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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

SATPLOT for Analysis of SECCHI Heliospheric Imager Data

Determining trajectories of solar transients such as coronal mass ejections is not always easy. White light images from SECCHI's (Sun Earth Connection Coronal and Heliospheric Investigation) heliospheric imagers are difficult to interpret because they represent a line-of-sight projection of optically thin solar wind structures. A structure's image by itself gives no information about its angle of propagation relative to the Sunspacecraft line, and an image may show a superposition of several structures, all propagating at different angles. Analyzing SECCHI heliospheric imager data using plots of elongation (angle from the Sun) versus time at fixed position angle (aka Jplots ) has proved extremely useful in understanding the observed solar wind structures. This technique has been used to study CME (coronal mass ejection) propagation, CIRs (corotating interaction regions), and blobs. SATPLOT software was developed to create and analyze such elongation versus time plots. The tool uses a library of cylindrical maps of the data for each spacecraft s panoramic field-of-view. Each map includes data from three SECCHI white-light telescopes (the COR2 coronagraph and both heliospheric imagers) at one time for one spacecraft. The maps are created using a Plate Carree projection, optimized for creating the elongation versus time plots. The tool can be used to analyze the observed tracks of features seen in the maps, and the tracks are then used to extract information, for example, on the angle of propagation of the feature.

Hall, Jeffrey R.↗
NASA NTRS1976

Shuttle autoland support program

The results of the space shuttle automatic landing support program studies performed from November 1, 1975 to March 31, 1976 were summarized. The following subjects were discussed: (1) software definition review (TAEM pre-final and Autoland only), (2) software definition review (KPIT scheduling), (3) deletion of air data, (4) June 1975 aero data update and check runs, (5) flat turn study, (6) guidance mode switching study, (7) flat turn study-additional data, (8) trajectory shaping study, (9) aero data tolerances, and (10) turbulence model study.

Source record↗
NASA NTRS2010

A Near-Term Concept for Trajectory Based Operations with Air/Ground Data Link Communication

An operating concept and required system components for trajectory-based operations with air/ground data link for today's en route and transition airspace is proposed. Controllers are fully responsible for separation as they are today, and no new aircraft equipage is required. Trajectory automation computes integrated solutions to problems like metering, weather avoidance, traffic conflicts and the desire to find and fly more time/fuel efficient flight trajectories. A common ground-based system supports all levels of aircraft equipage and performance including those equipped and not equipped for data link. User interface functions for the radar controller's display make trajectory-based clearance advisories easy to visualize, modify if necessary, and implement. Laboratory simulations (without human operators) were conducted to test integrated operation of selected system components with uncertainty modeling. Results are based on 102 hours of Fort Worth Center traffic recordings involving over 37,000 individual flights. The presence of uncertainty had a marginal effect (5%) on minimum-delay conflict resolution performance, and windfavorable routes had no effect on detection and resolution metrics. Flight plan amendments and clearances were substantially reduced compared to today s operations. Top-of-descent prediction errors are the largest cause of failure indicating that better descent predictions are needed to reliably achieve fuel-efficient descent profiles in medium to heavy traffic. Improved conflict detections for climbing flights could enable substantially more continuous climbs to cruise altitude. Unlike today s Conflict Alert, tactical automation must alert when an altitude amendment is entered, but before the aircraft starts the maneuver. In every other failure case tactical automation prevented losses of separation. A real-time prototype trajectory trajectory-automation system is running now and could be made ready for operational testing at an en route Center in 1-2 years.

McNally, David↗
NASA NTRS2022

Using Trajectory Smoothness Metrics to Identify Drones in Radar Track Data

The identification of unmanned aircraft systems (UAS) using trajectory data is considered. Specifically, a number of smoothness metrics are proposed, which can be used to distinguish UAS from other aerial objects even when they are engaged in accelerative maneuvers (non-constant-velocity flight). The metrics are evaluated on a data set from a UAS sense-and-avoid field test, which contains track data of aerial objects recorded by a vehicle-board radar system during a flight test. The metrics are found to effectively differentiate UAS from other objects such as birds for this data set. In addition, an initial statistical performance analysis of one of the smoothness metrics is undertaken, using 15 data sets deriving from multiple flight tests. The smoothness metric is shown to identify the target UAS with 95% accuracy (95% true positive rate), while achieving a false positive rate of less than 9%.

Sandip Roy↗
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 NTRS2011

The Trajectory, Orbit and Preliminary Fall Data of the JUNE BOOTID Superbolide of July 23, 2008

The results of the atmospheric trajectory, radiant, orbit and preliminary fall data calculations of an extremely bright slow-moving fireball are presented. The fireball had a -20.7 maximum absolute magnitude and the spectacular long-persistence dust trail (Fig 1 and 2) was observed in a widespread region of Tajikistan twenty eight minutes after sunset, precisely at 14h 45m 25s UT on July 23, 2008. The bolide was first recorded at a height of 38.2 km, and attained its maximum brightness at a height of 35.0 km and finished at a height of 19.6 km. These values are very much in line with other well-known fireballs producing meteorites. The first break-up must have occurred under an aerodynamic pressure Pdyn of about 1.5 MPa, similar to those derived from the study of atmospheric break-ups of previously reported meteorite-dropping bolides. Our trajectory, and dynamic results suggest that one might well expect to find meteorites on the ground in this case. The heliocentric orbit of the meteoroid determined from the observations is very similar to the mean orbit of the June Bootid meteor shower, whose parental comet is 7P/Pons-Winnecke (Lindblad et al. 2003). If the parent was indeed a comet, this has implications for the internal structure of comets, and for the survivability of cometary meteorites.

Konovalova, N. A.↗
NASA NTRS1982

Preliminary sonic boom correlation of predicted and measured levels for STS-1 entry

A preliminary analysis correlating peaks from sonic boom pressure signatures recorded during the descent trajectory of the Orbiter Columbia, which landed in the dry lake bed at Edwards Air Force Base (EAFB), California, with measured wind tunnel signatures extrapolated from flight altitudes to the ground has been made for Mach numbers ranging from 1.3 to 6. The flight pressure signatures were recorded by microphones positioned at ground level near the groundtrack, whereas the wind tunnel signatures were measured during a test of a 0.0041-scale model Orbiter. The agreement between overpressure estimates based on wind tunnel data using preliminary flight trajectory data and oscillograph traces from ground measurements appears reasonable at this time for the range of Mach numbers considered. More detailed studies using final flight trajectory data and digitized ground measured data will be performed.

Garcia, F., Jr.↗
NASA NTRS2011

Time Domain Tool Validation Using ARES I-X Flight Data

The ARES I-X vehicle was launched from NASA's Kennedy Space Center (KSC) on October 28, 2009 at approximately 11:30 EDT. ARES I-X was the first test flight for NASA s ARES I launch vehicle, and it was the first non-Shuttle launch vehicle designed and flown by NASA since Saturn. The ARES I-X had a 4-segment solid rocket booster (SRB) first stage and a dummy upper stage (US) to emulate the properties of the ARES I US. During ARES I-X pre-flight modeling and analysis, six (6) independent time domain simulation tools were developed and cross validated. Each tool represents an independent implementation of a common set of models and parameters in a different simulation framework and architecture. Post flight data and reconstructed models provide the means to validate a subset of the simulations against actual flight data and to assess the accuracy of pre-flight dispersion analysis. Post flight data consists of telemetered Operational Flight Instrumentation (OFI) data primarily focused on flight computer outputs and sensor measurements as well as Best Estimated Trajectory (BET) data that estimates vehicle state information from all available measurement sources. While pre-flight models were found to provide a reasonable prediction of the vehicle flight, reconstructed models were generated to better represent and simulate the ARES I-X flight. Post flight reconstructed models include: SRB propulsion model, thrust vector bias models, mass properties, base aerodynamics, and Meteorological Estimated Trajectory (wind and atmospheric data). The result of the effort is a set of independently developed, high fidelity, time-domain simulation tools that have been cross validated and validated against flight data. This paper presents the process and results of high fidelity aerospace modeling, simulation, analysis and tool validation in the time domain.

Hough, Steven↗
NASA NTRS1970

Space shuttle vehicle rocket plume impingement study for separation analysis. Tasks 2 and 3: Definition and preliminary plume impingement analysis for the MSC booster

The results are presented of a space shuttle plume impingement study for the Manned Spacecraft Center configuration. This study was conducted as two tasks which were to (1) define the orbiter main stage engine exhaust plume flow field, and (2) define the plume impingement heating, force and resulting moment environments on the booster during the staging maneuver. To adequately define these environments during the staging maneuver and allow for deviation from the nominal separation trajectory, a multitude of relative orbiter/booster positions are analyzed which map the region that contains the separation trajectories. The data presented can be used to determine a separation trajectory which will result in acceptable impingement heating rates, forces, and the resulting moments. The data, presented in graphical form, include the effect of roll, pitch and yaw maneuvers for the booster. Quasi-steady state analysis methods were used with the orbiter engine operating at full thrust. To obtain partial thrust results, simple ratio equations are presented.

Wojciechowski, C. J.↗
NASA NTRS1996

Attitude and Trajectory Estimation Using Earth Magnetic Field Data

The magnetometer has long been a reliable, inexpensive sensor used in spacecraft momentum management and attitude estimation. Recent studies show an increased accuracy potential for magnetometer-only attitude estimation systems. Since the Earth's magnetic field is a function of time and position, and since time is known quite precisely, the differences between the computer and measured magnetic field components, as measured by the magnetometers throughout the entire spacecraft orbit, are a function of both the spacecraft trajectory and attitude errors. Therefore, these errors can be used to estimate both trajectory and attitude. Traditionally, satellite attitude and trajectory have been estimated with completely separate system, using different measurement data. Recently, trajectory estimation for low earth orbit satellites was successfully demonstrated in ground software using only magnetometer data. This work proposes a single augmented extended Kalman Filter to simultaneously and autonomously estimate both spacecraft trajectory and attitude with data from a magnetometer and either dynamically determined rates or gyro-measured body rates.

Deutschmann, Julie↗
NASA NTRS2009

Trajectory Reconstruction of the ST-9 Sounding Rocket Experiment Using IMU and Landmark Data

This paper presents trajectory reconstruction of the ST-9 sounding rocket experiment using the onboard IMU data and descent imagery. The raw IMU accelerometer measurements are first converted into inertial acceleration and then used in trajectory integration. The descent images are pre-processed using a map-matching algorithm and unique landmarks for each image are created. Using the converted IMU data and descent images, the result from dead-reckoning and the kinematic-fix approaches are first compared with the GPS measurements. Then, both the IMU data and landmarks are processed together using a batch least-squares filter and the position, velocity, stochastic acceleration, and camera orientation of each image are estimated. The reconstructed trajectory is compared with the GPS data and the corresponding formal uncertainties are presented. The result shows that IMU data and descent images processed with a batch filter algorithm provide the trajectory accuracy required for pin-point landing.

Park, Ryan S.↗
NASA NTRS2022

Reconstruction of the Apollo 11 Moon Landing Final Descent Trajectory

Relatively limited data on the Apollo 11 pre-planned and as-flown trajectories are available in the open literature and in the NASA archives. Furthermore, a single report appears to be the only source containing plots comparing the pre-planned and as-flown final approach and landing trajectories. The plots in that report, however, are small and difficult to read, and contain data that are insufficient for directly reconstructing the final landing trajectory. In this report, several published graphics are digitized, and then a variety of least-squares and Kalman filter estimators are applied using kinematic equations and simplified dynamic equations to reconstruct the final descent trajectory. The reconstructed trajectory is important in the crew training effort for program Artemis, which intends to send humans back to the moon, as well as other studies focusing on landing on extraterrestrial worlds.

Apollo 11↗
NASA NTRS1983

Predictions of entry heating for lower surface of shuttle orbiter

A broad base of thermocouple and phase change paint data was assembled and correlated to the nominal design 14414.1 and proposed STS-1 (first flight of the space transportation system) entry trajectories. Averaged data from phase change paint tests compared favorably with thermocouple data for predicting heating rates. Laminar and turbulent radiation equilibrium heating rates were computed on the lower surface of the Shuttle orbiter for both trajectories, and the lower surface center line results were compared both with aerodynamic heating design data and with flight values from the STS-1 and STS-2 trajectories. The peak laminar heating values from the aerodynamic heating design data book were generally 40 to 60 percent higher than the laminar estimates of this study, except at the 55 percent location of maximum span where the design data book values were less than 10 percent higher. Estimates of both laminar and turbulent heating rates compared favorably with flight data.

Edwards, C. L. W.↗
NASA NTRS2011

An Intercomparison of Tropospheric Ozone Retrievals Derived from Two Aura Instruments and Measurements in Western North America in 2006

Two recently developed methods for quantifying tropospheric ozone abundances based on Aura data, the Trajectory‐enhanced Tropospheric Ozone Residual (TTOR) and an assimilation of Aura data into Goddard Earth Observing System Version 4 (ASM), are compared to ozone measurements from ozonesonde data collected in April-May 2006 during the INTEX Ozonesonde Network Study 2006 (IONS‐06) campaign. Both techniques use Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS) observations. Statistics on column ozone amounts for both products are presented. In general, the assimilation compares better to sonde integrated ozone to 200 hPa (28.6% difference for TTOR versus 2.7% difference for ASM), and both products are biased low. To better characterize the performance of ASM, ozone profiles based on the assimilation are compared to those from ozonesondes. We noted slight negative biases in the lower troposphere, and slight positive biases in the upper troposphere/lower stratosphere (UT/ LS), where we observed the greatest variability. Case studies were used to further understand ASM performance. We examine one case from 17 April 2006 at Bratt's Lake, Saskatchewan, where geopotential height gradients appear to be related to an underestimation in the ASM in the UT/LS region. A second case, from 21 April 2006 at Trinidad Head, California, is a situation where the overprediction of ozone in the UT/LS region does not appear to be due to current dynamic conditions but seems to be related to uncertainty in the flow pattern and large differences in MLS observations upstream.

UTLS↗
NASA NTRS2014

Background Error Covariance Estimation using Information from a Single Model Trajectory with Application to Ocean Data Assimilation into the GEOS-5 Coupled Model

An attractive property of ensemble data assimilation methods is that they provide flow dependent background error covariance estimates which can be used to update fields of observed variables as well as fields of unobserved model variables. Two methods to estimate background error covariances are introduced which share the above property with ensemble data assimilation methods but do not involve the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The Space Adaptive Forecast error Estimation (SAFE) algorithm estimates error covariances from the spatial distribution of model variables within a single state vector. The Flow Adaptive error Statistics from a Time series (FAST) method constructs an ensemble sampled from a moving window along a model trajectory. SAFE and FAST are applied to the assimilation of Argo temperature profiles into version 4.1 of the Modular Ocean Model (MOM4.1) coupled to the GEOS-5 atmospheric model and to the CICE sea ice model. The results are validated against unassimilated Argo salinity data. They show that SAFE and FAST are competitive with the ensemble optimal interpolation (EnOI) used by the Global Modeling and Assimilation Office (GMAO) to produce its ocean analysis. Because of their reduced cost, SAFE and FAST hold promise for high-resolution data assimilation applications.

Data Assimilation↗