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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 775 records · Page 43

Effects of Free Molecular Heating on the Space Shuttle Active Thermal Control System

During Space Transportation System (STS) flight 121, higher than predicted radiator outlet temperatures were experienced from post insertion and up until nominal correction (NC) burn two. Effects from the higher than predicted heat loads on the radiator panels led to an additional 50 lbm of supply water consumed by the Flash Evaporator System (FES). Post-flight analysis and research revealed that the additional heat loads were due to Free Molecular Heating (FMH) on the radiator panels, which previously had not been considered as a significant environmental factor for the Space Shuttle radiators. The current Orbiter radiator heat flux models were adapted to incorporate the effects of FMH in addition to solar, earth infrared and albedo sources. Previous STS flights were also examined to find additional flight data on the FMH environment. Results of the model were compared to flight data and verified against results generated by the National Aeronautics and Space Administration (NASA), Johnson Space Center (JSC) Aero-sciences group to verify the accuracy of the model.

McCloud, Peter L.↗

Application of a Near Infrared Imaging System for Thermographic Imaging of the Space Shuttle during Hypersonic Re-Entry

High resolution calibrated near infrared (NIR) imagery was obtained of the Space Shuttle s reentry during STS-119, STS-125, and STS-128 missions. The infrared imagery was collected using a US Navy NP-3D Orion aircraft using a long-range infrared optical package referred to as Cast Glance. The slant ranges between the Space Shuttle and Cast Glance were approximately 26-41 nautical miles at point of closest approach. The Hypersonic Thermodynamic Infrared Measurements (HYTHIRM) project was a NASA Langley led endeavor sponsored by the NASA Engineering Safety Center, the Space Shuttle Program Office and the NASA Aeronautics Research Mission Directorate to demonstrate a quantitative thermal imaging capability. HYTHIRM required several mission tools to acquire the imagery. These tools include pre-mission acquisition simulations of the Shuttle trajectory in relationship to the Cast Glance aircraft flight path, radiance modeling to predict the infrared response of the Shuttle, and post mission analysis tools to process the infrared imagery to quantitative temperature maps. The spatially resolved global thermal measurements made during the Shuttle s hypersonic reentry provides valuable flight data for reducing the uncertainty associated with present day ground-to-flight extrapolation techniques and current state-of-the-art empirical boundary-layer transition or turbulent heating prediction methods. Laminar and turbulent flight data is considered critical for the development of turbulence models supporting NASA s next-generation spacecraft. This paper will provide the motivation and details behind the use of an upgraded NIR imaging system used onboard a Navy Cast Glance aircraft and describe the characterizations and procedures performed to obtain quantitative temperature maps. A brief description and assessment will be provided of the previously used analog NIR camera along with image examples from Shuttle missions STS-121, STS-115, and solar tower test. These thermal observations confirmed the challenge of a long-range acquisition during re-entry. These challenges are due to unknown atmospheric conditions, image saturation, vibration etc. This provides the motivation for the use of a digital NIR sensor. The characterizations performed on the digital NIR sensor included radiometric, spatial, and spectral measurements using blackbody radiation sources and known targets. An assessment of the collected data for three Space Shuttle atmospheric re-entries, STS-119, STS-125, and STS-128, are provided along with a description of various events of interest captured using the digital NIR imaging system such as RCS firings and boundary layer transitions. Lastly the process used to convert the raw image counts to quantitative temperatures is presented along with comparisons to the Space Shuttle's onboard thermocouples.

Zalameda, Joseph N.↗

Overcoming the Challenges of Data Integration and Automation

Artificial Intelligence (AI) and machine learning (ML) are gaining increased attention as a way to leverage the world's data to solve problems. Although AI and ML offer much potential, there are often misconceptions about the application of such techniques. This panel discussion includes speakers from airlines and the research community who will present machine learning approaches they have developed on a variety of aviation data including digital flight data, safety reporting data, and traffic flow data. They will explain the purpose of the application, the data used, and the lessons learned in the development and deployment of their solutions. The panel discussion will focus on common pitfalls in developing and AI solution, the dangers of the current hype around AI, tips for gaining value from a machine learning solution, how to determine whether a machine learning approach is appropriate for a problem, and more.

Matthews, Bryan L.↗

Artificial Intelligence in Aviation Safety Applications - Exploring Myths and Truths of AI and ML

Artificial Intelligence (AI) and machine learning (ML) are gaining increased attention as ways to leverage the world's data to solve problems. Although AI and ML offer much potential, there are often misconceptions about the application of such techniques.Panel speakers will present machine learning approaches they have developed on a variety of aviation data, including digital flight data, safety reporting data, and voice communications data. They will discuss the purpose of the application, the data used, and the lessons learned in the development and deployment of their solutions. The panel will also discuss common pitfalls in developing an AI solution, the dangers of the current hype around AI, tips for gaining value from a ML solution, how to determine whether a ML approach is appropriate for a problem, and more.

Reeves, Scott (Capt.)↗

3D Representation of UAV-obstacle Collision Risk Under Off-nominal Conditions

Safe operations of autonomous unmanned aerial vehicles (UAVs) in low-altitude airspace with beyond visual line-of-sight (BVLOS) flights demand robust risk monitoring of airspace as well as of people and property on ground. One of the safety critical factors for UAV flights is the risk of collision with static and dynamic obstacles in proximity to its flight path. This paper presents a detailed formulation of risk of obstacle collision incorporating the effects of off-nominal conditions introduced by component failures, degraded controllability and environmental disturbances such as wind gusts. The risk is represented in terms of a matrix with rows corresponding to the likelihood of occurrence of collision and columns representing severity of collision to the vehicle and surrounding structures. Risk likelihood is generated using a Bayesian Belief Network (BBN) that compiles knowledge from related Failure Modes and Effects Analysis (FMEAs) and Subject Matter Experts (SMEs) to determine the probability of collision based on on-board sensor measurements indicative of vehicle health and controllability. Risk severity is computed utilizing a point-mass 3D kinematic model of the vehicle in presence of wind. The proposed risk factor is demonstrated on real flight data from experimental flights of an octocopter at NASA Langley Research Center in presence of simulated obstacles and wind conditions. Effect of varying wind conditions, level of controllability and obstacle measurement noise on the risk factor is demonstrated. The proposed approach enables risk-informed decision making for timely mitigation of current and future unsafe events in autonomous systems.

risk analysis↗

3D Representation of UAV-obstacle Collision Risk under off-nominal conditions

Safe operations of autonomous unmanned aerial vehicles (UAVs) in low-altitude airspace with beyond visual line-of-sight (BVLOS) flights demand robust risk monitoring of airspace as well as of people and property on ground. One of the safety critical factors for UAV flights is the risk of collision with static and dynamic obstacles in proximity to its flight path. This paper presents a detailed formulation of risk likelihood of obstacle collision incorporating the effects of off-nominal conditions introduced by component failures, degraded controllability and environmental disturbances such as wind gusts. The deviation in the planned trajectory caused due to wind is computed utilizing a point-mass 3D kinematic simulation model of the vehicle. Likelihood of risk for the flight plan is then analyzed based on generating the probability of collision for each point in the trajectory. The proposed risk factor is demonstrated on real flight data from experimental flights of an octocopter at NASA Langley Research Center in presence of simulated obstacles and wind conditions. Effect of varying wind conditions, distance from obstacles, level of controllability and obstacle measurement noise on the risk factor is demonstrated. The proposed approach enables risk-informed decision making for timely mitigation of current and future unsafe events in autonomous systems.

Portia Banerjee↗

Probability of Obstacle Collision for UAVs in Presence of Wind

For incorporation of unmanned aerial vehicles into the National Airspace, ensuring safety of the airspace including the vehicles, people, and property on the ground is of utmost importance. One of the safety-critical factors for unmanned aviation flights is the risk of deviating from a planned trajectory resulting in a variety of hazards, including potential loss of separation between vehicle and obstacles or unexpected battery energy consumption. Off-nominal conditions introduced by component failures, degraded controllability and environmental disturbances such as wind gusts can lead to unacceptable unexpected deviations from the flight trajectory. It is essential to accurately model such effects on the flight trajectory while computing safety thresholds such as minimum separation from surrounding obstacles, available battery resource to complete the mission or determining delay in the expected time of arrival of flights. In this paper, a tool is presented based on Gaussian Process Regression for wind representation over a pre-defined trajectory for fast, yet approximated, in-time evaluation of possible trajectory deviations caused by wind gusts. The deviation in the planned trajectory caused by wind is further simulated utilizing a 6 degrees-of-freedom (DOF) UAV trajectory simulator comprising of a rotorcraft lumped-mass model with LQRI controller. Both steady-state wind and wind gust effects are investigated. The probability of collision with obstacle is computed and demonstrated on real flight data from experimental flights of an octocopter at NASA Langley Research Center in the presence of simulated obstacles and wind conditions. Effect of varying wind conditions and varying UAV airspeed is further demonstrated on experimental flights in the presence of wind measured by ground based weather service stations. The proposed approach would eventually benefit timely mitigation of current and future safety-critical events in autonomous systems by enabling risk-informed decision making.

Portia Banerjee↗

Current flight test experience related to structural divergence of forward-swept wings

Flight testing the X-29A forward-swept wing aircraft has required development of new flight test techniques to accomplish subcritical extrapolations to the actual structural divergence dynamic pressure of the aircraft. This paper provides current experience related to applying these techniques to analysis of flight data from the forward-swept wing in order to assess the applicability of these techniques to flight test data. The measurements required, maneuvers flown, and flight test conditions are described. Supporting analytical predictions for the techniques are described and the results using flight data are compared to these predictions. Use of the results during envelope expansion and the resulting modifications to the techniques are discussed. Some of the analysis challenges that occurred are addressed and some preliminary conclusions and recommendations are made relative to the usefulness of these techniques in the flight test environment.

Schuster, Lawrence S.↗

Current flight test experience related to structural divergence of forward-swept wings

Flight testing the X-29A forward-swept wing aircraft has required development of new flight test techniques to accomplish subcritical extrapolations to the actual structural divergence dynamic pressure of the aircraft. This paper provides current experience related to applying these techniques to analysis of flight data from the forward-swept wing in order to assess the applicability of these techniques to flight test data. The measurements required, manuevers flown, and flight test conditions are described. Supporting analytical predictions for the techniques are described and the results using flight data are compared to these predictions. Use of the results during envelope expansion and the resulting modifications to the techniques are discussed. Some of the analysis challenges that occurred are addressed and some preliminary conclusions and recommendations are made relative to the usefulness of these techniques in the flight test environment.

Schuster, Lawrence S.↗

In-flight lift and drag measurements on a first generation jet transport equipped with winglets

A KC-135A aircraft equipped with wing tip winglets was flight tested to demonstrate and validate the potential performance gain of the winglet concept as predicted from analytical and wind tunnel data. Flight data were obtained at cruise conditions for Mach numbers of 0.70, 0.75, and 0.80 at a nominal altitude of 36,000 ft. and winglet configurations of 15 deg cant/-4 deg incidence, 0 deg cant/-4 deg incidence, and baseline. For the Mach numbers tested the data show that the addition of winglets did not affect the lifting characteristics of the wing. However, both winglet configurations showed a drag reduction over the baseline configuration, with the best winglet configuration being the 15 deg cant/-4 deg incidence configuration. This drag reduction due to winglets also increased with increasing lift coefficient. It was also shown that a small difference exists between the 15 deg cant/-4 deg incidence flight and wind tunnel predicted data. This difference was attributed to the pillowing of the winglet skins in flight which would decrease the winglet performance.

Lux, D. P.↗

Flight tests and preliminary aerodynamic parameter extraction of an externally piloted vehicle aircraft model

Model aircraft flight test investigations have been undertaken to develop a low cost flight data acquisition system and to evaluate aerodynamic parameter estimation techniques. The externally piloted vehicles (EPVs) used are instrumented with sensors measuring acceleration, angular rates, angles of attack and sideslip, flight path velocity, and control deflections. Measured state variables are downlink telemetered to a ground-based real time flight data acquisition system; the data thus recorded are used by flight test engineers and EPV pilots to monitor conditions and aid in piloting tasks. Attention is given to comparisons of F-16 EPV data with wind tunnel data.

White, E. R.↗

Simulation and Flight Test Data Collection to Support Phase 1 Detect-and-Avoid MOPS

The UAS Integration into the NAS (UASNAS) project is studying the minimum operational performance standards for unmanned aerial system (UAS) detect-and-avoid (DAA) systems in order to operate in the National Airspace System (NAS). The project is executing a series of fast-time simulation, human-in-the-loop experiments, and flight tests in support of this effort. Armstrong Flight Research Center is hosting a VIP Day in conjunction with the UAS-NAS Project's Flight Test 4 activity, and the Ames Project Engineer (or designate) will be presenting a briefing. This briefing will review the data collection and analysis activities for Flight Test 4 within the Separation assurance-Sense-and-avoid Interoperability (SSI) team.

data analysis↗

Initial Shuttle external tank flight evaluation

The objective of this paper is to evaluate aerothermal flight measurements made on the Space Shuttle External Tank (ET) during its initial flights. The ETs have been adequately instrumented to measure various quantities during flight including heat transfer, pressure, and structural temperature. The flight data have been compared with mathematical models based on an extensive wind tunnel data base, realistic flowfields, and empirical heat-transfer relationships. An analysis of the results points out the validity of the current aeroheating methodology and existing data base, and identifies problem areas in the methodology as indicated by the flight data.

Praharaj, S. C.↗

Ares I-X Separation and Reentry Trajectory Analyses

The Ares I-X Flight Test Vehicle was launched on October 28, 2009 and was the first and only test flight of NASA s two-stage Ares I launch vehicle design. The launch was successful and the flight test met all of its primary and secondary objectives. This paper discusses the stage separation and reentry trajectory analysis that was performed in support of the Ares I-X test flight. Pre-flight analyses were conducted to assess the risk of stage recontact during separation, to evaluate the first stage flight dynamics during reentry, and to define the range safety impact ellipses of both stages. The results of these pre-flight analyses were compared with available flight data. On-board video taken during flight showed that the flight test vehicle successfully separated without any recontact. Reconstructed trajectory data also showed that first stage flight dynamics were well characterized by pre-flight Monte Carlo results. In addition, comparisons with flight data indicated that the complex interference aerodynamic models employed in the reentry simulation were effective in capturing the flight dynamics during separation. Finally, the splash-down locations of both stages were well within predicted impact ellipses.

Tartabini, Paul V.↗

Multiphase Simulations of the SLS Launch Environment

NASA’s Space Launch System (SLS), which will send astronauts back to the Moon in the next few years, is powered by four RS-25 engines and two RSRMV solid rocket boosters (SRBs). During launch the SLS propulsion system generates intense acoustics and other powerful waves, such as ignition overpressure (IOP) which, if unmitigated, have the potential to damage the vehicle and possibly cause loss of mission or crew. To protect the vehicle from these powerful waves, the SLS launch pad design includes an ignition overpressure/sound suppression (IOP/SS) system which sprays 270,000 gallons per minute of water very close to the SRB and RS-25 nozzles. The SRB and RS-25 engine plumes, and the proximity of the IOP/SS water, create a complex multiphase (gas and liquid) environment during the SLS ignition sequence. The interplay among these systems creates challenges related to water spray into/onto engine nozzles, potential debris transport, and additional transient loads due to strong plume-water interactions - all of which the SLS vehicle must be able to withstand. Prior to the Artemis I launch, the SLS multiphase liftoff environment was largely unknown due to differences from the Space Shuttle and other programs. Some data was available from tests of individual systems, but no integrated testing or analysis was available. Even post-launch analysis of Artemis I cannot provide a full understanding of the complex physics involved due to limited (or obstructed) camera views and instrumentation. Computational fluid dynamics (CFD) is being used to investigate the details of the multiphase environment which could not be measured, help comprehend the data gathered from the launch, and ultimately identify phenomena that are a concern for future flights. Project Details Engineers at NASA’s Marshall Space Flight Center (MSFC) have executed simulations using the Loci/STREAM-Volume of Fluid (VoF) multiphase CFD solver to understand this environment. Initial efforts successfully validated the CFD solver on various tests, giving confidence to simulate the SLS multiphase liftoff environment prior to the Artemis I launch. The CFD simulation of the SLS ignition sequence was conducted in three phases. First the IOP/SS water system was simulated for approximately 6 seconds to reach a quasi-steady state. Next, the RS-25 engine plumes were activated and held at full power for 1 second. Lastly, the SRB booster was activated and the simulation was carried out until just prior to vehicle motion. This simulation process mimics the conditions that exist at launch. Results and Impact The SLS ignition sequence simulation results provide deep understanding of the underlying physics occuring during launch. Observations from the simulation include reduction of water splashing into/onto the engine nozzles, change in angling of the dense water sheets, and the origin of the powerful ignition overpressure (IOP) wave. These observations directly inform the SLS program on subjects including plume-water induced side loads, debris transport, and the acoustic launch environment. Additionally, with post launch comparison of CFD observations to flight data, these tools can be applied to launch vehicles and environments other than SLS with confidence. Why HPC Matters The SLS ignition sequence CFD simulations are conducted on meshes up to hundreds of millions of cells on thousands of processors for weeks at a time. These simulations generate terabytes of data that must also be stored and archived for future use on HPC systems. Simply put, the CFD simulations would not be possible without NASA HPC resources. What’s Next Comparisons between the Artemis I flight data and the CFD simulations will be continued to both improve confidence in the CFD results and provide deeper understanding into the SLS multiphase launch environment. This will be used to provide insight for decision making for the first manned SLS flight, Artemis II. Future simulations will target new configurations of the SLS IOP/SS water required to support the more powerful variants of the SLS vehicle, such as Block 1B. Additionally, this capability provides NASA the ability to investigate launch environments for vehicles other than SLS to support other missions.

Travis Rivord↗

Rendezvous of Gemini VII and Gemini VI-A

A description of the rendezvous techniques, procedures, and flight data charts developed for the Gemini VI-A mission is presented in this paper. The flight data charts and crew timeline activities were developed over an 8-month period. Successful rendezvous is critically dependent on the presentation to the flight crew of sufficient information developed onboard the spacecraft. The Gemini VI-A flight crew used this information to evaluate the rendezvous progress by several different methods and made critical decisions based on their evaluation. The system combination found most effective in making these evaluations was the range-rate data from the radar, and the angle data from the platform.

GEMINI PROJECT↗

Analytical study to define a helicopter stability derivative extraction method, volume 1

A method is developed for extracting six degree-of-freedom stability and control derivatives from helicopter flight data. Different combinations of filtering and derivative estimate are investigated and used with a Bayesian approach for derivative identification. The combination of filtering and estimate found to yield the most accurate time response match to flight test data is determined and applied to CH-53A and CH-54B flight data. The method found to be most accurate consists of (1) filtering flight test data with a digital filter, followed by an extended Kalman filter (2) identifying a derivative estimate with a least square estimator, and (3) obtaining derivatives with the Bayesian derivative extraction method.

Molusis, J. A.↗