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At least 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Developmental Flight Instrumentation: Review of Space Shuttle, Ares I-X, and Artemis I

Ascent vehicles in the developmental stages of the program are instrumented with Developmental Flight Instrumentation (DFI) sensors. These sensors establish a link between a vehicle and engineers on the ground to communicate conditions experienced during the ascent. These data are then compared to pre-flight predictions used in the design process. The aerodynamic, acoustic, thermal, and structural data are either telemetered to ground stations during the ascent or stored on the vehicle for post-flight recovery and archived at the Huntsville Operations Support Center (HOSC). Following NASA's Artemis I Space Launch System (SLS) launch on November 16, 2020, data from three separate programs are available at the HOSC: Space Shuttle Program (Space Transport System (STS)), Constellation Program (Ares I-X), and Artemis Program (SLS). Availability of these data presents a unique opportunity to examine DFI data from three distinct vehicles and analyze the broad impact of the DFI data on the understanding of transonic aerodynamics. Classical spectrogram and Empirical Mode Decomposition techniques were used to present data in aerodynamically analogous regions on each vehicle. On the SLS and Ares I-X, a region downstream of the Launch Abort System motors was chosen. Comparing SLS and the STS, a region downstream of booster Froward Attach Hardware was selected as analogous flow region. Some other regions of interest were also identified. Although similarities in flow features on three vehicles were identified, some challenges in the comparison were also encountered, especially due to poor temporal and spatial resolution of Shuttle measurements.

Space Shuttle↗
NASA NTRSDate not supplied

Developmental Flight Instrumentation: Review of Space Shuttle, Ares I-X, and Artemis I

Ascent vehicles in the developmental stages of the program are instrumented with Developmental Flight Instrumentation (DFI) sensors. These sensors establish a link between a vehicle and engineers on the ground to communicate conditions experienced during the ascent. These data are then compared to pre-flight predictions used in the design process. The aerodynamic, acoustic, thermal, and structural data are either telemetered to ground stations during the ascent or stored on the vehicle for post-flight recovery and archived at the Huntsville Operations Support Center (HOSC). Following NASA's Artemis I Space Launch System (SLS) launch on November 16, 2020, data from three separate programs are available at the HOSC: Space Shuttle Program (Space Transport System (STS)), Constellation Program (Ares I-X), and Artemis Program (SLS). Availability of these data presents a unique opportunity to examine DFI data from three distinct vehicles and analyze the broad impact of the DFI data on the understanding of transonic aerodynamics. Classical spectrogram and Empirical Mode Decomposition techniques were used to present data in aerodynamically analogous regions on each vehicle. On the SLS and Ares I-X, a region downstream of the Launch Abort System motors was chosen. Comparing SLS and the STS, a region downstream of booster Froward Attach Hardware was selected as analogous flow region. Some other regions of interest were also identified. Although similarities in flow features on three vehicles were identified, some challenges in the comparison were also encountered, especially due to poor temporal and spatial resolution of Shuttle measurements.

Space Shuttle↗
NASA NTRS1973

Distribution of surface extremes in the United States

Extreme design environment data are presented for consideration in aerospace vehicle transportation, fabrication, or testing. Values were obtained by using data from weather stations and published meteorological articles. Maps depict snow fall, hail distribution, atmospheric pressure, atmospheric temperature, and surface elevations.

Daniels, G. E.↗
NASA NTRS2020

NASA-ISRO Synthetic Aperture Radar (NISAR) Mission

NISAR is a multi-disciplinary Earth-observing radar mission that makes global measurements of land surface changes that will greatly improve Earth system models. NISAR data will clarify spatially and temporally complex phenomena, including ecosystem disturbances, ice sheet collapse, and natural hazards including earthquakes, tsunamis, volcanoes, and landslides. It provides societally relevant data that will enable better protection of life and property. The mission, a NASA-ISRO partnership, uses two fully polarimetric SARs, one at L-band (L-SAR) and one at S-band (S-SAR), in exact repeating orbits every 12 days that allows interferometric combination of data on repeated passes. NASA provides the L SAR; a shared deployable reflector; an engineering payload that supports mission-specific data handling, navigation and communication functions; science observation planning and L SAR data processing. ISRO provides the S-SAR, spacecraft, launch vehicle, satellite operations, and S-SAR data processing. The mission will be launched from the Satish Dhawan Space Centre, Sriharikota, India. Mission development has addressed many unique challenges and incorporates many “firsts” for a jointly-developed free-flyer radar science mission.

Sarma, C V H S↗
NASA NTRS1989

Pressure Distribution and Air Data System for the Aeroassist Flight Experiment

The Aeroassist Flight Experiment (AFE) is designed to provide critical flight data necessary for the design of future Aeroassist Space Transfer Vehicles (ASTV). This flight experiment will provide aerodynamic, aerothermodynamic, and environmental data for verification of experimental and computational flow field techniques. The Pressure Distribution and Air Data System (PD/ADS), one of the measurement systems incorporated into the AFE spacecraft, is designed to provide accurate pressure measurements on the windward surface of the vehicle. These measurements will be used to determine the pressure distribution and air data parameters (angle of attack, angle of sideslip, and free-stream dynamic pressure) encountered by the blunt-bodied vehicle over an altitude range of 76.2 km to 94.5 km. Design and development data are presented and include: measurement requirements, measurement heritage, theoretical studies to define the vehicle environment, flush-mounted orifice configuration, pressure transducer selection and performance evaluation data, and pressure tubing response analysis.

Gibson, Lorelei S.↗
NASA NTRS1976

Data acquisition and path selection decision making for an autonomous roving vehicle

Problems related to the guidance of an autonomous rover for unmanned planetary exploration were investigated. Topics included in these studies were: simulation on an interactive graphics computer system of the Rapid Estimation Technique for detection of discrete obstacles; incorporation of a simultaneous Bayesian estimate of states and inputs in the Rapid Estimation Scheme; development of methods for estimating actual laser rangefinder errors and their application to date provided by Jet Propulsion Laboratory; and modification of a path selection system simulation computer code for evaluation of a hazard detection system based on laser rangefinder data.

Frederick, D. K.↗
NASA NTRS2017

UAV Trajectory Modeling Using Neural Networks

Massive small unmanned aerial vehicles are envisioned to operate in the near future. While there are lots of research problems need to be addressed before dense operations can happen, trajectory modeling remains as one of the keys to understand and develop policies, regulations, and requirements for safe and efficient unmanned aerial vehicle operations. The fidelity requirement of a small unmanned vehicle trajectory model is high because these vehicles are sensitive to winds due to their small size and low operational altitude. Both vehicle control systems and dynamic models are needed for trajectory modeling, which makes the modeling a great challenge, especially considering the fact that manufactures are not willing to share their control systems. This work proposed to use a neural network approach for modelling small unmanned vehicle's trajectory without knowing its control system and bypassing exhaustive efforts for aerodynamic parameter identification. As a proof of concept, instead of collecting data from flight tests, this work used the trajectory data generated by a mathematical vehicle model for training and testing the neural network. The results showed great promise because the trained neural network can predict 4D trajectories accurately, and prediction errors were less than 2:0 meters in both temporal and spatial dimensions.

Neural Networks↗
NASA NTRS2013

Sleuthing the MSL EDL Performance from an X Band Carrier Perspective

During the Entry, Descent, and Landing (EDL) of NASA's Mars Science Laboratory (MSL), or Curiosity, rover to Gale Crater on Mars on August 6, 2012 UTC, the rover transmitted an X-band signal composed of carrier and tone frequencies and a UHF signal modulated with an 8kbps data stream. During EDL, the spacecraft's orientation is determined by its guidance and mechanical subsystems to ensure that the vehicle land safely at its destination. Although orientation to maximize telecom performance is not possible, antennas are especially designed and mounted to provide the best possible line of sight to Earth and to the Mars orbiters supporting MSL's landing. The tones and data transmitted over these links are selected carefully to reflect the most essential parameters of the vehicle's state and the performance of the EDL subsystems for post-EDL reconstruction should no further data transmission from the vehicle be possible. This paper addresses the configuration of the X band receive system used at NASA / JPL's Deep Space Network (DSN) to capture the signal spectrum of MSL's X band carrier and tone signal, examines the MSL vehicle state information obtained from the X band carrier signal only and contrasts the Doppler-derived information against the post-EDL known vehicle state. The paper begins with a description of the MSL EDL sequence of events and discusses the impact of the EDL maneuvers such as guided entry, parachute deploy, and powered descent on the frequency observables expected at the DSN. The range of Doppler dynamics possible is derived from extensive 6 Degrees-Of-Freedom (6 DOF) vehicle state calculations performed by MSL's EDL simulation team. The configuration of the DSN's receive system, using the Radio Science Receivers (RSR) to perform open-loop recording for both for nominal and off-nominal EDL scenarios, is detailed. Expected signal carrier power-to-noise levels during EDL are shown and their impact on signal detection is considered. Particular attention is given to the selection of the appropriate RSR processing bandwidths and to its configuration for real-time signal detection. The X-band carrier frequency obtained through post-processing of the open-loop recorded spectrum is given. Detection of spacecraft status and completion of key vehicle events through their Doppler signature is discussed and illustrated. This Doppler-derived information is compared against the very accurate vehicle data obtained post-EDL via MSL's UHF radio subsystem. The paper concludes with a discussion on the advantages and disadvantages of transmitting the X-band carrier and tone signal in the general context of EDL communications and lessons learned for future missions with EDL sequences are given

Mars Science Laboratory (MSL)↗
NASA NTRS1973

Results of tests OA12 and IA9 in the Ames Research Center unitary plan wind tunnels on an 0.030-scale model of the Space Shuttle Vehicle 2A to determine aerodynamic loads, volume 11

Tests were conducted in wind tunnels during April and May 1973, on an 0.030-scale replica of the Space Shuttle Vehicle Configuration 2A. Aerodynamic loads data were obtained at Mach numbers from 0.6 to 3.5. The investigation included tests on the integrated (launch) configuration and on the isolated orbiter (entry configuration). The integrated vehicle was tested at angles of attack from -15 degrees to +40 degrees and angles of sideslip from -10 degrees to +10 degrees as dictated by trajectory considerations. The effects of orbiter/external tank incidence angle and deflected control surfaces on aerodynamic loads were also investigated. Tabulated pressure data are presented for: orbiter fuselage and base, upper MPS nozzle, OMS nozzle, body flap, OMS pod outside, and lower wing surface.

Spangler, R. H.↗
NASA NTRS1974

Results of tests OA12 and IA9 in the Ames Research Center unitary plan wind tunnels on an 0.030-scale model of the space shuttle vehicle 2A to determine aerodynamic loads, volume 14

Tests were conducted in wind tunnels during April and May 1973, on a 0.030-scale replica of the Space Shuttle Vehicle Configuration 2A. Aerodynamic loads data were obtained at Mach numbers from 0.6 to 3.5. The investigation included tests on the integrated (launch) configuration and the isolated orbiter (entry configuration). The integrated vehicle was tested at angles of attack and sideslip from -8 degrees to +8 degrees. The isolated orbiter was tested at angles of attack from -15 degrees to +40 degrees and angles of sideslip from -10 degrees to +10 degrees as dictated by trajectory considerations. The effects of orbiter/external tank incidence angle and deflected control surfaces on aerodynamic loads were also investigated. Tabulated pressure data were obtained for upper and lower wing surfaces and left and right vertical tail surfaces.

Spangler, R. H.↗
NASA NTRS1997

Summary Report of Mission Acceleration Measurements for STS-79. Launched 16 Sep. 1996

The Space Acceleration Measurement System (SAMS) collected acceleration data in support of the Mechanics of Granular Materials experiment during the STS-79 Mir docking mission, September 1996. STS-79 was the first opportunity to record SAMS data on an Orbiter while it was docked to Mir. Crew exercise activities in the Atlantis middeck and the Mir base module are apparent in the data. The acceleration signals related to the Enhanced Orbiter Refrigerator Freezer had different characteristics when comparing the data recorded on Atlantis on STS-79 with the data recorded on Mir during STS-74. This is probably due, at least in part, to different transmission paths and SAMS sensor head mounting mechanisms. Data collected on Atlantis during the STS-79 docking indicate that accelerations due to vehicle and solar array structural modes from Mir transfer to Atlantis and that the structural modes of the Atlantis-Mir complex are different from those of either vehicle independently. A 0.18 Hz component of the SAMS data, present while the two vehicles were docked, was probably caused by the Mir solar arrays. Compared to Atlantis structural modes of about 3.9 and 4.9 Hz, the Atlantis-Mir complex has structural components of about 4.5 and 5.1 Hz. After docking, apparent structural modes appeared in the data at about 0.8 and 1.8 Hz. The appearance, disappearance, and change in the structural modes during the docking and undocking phases of the joint Atlantis-Mir operations indicates that the structural modes of the two spacecraft have an effect on the microgravity environment of each other. The transfer of structural and equipment related accelerations between vehicles is something that should be considered in the International Space Station era.

Rogers, Melissa J. B.↗
NASA NTRS1972

An investigation of the landing characteristics of the NASA-MSC August 1969 baseline orbiter configuration in ground effect

A 0.05 scale model of the NASA-MSC August 1969 baseline shuttle craft was tested in Texas A&M University's 7- x 10-foot low speed wind tunnel facility. The purpose of the test was to determine the landing aerodynamic characteristics of the shuttle craft vehicle in ground effect and to evaluate control surface hinge moments experienced in the cruise and landing operational phases of flight. Analysis of the final data will allow evaluation of vehicle flight stability in ground effect and estimation of vehicle control surface power system requirements.

Chambliss, E. B.↗
NASA NTRS2010

Payload-Directed Control of Geophysical Magnetic Surveys

Using non-navigational (e.g. imagers, scientific) sensor information in control loops is a difficult problem to which no general solution exists. Whether the task can be successfully achieved in a particular case depends highly on problem specifics, such as application domain and sensors of interest. In this study, we investigate the feasibility of using magnetometer data for control feedback in the context of geophysical magnetic surveys. An experimental system was created and deployed to (a) assess sensor integration with autonomous vehicles, (b) investigate how magnetometer data can be used for feedback control, and (c) evaluate the feasibility of using such a system for geophysical magnetic surveys. Finally, we report the results of our experiments and show that payload-directed control of geophysical magnetic surveys is indeed feasible.

Lee, Ritchie↗
NASA NTRS2006

Automated Announcements of Approaching Emergency Vehicles

Street intersections that are equipped with traffic lights would also be equipped with means for generating audible announcements of approaching emergency vehicles, according to a proposal. The means to generate the announcements would be implemented in the intersection- based subsystems of emergency traffic-light-preemption systems like those described in the two immediately preceding articles and in "Systems Would Preempt Traffic Lights for Emergency Vehicles" (NPO-30573), NASA Tech Briefs, Vol. 28, No. 10 (October 2004), page 36. Preempting traffic lights is not, by itself, sufficient to warn pedestrians at affected intersections that emergency vehicles are approaching. Automated visual displays that warn of approaching emergency vehicles can be helpful as a supplement to preemption of traffic lights, but experience teaches that for a variety of reasons, pedestrians often do not see such displays. Moreover, in noisy and crowded urban settings, the lights and sirens on emergency vehicles are often not noticed until a few seconds before the vehicles arrive. According to the proposal, the traffic-light preemption subsystem at each intersection would generate an audible announcement for example, emergency vehicle approaching, please clear intersection whenever a preemption was triggered. The subsystem would estimate the time of arrival of an approaching emergency vehicle by use of vehicle identity, position, and time data from one or more sources that could include units connected to traffic loops and/or transponders connected to diagnostic and navigation systems in participating emergency vehicles. The intersection-based subsystem would then start the announcement far enough in advance to enable pedestrians to leave the roadway before any emergency vehicles arrive.

Bachelder, Aaron↗
NASA NTRS1974

Results of tests OA12 and IA9 in the Ames Research Center unitary plan wind tunnels on an 0.030-scale model of the space shuttle vehicle 2A to determine aerodynamic loads, volume 13

Tests were conducted in wind tunnels during April and May 1973, on a 0.030-scale replica of the Space Shuttle Vehicle Configuration 2A. Aerodynamic loads data were obtained at Mach numbers from 0.6 to 3.5. The investigation included tests on the integrated (launch) configuration and on the isolated orbiter (entry configuration). The integrated vehicle was tested at angles of attack and sideslip from -8 deg to +8 deg. The isolated orbiter was tested at angles of attack from -15 deg to +40 deg and angles of sideslip from -10 deg to +10 deg as dictated by trajectory considerations. The effects of orbiter/external tank incidence angle and deflected control surfaces on aerodynamic loads were also investigated. Tabulated pressure data are given for the following components: orbiter fuselage and base; OMS and upper MPS nozzles; body flap; and OMS pod outside.

Spangler, R. H.↗
NASA NTRS2013

Analysis of International Space Station Vehicle Materials Exposed on Materials International Space Station Experiment from 2001 to 2011

Since August 2001, the Materials on International Space Station Experiment (MISSE) has provided data on a variety of materials and spacecraft components, including samples chosen to provide sustaining engineering and life extension data for the International Space Station vehicle itself. This Technical Publication is by no means a complete set of MISSE data but does provide changes in solar absorptance, infrared emittance, and visual appearance due to atomic oxygen, ultraviolet radiation, and thermal cycling in vacuum. Conversion coatings, anodizes, thermal control coatings with organic and inorganic binders, multilayer insulation components, optical materials, and part markings are discussed.

Finckenor, M. M.↗
NASA NTRS2023

Performance Modeling of Urban Air Mobility Vehicles to Support Air Traffic Management Research

The recent emergence of Urban Air Mobility (UAM) vehicles has resulted in a need for flight performance models that enable comprehensive simulation-based research on air traffic management topics such as route structure, scheduling, and separation standards. Successful performance modeling methods exist for a wide range of traditional aircraft designs. However, comparable modeling methods appropriate for UAM vehicles that combine fixed-wing and rotorcraft performance have not yet been established. One challenge to progress has been the lack of available data capturing the performance characteristics and unique flight profiles of these aircraft. This paper describes methods used to generate the required performance data and the development of performance models for UAM vehicles. Included is a review of the energy and power equations often used in developing performance models for traditional aircraft as well as a discussion of their applicability to UAM vehicles. The challenge of generating realistic performance data in over-actuated vehicles transitioning from hover to cruise flight is also addressed through an approach based on objective function optimization. A table-based performance model format adapted to UAM configurations is described, as well as parametric models intended to accompany the performance table to allow detailed modeling of power and fuel consumption during accelerated flight, turning flight, or flight at an arbitrary climb or descent rate. A discussion of future work is also provided, including the need for refinement of UAM performance modeling methods and formats, especially in conjunction with improvements to aerodynamic modeling of vehicles with complex designs where strong interaction effects may dominate important regions of the flight envelope.

Performance Modeling↗
NASA NTRS2023

Performance Modeling of Urban Air Mobility Vehicles to Support Air Traffic Management Research

The recent emergence of Urban Air Mobility (UAM) vehicles has resulted in a need for flight performance models that enable comprehensive simulation-based research on air traffic management topics such as route structure, scheduling, and separation standards. Successful performance modeling methods exist for a wide range of traditional aircraft designs. However, comparable modeling methods appropriate for UAM vehicles that combine fixed-wing and rotorcraft performance have not yet been established. One challenge to progress has been the lack of available data capturing the performance characteristics and unique flight profiles of these aircraft. This paper describes methods used to generate the required performance data and the development of performance models for UAM vehicles. Included is a review of the energy and power equations often used in developing performance models for traditional aircraft as well as a discussion of their applicability to UAM vehicles. The challenge of generating realistic performance data in over-actuated vehicles transitioning from hover to cruise flight is also addressed through an approach based on objective function optimization. A table-based performance model format adapted to UAM configurations is described, as well as parametric models intended to accompany the performance table to allow detailed modeling of power and fuel consumption during accelerated flight, turning flight, or flight at an arbitrary climb or descent rate. A discussion of future work is also provided, including the need for refinement of UAM performance modeling methods and formats, especially in conjunction with improvements to aerodynamic modeling of vehicles with complex designs where strong interaction effects may dominate important regions of the flight envelope.

Performance Modeling↗