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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Traverse Planning Experiments for Future Planetary Surface Exploration

The purpose of the investigation is to evaluate methodology and data requirements for remotely-assisted robotic traverse of extraterrestrial planetary surface to support human exploration program, assess opportunities for in-transit science operations, and validate landing site survey and selection techniques during planetary surface exploration mission analog demonstration at Haughton Crater on Devon Island, Nunavut, Canada. Additionally, 1) identify quality of remote observation data sets (i.e., surface imagery from orbit) required for effective pre-traverse route planning and determine if surface level data (i.e., onboard robotic imagery or other sensor data) is required for a successful traverse, and if additional surface level data can improve traverse efficiency or probability of success (TRPF Experiment). 2) Evaluate feasibility and techniques for conducting opportunistic science investigations during this type of traverse. (OSP Experiment). 3) Assess utility of remotely-assisted robotic vehicle for landing site validation survey. (LSV Experiment).

Hoffman, Stephen J.↗
NASA NTRS2018

New Neural Network Cloud Mask Algorithm Based on Radiative Transfer Simulations

Cloud detection and screening constitute critically important first steps required to derive many satellite data products. Traditional threshold-based cloud mask algorithms require a complicated design process and fine tuning for each sensor, and they have difficulties over areas partially covered with snow/ice. Exploiting advances in machine learning techniques and radiative transfer modeling of coupled environmental systems, we have developed a new, threshold-free cloud mask algorithm based on a neural network classifier driven by extensive radiative transfer simulations. Statistical validation results obtained by using collocated CALIOP and MODIS data show that its performance is consistent over different ecosystems and significantly better than the MODIS Cloud Mask (MOD35 C6) during the winter seasons over snow-covered areas in the mid-latitudes. Simulations using a reduced number of satellite channels also show satisfactory results, indicating its flexibility to be configured for different sensors. Comparedto threshold-based methods and previous machine-learning approaches, this new cloud mask (i) does not rely on thresholds, (ii) needs fewer satellite channels, (iii) has superior performance during winter seasons in mid-latitude areas, and (iv) can easily be applied to different sensors.

cloud mask algorithms↗
NASA NTRS2011

Plug-and-Play Environmental Monitoring Spacecraft Subsystem

A Space Environment Monitor (SEM) subsystem architecture has been developed and demonstrated that can benefit future spacecraft by providing (1) real-time knowledge of the spacecraft state in terms of exposure to the environment; (2) critical, instantaneous information for anomaly resolution; and (3) invaluable environmental data for designing future missions. The SEM architecture consists of a network of plug-and- play (PnP) Sensor Interface Units (SIUs), each servicing one or more environmental sensors. The SEM architecture is influenced by the IEEE Smart Transducer Interface Bus standard (IEEE Std 1451) for its PnP functionality. A network of PnP Spacecraft SIUs is enabling technology for gathering continuous real-time information critical to validating spacecraft health in harsh space environments. The demonstrated system that provided a proof-of-concept of the SEM architecture consisted of three SIUs for measurement of total ionizing dose (TID) and single event upset (SEU) radiation effects, electromagnetic interference (EMI), and deep dielectric charging through use of a prototype Internal Electro-Static Discharge Monitor (IESDM). Each SIU consists of two stacked 2X2 in. (approximately 5X5 cm) circuit boards: a Bus Interface Unit (BIU) board that provides data conversion, processing and connection to the SEM power-and-data bus, and a Sensor Interface Electronics (SIE) board that provides sensor interface needs and data path connection to the BIU.

Patel, Jagdish↗
DOE OSTI2024

An engineered lactate oxidase based electrochemical sensor for continuous detection of biomarker lactic acid in human sweat and serum

Lactate levels in humans reveal intensity and duration of exertion and provide a critical readout for the severity of life-threatening illnesses such as pediatric sepsis. Using the lactate oxidase enzyme (Lox) from Aerococcus viridians, we demonstrated its functionality for lactate electrochemical sensing in physiological fluids in a lab setting. The structure and dynamics of LOx were validated by crystallography, X-ray scattering, and hydroxyl radical protein footprinting. This provided a validated protein template for understanding and designing an enzyme-based electrochemical sensing elements. Using this template, LOx enzyme variants were generated and compared. Comparison of the variants demonstrates that one exhibits effective lactate sensing at significantly reduced operating voltages. Additionally, we demonstrate that the four hexahistidine-tags on each enzyme tetramer are sufficient for immobilization to create a durable, functional sensor, with no need for a covalent attachment, enabling self-immobilization and eliminating the need for additional immobilization steps. The functionality of the LOx enzyme variants was verified at physiological lactate concentrations in both human serum (0–4 mM) and artificial sweat (0–100 mM) using 3-electrode setups for analysis of the three variants in parallel. Accuracy of measurement in both artificial sweat and human serum were high. Employing a microfluidic flow cell, we successfully monitored varying lactate levels in physiological fluids continuously over a 2h period. Overall, this optimized LOx enzyme, which self-immobilizes onto gold sensing electrodes, facilitates efficient and reliable lactate detection and continuous monitoring at reduced operating voltages suitable for further development towards commercial use.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2024

Pre-Launch Calibration and Validation of the Airborne Hyper-Angular Rainbow Polarimeter (AirHARP) Instrument

The Airborne Hyper-Angular Rainbow Polarimeter (AirHARP) is a new imaging polarimeter instrument capable of sampling a single Earth target from up to 120 viewing angles, in four spectral channels, and in three linear polarization states across a 114° field of view (FOV). AirHARP is telecentric in the image space and simultaneously images three linear polarization states with no moving parts. These two aspects of the design allow for a simple and efficient quantitative calibration. Using coefficients derived at the center of the lens and the detector flatfields, we can calibrate the entire AirHARP sensor in a variety of laboratory, field, and space environments. We show that this telecentric calibration technique yields a 1σ absolute uncertainty of 0.25 % in degree of linear polarization (DOLP) in the laboratory for all channels and for pixels around the optical axis. To validate across the FOV, we compare our multi-angle reflectance and polarization data with the Research Scanning Polarimeter (RSP) over targets sampled during the NASA Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign. We use the error-normalized difference technique to estimate how well the instruments compare relative to their error models. We find that AirHARP and the RSP reasonably agree for reflectance and DOLP within 2 standard deviations of their mutual uncertainty at 550, 670, and 870 nm and over a limited set of ocean and desert scenes. This calibration technique makes the Hyper-Angular Rainbow Polarimeter (HARP) design attractive for new spaceborne climate missions: HARP CubeSat (2020–2022), HARP2 (2024–) on the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE), and beyond.

Airborne Hyper-Angular Rainbow Polarimeter↗
NASA NTRS2012

Detection Thresholds of Falling Snow from Satellite-Borne Active and Passive Sensors

Precipitation, including rain and snow, is a critical part of the Earth's energy and hydrology cycles. Precipitation impacts latent heating profiles locally while global circulation patterns distribute precipitation and energy from the equator to the poles. For the hydrological cycle, falling snow is a primary contributor in northern latitudes during the winter seasons. Falling snow is the source of snow pack accumulations that provide fresh water resources for many communities in the world. Furthermore, falling snow impacts society by causing transportation disruptions during severe snow events. In order to collect information on the complete global precipitation cycle, both liquid and frozen precipitation must be collected. The challenges of estimating falling snow from space still exist though progress is being made. These challenges include weak falling snow signatures with respect to background (surface, water vapor) signatures for passive sensors over land surfaces, unknowns about the spherical and non-spherical shapes of the snowflakes, their particle size distributions (PSDs) and how the assumptions about the unknowns impact observed brightness temperatures or radar reflectivities, differences in near surface snowfall and total column snow amounts, and limited ground truth to validate against. While these challenges remain, knowledge of their impact on expected retrieval results is an important key for understanding falling snow retrieval estimations. Since falling snow from space is the next precipitation measurement challenge from space, information must be determined in order to guide retrieval algorithm development for these current and future missions. This information includes thresholds of detection for various sensor channel configurations, snow event system characteristics, snowflake particle assumptions, and surface types. For example, can a lake effect snow system with low (approx 2.5 km) cloud tops having an ice water content (IWC) at the surface of 0.25 g / cubic m and dendrite snowflakes be detected? If this information is known, we can focus retrieval efforts on detectable storms and concentrate advances on achievable results. Here, the focus is to determine thresholds of detection for falling snow for various snow conditions over land and lake surfaces. The results rely on simulated Weather Research Forecasting (WRF) simulations of falling snow cases since simulations provide all the information to determine the measurements from space and the ground truth. Sensitivity analyses were performed to better ascertain the relationships between multifrequency microwave and millimeter-wave sensor observations and the falling snow/underlying field of view. In addition, thresholds of detection for various sensor channel configurations, snow event system characteristics, snowflake particle assumptions, and surface types were studied. Results will be presented for active radar at Ku, Ka, and W-band and for passive radiometer channels from 10 to 183 GHz.

Gail Skofronick-Jackson↗
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↗
DOE OSTI2015

Ultrasonic Transducer Irradiation Test Results

Ultrasonic technologies offer the potential for high-accuracy and -resolution in-pile measurement of a range of parameters, including geometry changes, temperature, crack initiation and growth, gas pressure and composition, and microstructural changes. Many Department of Energy-Office of Nuclear Energy (DOE-NE) programs are exploring the use of ultrasonic technologies to provide enhanced sensors for in-pile instrumentation during irradiation testing. For example, the ability of small diameter ultrasonic thermometers (UTs) to provide a temperature profile in candidate metallic and oxide fuel would provide much needed data for validating new fuel performance models. Other ongoing efforts include an ultrasonic technique to detect morphology changes (such as crack initiation and growth) and acoustic techniques to evaluate fission gas composition and pressure. These efforts are limited by the lack of identified ultrasonic transducer materials capable of long term performance under irradiation test conditions. For this reason, the Pennsylvania State University (PSU) was awarded an ATR NSUF project to evaluate the performance of promising magnetostrictive and piezoelectric transducers in the Massachusetts Institute of Technology Research Reactor (MITR) up to a fast fluence of at least 10 21 n/cm 2 . The goal of this research is to characterize and demonstrate magnetostrictive and piezoelectric transducer operation during irradiation, enabling the development of novel radiation-tolerant ultrasonic sensors for use in Material Testing Reactors (MTRs). As such, this test is an instrumented lead test and real-time transducer performance data is collected along with temperature and neutron and gamma flux data. The current work bridges the gap between proven out-of-pile ultrasonic techniques and in-pile deployment of ultrasonic sensors by acquiring the data necessary to demonstrate the performance of ultrasonic transducers. To date, one piezoelectric transducer and two magnetostrictive transducers have demonstrated reliable operation under irradiation. The irradiation is ongoing.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Employing MACS/ViBRANT as a Surrogate MARVEL Reactor for Startup Reactivity Tuning and Supervisory Control Processes

Advanced nuclear reactors are a key part of the future of nuclear energy both in the United States and globally. They offer unique benefits for various energy-demanding applications, including use in remote locations, compact size, modular manufacturing, remote monitoring, low and/or variable power rating operation, and reliance on novel technologies to enhance operational safety. To achieve economic feasibility, advanced reactors must significantly reduce their workforces in comparison with the current fleet. Achieving this reduction will occur through reducing staff workloads using technology to achieve autonomous or semi-autonomous operations, demonstrated by comprehensive testing and validation activities. These operations will require both software and hardware platforms during the design and testing phases. While simulations are useful during the design phase, their performance can significantly deviate during actual deployment on hardware. This report presents the outcomes of a collaborative technical initiative between the U.S. Department of Energy (DOE) Microreactor Program (MRP) and Advanced Sensors and Instrumentation (ASI) Program. The collaboration utilized the Microreactor Automated Control System (MACS) hardware platform to bridge the gap between theoretical reactor design and actual startup and control operations. Two key use cases were investigated: facilitating the startup testing period and demonstrating supervisory control. The first use case details the key Microreactor Applications Research Validation and Evaluation (MARVEL) reactor startup physics testing activities conducted using the MACS platform. These activities included drum worth measurements, shutdown margin assessment, temperature feedback analysis, and scram time evaluation, as well as unique testing that would apply to the MARVEL reactor to demonstrate the testing methodologies in a low-risk environment. The MACS platform, serving as a surrogate representation of the MARVEL reactor, proved instrumental in performing these tests. The exercise revealed aspects that led to optimized processes, refined hardware design, and enhanced base software capabilities. By maturing methods and technologies in this manner, the initiative promises to reduce wasted time in the actual on-site reactor deployment effort, thereby saving significant time and resources. The second use case focuses on the development and implementation of supervisory control methods aimed at managing core tilt, which can result from asymmetrical operations or manufacturing imperfections in fuel rods or reactivity control devices. A key objective was to assess and compare the use of artificial intelligence (AI) for supervisory control. The effort aimed to define the role of supervisory control to enhance performance without risking control instability. This effort explored three distinct approaches: rules-based (RB) methods, optimization techniques, and reinforcement learning (RL) algorithms. Each approach was evaluated for its ease of implementation, its usability, and its effectiveness in responding to asymmetries in neutron flux. Comparative analysis of these approaches provided valuable insights into their applicability and effectiveness, offering a robust framework for advanced reactor operations. Together, these two use cases highlight the potential of hardware test beds to help streamline the design, operation, and control of advanced nuclear reactors. This collaborative effort underscores the importance of continued innovation and experimentation in achieving the next generation of safe, reliable, and economically viable nuclear energy solutions.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Snow Distribution Patterns Revisited: A Physics-Based and Machine Learning Hybrid Approach to Snow Distribution Mapping in the Sub-Arctic

Snowpack distribution in Arctic and alpine landscapes often occurs in repeating, year-to-year patterns due to local topographic, weather, and vegetation characteristics. Previous studies have suggested that with years of observational data, these snow distribution patterns can be statistically integrated into a snow process modeling workflow. Recent advances in snow hydrology and machine learning (ML) have increased our ability to predict snowpack distribution using in-situ observations, remote sensing data sets, and simple landscape characteristics that can be easily obtained for most environments. Here, we propose a hybrid approach to couple a ML snow distribution pattern (MLSDP) map with a physics-based, snow process model. We trained a random forest ML algorithm on tens of thousands of snow survey observations from a subarctic study area on the Seward Peninsula, Alaska, collected during peak snow water equivalent (SWE). We validated hybrid model outputs using in-situ snow depth and SWE observations, as well as a light detection and ranging data set and a distributed temperature profiling sensor data set. When the hybrid results were compared with the physics-based method, the hybrid method more accurately depicted the spatial patterns of the snowpack, areas of drifting snow, and years when no in-situ observations were used in the random forest ML training data set. The hybrid method also showed improvements in root mean squared error at 61% of locations where time-series estimations of snow depth were observed. These results can be applied to any physics-based model to improve the snow distribution patterning to reflect observed conditions in high latitude and high elevation cold region environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Supervised Learning-Based Spatial Position Estimation with Vertical Displacement for Hovering UAV Wireless Power Transfer

This study presents a supervised learning-based spatial position estimation approach for wireless power transfer (WPT) systems supporting hovering unmanned aerial vehicle (UAV) charging. Unlike stationary charging scenarios, hovering UAVs introduce continuous lateral misalignment and vertical displacement, leading to variations in magnetic coupling and reduced power transfer efficiency. To address this challenge, the proposed method estimates the relative spatial position of the receiver coil using only electrical measurements obtained at the secondary side. A supervised learning model is trained to map output voltage and current features to spatial coordinates, enabling position awareness without requiring external sensors, vision systems, or communication links. The sensing functionality is inherently integrated into the WPT system, allowing simultaneous power transfer and localization through the same magnetic interface. Experimental validation is conducted on a laboratory-scale prototype under varying lateral offsets and air-gap conditions. In addition, spline-based interpolation is employed to increase spatial data density for training. The results demonstrate that the proposed framework can capture spatial variations associated with both lateral and vertical displacement, providing reliable position estimation under hovering conditions. This work establishes a hardware-efficient, sensorless solution for UAV wireless charging and serves as a baseline for advanced data-driven position estimation methods in dynamic WPT systems.

Asa, Erdem [ORNL] (ORCID:0000000190884812)↗
DOE OSTI2018

Fiber Optic Point Sensors for ESD Data Experiments

This NNSA NSR&D project will create an experimental data base of direct fiber optic point measurements of E(x,t) and B(x,t) from a ESD event. The data will be used to validate a physics based toolset being developed at LANL. The measurements can also be used to ascertain if a specific type of ESD event exceeds the NO FIRE limits for detonators.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

ThunderDOEME: A Seismoacoustic Deployment at Langmuir Observatory

This report documents a two-month deployment of seismoacoustic instrumentation at the Langmuir Observatory, located outside Socorro, New Mexico. A total of eleven Fairfield Nodal Seismometers and fifteen GEM infrasound loggers were deployed from June 2 to August 5, 2025. The nodal seismometers recorded data for an average of 34 days, while the GEMs had variable operational durations throughout the deployment period. The primary objective was to capture thunder signals using seismoacoustic instrumentation, contributing to a better understanding of the acoustic and seismic phenomena associated with thunder. Coinciding with this deployment, optical and electric field sensors were present, providing information regarding the timing and location of lightning strikes in the region. Additionally, triggered lightning strikes were conducted, serving as a ground truth for validating the captured thunder signals. Preliminary analysis of the data reveals clear thunder signals in both the seismic and infrasound recordings, with peak frequencies observed across a range of 4 to 40 Hz, depending on the event.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Evaluating the feasibility of using downwind methods to quantify point source oil and gas emissions using continuously monitoring fence-line sensors

The dependable reporting of methane (CH 4 ) emissions from point sources, such as fugitive leaks from oil and gas infrastructure, is important for profit maximization (retaining more hydrocarbons), evaluating climate impacts, assessing CH 4 fees for regulatory programs, and validating CH 4 intensity in differentiated gas programs. Currently, there are disagreements between emissions reported by different quantification techniques for the same sources. It has been suggested that downwind CH 4 quantification methods using CH 4 measurements on the fence line of production facilities could be used to generate emission estimates from oil and gas operations at the site level, but it is currently unclear how accurate the quantified emissions are. To investigate the accuracy of downwind methods, this study uses fence-line simulated data collected during controlled-release experiments as input for a non-standard closed-path eddy covariance (EC), the Gaussian plume inverse model (GPIM), and the backward Lagrangian stochastic (bLs) model in a range of atmospheric conditions. This study's EC attempt was unsuccessful due to data collection and instrumentation issues, resulting in invalid results characterized by underestimated emissions, large negative fluxes, and cospectra/ogives that deviated from their ideal shapes. Consequently, the EC results could not be compared with the GPIM and bLS model. The bLs model demonstrated the highest accuracy for single-release single-point emissions, though it exhibited greater uncertainty than GPIM under multi-release conditions. Across the GPIM and bLs model, the most reliable quantification was achieved with 15 min averaging and a narrow 5° wind sector range. Although EC was limited in this context, future studies should consider employing a standard EC system and further optimizing GPIM and bLs approaches – particularly for complex multi-source scenarios – to enhance quantification accuracy and reduce uncertainty.

03 NATURAL GAS↗
NASA NTRS1981

Remote sensing of high-latitude ionization profiles by ground-based and spaceborne instrumentation

Ionospheric specification and modeling are now largely based on data provided by active remote sensing with radiowave techniques (ionosondes, incoherent-scatter radars, and satellite beacons). More recently, passive remote sensing techniques have been developed that can be used to monitor quantitatively the spatial distribution of high-latitude E-region ionization. These passive methods depend on the measurement, or inference, of the energy distribution of precipitating kilovolt electrons, the principal source of the nighttime E-region at high latitudes. To validate these techniques, coordinated measurements of the auroral ionosphere have been made with the Chatanika incoherent-scatter radar and a variety of ground-based and spaceborne sensors

Vondrak, R. R.↗
NASA NTRS1989

The use of real-time, hardware-in-the-loop simulation in the design and development of the new Hughes HS601 spacecraft attitude control system

Realtime simulation and hardware-in-the-loop testing is being used extensively in all phases of the design, development, and testing of the attitude control system (ACS) for the new Hughes HS601 satellite bus. Realtime, hardware-in-the-loop simulation, integrated with traditional analysis and pure simulation activities is shown to provide a highly efficient and productive overall development program. Implementation of high fidelity simulations of the satellite dynamics and control system algorithms, capable of real-time execution (using applied Dynamics International's System 100), provides a tool which is capable of being integrated with the critical flight microprocessor to create a mixed simulation test (MST). The MST creates a highly accurate, detailed simulated on-orbit test environment, capable of open and closed loop ACS testing, in which the ACS design can be validated. The MST is shown to provide a valuable extension of traditional test methods. A description of the MST configuration is presented, including the spacecraft dynamics simulation model, sensor and actuator emulators, and the test support system. Overall system performance parameters are presented. MST applications are discussed; supporting ACS design, developing on-orbit system performance predictions, flight software development and qualification testing (augmenting the traditional software-based testing), mission planning, and a cost-effective subsystem-level acceptance test. The MST is shown to provide an ideal tool in which the ACS designer can fly the spacecraft on the ground.

Slafer, Loren I.↗
NASA NTRS2002

Microwave Anisotrophy Probe Launch and Early Operations

The Microwave Anisotropy Probe (MAP), a follow-on to the Differential Microwave Radiometer (DMR) instrument on the Cosmic Background Explorer (COBE), was launched from the Kennedy Space Center at 19:46:46 UTC on June 30, 2001. The powered flight and separation from the Delta II appeared to go as designed, with the launch placing MAP well within sigma launch dispersion and with less than 7 Nms of tip-off momentum. Because of this relatively low momentum, MAP was able to acquire the sun within only 15 minutes with a battery state of charge of 94%. After MAP's successful launch, a six week period of in-orbit checkout and orbit maneuvers followed. The dual purpose of the in-orbit checkout period was to validate the correct performance of all of MAP's systems and, from the attitude control system (ACS) point of view, to calibrate the performance of the spacecraft ACS sensors and actuators to maximize system performance. In addition to the checkout activities performed by the MAP team, the other critical activity taking place during the first six weeks after launch were a series of orbit maneuvers necessary to get the spacecraft from its launch orbit out to its desired orbit about L2, the second Earth-Sun Lagrange point. As MAP continues its standard operations, its ACS design is meeting all of its requirements to successfully complete the mission. This paper will describe the launch and early operations summarized above in greater detail, and show the performance of the attitude control and attitude determination system versus its requirements. Additionally, some of the unexpected events that occurred during this period will be discussed, including two events which dropped the spacecraft into its Safehold Mode and the presence of an "anomalous force" observed during each of the perigee orbit maneuvers that had the potential to cause these critical maneuvers to be prematurely aborted.

ODonnell, James R., Jr.↗