and integration process can be time consuming and cumbersome. Thus, the VMS facility capabilities were expanded to allow a Simulink vehicle math model to run in the MathWorks’ MATLAB environment during a piloted full-motion simulation experiment. The MATLAB Simulink based approach to driving the VMS was found to decrease development time by allowing quick integration of math model changes and providing the ability to run the same version of the model on researcher’s desktop computers. This accomplishment demonstrated that the development ease of the graphical Simulink environment could be retained, while working within the real-time environment of the VMS architecture and maintaining the unique flexibility of the VMS.

This paper discusses ballistic range testing at muzzle velocities of 0.7 to 2.7 km/s. Herein, we review several techniques for achieving these velocities - starting with the single stage gas gun and the powder gun. These techniques can have velocity limitations, both on the high end and on the low end, very high powder breech pressures, incomplete and inconsistent powder burn and can send unburned powder grains downrange to confound impact data. To try to resolve these issues, it was decided to study the use of the two stage light gas gun operated with a heavier working gas than is normally used. This would have the effect of lowering the usual muzzle velocity range of the two-stage gun using hydrogen to cover the desired low velocity range. Preliminary results are presented from firings with two NASA guns. Twenty-five shots were made with helium and nine shots with argon. Muzzle velocities of 1.1 to 4 km/s were obtained with helium and velocities of 0.7 to 2.7 km/s were obtained with argon. Overall, the heavy gas technique appears quite promising, but more firings are needed to fill out the data base.

Two large finned-tube heat exchangers at the NASA-GRC 10x10 SWT experienced significant freezing damage in January 2018. A recap of the incident, causes and repair issues will be presented.

A limited blockage study was performed in December 2017 to explore exceeding the current published blockage curve for the NASA Glenn 10- by 10-Foot (10x10) Supersonic Wind Tunnel (SWT) at two discrete operating conditions. For the two points tested, the tunnel was found to start outside of the published starting limitations curve, above a certain threshold of Mach and stagnation pressure. Blockage theory was reviewed to further understand these results. In order to gain a firm understanding of the aerodynamic effects a more-detailed follow up blockage study is recommended.

Prior to the NASA Glenn Research Center 9- by 15-Foot Low-Speed Wind Tunnel (9x15 LSWT) undergoing significant structural and acoustic modifications beginning in 2017, a flow quality survey (FQS) was conducted to characterize the flow quality of the 8- by 6-Foot Supersonic Wind Tunnel (8x6 SWT) test section and facility air dryer. The data from this FQS will be compared to data collected during a FQS following the completion of the 9x15 LSWT Acoustic Improvement Modifications. This document contains only the FQS data collected in November 2015 using the 16-inch-diameter cone cylinder and a set of twenty air dryer bed wind anemometers. The ability to reach the extents of the 8x6 SWT operating envelope with a large blockage model was verified through the 16-inch-diameter cone cylinder tests. The flow uniformity and angularity at the entrance of the facility air dryer was assessed and quantified using the air dryer bed wind anemometers.