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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Sample Handling in Extreme Environments

Harsh environments, such as that on Venus, preclude the use of existing equipment for functions that involve interaction with the environment. The operating limitations of current high temperature electronics are well below the actual temperature and pressure found on Venus (460 deg C and 92 atm), so proposed lander configurations typically include a pressure vessel where the science instruments are kept at Earth-like temperature and pressure (25 deg C and 1 atm). The purpose of this project was to develop and demonstrate a method for sample transfer from an external drill to internal science instruments for a lander on Venus. The initial concepts were string and pneumatically driven systems; and the latter system was selected for its ability to deliver samples at very high speed. The pneumatic system was conceived to be driven by the pressure difference between the Venusian atmosphere and the inside of the lander. The pneumatic transfer of a small capsule was demonstrated, and velocity data was collected from the lab experiment. The sample transfer system was modeled using CAD software and prototyped using 3D printing. General structural and thermal analyses were performed to approximate the proposed system's mass and effects on the temperature and pressure inside of the lander. Additionally, a sampler breadboard for use on Titan was tested and functionality problems were resolved.

sample handling↗
NASA NTRS2015

The NASA MSFC Electrostatic Levitation (ESL) Laboratory: Summary of Capabilities, Recent Upgrades, and Future Work

The NASA Marshall Space Flight Center (MSFC) electrostatic levitation (ESL) laboratory has a long history of providing materials research and thermophysical property data. A summary of the labs capabilities, recent upgrades, and ongoing and future work will be provided. The laboratory has recently added two new capabilities to its main levitation chamber: a rapid quench system and an oxygen control system. The rapid quench system allows samples to be dropped into a quench vessel that can be filled with a low melting point material, such as a gallium or indium alloy. Thereby allowing rapid quenching of undercooled liquid metals. The oxygen control system consists of an oxygen sensor, oxygen pump, and a control unit. The sensor is a potentiometric device that determines the difference in oxygen activity between two gas compartments separated by an electrolyte, which is yttria-stabilized zirconia. The pump utilizes coulometric titration to either add or remove oxygen. The system is controlled by a desktop control unit, which can also be accessed via a computer. This system allows the oxygen partial pressure within the vacuum chamber to be measured and controlled, theoretically in the range from 10-36 to 100 bar. The ESL laboratory also has an emissometer, called the High-Temperature Emissivity Measurement System (HiTEMS). This system measures the spectral emissivity of materials from 600degC to 3,000degC. The system consists of a vacuum chamber, a black body source, and a Fourier Transform Infrared Spectrometer (FTIR). The system utilizes optics to swap the signal between the sample and the black body. The system was originally designed to measure the hemispherical spectral emissivity of levitated samples, which are typically 2.5mm spheres. Levitation allows emissivity measurements of molten samples, but more work is required to develop this capability. The system is currently setup measure the near-normal spectral emissivity of stationary samples, which has been used to take measurements of ablative materials, rocket nozzle coating materials, and materials for spacecraft instruments.

SanSoucie, Michael P.↗
NASA NTRS2019

Emissions Relationships in Western Forest Fire Plumes: I. Reducing the Effect of Mixing Errors on Emission Factors

Studies of emission factors from biomass burning using aircraft data complement the results of lab studies and extend them to conditions of immense hot conflagrations. We illustrate and discuss emission relationships for 422 individual samples from many forest-fire plumes in the Western US. The samples are from two NASA investigations: ARCTAS (Arctic Research of the Composition of the Troposphere from Aircraft and Satellites) and SEAC4RS (Studies of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys). This work provides sample-by-sample enhancement ratios (EnRs) for 23 gases and particulate properties. Many EnRs provide candidates for emission ratios (ERs, corresponding to the EnR at the source) when the origin and degree of transformation is understood and appropriate. From these, emission factors (EFs) can be estimated when the fuel dry mass consumed is known or can be estimated using the carbon mass budget approach. This analysis requires understanding the interplay of mixing of the plume with surrounding air. Some initial examples emphasize that measured C(tot) = CO2 + CO in a fire plume does not necessarily describe the emissions of the total carbon liberated in the flames, C(burn). Rather, it represents C(tot) = C(burn) + C(bkgd), which includes possibly varying background concentrations for entrained air. Consequently, we present a simple theoretical description for plume entrainment for multiple tracers from flame to hundreds of kilometers downwind and illustrate some intrinsic linear behaviors. The analysis suggests a Mixed Effects Regression Emission Technique (MERET), which can eliminate occasional strong biases associated with the commonly used normalized excess mixing ratio (NEMR) method. MERET splits C(tot) to reveal C(burn) by exploiting the fact that C(burn) and all tracers respond linearly to dilution, while each tracer has consistent EnR behavior (slope of tracer concentration with respect to C(burn)). The two effects are separable. Two or three or preferably more emission indicators are required as a minimum; here we used ten. Limited variations in the EnRs for each tracer can be incorporated and the variations and co-variations analyzed. The percentage CO yield (or the modified combustion efficiency) plays some role. Other co-relationships involving nitrogen and organic classes are more prominent; these have strong relationships to the C(burn) to O3 emission relationship. In summary, MERET allows fine spatial resolution (EnRs for individual observations) and comparison of similar plumes distant in time and space. Alkene ratios provide us with an approximate photochemical timescale. This allows discrimination and definition, by fire situation, of ERs, allowing us to estimate emission factors.

Chatfield, Robert B.↗
NASA NTRSDate not supplied

Crew Autonomy Through Self-Scheduling: Operational Characterization

NASA’s future long-duration exploration missions (LDEMs) will encounter increasing communication transmission delays as they move farther from Earth-based ground stations. This necessitates a new approach, as crews can no longer rely on real-time support from ground planners and must self-schedule their own operational timelines effectively and efficiently. To enable this transition, our team has developed Playbook, a mission planning and scheduling tool. Our research focuses on quantifying scheduling performance using Playbook to inform the design and development of future features to streamline timeline creation. We also aim to propose standards and guidelines for autonomous crews in LDEMs. In the past year, we have focused on further validating and quantifying the effects of countermeasure aids on self-scheduling performance. There are two software aids in Playbook (self-scheduling platform): Suggested Fixes, which propose an edit to resolve violations within a timeline, and No-Go Zones, which highlight where activities should not be scheduled on a timeline. We have made significant progress in HERA Campaign 7 (C7) data collection, increasing the number of days crew must self-schedule from 4 to 8. As a result, almost 20% of the mission is self-scheduled by the analog astronauts. We have also started data collection on a controlled lab experiment designed to quantify performance effects due to the countermeasures. We expect to present the preliminary results from both efforts. Finally, we have conducted an exploratory analysis of NASA’s HERA Campaign 6 (C6), investigating the mission-level impacts of self-scheduling. We derived basic patterns and descriptive statistics to better characterize crew autonomy through self-scheduling. We also assessed if there are any individual indicators of preference for self-scheduling, such as experience or predilection for autonomy. Preliminary analysis indicates that the HERA C6 crew self-scheduled one out of four flexible activities, indicating unprompted adoption of self-scheduling as a concept of operation for crew autonomy.

analog↗
DOE OSTI2021

Accomplishments and Year-End Performance Report; Wind Energy Program: Fiscal Year 2021

The National Wind Technology Center (NWTC), located at the U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory (NREL) Flatirons Campus, has been a driving force in advancing wind energy technology research worldwide since its designation as a DOE national research center in 1992. Enabled by the Flatirons Campus's world-class facilities, scientists, engineers, analysts, and researchers are pushing the frontiers of science to pursue wind energy innovation. In Fiscal Year (FY) 2021, NREL continued to provide the technical expertise, research capabilities, and industry understanding to support DOE's ambitious climate action and research goals by advancing technology, addressing market and deployment barriers, and driving down costs with more efficient, reliable, and predictable wind energy systems. One of several highlights, NREL received an R&D 100 Special Recognition Award for its Thermoplastic Resin System for Wind Turbine Blades. This breakthrough in the wind turbine manufacturing process will enable the production of recyclable blades that are stronger, longer, and less expensive, while increasing energy capture, decreasing energy and transportation costs, and increasing blade reliability. In a year when the entire U.S. economy struggled to address workforce gaps, an NREL study compared wind industry needs, training programs, and hiring practices with perspectives from students and recent college graduates. Researchers hope that, by pinpointing areas of disconnect, the expectations of employers who have difficulty filling entry-level jobs can better align with the preparation of the potential applicants who find it hard to break into the field. The lab also made numerous new data and modeling resources available in FY 2021. Recent NREL releases include a modeling tool for predicting the power performance and structural loads of wind turbines within a wind farm (FAST.Farm), a computational framework for modeling golden eagle behavior near wind farms, and 20 years of offshore wind data. Updates were also made to the widely used Wind Plant Integrated Systems Design and Engineering Model (WISDEM), which couples engineering and cost models to examine system-level trade-offs. Now, bolstered by a renewed national commitment to tackle climate change and revitalize the U.S. economy through increased investment in clean energy - particularly in offshore wind energy - NREL stands poised to lead the way to a sustainable future that powers the United States with significant levels of reliable, low-cost, accessible wind energy. This report provides an overview of the achievements NREL made on behalf of DOE's Wind Energy Technologies Office (WETO) and other partners during FY 2021 (between Oct. 1, 2020, and Sept. 30, 2021).

Flatirons Campus↗
DOE OSTI2023

Understanding the EMC effect with tagged DIS measurements

Understanding the modification of quarks in nucleons within nuclei (EMC effect) is a longstanding open question in nuclear physics. Recent experimental results from electron scattering at Jefferson Lab strengthen the correlation between the EMC effect and short- range correlated pairs (SRC) of nucleons in nuclei. That means that the EMC effect is probably driven by the high-momentum highly-virtual nucleons of the SRC pairs. This connection can be tested experimentally by measuring electron deep inelastic scattering from a nucleon and detecting its correlated SRC partner nucleon (tagging). This allows us to measure the quark modification of high-momentum nucleons. Two tagged experiments on deuterium are underway at Jefferson Lab of which one already took data and the other will take data in the upcoming years. In my talk, I will present the current knowledge of the EMC effect and its correlation to SRC pairs, the status of the tagged measurements at Jefferson Lab, and simulation results for tagged measurements at the EIC.

Hauenstein, Florian↗
DOE OSTI2022

Understanding the EMC effect with tagged DIS measurements

Understanding the modification of quarks in nucleons within nuclei (EMC effect) is a longstanding open question in nuclear physics. Recent experimental results from electron scattering at Jefferson Lab strengthen the correlation between the EMC effect and short- range correlated pairs (SRC) of nucleons in nuclei. That means that the EMC effect is probably driven by the high-momentum highly-virtual nucleons of the SRC pairs. This connection can be tested experimentally by measuring electron deep inelastic scattering from a nucleon and detecting its correlated SRC partner nucleon (tagging). This allows us to measure the quark modification of high-momentum nucleons. Two tagged experiments on deuterium are underway at Jefferson Lab of which one already took data and the other will take data in the upcoming years. In my talk, I will present the current knowledge of the EMC effect and its correlation to SRC pair and the status of the tagged measurements at Jefferson Lab.

Hauenstein, Florian↗
DOE OSTI2021

UEMtomaton: A Source-Available Platform to Aid in Start-up of Ultrafast Electron Microscopy Labs

The steady rise in the number of ultrafast electron microscopy (UEM) labs, in addition to the opacity and lack of detailed descriptions of current approaches that would enable point-by-point construction, has created an opportunity for sharing common methods and instrumentation for (for example) automating data acquisition to assist in efficient lab start-up and to learn about common and robust protocols. In the spirit of open sharing of methods, we provide here a description of an entry-level method and user interface (UI) for automating UEM experiments, and we provide access to the source code and scripts (source-available) for ease of implementation or as a starting reference point for those entering or seeking to enter the field (https://github.com/CEMSFlannigan/UEMtomaton/releases/tag/v1.0). Core instrumentation and physical connections in the UEM lab at Minnesota are described. Interface communication schemes consisting of duo server-client pairs between critical components – the optical delay stage and the UEM digital camera – are presented, with emphasis placed on describing the logic and communications sequence designed to conduct automated series acquisitions. An application designed and programmed with C++/CLI as Windows Forms in Microsoft Visual Studio – dubbed UEMtomaton – is also presented. Key to the UI layout is centralization of the automation tasks and establishment of communication within the software rather than by interfacing with each individual workstation. It is our hope that this note provides useful insight for current and future UEM researchers, particularly with respect to generalizability and portability of the approach to emerging labs. Here, we note that while this basic, entry-level approach is certainly not the most sophisticated or comprehensive of those currently in use, we feel there is nevertheless value in clearly communicating a proven straightforward method to hopefully lower the barrier to entry into the field.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Dispersive corrections in elastic electron-nucleus scattering: an investigation in the intermediate energy regime and their impact on the nuclear matter

Measurements of elastic electron scattering data within the past decade have highlighted two-photon exchange contributions as a necessary ingredient in theoretical calculations to precisely evaluate hydrogen elastic scattering cross sections. This correction can modify the cross section at the few percent level. In contrast, dispersive effects can cause significantly larger changes from the Born approximation. The purpose of this experiment is to extract the carbon-12 elastic cross section around the first diffraction minimum, where the Born term contributions to the cross section are small to maximize the sensitivity to dispersive effects. The analysis uses the LEDEX data from the high resolution Jefferson Lab Hall A spectrometers to extract the cross sections near the first diffraction minimum of 12 C at beam energies of 362 MeV and 685 MeV. The results are in very good agreement with previous world data, although with less precision. The average deviation from a static nuclear charge distribution expected from linear and quadratic fits indicate a 30.6% contribution of dispersive effects to the cross section at 1 GeV. The magnitude of the dispersive effects near the first diffraction minimum of 12 C has been confirmed to be large with a strong energy dependence and could account for a large fraction of the magnitude for the observed quenching of the longitudinal nuclear response. These effects could also be important for nuclei radii extracted from parity-violating asymmetries measured near a diffraction minimum.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2020

CyberGAN: Generating High-fidelity Cybersecurity Data With Generative Adversarial Networks

Machine learning for cyber defense offers the promise of detecting adversarial activity against the ground data systems managing critical space assets. A fundamental challenge facing machine learning research in cybersecurity is the lack of high-fidelity, shareable datasets for robust evaluation and testing of machine learning-based solutions. High-fidelity, real-world datasets are necessary for reliable benchmarking of nominal system behavior and malicious activity. Unfortunately, such realistic datasets of both nominal and adversarial activity are rarely shared publicly by data owners due to security and privacy concerns. Besides, the available adversarial data is sparse, which makes training models on malicious activity much harder. This situation has impeded and continues to impede the research and successful adoption of machine learning methods for cyber defense. Researchers have dealt with this problem by generating data within a low-fidelity lab environment, using classified and thus unshareable datasets, or downloading low-fidelity public datasets made available by others. We propose an innovative solution to the problem by employing machine learning methods to generate high-fidelity data. Specifically, we propose the use of Generative Adversarial Networks (GANs) to generate high-fidelity data for cybersecurity purposes. GANs have found successful image processing and natural language applications, but have not yet been investigated for cyber data generation. Our proposed approach first involves training the `discriminator' network of the GAN with a sample of real-world data consisting of malicious and nominal samples. We then use the `generator' network to generate new high-fidelity data samples consisting of an appropriate mix of malicious and nominal activity. We demonstrate applications of our architecture by generating high-fidelity cybersecurity data containing both malicious and nominal samples. We thoroughly evaluate the fidelity of our generated data using heuristics and evaluate its usefulness for machine learning applications using three different datasets. Overall, our approach results in high-fidelity, shareable datasets.

Zhang, Yuening↗
DOE OSTI2022

UAS remote sensing (DJI Phantom 4 RTK platform): RGB orthomosaic, digital surface and canopy height models, plant functional type map, Seward Peninsula, Alaska, 2019

Airborne remote sensing data collected using a DJI Phantom 4 RTK unoccupied aerial system (UAS) ? operated by the University of Maine Wheatland Geospatial Lab (https://wheatlandlab.org/). This package includes data from 17 flights flown over the NGEE-Arctic Council, Kougarok, Kougarok Mile80, Teller, and Teller Mile32 sites in July 2019. The Phantom 4 RTK is a drone platform that collects very high spatial resolution optical red/green/blue (RGB) imagery. Derived image products include point cloud, ortho-mosaiced RGB, a digital surface model (DSM) using the structure from motion (SfM) technique, and a canopy height model (CHM). Unprocessed and processed data products (1,000+ files) are included in this package (processing levels 0-3). Data and metadata are provided as text (*.txt, *.json, *hdr,), ENVI image file (*.dat), point cloud (*.laz) and image (*.jpg, *.tif, *png) formats. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Determination of the argon spectral function from ( e , e ' p ) data

The E12-14-012 experiment, performed in Jefferson Lab Hall A, has measured the $(e, e'p)$ cross section in parallel kinematics using a natural argon target. Here, we report the full results of the analysis of the data set corresponding to beam energy 2.222 GeV, and spanning the missing momentum and missing energy range $15 \lesssim p_m \lesssim 300$ MeV/c and $12 \lesssim E_m \lesssim 80$ MeV. The reduced cross section, determined as a function of $p_m$ and $E_m$ with $\approx$4\% accuracy, has been fitted using the results of Monte Carlo simulations involving a model spectral function and including the effects of final state interactions. The overall agreement between data and simulations turns out to be quite satisfactory ($\chi^2$/n.d.o.f.=1.9). Furthermore, the resulting spectral function will provide valuable new information, needed for the interpretation of neutrino interactions in liquid argon detectors.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2005

Stennis Space Center Verification & Validation Capabilities

Scientists within NASA s Applied Sciences Directorate have developed a well-characterized remote sensing Verification & Validation (V&V) site at the John C. Stennis Space Center (SSC). This site enables the in-flight characterization of satellite and airborne high spatial and moderate resolution remote sensing systems and their products. The smaller scale of the newer high resolution remote sensing systems allows scientists to characterize geometric, spatial, and radiometric data properties using a single V&V site. The targets and techniques used to characterize data from these newer systems can differ significantly from the techniques used to characterize data from the earlier, coarser spatial resolution systems. Scientists are also using the SSC V&V site to characterize thermal infrared systems and active lidar systems. SSC employs geodetic targets, edge targets, radiometric tarps, atmospheric monitoring equipment, and thermal calibration ponds to characterize remote sensing data products. The SSC Instrument Validation Lab is a key component of the V&V capability and is used to calibrate field instrumentation and to provide National Institute of Standards and Technology traceability. This poster presents a description of the SSC characterization capabilities and examples of calibration data.

Pagnutti, Mary↗
DOE OSTI2020

SNL will be able to provide well-calibrated models to weapons systems analysts by integrating an engine for constitutive model calibration with the GRANTA materials database

Researchers at Sandia National Laboratories have integrated the GRANTA materials database with the MatCal calibration engine to calibrate material models from characterization data. GRANTA is gaining acceptance across the NNSA Tri-lab complex and is being populated with weapons-specific test data by Sandia experimentalists. To use that data to create material models for use by weapons systems analysts, MatCal has been enabled import calibration data and test conditions from GRANTA to quickly and reproducibly produce a calibrated set of parameters for a given constitutive model. The team is currently working to store the parameters characterizing material behavior in GRANTA to make them accessible by all weapons analysts.

36 MATERIALS SCIENCE↗
NASA NTRS1991

Software reliability report

There are many software reliability models which try to predict future performance of software based on data generated by the debugging process. Unfortunately, the models appear to be unable to account for the random nature of the data. If the same code is debugged multiple times and one of the models is used to make predictions, intolerable variance is observed in the resulting reliability predictions. It is believed that data replication can remove this variance in lab type situations and that it is less than scientific to talk about validating a software reliability model without considering replication. It is also believed that data replication may prove to be cost effective in the real world, thus the research centered on verification of the need for replication and on methodologies for generating replicated data in a cost effective manner. The context of the debugging graph was pursued by simulation and experimentation. Simulation was done for the Basic model and the Log-Poisson model. Reasonable values of the parameters were assigned and used to generate simulated data which is then processed by the models in order to determine limitations on their accuracy. These experiments exploit the existing software and program specimens which are in AIR-LAB to measure the performance of reliability models.

Wilson, Larry↗
DOE OSTI2023

Verifying MCNP Models of the TEX High 240 Plutonium Benchmark

Computational modeling programs are invaluable tools that allow us to understand systems, safely develop new processes, and make reliable predictions about future designs. However, the effectiveness of these codes is limited by the degree to which their parameters match the real world. In the field of nuclear engineering, cross section data is one of these vital parameters. Accurate cross section data on important fissile and fissionable isotopes promotes the design of safer and more efficient fabrication, transportation, storage, and stockpiling of nuclear fuel. Unfortunately, there are knowledge gaps in data on key isotopes. In 2011, a multinational meeting hosted by the US Department of Energy Nuclear Criticality Safety Program ranked the priority of certain cross section data needs. In response, Lawrence Livermore National Lab (LLNL) designed the Thermal and Epithermal eXperiment (TEX) series of benchmark experiments. Benchmark experiments are used to validate current cross section data. They validate data by comparing the results of an actual experiment to the predicted results from a computational model. The data a benchmark applies to depends on the isotope and energy range the experiment’s neutron multiplication factor ( k eff ) is most sensitive to. The development and testing of the TEX High 240 Plutonium Benchmark will help validate 240 Pu cross section data. The configuration and materials of this benchmark are designed to be most sensitive to 240 Pu's intermediate energy range (from 0.625 ev to 100 keV ). MCNP® models of the assembly have been developed by LLNL and the results have been written in the final design report. In order for the discrepancies between benchmark models and experiments to be attributed to cross section inaccuracies, the accuracy of the models needs to be verified. The goal of this project is to verify of the results of LLNL's modeling by creating a new set of MCNP models and comparing the results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Hard exclusive $\pi^{+}n$ electro production beam spin asymmetries off the proton in the GPD and TDA regimes

Hard exclusive \pi^{+} π + n electro-production can be used to gain access to the 3D nucleon structure. The QCD factorisation mechanism in the “nearly forward region” ( t/Q^{2} t / Q 2 small) allows a description by Generalized Parton Distributions (GPDs), while for the “nearly backward” kinematic region ( u/Q^{2} u / Q 2 small) a description based on nucleon to pion transitions (TDAs) is available. The paper presents a measurement of single beam spin asymmetries to extract the A^{\sin\phi}_{LU} A L U sin ϕ moments and the related cross section ratio \sigma_{LT^\prime}/\sigma_{0} σ L T ′ / σ 0 from the hard exclusive \pi^{+} π + channel off the unpolarized hydrogen target in a wide range of kinematics based on data taken with the CLAS spectrometer at Jefferson Lab. In addition, under forward angles a detailed multidimensional study will be presented based on CLAS12 data and compared to theoretical predictions.

Diehl, Stefan↗
NASA NTRS2004

Orbit Determination of the Thermosphere, Ionosphere, Mesosphere, Energetics and Dynamics (TIMED) Mission Using Differenced One-way Doppler (DOWD)Tracking Data from the Tracking and Data Relay Satellite System (TDRSS)

Over an approximately 48-hour period from September 26 to 28,2002, the Thermosphere, Ionosphere, Mesosphere, Energetics and Dynamics (TIMED) mission was intensively supported by the Tracking and Data Relay Satellite System (TDRSS). The TIMED satellite is in a nearly circular low-Earth orbit with a semimajor axis of approximately 7000 km and an inclination of approximately 74 degrees. The objective was to provide TDRSS tracking support for orbit determination (OD) to generate a definitive ephemeris of 24-hour duration or more with a 3-sigma position error no greater than 100 meters, and this tracking campaign was successful. An ephemeris was generated by Goddard Space Flight Center (GSFC) personnel using the TDRSS tracking data and was compared with an ephemeris generated by the Johns Hopkins University's Applied Physics Lab (APL) using TIMED Global Positioning System (GPS) data. Prior to the tracking campaign OD error analysis was performed to justify scheduling the TDRSS support.

Marr, Greg C.↗