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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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NASA NTRS2010

Lunar Reconnaissance Orbiter (LRO) Thruster Control Mode Design and Flight Experience

National Aeronautics and Space Administration s (NASA) Goddard Space Flight Center (GSFC) in Greenbelt, MD, designed, built, tested, and launched the Lunar Reconnaissance Orbiter (LRO) from Cape Canaveral Air Force Station on June 18, 2009. The LRO spacecraft is the first operational spacecraft designed to support NASA s return to the Moon, as part of the Vision for Space Exploration. LRO was launched aboard an Atlas V 401 launch vehicle into a direct insertion trajectory to the Moon. Twenty-four hours after separation the propulsion system was used to perform a mid-course correction maneuver. Four days after the mid-course correction a series of propulsion maneuvers were executed to insert LRO into its commissioning orbit. The commission period lasted eighty days and this followed by a second set of thruster maneuvers that inserted LRO into its mission orbit. To date, the spacecraft has been gathering invaluable data in support of human s future return to the moon. The LRO Attitude Control Systems (ACS) contains two thruster based control modes: Delta-H and Delta-V. The design of the two controllers are similar in that they are both used for 3-axis control of the spacecraft with the Delta-H controller used for momentum management and the Delta-V controller used for orbit adjust and maintenance maneuvers. In addition to the nominal purpose of the thruster modes, the Delta-H controller also has the added capability of performing a large angle slew maneuver. A suite of ACS components are used by the thruster based control modes, for both initialization and control. For initialization purposes, a star tracker or the Kalman Filter solution is used for providing attitude knowledge and upon entrance into the thruster based control modes attitude knowledge is provided via rate propagation using a inertial reference unit (IRU). Rate information for the controller is also supplied by the IRU. Three-axis control of the spacecraft in the thruster modes is provided by eight 5-lbf class attitude control thrusters configured in two sets of four thrusters for redundancy purposes. Four additional 20-lbf class thrusters configured in two sets of two thrusters are used for Lunar Orbit Insertion maneuvers. The propulsion system is one the few systems on-board the LRO spacecraft that has built in redundancy. The Delta-H controller consists of a Proportional-Derivative (PD) controller with a structural filter on the thrusters and a Proportional controller on the reaction wheels. The PD control that employs the thrusters is used for attitude and rate control. The Proportional controller on the reaction wheels is used for commanding the wheels to a new momentum state. The ground commands used for the Delta-H controller are the system momentum vector, reaction wheel momentum, maximum expected command time, and which set of attitude control thrusters to use. The ability to command both the system momentum vector and reaction wheel momentum in the Delta-H controller provides both a capability and an additional source of operator error. Large angle slews via the Delta-H controller is achievable via this commands because these commands are used for the exit mode criteria. Setting these commands to non-consistent values prevents the mode from exiting nominally.

Hsu, Oscar C.↗
NASA NTRSDate not supplied

Evaluation of Markerless Motion Capture for Monitoring Sensorimotor Performance

BACKGROUND Astronauts returning from long-duration exposure to microgravity frequently exhibit alterations in sensorimotor function leading to postural imbalance, impaired locomotion, and operational challenges to manual control. Mission duration and individual responses often influence both the severity of performance decrements and the variability in adaptation timelines. Postflight disruptions during functional tasks are often detected through body-worn inertial measurement unit (IMU) devices. While IMU sensors are relatively compact, the long-term wear may lead to discomfort, displacement of the sensors on the body, and restrictions in movement or crew behavior. Although IMU data offers valuable insights from a research standpoint, interpreting changes in pre- and post-flight measures can be difficult for crew support personnel beyond the research domain, which can hinder the application for medical assessments and rehabilitation. Finally, the availability of inertial sensors in-flight is limited. There is a need for unobtrusive monitoring tools to improve our ability to monitor adaptation following gravitational transitions in various postflight evaluations and rehabilitation settings. Markerless motion capture (MMC) is an evolving unobtrusive technology that builds upon decades of research with marker-based motion capture systems to provide 3D human pose estimation from multiple synchronized 2D camera views using deep learning algorithms. Markerless technology can revolutionize how data is captured pre- and post-flight and potentially in-flight during intravehicular activity by enabling pose estimation of multiple crew members from onboard camera hardware. METHODS The following presents the initial evaluation of a state-of-the-art commercial-off-the-shelf MMC system, Theia Markerless, compared to IMU devices during various ground-based functional tasks and environmental conditions. The featured functional tasks include assessments from Human Research Program (HRP) funded studies such as Sensorimotor Standard Measures and Sensorimotor Assessments. Synchronous data collected using both motion capture and IMUs are analyzed for six male and female subjects of varying anthropometry. The analysis includes limited assessments of clothing, capture volume configurations, and the tool's sensitivity to detecting performance changes after a spaceflight analog centrifuge exposure. The development of visualization tools to enhance the application of the pose estimation output is also presented. RESULTS Initial results demonstrate comparable root mean square error (RMSE) to existing literature evaluating markerless and marker-based motion capture systems. Considering the relative functional range of motion of the cervical spine, normalized error values for the markerless system’s accuracy of the head was 0.032 in pitch, 0.025 in roll, and 0.018 in yaw plane of motion across a subset of functional tasks. The raw RMSE values were 3.49, 2.25, and 2.81 degrees respectively. For the torso, results suggest normalized errors of 0.469 in pitch, 0.191 in roll, and 0.307 in yaw planes of motion and raw RMSE values of 3.52, 1.53, and 3.07 degrees respectively. The data suggests the functional demands of a particular task influences the estimation accuracy of the MMC system where more dynamic motion and cases where subjects are not upright may introduce diminished tracking accuracy. DISCUSSION The following work lays the foundation for future implementations leveraging markerless motion capture to assess the time course of recovery and provide insight for rehabilitation protocols to enhance crew readiness for the resumption of daily activities. These tools offer effective methods for anonymizing sensitive crew data, facilitating numerous applications across research, medical, and rehabilitation groups. Collaborations with the Anthropometry and Biomechanics Facility will provide further comparisons of the Markerless system to a marker-based system. ACKNOWLEDGEMENT</ This work is supported by NASA’s Exploration Systems Development Mission Directorate Mars Campaign Office Crew Health Countermeasures.

Hannah M. Weiss↗
NASA NTRS2009

Robotic Recon for Human Exploration

Robotic reconnaissance has the potential to significantly improve scientific and technical return from lunar surface exploration. In particular, robotic recon may increase crew productivity and reduce operational risk for exploration. However, additional research, development and field-testing is needed to mature robot and ground control systems, refine operational protocols, and specify detailed requirements. When the new lunar surface campaign begins around 2020, and before permanent outposts are established, humans will initially be on the Moon less than 10% of the time. During the 90% of time between crew visits, robots will be available to perform surface operations under ground control. Understanding how robotic systems can best address surface science needs, therefore, becomes a central issue Prior to surface missions, lunar orbiters (LRO, Kaguya, Chandrayyan-1, etc.) will map the Moon. These orbital missions will provide numerous types of maps: visible photography, topographic, mineralogical and geochemical distributions, etc. However, remote sensing data will not be of sufficient resolution, lighting, nor view angle, to fully optimize pre-human exploration planning, e.g., crew traverses for field geology and geophysics. Thus, it is important to acquire supplemental and complementary surface data. Robotic recon can obtain such data, using robot-mounted instruments to scout the surface and subsurface at resolutions and at viewpoints not achievable from orbit. This data can then be used to select locations for detailed field activity and prioritize targets to improve crew productivity. Surface data can also help identify and assess terrain hazards, and evaluate alternate routes to reduce operational risk. Robotic recon could be done months in advance, or be part of a continuing planning process during human missions.

Deans, Matthew↗
DOE OSTI2017

Human Factors and Modeling Methods in the Development of Control Room Modernization Concepts

nuclear power plants. Although the nuclear industry has made steady improvement in outage optimization, each day of a refueling outage still represents an opportunity to save millions of dollars and each day an outage extends past its planned end date represents millions of dollars that may have been spent unnecessarily. Reducing planned outage duration or preventing outage extensions requires careful management of the outage schedule as well as constant oversight and monitoring of work completion during the outage execution. During a typical outage, there are typically more than 10,000 activities on the schedule that, if not managed efficiently, may cause expensive outage delays. Management of outages currently relies largely on paper-based resources and general-purpose office software. A typical tool currently used to monitor work performance is a burn-down curve, where total remaining activities are plotted against the baseline schedule to track bulk work completion progress. While these tools are useful, there is still considerable uncertainty during a typical outage that bulk work progress is adequate and therefore a lot of management time is spent analyzing the situation on a daily basis. This paper describes recent advances made in developing a framework for the design of visual outage information presentation, as well as an overview of the scientific principles that informed the development of the visualizations. To test the utility of advanced visual outage information presentation, an outage management dashboard software application was created as part of the Department of Energy’s Advanced Outage Control Center project. This dashboard is intended to present all the critical information an outage manager would need to understand the current status of a refueling outage. The dashboard presents the critical path, bulk work performance, key performance indicators, outage milestones and metrics relating current performance to historical performance. Additionally, the dashboard includes data analysis tools to allow outage managers to drill down into the underlying data to understand the drivers of the indicators.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Understanding collective human movement dynamics during large-scale events using big geosocial data analytics

Conventional approaches for modeling human mobility pattern often focus on human activity and movement dynamics in their regular daily lives and cannot capture changes in human movement dynamics in response to large-scale events. With the rapid advancement of information and communication technologies, many researchers have adopted alternative data sources (e.g., cell phone records, GPS trajectory data) from private data vendors to study human movement dynamics in response to large-scale natural or societal events. Big geosocial data such as georeferenced tweets are publicly available and dynamically evolving as real-world events are happening, making it more likely to capture the real-time sentiments and responses of populations. However, precisely-geolocated geosocial data is scarce and biased toward urban population centers. In this research, we developed a big geosocial data analytical framework for extracting human movement dynamics in response to large-scale events from publicly available georeferenced tweets. The framework includes a two-stage data collection module that collects data in a more targeted fashion in order to mitigate the data scarcity issue of georeferenced tweets; in addition, a variable bandwidth kernel density estimation(VB-KDE) approach was adopted to fuse georeference information at different spatial scales, further augmenting the signals of human movement dynamics contained in georeferenced tweets. To correct for the sampling bias of georeferenced tweets, we adjusted the number of tweets for different spatial units (e.g., county, state) by population. To demonstrate the performance of the proposed analytic framework, we chose an astronomical event that occurred nationwide across the United States, i.e., the 2017 Great American Eclipse, as an example event and studied the human movement dynamics in response to this event. Finally, this analytic framework can easily be applied to other types of large-scale events such as hurricanes or earthquakes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Development of a Translational Model to Assess the Impact of Opioid Overdose and Naloxone Dosing on Respiratory Depression and Cardiac Arrest

In response to a surge of deaths from synthetic opioid overdoses, there have been increased efforts to distribute naloxone products in community settings. Prior research has assessed the effectiveness of naloxone in the hospital setting; however, it is challenging to assess naloxone dosing regimens in the community/first‐responder setting, including reversal of respiratory depression effects of fentanyl and its derivatives (fentanyls). Here, we describe the development and validation of a mechanistic model that combines opioid mu receptor binding kinetics, opioid agonist and antagonist pharmacokinetics, and human respiratory and circulatory physiology, to evaluate naloxone dosing to reverse respiratory depression. Validation supports our model, which can quantitatively predict displacement of opioids by naloxone from opioid mu receptors in vitro , hypoxia‐induced cardiac arrest in vivo , and opioid‐induced respiratory depression in humans from different fentanyls. After validation, overdose simulations were performed with fentanyl and carfentanil followed by administration of different intramuscular naloxone products. Carfentanil induced more cardiac arrest events and was more difficult to reverse than fentanyl. Opioid receptor binding data indicated that carfentanil has substantially slower dissociation kinetics from the opioid receptor compared with nine other fentanyls tested, which likely contributes to the difficulty in reversing carfentanil. Administration of the same dose of naloxone intramuscularly from two different naloxone products with different formulations resulted in differences in the number of virtual patients experiencing cardiac arrest. This work provides a robust framework to evaluate dosing regimens of opioid receptor antagonists to reverse opioid‐induced respiratory depression, including those caused by newly emerging synthetic opioids.

Pharmacology & Pharmacy↗
DOE OSTI2018

Annual Closure Monitoring Report for Corrective Action Unit 98, Frenchman Flat, Underground Test Area, Nevada National Security Site, Nevada: (CY2017 January 2017–December 2017, Rev. 0)

Corrective Action Unit (CAU) 98: Frenchman Flat on the Nevada National Security Site was the location of 10 underground nuclear tests. CAU 98 underwent a series of investigations and actions in accordance with the Federal Facility Agreement and Consent Order to assess contamination of groundwater by radionuclides from the tests. A Closure Report completed that process in 2016 and called for long-term monitoring, use restrictions (URs), and institutional controls to protect the public and environment from potential exposure to contaminated groundwater. Three types of monitoring are performed for CAU 98: water quality, water level, and institutional control. These are monitored to determine whether the URs remain protective of human health and the environment, and to ensure that the regulatory boundary objectives are being met. Monitoring data will be used in the future, once multiple years of data are available, to evaluate consistency with the groundwater flow and contaminant transport models because the contaminant boundaries calculated with the models are the primary basis of the UR boundaries. Six wells were sampled for water-quality monitoring in 2017. Contaminants of concern were detected only in the two source/plume wells already known to contain contamination as a result of a radionuclide migration experiment. The 86,000-picocuries-per-liter (pCi/L) tritium concentration in one of the wells is about 12 percent higher than measured in 2016 but is over an order of magnitude less than the peak value measured in the well in 1980. The concentration in the other source/plume well is lower than measured in 2016. The water-level monitoring network includes 16 wells. Depth to water measured in 2017 is generally consistent with recent measurements for most wells. Water-level declines differing from long-term trends were observed in four wells. Three of these (WW-4, WW-4A, and WW-5B) are water-supply wells that experienced increases in pumping during the year. No definitive cause for the sharp decline in the fourth well (ER-5-3-2) in 2016 is known as yet. Institutional control monitoring confirmed the URs are recorded in U.S. Department of Energy and U.S. Air Force land management systems, and that no activities within Frenchman Flat basin are occurring that could potentially affect the contaminant boundaries. Survey of groundwater resources in basins surrounding Frenchman Flat similarly identify no current or pending development that would indicate the need to increase monitoring activities or would otherwise cause concern for the closure decision. The URs continue to prevent exposure of the public, workers, and the environment to contaminants of concern by preventing use of potentially contaminated groundwater.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

CY2018 Annual Closure Monitoring Report for Corrective Action Unit 98, Frenchman Flat, Underground Test Area, Nevada National Security Site, Nevada (January 2018–December 2018, Revision 1)

Corrective Action Unit (CAU) 98: Frenchman Flat on the Nevada National Security Site was the location of 10 underground nuclear tests. CAU 98 underwent a series of investigations and actions in accordance with the Federal Facility Agreement and Consent Order to assess contamination of groundwater by radionuclides from the tests. A Closure Report completed that process in 2016 and called for long-term monitoring, use restrictions (URs), and institutional controls to protect the public and environment from potential exposure to contaminated groundwater. Three types of monitoring are performed for CAU 98: water quality, water level, and institutional control. These are monitored to determine whether the URs remain protective of human health and the environment, and to ensure that the regulatory boundary objectives are being met. Monitoring data will be used in the future, once multiple years of data are available, to evaluate consistency with the groundwater flow and contaminant transport models because the contaminant boundaries calculated with the models are the primary basis of the UR boundaries. Six wells were sampled for water-quality monitoring in 2018. Contaminants of concern were detected only in the two source/plume wells already known to contain contamination as a result of a radionuclide migration experiment. Tritium concentrations in both of these wells, RNM-2S and UE-5n, remain above the Safe Drinking Water Act maximum contaminant level of 20,000 picocuries per liter but declined in 2018 as compared to measurements in 2017. All other contaminants of concern are below the minimum detection level plus analytical error. The water-level monitoring network includes 16 wells. Depth to water measured in 2018 is generally consistent with recent measurements for all wells. Many wells continue to exhibit a long-term downward trend in water level, despite small increases in measured water levels in 2018. The sharp 2016 decline in water level in Well ER-5-3-2 remains unexplained, with the lower level persisting through 2018. Rising water-level trends continue to be observed in two relatively deep wells (ER-5-3 deep piezometer and ER-5-4-2), and also in former supply Well WW-5A. The current supply wells exhibit relatively erratic water levels associated with pumping activities. Institutional control monitoring confirmed the URs are recorded in U.S. Department of Energy and U.S. Air Force land management systems, and that no activities within Frenchman Flat basin are occurring that could potentially affect the contaminant boundaries. Survey of groundwater resources in basins surrounding Frenchman Flat similarly identify no current or pending development that would indicate the need to increase monitoring activities or would otherwise cause concern for the closure decision. The URs continue to prevent exposure of the public, workers, and the environment to contaminants of concern by preventing use of potentially contaminated groundwater.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

CY2019 Annual Closure Monitoring Report for Corrective Action Unit 98, Frenchman Flat, Underground Test Area, Nevada National Security Site, Nevada (January 2019–December 2019), Revision 1

Three types of monitoring are performed for CAU 98: water quality, water level, and institutional control. These are monitored to determine whether the URs remain protective of human health and the environment, and to ensure that the regulatory boundary objectives are being met. Monitoring data will be used in the future, once multiple years of data are available, to evaluate consistency with the groundwater flow and contaminant transport models because the contaminant boundaries calculated with the models are the primary basis of the UR boundaries. Six wells were sampled for water-quality monitoring in 2019. Contaminants of concern were detected only in the two source/plume wells already known to contain contamination as a result of a radionuclide migration experiment. Tritium concentrations in both of these wells, RNM-2S and UE-5n, remain above the Safe Drinking Water Act maximum contaminant level of 20,000 picocuries per liter but declined in 2019 as compared to measurements in 2018. All other contaminants of concern are below the minimum detection level plus analytical error. The water-level monitoring network includes 16 wells. Depth to water measured in 2019 is generally consistent with recent measurements for all wells. Many wells continue to exhibit a long-term downward trend in water level, though changes from 2018 to 2019 are minimal. The sharp 2016 decline in water level in Well ER-5-3-2 remains unexplained, with the lower level persisting through 2019. Rising water-level trends continue to be observed in Well ER-5-3 deep piezometer and former water supply Well WW-5A. Water supply Well WW-5B experienced a rise in water level as a result of an absence of pumping in the first part of the year (due to a mechanical problem), whereas water levels declined in WW-4 and WW-4A in response to greater pumping in 2019. Institutional control monitoring confirmed the URs are recorded in U.S. Department of Energy and U.S. Air Force land management systems, and that no activities within Frenchman Flat basin are occurring that could potentially affect the contaminant boundaries. Survey of groundwater resources in basins surrounding Frenchman Flat similarly identify no current or pending development that would indicate the need to increase monitoring activities or would otherwise cause concern for the closure decision. The URs continue to prevent exposure of the public, workers, and the environment to contaminants of concern by preventing use of potentially contaminated groundwater.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1975

A multiloop approach to modeling motion sensor responses

By using a least squares identification algorithm, a multiloop approach is taken to effectively model the response characteristics of the motion sensors. The inputs to the model include the possible sources of information provided to the human via his motion sensing system. One input models the response of the angular acceleration sensors (second derivative of position) and the second input models the response of the linear sensors (sine of position). The third input is the visual display error provided to the human in the closed loop tracking experiment. Data from a roll axis tracking simulation were analyzed. The major source of pilot lead under the motion mode of operation is discussed for control of plants in which motion information improved performance and in which there was no improvement in performance.

Junker, A. M.↗
NASA NTRS2002

Information Technology and the Human Research Facility

This slide presentation reviews how information technology supports the Human Research Facility (HRF) and specifically the uses that contractor has for the information. There is information about the contractor, the HRF, some of the experiments that were performed using the HRF on board the Shuttle, overviews of the data architecture, and software both commercial and specially developed software for the specific experiments.

Klee, Margaret↗
NASA NTRS2010

Development of a Ground-Based Analog to the Advanced Resistive Exercise Device Aboard the International Space Station

NASA and Wyle engineers constructed a Horizontal Exercise Fixture (HEF) that was patented in 2006. Recently modifications were made to HEF with the goal of creating a device that mimics squat exercise on the Advanced Resistive Exercise Device (ARED) and can be used by bed rest subjects who must remain supine during exercise. This project posed several engineering challenges, such as how best to reproduce the hip motions (we used a sled that allowed hip motion in the sagittal plane), how to counterweight the pelvis against gravity (we used a pulley and free-weight mechanism), and how to apply large loads (body weight plus squat load) to the shoulders while simultaneously supporting the back against gravity (we tested a standard and a safety bar that allowed movement in the subject s z-axis, both of which used a retractable plate for back support). METHODS An evaluation of the HEF was conducted with human subjects (3F, 3M), who performed sets of squat exercises of increasing load from 10-repetition maximum (RM) up to 1-RM. Three pelvic counterweight loads were tested along with each of the two back-support squat bars. Data collection included 3-dimensional ground reaction forces (GRF), muscle activation (EMG), body motion (video-based motion capture), and subjective comments. These data were compared with previous ground-based ARED study data. RESULTS All subjects in the evaluation were able to perform low- to high-loading squats on the HEF. Four of the 6 subjects preferred a pelvic counterweight equivalent to 60 percent of their body weight. Four subjects preferred the standard squat bar, whereas 2 female subjects preferred the safety bar. EMG data showed muscle activation in the legs and low back typical of squat motion. GRF trajectories and eccentric-concentric loading ratios were similar to ARED. CONCLUSION: Squat exercise performed on HEF approximated squat exercise on ARED.

Newby, Nathaniel J.↗
NASA NTRS2004

Creating Simulated Microgravity Patient Models

The Medical Operational Support Team (MOST) has been tasked by the Space and Life Sciences Directorate (SLSD) at the NASA Johnson Space Center (JSC) to integrate medical simulation into 1) medical training for ground and flight crews and into 2) evaluations of medical procedures and equipment for the International Space Station (ISS). To do this, the MOST requires patient models that represent the physiological changes observed during spaceflight. Despite the presence of physiological data collected during spaceflight, there is no defined set of parameters that illustrate or mimic a 'space normal' patient. Methods: The MOST culled space-relevant medical literature and data from clinical studies performed in microgravity environments. The areas of focus for data collection were in the fields of cardiovascular, respiratory and renal physiology. Results: The MOST developed evidence-based patient models that mimic the physiology believed to be induced by human exposure to a microgravity environment. These models have been integrated into space-relevant scenarios using a human patient simulator and ISS medical resources. Discussion: Despite the lack of a set of physiological parameters representing 'space normal,' the MOST developed space-relevant patient models that mimic microgravity-induced changes in terrestrial physiology. These models are used in clinical scenarios that will medically train flight surgeons, biomedical flight controllers (biomedical engineers; BME) and, eventually, astronaut-crew medical officers (CMO).

Hurst, Victor↗
NASA NTRSDate not supplied

An Agile-Like Approach to Hardware Development: The Ejectable Data Recorder (EDR) for Orion's Ascent Abort 2 (AA-2) Test Flight

On July 2, 2019, the Ascent Abort 2 (AA-2) Flight Test Vehicle was launched from Cape Canaveral, with the goal of demonstrating the performance of Orion’s Launch Abort System (LAS) and collecting data from hundreds of sensors throughout the vehicle. The data collected during this test flight is of paramount importance, as it will be used to certify the Orion vehicle for human spaceflight. Originally, the data was to be downlinked via a single string network of antennas on the LAS, with the associated risk of potential data dropouts, as well as loss of data once the LAS was jettisoned. Thus, additional antennas were added onto the crew module (CM) to support data downlink post-LAS jettison, a buffer rebroadcast capability was added to fill in any gaps in data downlink transmissions, and an ejectable data recorder (EDR) subsystem was added to the CM as a redundant measure to collect all the instrumentation data. The EDR subsystem was added to the project about one year after the project commenced, which significantly reduced the available development time when compared with the other subsystems of the AA-2 Test Flight. The project was further accelerated by six months, around the critical design review gate. Due to the schedule compression challenge and the fact that the EDR subsystem was a backup system and not flight critical, the EDR subsystem was further challenged to find a new and more efficient way to develop hardware. Thus, the EDR subsystem experimented with different management and systems engineering processes, team sizes, communication methods, and tools. Some examples are novel uses of SharePoint as a Data-centric Project Management & Systems Engineering environment, a continuous testing approach through the lifecycle, and a Skunkworks approach to managing the team. The EDR subsystem blended Commercial Off The Shelf (COTS) hardware with in-house developed hardware and software to create a novel data retrieval capability. The capability evolved rapidly through a hardware in the loop simulation environment that enabled incremental component updates for not only the EDR subsystem but across the entire Crew Module. This paper will present an overview of how the EDR subsystem was managed and compare it to an Agile approach to managing projects. The paper will further provide a recommended approach to future Agile-like hardware development that incorporates lessons learned from the EDR experience.

Agile↗
DOE OSTI2021

Uranium Oxide Synthetic Pathway Discernment through Unsupervised Morphological Analysis

We present a novel unsupervised machine learning method for quantitative representation of scanning electron micrographs and its applications and performance for nuclear forensic analysis of uranium ore concentrates. The method uses a vector quantizing variational autoencoder followed by a histogram operation to encode a micrograph into a single dimensional representation, called the latent vector. The method requires no extant labeling of the data and can be applied over large datasets of micrographs with minimal human interaction. The representations generated are broadly descriptive of each micrograph and the microstructure of the material imaged. In the case of uranium ore concentrate analysis, the representations were amenable to processing reagent and ore concentrate species classification with accuracy of 81:8%, which is competitive with state-of-the-art supervised networks. The representations were also used to classify previously unseen processing routes, were able to classify imaging parameters such as magnification (to 76:0% accuracy), were able to classify fine grained process parameters such as calcining temperature (to 74:4% accuracy), and their informatic properties indicate that they are generally descriptive of the image represented. This method can be applied across microstructure analysis fields to perform quantitative analysis without the need for labor intensive and possibly biased human analysis.

Scanning Electron Microscopy, Vector Quantizing Va↗
NASA NTRS1997

Human heading estimation during visually simulated curvilinear motion

Recent studies have suggested that humans cannot estimate their direction of forward translation (heading) from the resulting retinal motion (flow field) alone when rotation rates are higher than approximately 1 deg/sec. It has been argued that either oculomotor or static depth cues are necessary to disambiguate the rotational and translational components of the flow field and, thus, to support accurate heading estimation. We have re-examined this issue using visually simulated motion along a curved path towards a layout of random points as the stimulus. Our data show that, in this curvilinear motion paradigm, five of six observers could estimate their heading relatively accurately and precisely (error and uncertainty < approximately 4 deg), even for rotation rates as high as 16 deg/sec, without the benefit of either oculomotor or static depth cues signaling rotation rate. Such performance is inconsistent with models of human self-motion estimation that require rotation information from sources other than the flow field to cancel the rotational flow.

NASA Center ARC↗
NASA NTRS2006

Comprehensive Environmental Informatics System (CEIS) Integrating Crew and Vehicle Environmental Health

Integrated Vehicle Health Management (IVHM) systems have been pursued as highly integrated systems that include smart sensors, diagnostic and prognostics software for assessments of real-time and life-cycle vehicle health information. Inclusive to such a system is the requirement to monitor the environmental health within the vehicle and the occupants of the vehicle. In this regard an enterprise approach to informatics is used to develop a methodology entitled, Comprehensive Environmental Informatics System (CEIS). The hardware and software technologies integrated into this system will be embedded in the vehicle subsystems, and maintenance operations, to provide both real-time and life-cycle health information of the environment within the vehicle cabin and of its occupants. This comprehensive information database will enable informed decision making and logistics management. One key element of the CEIS is interoperability for data acquisition and archive between environment and human system monitoring. With comprehensive components the data acquired in this system will use model based reasoning systems for subsystem and system level managers, advanced on-board and ground-based mission and maintenance planners to assess system functionality. Knowledge databases of the vehicle health state will be continuously updated and reported for critical failure modes, and routinely updated and reported for life cycle condition trending. Sufficient intelligence, including evidence-based engineering practices which are analogous to evidencebased medicine practices, will be included in the CEIS to result in more rapid recognition of off-nominal operation to enable quicker corrective actions. This will result from better information (rather than just data) for improved crew/operator situational awareness, which will produce significant vehicle and crew safety improvements, as well as increasing the chance for mission success, future mission planning as well as training. Other benefits include improved reliability, increase safety in operations and cost of operations. The cost benefits stem from significantly reduced processing and operations manpower, predictive maintenance for systems and subjects. The improvements in vehicle functionality and cost will result from increased prognostic and diagnostic capability due to the detailed total human exploration system health knowledge from CEIS. A collateral benefit is that there will be closer observations of the vehicle occupants as wrist watch sized devices are worn for continuous health monitoring. Additional database acquisition will stem from activities in countermeasure practices to ensure peak performance capability by occupants of the vehicle. The CEIS will provide data from advanced sensing technologies and informatics modeling which will be useful in problem troubleshooting, and improving NASA s awareness of systems during operation.

Nall, Mark E.↗
NASA NTRS2014

Ames Life Science Data Archive: Translational Rodent Research at Ames

The Life Science Data Archive (LSDA) office at Ames is responsible for collecting, curating, distributing and maintaining information pertaining to animal and plant experiments conducted in low earth orbit aboard various space vehicles from 1965 to present. The LSDA will soon be archiving data and tissues samples collected on the next generation of commercial vehicles; e.g., SpaceX & Cygnus Commercial Cargo Craft. To date over 375 rodent flight experiments with translational application have been archived by the Ames LSDA office. This knowledge base of fundamental research can be used to understand mechanisms that affect higher organisms in microgravity and help define additional research whose results could lead the way to closing gaps identified by the Human Research Program (HRP). This poster will highlight Ames contribution to the existing knowledge base and how the LSDA can be a resource to help answer the questions surrounding human health in long duration space exploration. In addition, it will illustrate how this body of knowledge was utilized to further our understanding of how space flight affects the human system and the ability to develop countermeasures that negate the deleterious effects of space flight. The Ames Life Sciences Data Archive (ALSDA) includes current descriptions of over 700 experiments conducted aboard the Shuttle, International Space Station (ISS), NASA/MIR, Bion/Cosmos, Gemini, Biosatellites, Apollo, Skylab, Russian Foton, and ground bed rest studies. Research areas cover Behavior and Performance, Bone and Calcium Physiology, Cardiovascular Physiology, Cell and Molecular Biology, Chronobiology, Developmental Biology, Endocrinology, Environmental Monitoring, Gastrointestinal Physiology, Hematology, Immunology, Life Support System, Metabolism and Nutrition, Microbiology, Muscle Physiology, Neurophysiology, Pharmacology, Plant Biology, Pulmonary Physiology, Radiation Biology, Renal, Fluid and Electrolyte Physiology, and Toxicology. These experiment descriptions and data can be accessed online via the public LSDA website (http://lsda.jsc.nasa.gov) and information can be requested via the Data Request form at http://lsda.jsc.nasa.gov/common/dataRequest/dataRequest.aspx or by contacting the ALSDA Office at: Alison.J.French@nasa.gov

Life Sciences↗