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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Nitrogen Metabolism in Pseudomonas putida : Functional Analysis Using Random Barcode Transposon Sequencing

Pseudomonas putida KT2440 has long been studied for its diverse and robust metabolisms, yet many genes and proteins imparting these growth capacities remain uncharacterized. Using pooled mutant fitness assays, we identified genes and proteins involved in the assimilation of 52 different nitrogen containing compounds. To assay amino acid biosynthesis, 19 amino acid drop-out conditions were also tested. From these 71 conditions, significant fitness phenotypes were elicited in 672 different genes including 100 transcriptional regulators and 112 transport-related proteins. We divide these conditions into 6 classes, and propose assimilatory pathways for the compounds based on this wealth of genetic data. To complement these data, we characterize the substrate range of three promiscuous aminotransferases relevant to metabolic engineering efforts in vitro. So we examine the specificity of five transcriptional regulators, explaining some fitness data results and exploring their potential to be developed into useful synthetic biology tools. In addition, we use manifold learning to create an interactive visualization tool for interpreting our BarSeq data, which will improve the accessibility and utility of this work to other researchers.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2011

An Ontology Driven Information Architecture for Interoperable Disparate Data Sources

The mission of the Planetary Data System is to facilitate achievement of NASA's planetary science goals by efficiently collecting, archiving, and making accessible digital data produced by or relevant to NASA's planetary missions, research programs, and data analysis programs. The vision is: (1) To gather and preserve the data obtained from exploration of the Solar System by the U.S. and other nations (2) To facilitate new and exciting discoveries by providing access to and ensuring usability of those data to the worldwide community (3) To inspire the public through availability and distribution of the body of knowledge reflected in the PDS data collection PDS is a federation of heterogeneous nodes including science and support nodes

planetary data systems↗
NASA NTRS2017

Exploiting Dark Information Resources to Create New Value Added Services to Study Earth Science Phenomena

This paper presents two research applications exploiting unused metadata resources in novel ways to aid data discovery and exploration capabilities. The results based on the experiments are encouraging and each application has the potential to serve as a useful standalone component or service in a data system. There were also some interesting lessons learned while designing the two applications and these are presented next.

Earth Science Informatics↗
NASA NTRSDate not supplied

Data Democratization: Challenges and Opportunities

Democratizing Earth data is one of the challenges many organizations around the world face in order to maximize the use of their Earth data for research, applications, education, and societal benefits. For example, at the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC), over 1600 global and regional datasets in several NASA Earth science focus areas, including atmospheric composition, water and energy cycles, and climate variability, are archived and distributed to the public. Giovanni, the Geospatial Interactive Online Visualization and Analysis Infrastructure, was developed by GES DISC to facilitate data access and exploration, especially for novice users of Earth science. With Giovanni, users can analyze and visualize over 2000 Earth science variables (e.g., precipitation, aerosol, surface wind) without downloading data, software, the expert understanding of data formats and structures, and coding skills, lowering the barrier to data analysis/comparison by preprocessing and accessing to the data. Results of data analysis and visualization can be accessed in several popular formats (e.g., NetCDF, CSV). As a result of Giovanni's efforts, more than 3000 referral papers have been published in various fields. In spite of this, Giovanni is still difficult to use for some users. For instance, if one searches for "precipitation," it will return over 150 related variables. The question is, which one to use? Furthermore, variables from different data providers (e.g., satellites and models) are named differently with different units, further confusing users, especially those outside the communities. Data democratization is complex and multifaceted. Challenges include service and data discovery, user experiences, visualization, data quality, trustworthiness, and more. In this presentation, we will examine Giovanni as an example of challenges and opportunities in developing data democratization services.

data democratization↗
NASA NTRS2017

Medical Data Architecture Project Status

The Medical Data Architecture (MDA) project supports the Exploration Medical Capability (ExMC) risk to minimize or reduce the risk of adverse health outcomes and decrements in performance due to in-flight medical capabilities on human exploration missions. To mitigate this risk, the ExMC MDA project addresses the technical limitations identified in ExMC Gap Med 07: We do not have the capability to comprehensively process medically-relevant information to support medical operations during exploration missions. This gap identifies that the current International Space Station (ISS) medical data management includes a combination of data collection and distribution methods that are minimally integrated with on-board medical devices and systems. Furthermore, there are variety of data sources and methods of data collection. For an exploration mission, the seamless management of such data will enable an increasingly autonomous crew than the current ISS paradigm. The MDA will develop capabilities that support automated data collection, and the necessary functionality and challenges in executing a self-contained medical system that approaches crew health care delivery without assistance from ground support. To attain this goal, the first year of the MDA project focused on reducing technical risk, developing documentation and instituting iterative development processes that established the basis for the first version of MDA software (or Test Bed 1). Test Bed 1 is based on a nominal operations scenario authored by the ExMC Element Scientist. This narrative was decomposed into a Concept of Operations that formed the basis for Test Bed 1 requirements. These requirements were successfully vetted through the MDA Test Bed 1 System Requirements Review, which permitted the MDA project to begin software code development and component integration. This paper highlights the MDA objectives, development processes, and accomplishments, and identifies the fiscal year 2017 milestones and deliverables in the upcoming year.

Data management↗
NASA NTRS2019

Assessing Reliability of NDE Flaw Detection Using Smaller Number of Demonstration Data Points

The paper provides an engineering analysis approach for assessing reliability of NDE flaw detection using smaller number of demonstration data points. It explores dependence of probability of detection (POD), probability of false positive (POF), on contrast-to-noise ratio, and net decision threshold-to-noise ratio in a simulated data; and draws some generically applicable inferences to devise the approach. ASTM nondestructive evaluation standards provide requirements on signal-to-noise ratio and/or contrast-to-noise ratio in order to provide reliable flaw detection and limit false positive calls. POD analysis of inspection test data results in an estimated flaw size, denoted by 𝑎90/95. This flaw size has 90% POD and minimum 95% confidence. POF is also estimated in the analysis. POD demonstration requires specimens with flaws of known size. In many situations, it is very expensive to produce the large number of flaws required for the POD analysis. In some situations, only real flaws can truly represent the flaws for demonstration. Real flaws of correct size and location in part configuration specimen may be difficult to produce, if not impossible. Here, an engineering analysis approach is devised using simulation to assess reliability of NDE technique when a limited number of flaws are available for demonstration. In this simulation, a technique is considered reliable, if it provides flaw detectability size equal to or better than the theoretical 𝑎90𝑡ℎ used in simulation and also provides a POF less than or equal to a chosen value. The paper uses simulated signal response versus flaw size data to devise the approach. Linear correlation is used between the signal response data and flaw size. POD software mh1823 uses generalized linear model (GLM) in POD analysis after transforming the flaw size and signal response, if needed, using logarithm. Therefore, this approach is in agreement with the linear signal correlation used in mh1823. Using the POD analysis of data, generic conditions on contrast-to-noise ratio and net decision threshold-to-noise ratio are derived for reliable flaw detection. In order to assess technique reliability using the engineering approach, signal response-to-flaw size correlation about the flaw size of concern is needed. In addition, measurement of noise is also needed. If the technique meets the above requirements, assumption of linear signal-to-flaw size correlation and conditions on noise, then the technique can be assessed using this analysis as it fits the underlying POD model used here. The approach is conservative and is designed to provide a larger flaw size compared to the POD approach. Such NDE technique assessment approach, although, not as rigorous as POD, can be cost effective if the larger flaw size can be tolerated. Typically, this is a situation for all quality control NDE inspections. Here, an NDE technique needs to be reliable and 𝑎90/95 is not estimated, but the assessed flaw size is assumed to be larger than the unknown a90 due to conservative factors or margins. Applicability of the approach for assessing reliability of flaw detection in x-ray radiography and 2D imaging in general is also explored.

Koshti, Ajay M.↗
NASA NTRS1979

Cost and performance characteristics of data system configurations for processing remotely sensed data

Some alternative approaches to constructing a large remote-sensing data system are explored. The cost and performance implications of using a collection of 'small' computers versus using one large computer are examined. Several architectures and associated costs for the large data system supporting a single data center are presented. Recurring cost factors (maintenance and operations) currently slightly favor the single large-machine architecture, but other factors may dictate the choice of one of the two multimachine architectures discussed.

Gregor, P. J.↗
NASA NTRS2024

Crew Health and Performance Integrated Data Architecture Project Updates

Future Human Exploration missions will face new constraints as crews move further from terrestrial communication, resupply, and the real-time support enjoyed by Low Earth Orbit missions today. Exploration crews will need to be more self-reliant and able to respond to emergencies without immediate support from ground-based personnel. A new generation of technologies, employing advanced analytical and predictive modeling techniques, is needed to assist the crew’s work, help maintain their health, and inform the decisions they make on these future Exploration missions. The Crew Health and Performance Integrated Data Architecture (CHP-IDA) project is laying a foundation for these future technologies by integrating sources of data generated by and around the crew and then providing them though common data models and Application Programming Interfaces to external systems. The combined data model makes comprehensive Crew Health and Performance data accessible and more meaningful to the decision-making process. This presentation will describe the currently ongoing effort to develop and evaluate a path-to-flight concept of the CHP-IDA software, current integrations, updates to the architecture, and examples of exploration scenarios in which CHP-IDA would be used.

B Schmitt↗
DOE OSTI2022

Multiphysics FISPACT-II and TENDL-2019 simulation: neutron-induced damage metrics

Nuclear interactions can be the source of atomic displacement, irradiation-induced defects and transmutation in structural materials. Such quantities are derived from, or can be correlated to, nuclear kinematic simulations of primary atomic energy distributions spectra and the quantification of the numbers of secondary defects produced per primary as a function of the available recoils, residual and emitted, energies. Recoil kinematics of neutral, residual, gas, proton, alpha particle emissions are now more rigorously treated based on recent, complete and enhanced nuclear data parsed in state-of-the-art processing tools. Defect production metrics are the starting point in the complex problem of correlating and simulating the behaviour of materials under irradiation, as experimental information is rare or scattered. Detailed, segregated primary knock-on-atom metrics are now becoming available as the starting point of further simulation processes of isolated and clustered defects in material lattices. This allows more materials, lattices, neutron incident energy ranges, and irradiation conditions to be explored with sufficient data to adequately cover both standard and novel applications and materials: the broader reactor applications landscape. The damage metrics of of materials are systematically explored under typical but different reactor's type environment. The inventory code FISPACT-II combined with the enhanced nuclear data forms of the TENDL-2019 libraries allow one to not only calculate dpa from mostly scattering events but to also properly predict gas production, nuclear heating and transmutation under the same conditions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

A Safe Response to Renewable Energy Hazards

The International Association of Fire Fighters (IAFF) and Underwriters Laboratories, LLC (UL) in conjunction with UL Solutions initiated a joint project in 2022 under an agreement with the United States Department of Energy-Office of Energy Efficiency and Renewable Energy (DOE-EERE). This project focused on two separate and important initiatives related to energy efficiency in residential buildings. Initiative 1: Fire Performance on Energy Efficient Exterior Walls. Initiative 2: Firefighting Tactics in Residential Properties with Building Energy Storage Systems (BESS). The project’s first initiative addresses concerns surrounding new technologies with enhanced, energy-efficient exterior walls installed on residential properties. The concerns of fire rapidly traveling vertically up the exterior of these walls were examined. This addressed a growing concern from the first responder community that many times, the fires on the exterior of residential buildings have already evolved into an attic fire by the time of arrival – making it problematic to address the fire scenario. The test plan for Initiative 1 incorporated a modified version of an American Society for Testing and Materials (ASTM) test method, ASTM E2707, Standard Test Method for Determining Fire Penetration of Exterior Wall Assemblies Using a Direct Flame Impingement Exposure, as the foundation of the research. The test method involved a wall structure intended to represent retrofit construction to evaluate how fire would spread vertically or laterally. The second aspect of the UL-IAFF Project focuses on the fire service response to Residential Battery Energy Storage System (RBESS) incidents. These simulation tests were constructed in the large-scale fire test facility at UL Solutions’ Northbrook, IL campus. A baseline test was conducted that involved a test structure with no batteries—shelving units populated with standardized commodities, representing a typical garage with cellulosic and plastic contents. Three additional tests have been conducted to generate data with the contribution of energy storage system (ESS) batteries to compare fire and explosion hazards against the baseline test. Through this work, fire service tactical considerations can be explored. From the data, the team can determine 1) the visual indicators of a residential fire that has involved an RBESS (or, potentially, other large batteries) and 2) the impact of fire service-initiated ventilation of the structure on the fire conditions and explosion risks.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRSDate not supplied

Spaceflight Biospecimen and Data Sharing in Support of Science Discovery and Exploration

For decades, NASA and international partners have conducted biological experiments in space to understand effects of spaceflight and address potential hazards. To enable spaceflight back to the Moon, and then to Mars and beyond, it is imperative to further understand basic science and health risks associated with spaceflight, along with developing countermeasures. The sending of experiments and organisms into space is a costly endeavor. To maximize scientific return, sharing with the scientific community both space-flown biospecimens and data from completed experiments is essential. New fundamental, applied, and bioinformatic science insights can be gained from specimen and data sharing efforts. Data reuse enables spaceflight health risk modeling, analyzing adverse outcomes across spaceflight hazards, and deep space autonomous support for the flight medical officer. Space-flown biospecimens not required by mission Principal Investigators are regularly archived and made available for scientific request. The largest biorepository of these samples are found within NASA’s Institutional Scientific Collection at Ames Research Center (ISC-ARC), which stores over 32,000 specimens mostly from Shuttle and International Space Station (ISS) missions, but also some ground-based analog samples. The Ames Life Sciences Data Archive manages the ISC-ARC. Tissues are predominantly from mice and rats, though samples are also available from bacteria and quail. Only a handful of other similar collections exist worldwide. Rodent biospecimens exposed to simulated space radiation at Brookhaven National Laboratory are archived under the purview of NASA HRP Space Radiation Element. Microbial collection and analyses from 20 years of routine environmental monitoring of air, surfaces, and water systems of the ISS were performed to ensure a safe environment for astronauts. Samples from the ISC-ARC, space radiation and microbial collections are searchable and requestable through the NASA Life Sciences Data Archive (LSDA). Decades of planetary protection microbial isolates derived from spacecraft bioburden are archived in JPL’s microbial collection. Rodent biospecimens from spaceflight investigations conducted by the Japan Aerospace Exploration Agency (JAXA) are archived and available at the JAXA Biorepository at Tsukuba Space Center. The Russian Institute of Biomedical Problems also has a collection of animal, microbial, cellular, and fungi available for research from ground analog experiments. Several data repositories exist for scientists to utilize. The LSDA is the primary NASA source of life sciences research data and information. It contains decades of spaceflight and ground-analog research involving human, microbial, cellular, plant, and animal subjects. Data is collected from NASA-funded investigations through the Human Research Program and the Space Biology Program. The NASA Lifetime Surveillance of Astronaut Health collects and grants access to clinical and occupational health monitoring data from astronauts, with a list and description of data collected available for request through the LSDA. NASA GeneLab at ARC collects genomic, transcriptomic, proteomic, and metabolomic data from any species. It is a repository and platform for collaborative open-science bioinformatic approaches. JAXA is establishing an ‘omics-based repository in collaboration with the Tohoku Medical Megabank (ToMMo), called the JAXA-ToMMo Integrated Biobank for Space Life Science. Overall, the sharing of these biospecimen and data resources can assist researchers worldwide in understanding spaceflight effects on biology, along with enabling next generation data science applications for space exploration platforms. Websites: https://lsda.jsc.nasa.gov/ ; https://www.nasa.gov/ames/research/space-biosciences/isc-bsp ; https://www.nasa.gov/ames/research/space-biosciences/alsda

Ryan T. Scott↗
DOE OSTI2021

Knowledge extraction and transfer in data-driven fracture mechanics

Significance Data-driven approaches have launched a new paradigm in scientific research that is bound to have an impact on all disciplines of science and engineering. However, at this juncture, the exploration of data-driven techniques in the century-old field of fracture mechanics is highly limited, and there are key challenges including accurate and intelligent knowledge extraction and transfer in a data-limited regime. Here, we propose a framework for data-driven knowledge extraction in fracture mechanics with rigorous accuracy assessment which employs active learning for optimizing data usage and for data-driven knowledge transfer that allows efficient treatment of three-dimensional fracture problems based on two-dimensional solutions.

Liu, Xing↗
DOE OSTI2020

Nuclear Data Covariances and Sampling

In this report, we present an overview of the task of producing sample nuclear data sets for the purpose of exploring the effects of nuclear data uncertainties on physics simulations. These sample data sets (or, as we sometimes call them variations) are produced based on uncertainties specified in the ENDF/B-VIII nuclear data library, although the principles discussed here apply to sampling based on similar libraries, such as JENDL. The uncertainties in ENDF and similar libraries are given in the form of mean values (a mean vector) and a covariance matrix. The components of the mean vector are what are normally thought of as the values of the nuclear data (cross sections, $\bar{v}$, the prompt fission neutron spectrum, etc.) and the covariance matrix contains the information about the uncertainties in these values and correlations between them, including correlations across different energies in a single channel and correlations across different channels.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2001

Human Exploration Missions Study Launch Window from Earth Orbit

The determination of orbital launch window characteristics is of major importance in the analysis of human interplanetary missions and systems. The orbital launch window characteristics are directly involved in the selection of mission trajectories, the development of orbit operational concepts, and the design of orbital launch systems. The orbital launch window problem arises because of the dynamic nature of the relative geometry between outgoing (departure) asymptote of the hyperbolic escape trajectory and the earth parking orbit. The orientation of the escape hyperbola asymptotic relative to earth is a function of time. The required hyperbola energy level also varies with time. In addition, the inertial orientation of the parking orbit is a function of time because of the perturbations caused by the Earth's oblateness. Thus, a coplanar injection onto the escape hyperbola can be made only at a point in time when the outgoing escape asymptote is contained by the plane of parking orbit. Even though this condition may be planned as a nominal situation, it will not generally represent the more probable injection geometry. The general case of an escape injection maneuver performed at a time other than the coplanar time will involve both a path angle and plane change and, therefore, a Delta(V) penalty. Usually, because of the Delta(V) penalty the actual departure injection window is smaller in duration than that determined by energy requirement alone. This report contains the formulation, characteristics, and test cases for five different launch window modes for Earth orbit. These modes are: (1) One impulsive maneuver from a Low Earth Orbit (LEO), (2) Two impulsive maneuvers from LEO, (3) Three impulsive maneuvers from LEO, (4) One impulsive maneuvers from a Highly Elliptical Orbit (HEO), (5) Two impulsive maneuvers from a Highly Elliptical Orbit (HEO) The formulation of these five different launch window modes provides a rapid means of generating realistic parametric data for space exploration studies. Also the formulation provides vector and geometrical data sufficient for use as a good starting point in detail trajectory analysis based on calculus of variations, steepest descent, or parameter optimization program techniques.

Young, Archie↗
NASA NTRS2012

Bridging Informatics and Earth Science: a Look at Gregory Leptoukh's Contributions

With the tragic passing this year of Gregory Leptoukh, the Earth and Space Sciences community lost a tireless participant in--and advocate for--science informatics. Throughout his career at NASA, Dr. Leptoukh established a theme of bridging the gulf between the informatics and science communities. Nowhere is this more evident than his leadership in the development of Giovanni (GES DISC Interactive Online Visualization ANd aNalysis Infrastructure). Giovanni is an online tool that serves to hide the often-complex technical details of data format and structure, making science data easier to explore and use by Earth scientists. To date Giovanni has been acknowledged as a contributor in 500-odd scientific articles. In recent years, Leptoukh concentrated his efforts on multi-sensor data inter-comparison, merging and fusion. This work exposed several challenges at the intersection of data and science. One of these was the ease with which a naive user might generate spurious comparisons, a potential hazard that was the genesis of the Multi-sensor Data Synergy Advisor (MDSA). The MDSA uses semantic ontologies and inference rules to organize knowledge about dataset quality and other salient characteristics in order to advise users on potential caveats for comparing or merging two datasets. Recently, Leptoukh also led the development of AeroStat, an online Giovanni instance to investigate aerosols via statistics from station and satellite comparisons and merged maps of data from more than one instrument. Aerostat offers a neural net based bias adjustment to harmonize the data by removing systematic offsets between datasets before merging. These examples exhibit Leptoukh's talent for adopting advanced computer technologies in the service of making science data more accessible to researchers. In this, he set an example that is at once both vital and challenging for the ESSI community to emulate.

Source record↗
DOE OSTI2025

The Pierre Auger Observatory open data

The Pierre Auger Collaboration has embraced the concept of open access to their research data since its foundation, with the aim of giving access to the widest possible community. A gradual process of release began as early as 2007 when 1% of the cosmic-ray data was made public, along with 100% of the space-weather information. In February 2021, a portal was released containing 10% of cosmic-ray data collected by the Pierre Auger Observatory from 2004 to 2018, during the first phase of operation of the Observatory. The Open Data Portal includes detailed documentation about the detection and reconstruction procedures, analysis codes that can be easily used and modified and, additionally, visualization tools. Since then, the Portal has been updated and extended. In 2023, a catalog of the highest-energy cosmic-ray events examined in depth has been included. A specific section dedicated to educational use has been developed with the expectation that these data will be explored by a wide and diverse community, including professional and citizen scientists, and used for educational and outreach initiatives. This paper describes the context, the spirit, and the technical implementation of the release of data by the largest cosmic-ray detector ever built and anticipates its future developments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗