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At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

An on-orbit viewpoint of life sciences research

As a Payload Specialist and a life science researcher, I want to present several issues that impact life science research in space. During early space station operations, life science and other experiments will be conducted in a time-critical manner and there will be the added duties of both space shuttle and space station systems operation (and the concomittent training overhead). Life sciences research is different from other science research done in space because the crew is involved both as an operator and as a subject. There is a need for pre- and post-flight data collection as well as in flight data collection. It is imperative that the life science researcher incorporate the crew members into their team early enough in the training cycle to fully explain the science and to make the crew aware of the importance and sensitivities of the experiment. During the pre-flight phase, the crew is incredibly busy with a myriad of duties. Therefore, it is difficult to get 'pristine' subjects for the baseline data collection. There are also circadian shifts, travel, and late nights to confound the data. During this time it is imperative that the researcher develop, along with the crew, a realistic estimate of crew-time required for their experiment. In flight issues that affect the researcher are the additional activities of the crew, the stresses inherent in space flight, and the difficulty of getting early in-flight data. During SSF activities, the first day or two will be taken up with rendezvous and docking. Other issues are the small number of subjects on any given flight, the importance of complete and concise procedures, and the vagaries of on-board data collection. Post flight, the crew is tired and experiences a 'relaxation.' This along with circadian shifts and rapid re-adaptation to 1-g make immediate post-flight data collection difficult. Finally, the blending of operational medicine and research can result in either competition for resources (crew time, etc.) or influence on the physiological state of the crew. However, the unique opportunity to conduct research in an environment that cannot be duplicated on Earth outweighs the 'challenges' that exist for space life researchers.

Lichtenberg, Byron K.↗
NASA NTRS1994

Software agents for the dissemination of remote terrestrial sensing data

Remote terrestrial sensing (RTS) data is constantly being collected from a variety of space-based and earth-based sensors. The collected data, and especially 'value-added' analyses of the data, are finding growing application for commercial, government, and scientific purposes. The scale of this data collection and analysis is truly enormous; e.g., by 1995, the amount of data available in just one sector, NASA space science, will reach 5 petabytes. Moreover, the amount of data, and the value of analyzing the data, are expected to increase dramatically as new satellites and sensors become available (e.g., NASA's Earth Observing System satellites). Lockheed and other companies are beginning to provide data and analysis commercially. A critical issue for the exploitation of collected data is the dissemination of data and value-added analyses to a diverse and widely distributed customer base. Customers must be able to use their computational environment (eventually the National Information Infrastructure) to obtain timely and complete information, without having to know the details of where the relevant data resides and how it is accessed. Customers must be able to routinely use standard, widely available (and, therefore, low cost) analyses, while also being able to readily create on demand highly customized analyses to make crucial decisions. The diversity of user needs creates a difficult software problem: how can users easily state their needs, while the computational environment assumes the responsibility of finding (or creating) relevant information, and then delivering the results in a form that users understand? A software agent is a self-contained, active software module that contains an explicit representation of its operational knowledge. This explicit representation allows agents to examine their own capabilities in order to modify their goals to meet changing needs and to take advantage of dynamic opportunities. In addition, the explicit representation allows agents to advertize their capabilities and results to other agents, thereby allowing the collection of agents to reuse each others work.

Toomey, Christopher N.↗
NASA NTRS2018

Initial Approach to Collect Small Unmanned Aircraft System Off-Nominal Operational Situations Data

NASA is developing the Unmanned Aircraft System Traffic Management research platform to safely integrate small unmanned aircraft operations in large-scale at low-altitudes. As a part of this effort, small unmanned aircraft system off-nominal operational situations data collection process has been developed to take lessons learned and to reinforce operational compliance. In this paper, descriptions of variables used for digital data collection and an online report form for collection of observational data from the operators (contextual data) are provided. They are used to collect off-nominal data from the Unmanned Aircraft System Traffic Management National Campaign in 2017. The digital data show that 2 out of 118 campaign operations (1.7%) encountered loss of navigation. Since the campaign aircraft used Global Positioning System for navigation, it is likely that unobstructed view of the sky at the campaign locations contributed to this small number. Also, 4 out of 47 operations (8.5%) encountered loss of communications. A relatively short distance between ground control system and aircraft, ranging from 2300 feet to 4200 feet, likely contributed to this small number. There was no data to identify the loss of communications condition, aircraft received signal strength, for the remaining 71 operations suggesting that some operators may not be monitoring unmanned aircraft communications system performance or monitoring it with different parameters. For the contextual data, due to the low number of total reports during the campaign, no significant trends emerged. This is an initial attempt to collect contextual data from small unmanned aircraft operators about off-nominal situations, and changes will be made to the future data collection to improve the amount and quality of the information.

unmanned aviation systems traffic management (UTM)↗
NASA NTRS2018

Initial Approach to Collect Small Unmanned Aircraft System Off-Nominal Operational Situations Data

NASA is developing the Unmanned Aircraft System Traffic Management research platform to safely integrate small unmanned aircraft operations in large-scale at low-altitudes. As a part of this effort, small unmanned aircraft system off-nominal operational situations data collection process has been developed to take lessons learned and to reinforce operational compliance. In this paper, descriptions of variables used for digital data collection and an online report form for collection of observational data from the operators (contextual data) are provided. They are used to collect off-nominal data from the Unmanned Aircraft System Traffic Management National Campaign in 2017. The digital data show that 2 out of 118 campaign operations (1.7%) encountered loss of navigation. Since the campaign aircraft used Global Positioning System for navigation, it is likely that unobstructed view of the sky at the campaign locations contributed to this small number. Also, 4 out of 47 operations (8.5%) encountered loss of communications. A relatively short distance between ground control system and aircraft, ranging from 2300 feet to 4200 feet, likely contributed to this small number. There was no data to identify the loss of communications condition, aircraft received signal strength, for the remaining 71 operations suggesting that some operators may not be monitoring unmanned aircraft communications system performance or monitoring it with different parameters. For the contextual data, due to the low number of total reports during the campaign, no significant trends emerged. This is an initial attempt to collect contextual data from small unmanned aircraft operators about off-nominal situations, and changes will be made to the future data collection to improve the amount and quality of the information.

Jung, Jaewoo↗
NASA NTRS2000

BOREAS TE-9 NSA Canopy Biochemistry

The BOREAS TE-9 team collected several data sets related to chemical and photosynthetic properties of leaves. This data set contains canopy biochemistry data collected in 1994 in the NSA at the YJP, OJR, OBS, UBS, and OA sites, including biochemistry lignin, nitrogen, cellulose, starch, and fiber concentrations. These data were collected to study the spatial and temporal changes in the canopy biochemistry of boreal forest cover types and how a high-resolution radiative transfer model in the mid-infrared could be applied in an effort to obtain better estimates of canopy biochemical properties using remote sensing. The data are available in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗
NASA NTRS2004

Evaluation of Experimental Data from the GAINS Balloon GPS Surface Reflection Instrument

The GPS Surface Reflection Instrument was integrated as an experiment on the GAINS (Global Airocean IN-situ System) 48-hour balloon mission flown in September 2001. The data collected by similar instruments in the past has been used to measure sea state from which ocean surface winds can be accurately estimated. The GPS signal has also been shown to be reflected from wetland areas and even from subsurface moisture. The current version of the instrument has been redesigned to be more compact, use less power, and withstand a greater variation in environmental conditions than previous versions. This instrument has also incorporated a new data collection mode to track 5 direct satellites (providing a continuous navigation solution) and multiplex the remaining 7 channels to track the reflected signal of the satellite tracked in channel 0. The new software mode has been shown to increase the signal to noise ratio of the collected data and enhance the science return of the instrument. During the 48-hour flight over the Northwest US, the instrument will measure surface reflections that can be detected over the balloon's ground track. Since ground surface elevations in this area vary widely from the WGS-84 ellipsoid altitude, the instrument software has been modified to incorporate a surface altitude correction based on USGS 30-minute Digital Elevation Models. Information presented will include facts about instrument design goals, data collection methodologies and algorithms, and results of the science data analyses for the 48-hour mission.

Gance, George G.↗
NASA NTRS2002

Evaluation of Experimental Data from the Gains Balloon GPS Surface Reflection Instrument

The GPS Surface Reflection Instrument was integrated as an experiment on the GAINS (Global Airocean IN-situ System) 48-hour balloon mission flown in June 2002. The data collected by similar instruments in the past has been used to measure sea state from which ocean surface winds can be accurately estimated. The GPS signal has also been shown to be reflected from wetland areas and even from subsurface moisture. The current version of the instrument has been redesigned to be more compact, use less power, and withstand a greater variation in environmental conditions than previous versions. This instrument has also incorporated a new data collection mode to track 5 direct satellites (providing a continuous navigation solution) and multiplex the remaining 7 channels to track the reflected signal of the satellite tracked in channel 0. The new software mode has been shown to increase the signal to noise ratio of the collected data and enhance the science return of the instrument. During the GAINS balloon flight over the Northwest US, the instrument measured surface reflections as they were detected over the balloon's ground track. Since ground surface elevations in this area vary widely from the WGS-84 ellipsoid altitude, the instrument software has been modified to incorporate a surface altitude correction based on USGS 30-minute Digital Elevation Models. Information presented will include facts about instrument design goals, data collection methodologies and algorithms, and will focus on results of the science data analyses for the mission.

Ganoe, George G.↗
NASA NTRS2020

Psyche Magnetometer Engineering Model Test and Thermal Model Correlation to Validate Operational Thermal Requirement

Psyche Fluxgate Magnetometer candidate fabricated by UCLA has a critical temperature gradient requirement inside the magnetometer sensor head. Since the temperature gradient requirement is a driving factor for the magnetometer operation and science data collection at 16 Psyche, it is critical to validate and verify this requirement via modeling and test. In this work, a thermal vacuum test was completed for Psyche flight-like magnetometer engineering model. Flight-like environments were simulated for a hot operational case (after launch), a cold survival case (cruise), and two cold operational cases to characterize thermal performance of the instrument. An additional, non-flight, steady-state test case was completed to better correlate the magnetometer thermal model. During the test, sensitive Cernox temperature sensors with accuracy of ±0.1°C were used to precisely characterize the temperature gradient and correlate the model to the best accuracy. Collected test data indicated power consumption of 28% lower than predicted. The temperature gradient measured met the expected value and the requirement. Test data indicated the magnetometer also met the AFTs in relevant hot and cold environments. Test Results were used to correlate the thermal model. The correlated thermal model will be integrated to the spacecraft thermal model to predict magnetometer thermal performance while collecting science data in Psyche orbits.

Caron, Ryan↗
NASA NTRS2017

The Functional Task Test: Results from the One-Year Mission

Exposure to the microgravity conditions of spaceflight causes astronauts to experience alterations in multiple physiological systems including sensorimotor disturbances, cardiovascular deconditioning, and loss of muscle mass and strength. Some or all of these changes might affect the ability of crewmembers to perform critical mission tasks immediately after landing on a planetary surface. The goal of our recently completed Functional Task Test (FTT) study was to determine the effects of spaceflight on functional tests that are representative of high priority exploration mission tasks and to identify the key underlying physiological factors that contribute to decrements in performance. The FTT is comprised of seven functional tests and a corresponding set of interdisciplinary physiological measures specifically targeting the sensorimotor, cardiovascular and muscular changes associated with exposure to spaceflight. Both Shuttle and International Space Station (ISS) astronauts were tested before and after spaceflight. Additionally, we conducted a supporting study in which subjects performed the FTT protocol before and after 70 days of 6 deg head-down bed rest, an analog for spaceflight. Two groups of bed rest subjects were studied: one group who performed aerobic and resistive exercise during bed rest using protocols similar to astronauts and one group who served as non-exercise controls. The bed rest analog allowed us to isolate the impact of body unloading without other spaceflight environmental factors on both functional tasks and on the underlying physiological factors that lead to decrements in performance, and then to compare those results with the results obtained in our spaceflight study. As an extension to the FTT study we collected data from one ISS crewmember who experienced 340 days in space using the same FTT protocol used previously to test spaceflight and bed rest subjects. Data were collected three times preflight and 1.7, 7.5 and 36.5 days after landing. The FTT one-year results will be presented at the meeting, and a comparison will be made with data previously obtained using the same protocol on astronauts tested before and after 6 months in space. Future work will focus on collecting data from additional subjects from one-year flights to gain a better assessment of extreme long-duration exposure to spaceflight on both functional measure of performance and physiological metrics.

Bloomberg, J. J↗
NASA NTRS1997

The Automated Instrumentation and Monitoring System (AIMS): Design and Architecture

Whether a researcher is designing the 'next parallel programming paradigm', another 'scalable multiprocessor' or investigating resource allocation algorithms for multiprocessors, a facility that enables parallel program execution to be captured and displayed is invaluable. Careful analysis of such information can help computer and software architects to capture, and therefore, exploit behavioral variations among/within various parallel programs to take advantage of specific hardware characteristics. A software tool-set that facilitates performance evaluation of parallel applications on multiprocessors has been put together at NASA Ames Research Center under the sponsorship of NASA's High Performance Computing and Communications Program over the past five years. The Automated Instrumentation and Monitoring Systematic has three major software components: a source code instrumentor which automatically inserts active event recorders into program source code before compilation; a run-time performance monitoring library which collects performance data; and a visualization tool-set which reconstructs program execution based on the data collected. Besides being used as a prototype for developing new techniques for instrumenting, monitoring and presenting parallel program execution, AIMS is also being incorporated into the run-time environments of various hardware testbeds to evaluate their impact on user productivity. Currently, the execution of FORTRAN and C programs on the Intel Paragon and PALM workstations can be automatically instrumented and monitored. Performance data thus collected can be displayed graphically on various workstations. The process of performance tuning with AIMS will be illustrated using various NAB Parallel Benchmarks. This report includes a description of the internal architecture of AIMS and a listing of the source code.

Yan, Jerry C.↗
NASA NTRS2016

UAS in the NAS Flight Test Series 4 Overview

Flight Test Series 4 (FT4) provides the researchers with an opportunity to expand on the data collected during the first flight tests. Following Flight Test Series 3, additional scripted encounters with different aircraft performance and sensors will be conducted. FT4 is presently planned for Spring of 2016 to ensure collection of data to support the validation of the final RTCA Phase 1 DAA (Detect and Avoid) Minimum Operational Performance Standards (MOPS). There are three research objectives associated with this goal: Evaluate the performance of the DAA system against cooperative and non-cooperative aircraft encounters Evaluate UAS (Unmanned Aircraft Systems) pilot performance in response to DAA maneuver guidance and alerting with live intruder encounters Evaluate TCAS/DAA (Traffic Alert and Collision Avoidance System/Detect and Avoid) interoperability. This flight test series will focus on only the Scripted Encounters configuration, supporting the collection of data to validate the interoperability of DAA and collision avoidance algorithms.

flight test↗
NASA NTRS1995

Minimum fuel mode evaluation

The minimum fuel mode of the NASA F-15 research aircraft is designed to minimize fuel flow while maintaining constant net propulsive force (FNP), effectively reducing thrust specific fuel consumption (TSFC), during cruise flight conditions. The test maneuvers were at stabilized flight conditions. The aircraft test engine was allowed to stabilize at the cruise conditions before data collection initiated; data were then recorded with performance seeking control (PSC) not-engaged, then data were recorded with the PSC system engaged. The maneuvers were flown back-to-back to allow for direct comparisons by minimizing the effects of variations in the test day conditions. The minimum fuel mode was evaluated at subsonic and supersonic Mach numbers and focused on three altitudes: 15,000; 30,000; and 45,000 feet. Flight data were collected for part, military, partial, and maximum afterburning power conditions. The TSFC savings at supersonic Mach numbers, ranging from approximately 4% to nearly 10%, are in general much larger than at subsonic Mach numbers because of PSC trims to the afterburner.

Orme, John S.↗
NASA NTRSDate not supplied

AssistTaxi: A Comprehensive Dataset for Taxiway Analysis and Autonomous Operations

The availability of high-quality datasets play a crucial role in advancing research and development especially, for safety critical and autonomous systems. This poster presents AssistTaxi, which is a comprehensive novel dataset which is a collection of images for runway and taxiway analysis. The dataset comprises of more than 300,000 frames of diverse and carefully collected data, gathered from Melbourne (MLB) and Grant-Valkaria (X59) general aviation airports. The importance of AssistTaxi lies in its potential to advance autonomous operations, enabling researchers and developers to train and evaluate algorithms for efficient and safe taxiing. Researchers can utilize AssistTaxi to benchmark their algorithms, assess performance, and explore novel approaches for runway and taxiway analysis. Additionally, the dataset serves as a valuable resource for validating and enhancing existing algorithms as well as facilitating innovation in autonomous operations for aviation. We also propose an initial approach to label the dataset using a contour based detection and line extraction technique.

Data Collection↗
NASA NTRS2016

Storage of Physical Sample Metadata in the Astrobiology Habitable Environments Database (AHED)

The National Aeronautics and Space Administration has begun an effort to store, curate, and publish information about physical samples collected and analyzed in conjunction with NASA-funded astrobiology research. Astrobiology is a multidisciplinary area of scientific research being conducted by collaborating teams of biologists, chemists, geologists, atmospheric scientists, oceanographers, astrophysicists, astronomers, and other specialists. Astrobiology studies the origin, evolution, and distribution of life in the Universe. NASA uses the results of astrobiology research to focus its future missions on targets of opportunity for the discovery of life off Earth. Astrobiology researchers conduct both field-based and laboratory-based research, during which physical samples are collected, processed, and catalogued. The cataloguing practices employed by different teams of astrobiologists vary widely, and there are no specific standards available to guide the collection and recording of astrobiology sample data. The disparity in data collection approaches and the lack of a centralized sample repository makes it difficult for astrobiology teams to share data and benefit from resultant synergies.To facilitate data sharing within the astrobiology community, NASA is developing a prototype database the Astrobiology Habitable Environments Database (AHED) and an associated set of data collection templates. The database will store information about samples, along with associated measurements and analyses, including information about biological cultures enriched or isolated from samples, and the results of analyses performed on the samples (e.g., via spectrography, microscopy, etc.). In addition, the system will store contextual information about field sites where samples were collected, the instruments or equipment used for analysis, and people and institutions involved in their collection. AHED is being implemented on top of Open Data Repository's Data Publisher [1], an open source software platform for the publication of scientific datasets. The data collection templates under development represent an initial attempt to propose a set of metadata for capture and storage within AHED. The design of these templates is being conducted by a consolidated group of astrobiologists from active research teams at NASA Ames Research Center, assisted by data science and software engineering specialists. These initial templates must be vetted with the broader astrobiology community through a defined process to ensure that they meet community needs. Each template captures a different type of data collection record. For each template, we are developing a list of fields to be captured, including a set of required entry fields, a set of recommended but optional fields, and a set of discretionary fields. A datatype selected from a variety of text and numeric types is specified for each field. Included is a 'choice' type that restricts user input to an enumerated list of values. Many of the fields and field values capture information of particular interest to the astrobiology community, and are intended to facilitate search and retrieval of relevant data across multiple datasets.

Keller, Rich↗
NASA NTRSDate not supplied

A PI’s Guide to Analog Research

Congratulation on being awarded a grant to conduct research in a spaceflight analog! NASA funded research in a Human Research Program (HRP) managed analog environment is very different from research in a traditional laboratory. This presentation will provide a guide to help investigators successfully plan studies for integration and implementation in an HRP analog platform. There are many things to consider when planning a study for implementation in an analog facility and campaign or mission. How do you get from grant approval to data analysis? This is where HRP’s Research Operations and Integration (ROI) team comes in. The ROI team works with sponsoring HRP elements and PI teams to capture requirements and help the PI teams through the phases of research complement development, integration and implementation. A complement is comprised of a group of studies requiring a common platform and/or scenario that are able to be integrated on a noninterference basis for implementation. Properly defining and documenting requirements and study needs is crucial in successful integration and implementation. This presentation will outline and provide the information needed for PI teams to understand the integration process and the role of the ROI team in the successful integration and implementation of their study. Topics to be discussed will include but not be limited to science requirement definition and documentation, NASA IRB submissions, subject recruitment, screening and selection, study integration process, efficiency in data collection and data sharing, daily crew schedules, hardware and software shipping, receipt and checkout, biological sample collection, mission support, data management and receipt of data.

B. Caldwell↗
DOE OSTI2025

Fast event-based electron counting for small-molecule structure determination by MicroED

Electron counting helped realize the resolution revolution in single-particle cryoEM and is now accelerating the determination of MicroED structures. Its advantages are best demonstrated by new direct electron detectors capable of fast (kilohertz) event-based electron counting (EBEC). This strategy minimizes the inaccuracies introduced by coincidence loss (CL) and promises rapid determination of accurate structures. We used the Direct Electron Apollo camera to leverage EBEC technology for MicroED data collection. Given its ability to count single electrons, the Apollo collects high-quality MicroED data from organic small-molecule crystals illuminated with incident electron beam flux densities as low as 0.01–0.045 e − /Å 2 /s. Under even the lowest flux density (0.01 e − /Å 2 /s) condition, fast EBEC data produced ab initio structures of a salen ligand (268 Da) and biotin (244 Da). Each structure was determined from a 100° wedge of data collected from a single crystal in as few as 50 s, with a delivered fluence of only ∼0.5 e − /Å 2 . Fast EBEC data collected with a fluence of 2.25 or 3.33 e − /Å 2 also facilitated a 1.5 Å structure of thiostrepton (1665 Da). While refinement of these structures appeared unaffected by CL, a CL adjustment applied to EBEC data further improved the distribution of intensities measured from the salen ligand and biotin crystals. However, CL adjustment only marginally improved the refinement of their corresponding structures, signaling the already high counting accuracy of detectors with counting rates in the kilohertz range. Overall, by delivering low-dose structure-worthy data, fast EBEC collection strategies open new possibilities for high-throughput MicroED.

EBEC↗
NASA NTRS2019

A Suite of High-Resolution Atmospheric Carbon Dioxide Simulations in Support of the OCO-3 Snapshot Area Mapping (SAM) Mode Observation: PSU-WRF, CSU-OLAM and NASA GEOS

Cities and power plants are responsible more than 70% of GHG emissions. The emissions from the subnational localized sources need to be accurately quantified and properly managed in order to achieve the Paris Climate Agreement goals. The accurate estimation of these emission is also crucial for assessing the capacity of natural sinks to uptake the carbon released into the atmosphere that ultimately defines our emission allowance for the 1.5 or 2.0 degree temperature goals. New data collected by the Orbiting Carbon Observatory 3 (OCO-3) Snapshot Area Mapping (SAM) observations should provide a tremendous new opportunity for us to study CO2 emissions from targeted large localized sources, such as cities, power plants and beyond. Since 2018 (prior to the OCO-3 launch), we have studied the observational strategies for the SAM mode observation in order to collect the useful data for estimating CO2 emissions from target sources. To maximize the benefit of the SAM mode observation data for quantifying CO2 emission, it is important to define how to observe the localized sources depending on the local environmental and emission specificities. We employ a suite of state-of-the-art CO2 modeling systems, such as PSU's WRF-CO2, CSU's OLAM and NASA's GEOS models. All of these CO2 modeling systems are prescribedwith the high-resolution fuel CO2 emission estimates from the ODIAC data product to achieve realistic urban CO2 variations. We focus on cities with established ground-based observation networks, such as Los Angeles, Indianapolis, and Paris. We have examined the urban emission signal detectability in response to the influence of local background conditions that can observed by the SAM and biospheric contributions that will be a new challenge for urban emission inverse estimation. Based on the results of our simulation experiments, we plan to propose city-specific observation strategies. Upon the availability of the OCO-3 data, we will attempt to estimate city emissions using inverse models. We also developed synthetic OCO-3 data using NASA's GEOS5 model, which should be useful to assess the utility of the OCO-3 data in combination with data collected by carbon satellites in other orbits, such as NASA's OCO-2 and Japanese GOSAT-1/2. The synthetic data also provide an opportunity to study the errors due to clouds and aerosols, which have been not fully studied in the past.

Oda, Tomohiro↗