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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 433 records · Page 24

Magnetometer Data Tests Models for the Origin of the Martian Crustal Dichotomy; Dichotomy Models Constrain Timing of Martian Magnetic Field

Measurements recently supplied by the MGS Magnetometer/Electron Reflectometer (MAG/ER) on MGS can be applied to test theories of the origin of the martian crustal dichotomy. Strong (+/- 1500 nT) magnetic anomalies are observed in the Martian crust. The observations can be summarized as follows: 1) strong crustal magnetic sources are generally confined to the southern highlands, although weaker (approx. 40 nT) anomalies were observed during close periapsis; 2) strong magnetic anomalies are absent in the vicinity of Hellas and Argyre; 3) the anomalies in the region 0 deg to 90 deg S, 120 deg to 240 deg west have a linear geometry, strike generally east west for 1000s km, and show several reversals. This latter point has led to the suggestion that some form of lateral plate tectonics may have been operative in the southern highlands of Mars. These observations have led previous workers to hypothesize that the magnetic anomalies were present prior to and were destroyed by the formation of Hellas and Argyre. As such large impacts are confined to the era of heavy bombardment, this places the time of formation of large magnetic anomalies prior to approx. 3.9 Ga. One obvious extension of this is that the northern lowlands lack significant anomalies because they were erased by impacts and/or the northern lowlands represent crust completely reheated above the Curie temperature. Preliminary observations of the distributions of the large crustal magnetic anomalies show that many of them extend continuously over the highland lowland boundary. This occurs particularly north of the boundary between 30 deg W and 270 deg W, corresponding to northern Arabia, but also occurs in southern Elysium (approx. 10 deg S, 200 deg) and the SW portion of Tharsis (approx. 15 deg S, 140 deg). This suggests that, in these areas, Noachian crust containing the greater than 3.9 Ga magnetic signature, lies beneath the northern highlands. This geometry can be used to test models for the formation of the martian crustal dichotomy. Additional information is contained in the original extended abstract.

Gilmore, M. S.↗

Estimation of Unsteady Aerodynamic Models from Flight Test Data

This report summarizes the activities in aerodynamic model estimation from flight data. In addition to public presentations at the AIAA Atmospheric Flight Mechanics Conferences, two presentations at Boeing-Seattle were made during personal trips. These are discussed in the following: 1. Methodology of Aerodynamic Model Estimation from Flight Data. 2. Applications of F-16XL aerodynamic modeling. 3. Modeling of turbulence response. 5. Presentations at Boeing-Seattle. 6. Recommendations. and 7. References.

Lan, C. Edward↗

CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF)- Test data in HDF (CER_SSF_TRMM-PFM-VIRS_Subset-Edition1)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=1998-08-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

CLOUD LAYER AREA↗

Predicting Ares I Reaction Control System Performance by Utilizing Analysis Anchored with Development Test Data

The Ares I launch vehicle is an integral part of NASA s Constellation Program, providing a foundation for a new era of space access. The Ares I is designed to lift the Orion Crew Module and will enable humans to return to the Moon as well as explore Mars.1 The Ares I is comprised of two inline stages: a Space Shuttle-derived five-segment Solid Rocket Booster (SRB) First Stage (FS) and an Upper Stage (US) powered by a Saturn V-derived J-2X engine. A dedicated Roll Control System (RoCS) located on the connecting interstage provides roll control prior to FS separation. Induced yaw and pitch moments are handled by the SRB nozzle vectoring. The FS SRB operates for approximately two minutes after which the US separates from the vehicle and the US Reaction Control System (ReCS) continues to provide reaction control for the remainder of the mission. A representation of the Ares I launch vehicle in the stacked configuration and including the Orion Crew Exploration Vehicle (CEV) is shown in Figure 1. Each Reaction Control System (RCS) design incorporates a Gaseous Helium (GHe) pressurization system combined with a monopropellant Hydrazine (N2H4) propulsion system. Both systems have two diametrically opposed thruster modules. This architecture provides one failure tolerance for function and prevention of catastrophic hazards such as inadvertent thruster firing, bulk propellant leakage, and over-pressurization. The pressurization system on the RoCS includes two ambient pressure-referenced regulators on parallel strings in order to attain the required system level single Fault Tolerant (FT) design for function while the ReCS utilizes a blow-down approach. A single burst disk and relief valve assembly is also included on the RoCS to ensure single failure tolerance for must-not-occur catastrophic hazards. The Reaction Control Systems are designed to support simultaneously firing multiple thrusters as required

Stein, William B.↗

Anomaly Detection Techniques with Real Test Data from a Spinning Turbine Engine-Like Rotor

Online detection techniques to monitor the health of rotating engine components are becoming increasingly attractive to aircraft engine manufacturers in order to increase safety of operation and lower maintenance costs. Health monitoring remains a challenge to easily implement, especially in the presence of scattered loading conditions, crack size, component geometry, and materials properties. The current trend, however, is to utilize noninvasive types of health monitoring or nondestructive techniques to detect hidden flaws and mini-cracks before any catastrophic event occurs. These techniques go further to evaluate material discontinuities and other anomalies that have grown to the level of critical defects that can lead to failure. Generally, health monitoring is highly dependent on sensor systems capable of performing in various engine environmental conditions and able to transmit a signal upon a predetermined crack length, while acting in a neutral form upon the overall performance of the engine system.

Abdul-Aziz, Ali↗

Validation of US3D for Capsule Aerodynamics using 05-CA Wind Tunnel Test Data

RANS is ill-suited for analysis of these problems. For transonic and supersonic cases, US3D shows fairly good agreement using DES across all cases. Separation prediction and resulting backshell pressure are problems across all portions of this analysis. This becomes more of an issue at lower Mach numbers: .Stagnation pressures not as large - wake and backshell are more significant .Errors on shoulder act on a large area - small discrepancies manifest as large changes Subsonic comparisons are mixed with regard to integrated loads and merit more attention. Dominant unsteady behavior (wake shedding) resolved well, though.

Schwing, Alan↗

Functional Task Test: Data Review

After space flight there are changes in multiple physiological systems including: Cardiovascular function; Sensorimotor function; and Muscle function. How do changes in these physiological system impact astronaut functional performance?

Cromwell, Ronita↗

Fitting a Model to Floating Gate Prompt Charge Loss Test Data for the Samsung 8 Gb SLC NAND Flash Memory

A recent model provides risk estimates for the deprogramming, of initially programmed floating gates, via prompt charge loss produced by an ionizing radiation environment. The environment can be a mixture of electrons, protons, and heavy ions. The model requires several input parameters. Parameters intended to produce conservative risk estimates for the Samsung 8 Gb SLC NAND flash memory are given, subject to some qualifications.

Edmonds, L. D.↗

Acquisition and Processing of Passive Thermography Fatigue Test Data

Passive thermography is a large area inspection technique and is commonly used during fatigue loading of composite structures. Passive thermography allows for real time tracking of damage. This provides an accurate assessment of the damage progression as a function of load cycles and determines when the loading is stopped for ultrasonic or X-ray CT evaluations for detail damage assessment through-the-thickness. In addition, if new areas of damage growth are detected, with passive thermography, then those areas are additionally inspected with ultrasound or X-ray CT. A custom developed passive thermography inspection system for fatigue loading is presented. Passive thermography of damage progression is compared to ultrasound inspections as a function of the fatigue cycles. Discussion is made on processing of the thermal data for periodic and non-periodic thermal responses.

Thermal nondestructive evaluation↗

Evaluation, Analysis and Results of the DANTi Flight Test Data, the DAIDALUS Detect and Avoid Algorithm, and the DANTi Concept for Detect and Avoid in the Cockpit

The DAIDALUS Detect and Avoid Algorithm [1] was developed to address the operational needs of Unmanned Aerial Systems (UAS) and meet the Minimum Operational Performance Standards for Detect and Avoid [2]. The DANTi (Detect and Avoid iN the cockpit) concept [3], developed at the National Aeronautics and Space Administration (NASA) Langley Research Center, leverages advancements achieved in surveillance and Detect and Avoid technologies for unmanned aircraft systems as a safety enhancing capability for pilots of manned aircraft. Pilots operating under Visual Flight Rules and not receiving Air Traffic Control radar services rely on see and avoid to remain well clear of other aircraft and avoid collisions. The DANTi concept has been conceived as a safety enhancement capability to remain well clear and avoid potential collisions. The DANTi concept uses a traffic display to provide situational awareness, conflict detection, alerting, and guidance to remain well clear.

Detect and Avoid↗

Frequency Domain Quasi-Maximum Likelihood Identification of Low Order Aeroservoelastic Models from Flight-Test Data

Background and Motivation - Low Order Equivalent System (LOES) - From handling qualities analysis - Traditionally simplifying complex control law and plant - More easily understood form - Extend LOES to a complex model due to aeroelasticity - Maximum likelihood (Filter Error) System Identification - Z = H_loes (U + W) + V - There are a lot of parameters - System identification usually simplifies by assuming a value - Output Error and Equation Error - Results in biased estimates of the parameters - We are proposing a new method to solving this problem

Jeffrey Ouellette↗