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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 217 records · Page 12

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NASA NTRS2003

An Analysis of the Automated Meteorological Profiling System Low Resolution Flight Element

A study was conducted to determine the quality of thermodynamic and wind data measured by or derived from the Low Resolution Flight Element (LRFE) of the Automated Meteorological Profiling System (AMPS). The AMPS LRFE replaced the Meteorological Sounding System (MSS), which was used to provide vertical profiles of thermodynamic and low-resolution wind data in support of spacecraft launch operations at the Cape Canaveral Air Force Station (CCAFS) and NASA Kennedy Space Center (KSC), Florida. Air temperature, relative humidity, and height, which are directly measured by the LRFE, are used to derive air pressure and density. Test flights were conducted where an LRFE sonde and an MSS sonde were attached to the same balloon and the two profiles were compared. MSS data was used as the standard reference data. The objective of the thermodynamic testing was to determine a) if the LRFE met Space Shuttle Program (SSP) accuracy requirements outlined in the Space Shuttle Launch and Landing Program Requirements Document (PRD) and/or, b) if the LRFE met or exceeded MSS data quality. AMPS uses the Global Positioning System (GPS) to determine wind speed and direction. In order to provide a basis for comparison, either an AMPS High Resolution Flight Element (HRFE) or a radar tracked Jimsphere was released simultaneously with each AMPS LRFE at CCAFS. The goal of these tests was to determine if the LRFE wind data met the requirement for low-resolution wind data defined in the Shuttle PRD. Based on the available data, the LRFE is shown to produce more consistent thermodynamic measurements than the MSS. The LRFE is also shown to meet the Shuttle PRD requirements for low resolution wind data.

Leahy, Frank B.↗

NASA NTRS1947

Flight-Test Evaluation of the Longitudinal Stability and Control Characteristics of 0.5-Scale Models of the Fairchild Lark Pilotless-Aircraft Configuration: Standard Configuration with Wing Flaps Deflected 60 Degrees and Model having Tail in Line with Wings, TED No. NACA 2387

Flight tests were conducted at the Flight Test Station of the Pilotless Aircraft Research Division at Wallop Island, Va., to determine the longitudinal control and stability characteristics of 0.5-scale models of the Fairchild Lark pilotless aircraft with the tail in line with the wings a d with the horizontal wing flaps deflected 60 deg. The data were obtained by the use of a telemeter and by radar tracking.

Stone, David G.↗

NASA NTRS1946

Flight-Test Evaluation of the Longitudinal Stability and Control Characteristics of 0.5-Scale Models of the Fairchild Lark Pilotless-Aircraft Configuration. Model with Wing Flaps Deflected 15 Degrees, TED No. NACA 2387

A flight test was conducted at the Flight Test Station of the Pilotless Aircraft Research Division at Wallops Island, Va., to determine the longitudinal control and stability characteristics of a 0.5-scale model of the Fairchild Lerk Pilotless aircraft with the horizontal wing flaps deflected 15 degrees. The data were obtained by the use of a telemeter and also by radar tracking. The results show an increase of effectiveness of the longitudinal control in producing normal accelerations up to a Mach number of 0.75 where this effectiveness gradually decreased becoming negative at a Mach number of 0.89. Previous tests with wing flaps undeflected an increase in effectiveness up to Mach number of 0.93 where a sudden loss of control occurred. The model was dynamically stable throughout the speed range. The data confirmed the drag increase at the critical Mach number for large angles of attack is indicated in high-speed wind-tunnel tests.

Stone, David G.↗

NASA NTRS2005

Assessment of Atmospheric Winds Aloft during NASA Space Shuttle Program Day-of-Launch Operations

The Natural Environments Branch at the National Aeronautics and Space Administration s Marshall Space Flight Center monitors the winds aloft at Kennedy Space Center in support of the Space Shuttle Program day of launch operations. High resolution wind profiles are derived from radar tracked Jimsphere balloons, which are launched at predetermined times preceding the launch, for evaluation. The spatial (shear) and temporal (persistence) wind characteristics are assessed against a design wind database to ensure wind change does not violate wind change criteria. Evaluations of wind profies are reported to personnel at Johnson Space Center.

Decker, Ryan K.↗

NASA NTRS2005

Airdata Measurement and Calibration

This Section provides a brief introduction to airdata measurement and calibration. Readers will learn about typical test objectives, quantities to measure, and flight maneuvers and operations for calibration. The Section informs readers about tower-flyby, trailing cone, pacer, radar-tracking, and dynamic airdata calibration maneuvers. Readers will also begin to understand how some data analysis considerations and special airdata cases, including high-angle-of-attack flight, high-speed flight, and nonobtrusive sensors are handled. This section is not intended to be all inclusive; readers should review AGARDograph 300, Volume 1, "Calibration of Airdata Systems and Flow Direction Sensors" for more detailed information. [11-1] References 11-2, 11-3, and 11-4 also supply pertinent information to better understand airdata measurement and calibration and related terminology. Airdata are vital to successfully complete an aircraft's mission and are derived from the air surrounding the aircraft. These airdata encompass indicated and true airspeed, pressure altitude, ambient air temperature, angles of attack and sideslip, Mach number, and rate of climb. Typically, pitot and static pressures are sensed and converted (by mechanical means in the instruments themselves) into indications on the altimeter, vertical speed indicator, airspeed indicator, and Machmeter. Similarly, measured local flow angles establish angles of attack and sideslip, and the outside air temperature is measured and indicated in the cockpit. (Instruments that can perform the conversion, such as airspeed indicators, altimeters, and Machmeters, do not correct for errors in the input values.) These measured parameters are commonly input to the airdata computer which, using appropriate algorithms and correction factors (or calibrations, as discussed later), can provide other parameters, such as true airspeed, required by the aircraft's avionics or flight control system. The presence of the aircraft in the airstream causes input errors to the measuring instruments - the aircraft disturbs the air that it flies through, thereby also disturbing the airdata measurements. Figure 11-1 shows the airflow around an airplane wing. The air above the wing has lower pressure than the ambient air, while the pressure below the wing is higher than the ambient air. Compressibility and shock waves also disturb the air and affect the measurements. Compressibility effects become important above approximately Mach number 0.3. As a result the static pressure around an airplane varies considerably with location. Local flow angles also differ from the free-stream flow direction. In straight-and-level flight the airflow rises to the wing leading edge and falls below the trailing edge, causing errors in flow direction measurements. To some extent these errors can be studied in wind tunnels, but wind-tunnel measurements cannot replace in-flight measurements.

Haering, Edward A., Jr.↗

NASA NTRS2005

Hyper-X (X-43A) Flight Test Range Operations

The Hyper-X program flew X-43A research vehicles to hypersonic speeds over the Pacific Ocean in March and November 2004 from the Western Aeronautical Test Range, NASA Dryden Flight Research Center, Edwards, California. The program required multiple telemetry ground stations to provide continuous coverage of the captive carry, launch, boost, experiment, and descent phases of these missions. An overview is provided of vehicle telemetry and distributed assets that supported telemetry acquisition, best-source selection, radar tracking, video tracking, flight termination systems, and voice communications. Real-time data display and processing are discussed, and postflight analysis and comparison of data acquired are presented.

Hyper-X↗

NASA NTRS2006

Generalized Orbital Projections of a Sublimating Ice Particle

The issue of orbital debris resulting from human activities in space is a growing concern for the space users' community. Waste generated in Low Earth Orbit (LEO) can stay in orbit for a long time, creating significant hazards for other spacecraft flying at lower intercepting orbits. Many spacecraft, especially crewed vehicles, are required to vent fluids into space. These fluids include propellant, wastewater, excess condensate, and others. It is important to analyze the behavior of particles that result from these activities, since each individual particle is capable of damaging or destroying a spacecraft in a lower, crossing orbit, and such particles are invisible to tracking radar systems on the ground. The deorbit trajectory of an ice particle is complex. It depends on factors including attitude of the vehicle during vent, initial velocities of particles, altitude at which the vent occurred, and numerous evaporation and sublimation factors. These include contamination within the vented water, evolution of bubbles within the clear water, and sun flux factors such as time of the year and current beta angle. The purpose of this study is to examine the influences of these factors on the trajectories of ice particles resulting from condensate water dumps, and to bound the safe trajectories of spacecraft that lie below the venting spacecraft.

Menkin, Evgeny↗

NASA NTRS2008

Hyper-X (X-43A) Flight Test Range Operations Overview

The Hyper-X program flew X-43A research vehicles to hypersonic speeds over the Pacific Ocean in March and November 2004 from the Western Aeronautical Test Range, NASA Dryden Flight Research Center. The program required multiple telemetry ground stations to provide continuous coverage of the captive carry, launch, boost, experiment, and descent phases of these missions. An overview is provided of vehicle telemetry and distributed assets that supported telemetry acquisition, best source selection, radar tracking, video tracking, flight termination systems, and voice communications. Real-time data display and processing are discussed, and postflight analysis and comparison of the acquired data are presented.

Lux, Jessica↗

NASA NTRS2008

DARPA/USAF/USN J-UCAS X-45A System Demonstration Program: A Review of Flight Test Site Processes and Personnel

The Joint Unmanned Combat Air Systems (J-UCAS) program is a collaborative effort between the Defense Advanced Research Project Agency (DARPA), the US Air Force (USAF) and the US Navy (USN). Together they have reviewed X-45A flight test site processes and personnel as part of a system demonstration program for the UCAV-ATD Flight Test Program. The goal was to provide a disciplined controlled process for system integration and testing and demonstration flight tests. NASA's Dryden Flight Research Center (DFRC) acted as the project manager during this effort and was tasked with the responsibilities of range and ground safety, the provision of flight test support and infrastructure and the monitoring of technical and engineering tasks. DFRC also contributed their engineering knowledge through their contributions in the areas of autonomous ground taxi control development, structural dynamics testing and analysis and the provision of other flight test support including telemetry data, tracking radars, and communications and control support equipment. The Air Force Flight Test Center acted at the Deputy Project Manager in this effort and was responsible for the provision of system safety support and airfield management and air traffic control services, among other supporting roles. The T-33 served as a J-UCAS surrogate aircraft and demonstrated flight characteristics similar to that of the the X-45A. The surrogate served as a significant risk reduction resource providing mission planning verification, range safety mission assessment and team training, among other contributions.

Cosentino, Gary B.↗

NASA NTRS2006

Hyper-X (X-43A) Flight Test Range Operations Overview

Lux-Baumann, Jessica↗

NASA NTRS2007

Launching Payloads Into Orbit at Relatively Low Cost

A report proposes the development of a system for launching payloads into orbit at about one-fifth the cost per unit payload weight of current systems. The PILOT system was a solid-fuel, aerodynamically spun and spin-stabilized, five-stage rocket with onboard controls including little more than an optoelectronic horizon sensor and a timer for triggering the second and fifth stages, respectively. The proposal calls for four improvements over the PILOT system to enable control of orbital parameters: (1) the aerodynamic tipover of the rocket at the top of the atmosphere could be modeled as a nonuniform gyroscopic precession and could be controlled by selection of the initial rocket configuration and launch conditions; (2) the attitude of the rocket at the top of the first-stage trajectory could be measured by use of radar tracking or differential Global Positioning System receivers to determine when to trigger the second stage; (3) the final-stage engines could be configured around the payload to enhance spin stabilization during a half-orbit coast up to apoapsis where the final stage would be triggered; and (4) the final payload stage could be equipped with a "beltline" of small thrusters for correcting small errors in the trajectory as measured by an off-board tracking subsystem.

Wilcox, Brian↗

NASA NTRS2013

Trajectory Reconstruction and Uncertainty Analysis Using Mars Science Laboratory Pre-Flight Scale Model Aeroballistic Testing

As part of the Mars Science Laboratory (MSL) trajectory reconstruction effort at NASA Langley Research Center, free-flight aeroballistic experiments of instrumented MSL scale models was conducted at Aberdeen Proving Ground in Maryland. The models carried an inertial measurement unit (IMU) and a flush air data system (FADS) similar to the MSL Entry Atmospheric Data System (MEADS) that provided data types similar to those from the MSL entry. Multiple sources of redundant data were available, including tracking radar and on-board magnetometers. These experimental data enabled the testing and validation of the various tools and methodologies that will be used for MSL trajectory reconstruction. The aerodynamic parameters Mach number, angle of attack, and sideslip angle were estimated using minimum variance with a priori to combine the pressure data and pre-flight computational fluid dynamics (CFD) data. Both linear and non-linear pressure model terms were also estimated for each pressure transducer as a measure of the errors introduced by CFD and transducer calibration. Parameter uncertainties were estimated using a "consider parameters" approach.

Lugo, Rafael A.↗

NASA NTRS2004

Space-Based Telemetry And Range Safety Flight Demonstration #1

The basic ability of STARS to maintain a satellite communications link with TDRSS satellites during dynamic aircraft flights was successfully demonstrated during FD 1. The Range Safety and Range User systems' link margins were measured. The ability to acquire/reacquire and maintain lock between a high-dynamic vehicle and a satellite-based system was demonstrated. The Range Safety system simultaneously received and processed command links from space and ground transmitters and provided near real-time Range Safety telemetry to DFRC, which then sent it in near real time to KSC, GSFC, and WFF for monitoring. The GPS receiver maintained track except during extremely dynamic maneuvers. The Range User system sent data at three different data rates. There were excellent cooperation and support from the different Centers, contractors, and Ranges. A large amount of data was recorded and extensive post-flight analysis was performed. The Range User TDRSS link margin met or exceeded the predicted performance at three different data rates. The Range Safety launch-head link margins generally agreed with the predicted performance. The UPS positions and velocities agreed with those from tracking radar to within about 20 m and a few rn/s. The link margins for the Range Safety TDRSS telemetry link were less than expected. The link margin for one TDRSS command link LPT channel was occasionally much less than the other. Additional post-flight testing has yet to identify the root causes of these results. There were many lessons learned from this first set of test flights. The most important one is that more time and testing are needed for each step to deal with the inevitable problems. It is vital that these lessons be among the primary areas of study that will carry over from FD#1 to FD#2, which is currently scheduled for early FY05 at DFRC and will use a specially designed Ku-band phased array antenna for the Range User system. The next series of flight demonstrations scheduled for late 2004 at DFRC will incorporate many lessons learned from FD#1. A specially designed Ku-band phased array antenna will be used with the Range User system. A test flight on a hypersonic vehicle is planned by the end of 2006.

Demspm. Erol↗

NASA NTRS2013

Validating an Air Traffic Management Concept of Operation Using Statistical Modeling

Validating a concept of operation for a complex, safety-critical system (like the National Airspace System) is challenging because of the high dimensionality of the controllable parameters and the infinite number of states of the system. In this paper, we use statistical modeling techniques to explore the behavior of a conflict detection and resolution algorithm designed for the terminal airspace. These techniques predict the robustness of the system simulation to both nominal and off-nominal behaviors within the overall airspace. They also can be used to evaluate the output of the simulation against recorded airspace data. Additionally, the techniques carry with them a mathematical value of the worth of each prediction-a statistical uncertainty for any robustness estimate. Uncertainty Quantification (UQ) is the process of quantitative characterization and ultimately a reduction of uncertainties in complex systems. UQ is important for understanding the influence of uncertainties on the behavior of a system and therefore is valuable for design, analysis, and verification and validation. In this paper, we apply advanced statistical modeling methodologies and techniques on an advanced air traffic management system, namely the Terminal Tactical Separation Assured Flight Environment (T-TSAFE). We show initial results for a parameter analysis and safety boundary (envelope) detection in the high-dimensional parameter space. For our boundary analysis, we developed a new sequential approach based upon the design of computer experiments, allowing us to incorporate knowledge from domain experts into our modeling and to determine the most likely boundary shapes and its parameters. We carried out the analysis on system parameters and describe an initial approach that will allow us to include time-series inputs, such as the radar track data, into the analysis

Statistical emulation↗

NASA NTRS2012

Integrating the Base of Aircraft Data (BADA) in CTAS Trajectory Synthesizer

The Center-Terminal Radar Approach Control (TRACON) Automation System (CTAS), developed at NASA Ames Research Center for assisting controllers in the management and control of air traffic in the extended terminal area, supports the modeling of more than four hundred aircraft types. However, 90% of them are supported indirectly by mapping them to one of a relatively few aircraft types for which CTAS has detailed drag and engine thrust models. On the other hand, the Base of Aircraft Data (BADA), developed and maintained by Eurocontrol, supports more than 300 aircraft types, about one third of which are directly supported, i.e. they have validated performance data. All these data were made available for CTAS by integrating BADA version 3.8 into CTAS Trajectory Synthesizer (TS). Several validation tools were developed and used to validate the integrated code and to evaluate the accuracy of trajectory predictions generated using CTAS "native" and BADA Aircraft Performance Models (APM) comparing them with radar track data. Results of these comparisons indicate that the two models have different strengths and weaknesses. The BADA APM can improve the accuracy of CTAS predictions at least for some aircraft types, especially small aircraft, and for some flight phases, especially climb.

Abramson, Michael↗

NASA NTRS2016

Orion Exploration Flight Test 1 (EFT-1) Best Estimated Trajectory Development

The Orion Exploration Flight Test 1 (EFT-1) mission successfully flew on Dec 5, 2014 atop a Delta IV Heavy launch vehicle. The goal of Orions maiden flight was to stress the system by placing an uncrewed vehicle on a high-energy trajectory replicating conditions similar to those that would be experienced when returning from an asteroid or a lunar mission. The Orion navigation team combined all trajectory data from the mission into a Best Estimated Trajectory (BET) product. There were significant challenges in data reconstruction and many lessons were learned for future missions. The team used an estimation filter incorporating radar tracking, onboard sensors (Global Positioning System and Inertial Measurement Unit), and day-of-flight weather balloons to evaluate the true trajectory flown by Orion. Data was published for the entire Orion EFT-1 flight, plus objects jettisoned during entry such as the Forward Bay Cover. The BET customers include approximately 20 disciplines within Orion who will use the information for evaluating vehicle performance and influencing future design decisions.

Holt, Greg N.↗

NASA NTRS2017

RNAV STAR Procedural Adherence

In this exploratory archival study we mined the performance of 24 major US airports area navigation standard terminal arrival routes (RNAV STARs) over the preceding three years. Overlaying radar track data on top of RNAV STAR routes provided a comparison between aircraft flight paths and the waypoint positions and altitude restrictions. NASA Ames Supercomputing resources were utilized to perform the data mining and processing. We investigated STARs by lateral transition path (full-lateral), vertical restrictions (full-lateral/full-vertical), and skipped waypoints (skips). In addition, we graphed altitudes and their frequencies of occurrence for altitude restrictions. Full-lateral compliance was generally greater than Full-lateral/full-vertical, but the delta between the rates was not always consistent. Full-lateral/full-vertical usage medians of the 2016 procedures ranged from 0 in KDEN (Denver) to 21 in KMEM (Memphis). Waypoint skips ranged from 0 to nearly 100 for specific waypoints. Altitudes restrictions were sometimes missed by systemic amounts in 1000 ft. increments from the restriction, creating multi-modal distributions. Other times, altitude misses looked to be more normally distributed around the restriction. This work is a preliminary investigation into the objective performance of instrument procedures and provides a framework to track how procedural concepts and design intervention function. In addition, this tool may aid in providing acceptability metrics as well as risk assessment information.

Stewart, Michael J.↗

NASA NTRSDate not supplied

Post-Flight Reconstruction Approach for Space Launch System Artemis I Mission

Upon completion of the first Space Launch System flight, NASA personnel will begin post-flight analyses. Telemetry from across the vehicle will be combined with external radar tracking and environmental observation data in order to close validation criteria and generate a best estimated trajectory (BET). This paper will describe the approach taken by the SLS team to integrate flight data from multiple flights sources into BET, pre-flight simulation and testing results, primary sources of uncertainty, and path towards processing flight results. This paper also includes a brief description of algorithms and approaches to estimate as-flown vehicle parameters such as booster specific impulse, booster (and core) thrust multipliers and dry mass.

Evan John Anzalone↗