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NASA NTRS2018

A Concept of Operations for Earth Science Data Archive and Distribution in the Cloud

Science data systems can enable more comprehensive Earth system research by evolving to take advantage of advances in commercial computer technology services. Since their inception twenty five years ago, NASA's Earth Observing System Data and Information System (EOSDIS) Distributed Active Archive Centers (DAACs) have periodically evolved to utilize new technology and expand research using the exponential growth and diversity of Earth observations. Recently, with the advent of a maturing commercial compute services industry and upcoming high data volume missions such as the Surface Water and Ocean Topography (SWOT) mission and the NASA-Indian Space Research Organization Synthetic Aperture Radar (NISAR) mission, options were explored and a decision made to utilize commercial compute and storage services. This paper presents an overview of the concept of operations under development for the DAACs in the Cloud. We highlight the goals and expected advantages of utilizing Cloud services. We outline EOSDIS operations tenets and driving principles. A high-level view of EOSDIS system of systems target architecture serves as context for describing principle interactions. Concepts for key DAAC system and EOSDIS enterprise functions characterize automated end-to-end operations but mark nominal check and recovery points. Concepts are presented for managing Cloud resources, including organizational roles and responsibilities of the NASA project and DAAC personnel. Scenarios we use to further distinguish between what the system will do and what configuration and controls operators will have. Examples include interactions with data providers and data consumers with both in-cloud and on-premise facilities.

Moses, John F.↗

DOE OSTI2016

Collaborative Research: A Model of Partially Ionized Plasma Flows with Kinetic Treatment of Neutral Atoms and Nonthermal Ions

Interactions of flows of partially ionized, magnetized plasma are frequently accompanied by the presence of both thermal and non-thermal (pickup) ion components. Such interactions cannot be modeled using traditional MHD equations and require more advanced approaches to treat them. If a nonthermal component of ions is formed due to charge exchange and collisions between the thermal (core) ions and neutrals, it experiences the action of magnetic field, its distribution function is isotropized, and it soon acquires the velocity of the ambient plasma without being thermodynamically equilibrated. This situation, e. g., takes place in the outer heliosphere - the part of interstellar space beyond the solar system whose properties are determined by the solar wind interaction with the local interstellar medium. This is also possible in laboratory, at million degrees and above, when plasma is conducting electricity far too well, which makes Ohmic heating ineffective. To attain the target temperatures one needs additional heating eventually playing a dominant role. Among such sources is a so-called neutral particle beam heating. This is a wide-spread technique (Joint European Torus and International Thermonuclear Experimental Reactor experiments) based on the injection of powerful beams of neutral atoms into ohmically preheated plasma. In this project we have investigated the energy and density separation between the thermal and nonthermal components in the solar wind and interstellar plasmas. A new model has been developed in which we solve the ideal MHD equations for mixture of all ions and the kinetic Boltzmann equation to describe the transport of neutral atoms. As a separate capability, we can treat the flow of neutral atoms in a multi-component fashion, where neutral atoms born in each thermodynamically distinct regions are governed by the Euler gas dynamic equations. We also describe the behavior of pickup ions either kinetically, using the Fokker–Planck equation, or as a separate fluid. Our numerical simulations have demonstrated that pickup ions play a major role in the interaction of the solar wind and (partially ionized) interstellar medium plasmas. Our teams have investigated the stability of the surface (the heliopause) that separates the solar wind from the local interstellar medium, the transport of galactic cosmic rays, the properties of the heliotail flow, and modifications to the bow wave in front of the heliopause due to charge exchange between the neutral H atoms born in the solar wind and interstellar ions. Modeling results have been validated against observational data, such as obtained by the Interstellar Boundary Explorer (IBEX), and made it possible to shed light on the structure of energetic neutral atom maps created by this spacecraft.. We have also demonstrated that charge-exchange modulated heliosphere is a source of anisotropy of the multi-TeV cosmic ray flux observed in a number of Earth-bound air shower experiments. Newly developed codes are implemented within a Multi-Scale Fluid-Kinetic Simulation Suite (MS-FLUKSS), a publicly available code being developed by our team for over 12 years. MS-FLUKSS scales well up to 160,000 computing cores and has been ported on major supercomputers in the country. Efficient parallelization and data choreography in the continuum simulation modules are provided by Chombo, an adaptive mesh refinement framework managed by Phillip Colella’s team at LBNL. We have implemented in-house, hybrid (MPI+OpenMP) parallelization of the kinetic modules that solve the Boltzmann equation with a Monte Carlo method. Currently, the kinetic modules are being rewritten to take advantage of the modern CPU-GPU supercomputer architecture. The scope of the project allowed us to enhance plasma research and education in such broad, multidis- ciplinary field as physics of partially ionized plasma and its application to space physics and fusion science. Besides the impact on the modeling of complex physical systems, our approach to computational resource management for complex codes utilizing multiple algorithm technologies appears to be a major advance on current approaches. The development of sophisticated resource management will be essential for all future modeling efforts that incorporate a diversity of scales and physical processes. Our effort provided leadership in promoting computational science and plasma physics within the UAH and FIT campuses and, through the training of a broad spectrum of scientists and engineers, foster new technologies across the country.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Methodology for Digital Image Correlation and Infrared Measurement of Melting Aluminum Bars

Ultimately, our experiment measures two quantities on an aluminum bar: motion (which modeling must predict) and temperature (which sets thermal boundary conditions). For motion, stereo DIC is a technique to use imaging data to provide displacements relative to a reference image down to 1/100th of a pixel. We use a calibrated infrared imaging method for accurate temperature measurements. We will be capturing simultaneous data and then registering temperature data in space to the same coordinate system as the displacement data. While we will later show that our experiments are repeatable, indicating that separate experiments for motion and temperature would provide similar data, the simultaneous and registered data removes test to test variability as a source of uncertainty for model calibration and reduces the number of time-consuming tests that must be performed.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Study of Space Charge Effects in MicroBooNE

We present a study of the impact of space charge effects within the MicroBooNE liquid argon time projection chamber (LArTPC). The space charge effect is the build-up of slow-moving positive ions in a detector due to, for instance, ionization from cosmic rays, leading to a distortion of the electric field within the detector. This effect leads to a displacement in the reconstructed position of signal ionization electrons in LArTPC detectors, as well as variations in the amount of charge quenching experienced by ionization throughout the volume of the TPC. The LArTPC utilized in MicroBooNE is expected to be modestly impacted from the space charge effect, with the electric field magnitude changing by up to 15% (at a drift field of 273 V/cm) in some locations within the TPC. Studying tracks in the TPC matched to an external small cosmic ray counter system, we observe offsets in the reconstructed track ends from their expected positions at the TPC edges, consistent with the presence of space charge effects in the detector. Data is compared to a simulation including space charge effects, which reproduces the observed track distortions. Finally, the derivation of a correction for the reconstruction of track direction is described, illustrating how one might remove the impact of these effects within the MicroBooNE LArTPC.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2014

THE NEW ONLINE METADATA EDITOR FOR GENERATING STRUCTURED METADATA

Nobody is better suited to “describe” data than the scientist who created it. This “description” about a data is called Metadata. In general terms, Metadata represents the who, what, when, where, why and how of the dataset [1]. eXtensible Markup Language (XML) is the preferred output format for metadata, as it makes it portable and, more importantly, suitable for system discoverability. The newly developed ORNL Metadata Editor (OME) is a Web-based tool that allows users to create and maintain XML files containing key information, or metadata, about the research. Metadata include information about the specific projects, parameters, time periods, and locations associated with the data. Such information helps put the research findings in context. In addition, the metadata produced using OME will allow other researchers to find these data via Metadata clearinghouses like Mercury [2][4]. OME is part of ORNL’s Mercury software fleet [2][3]. It was jointly developed to support projects funded by the United States Geological Survey (USGS), U.S. Department of Energy (DOE), National Aeronautics and Space Administration (NASA) and National Oceanic and Atmospheric Administration (NOAA). OME’s architecture provides a customizable interface to support project-specific requirements. Using this new architecture, the ORNL team developed OME instances for USGS’s Core Science Analytics, Synthesis, and Libraries (CSAS&L), DOE’s Next Generation Ecosystem Experiments (NGEE) and Atmospheric Radiation Measurement (ARM) Program, and the international Surface Ocean Carbon Dioxide ATlas (SOCAT).Researchers simply use the ORNL Metadata Editor to enter relevant metadata into a Web-based form. From the information on the form, the Metadata Editor can create an XML file on the server that the editor is installed or to the user’s personal computer. Researchers can also use the ORNL Metadata Editor to modify existing XML metadata files.As an example, an NGEE Arctic scientist use OME to register their datasets to the NGEE data archive and allows the NGEE archive to publish these datasets via a data search portal (http://ngee.ornl.gov/data). These highly descriptive metadata created using OME allows the Archive to enable advanced data search options using keyword, geo-spatial, temporal and ontology filters. Similarly, ARM OME allows scientists or principal investigators (PIs) to submit their data products to the ARM data archive.How would OME help Big Data Centers like the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC)?The ORNL DAAC is one of NASA’s Earth Observing System Data and Information System (EOSDIS) data centers managed by the Earth Science Data and Information System (ESDIS) Project. The ORNL DAAC archives data produced by NASA's Terrestrial Ecology Program. The DAAC provides data and information relevant to biogeochemical dynamics, ecological data, and environmental processes, critical for understanding the dynamics relating to the biological, geological, and chemical components of the Earth's environment. Typically data produced, archived and analyzed is at a scale of multiple petabytes, which makes the discoverability of the data very challenging. Without proper metadata associated with the data, it is difficult to find the data you are looking for and equally difficult to use and understand the data.OME will allow data centers like the NGEE and ORNL DAAC to produce meaningful, high quality, standards-based, descriptive information about their data products in-turn helping with the data discoverability and interoperability. Useful Links:USGS OME: http://mercury.ornl.gov/OME/NGEE OME: http://ngee-arctic.ornl.gov/ngeemetadata/ARM OME: http://archive2.ornl.gov/armome/Contact: Ranjeet Devarakonda (devarakondar@ornl.gov)References:[1] Federal Geographic Data Committee. Content standard for digital geospatial metadata. Federal Geographic Data Committee, 1998.[2] Devarakonda, Ranjeet, et al. "Mercury: reusable metadata management, data discovery and access system." Earth Science Informatics 3.1-2 (2010): 87-94.[3] Wilson, B. E., Palanisamy, G., Devarakonda, R., Rhyne, B. T., Lindsley, C., & Green, J. (2010). Mercury Toolset for Spatiotemporal Metadata.[4] Pouchard, L. C., Branstetter, M. L., Cook, R. B., Devarakonda, R., Green, J., Palanisamy, G., ... & Noy, N. F. (2013). A Linked Science investigation: enhancing climate change data discovery with semantic technologies. Earth science informatics, 6(3), 175-185.

FGDC CSDGM↗

DOE OSTI2024

Deep kernel methods learn better: from cards to process optimization

Abstract The ability of deep learning methods to perform classification and regression tasks relies heavily on their capacity to uncover manifolds in high-dimensional data spaces and project them into low-dimensional representation spaces. In this study, we investigate the structure and character of the manifolds generated by classical variational autoencoder (VAE) approaches and deep kernel learning (DKL). In the former case, the structure of the latent space is determined by the properties of the input data alone, while in the latter, the latent manifold forms as a result of an active learning process that balances the data distribution and target functionalities. We show that DKL with active learning can produce a more compact and smooth latent space which is more conducive to optimization compared to previously reported methods, such as the VAE. We demonstrate this behavior using a simple cards dataset and extend it to the optimization of domain-generated trajectories in physical systems. Our findings suggest that latent manifolds constructed through active learning have a more beneficial structure for optimization problems, especially in feature-rich target-poor scenarios that are common in domain sciences, such as materials synthesis, energy storage, and molecular discovery. The Jupyter Notebooks that encapsulate the complete analysis accompany the article.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1982

Proceedings: Sixth Annual Workshop on Meteorological and Environmental Inputs to Aviation Systems

The proceedings of a workshop on meteorological and environmental inputs to aviation systems held at The University of Tennessee Space Institute, Tullahoma, Tennessee. October 26 - 28, 1982, are reported. The workshop, jointly sponsored by NASA, NOAA, and FAA, brought together many disciplines of the aviation communities in round table discussions. The major objectives of the workshop are to satisfy such needs of the sponsoring agencies as the expansion of our understanding and knowledge of the interaction of the atmosphere with aviation systems, the better definition and implementation of services to operators, and the collection and interpretation of data for establishing operational criteria relating the total meteorological inputs from the atmospheric sciences to the needs of aviation communities. The unique aspects of the workshop were the diversity of the participants and the achievement of communication across the interface of the boundaries between pilots, meteorologists, training personnel, accident investigators, traffic controllers, flight operation personnel from military, civil, general aviation, and commercial interests alike. Representatives were in attendance from government, airlines, private agencies, aircraft manufacturers, Department of Defense, industries, research institutes, and universities.

Walter Frost↗

NASA NTRS1989

Closed loop navigation and guidance for gravity probe B orbit insertion

This paper addresses the problem of guiding the Gravity Probe B (GP-B) spacecraft from its location after initial insertion to a very precise low earth orbit. Specifically, the satellite orbit is required to be circular to within 0.001 eccentricity, polar to within 0.001 deg inclination, and aligned with the direction of the star Rigel to within 0.001 deg. Navigation data supplied by an on-board GPS receiver is used as feedback to a control algorithm designed to minimize the time to achieve the desired orbit. Translational control is provided by the proportional helium thrusters, which are used for drag-free and attitude control during the remainder of the science mission. Simulations of the guidance system are presented which give an indication of performance characteristics for several types of orbit injection errors. This research is the first reported effort to use GPS as a sensor for a closed loop space guidance system.

Axelrad, P.↗

NASA NTRS1993

The GPS Topex/Poseidon precise orbit determination experiment - Implications for design of GPS global networks

Topex/Poseidon, a cooperative satellite mission between United States and France, aims to determine global ocean circulation patterns and to study their influence on world climate through precise measurements of sea surface height above the geoid with an on-board altimeter. To achieve the mission science aims, a goal of 13-cm orbit altitude accuracy was set. Topex/Poseidon includes a Global Positioning System (GPS) precise orbit determination (POD) system that has now demonstrated altitude accuracy better than 5 cm. The GPS POD system includes an on-board GPS receiver and a 6-station GPS global tracking network. This paper reviews early GPS results and discusses multi-mission capabilities available from a future enhanced global GPS network, which would provide ground-based geodetic and atmospheric calibrations needed for NASA deep space missions while also supplying tracking data for future low Earth orbiters. Benefits of the enhanced global GPS network include lower operations costs for deep space tracking and many scientific and societal benefits from the low Earth orbiter missions, including improved understanding of ocean circulation, ocean-weather interactions, the El Nino effect, the Earth thermal balance, and weather forecasting.

Lindqwister, Ulf J.↗

NASA NTRS1993

Design considerations for the CELSS test facility engineering development unit

The NASA Controlled Ecological Life Support System (CELSS) Program has the goal of developing life support systems for humans in space based on the use of higher plants. The program has supported research at universities with a primary focus of increasing the productivity of candidate crop plants. To understand the effects of the space environment on plant productivity, the CELSS Test Facility (CTF) has been developed as an instrument that will permit the evaluation of plant productivity on Space Station Freedom. The CFT will maintain specific environmental conditions and collect data on gas exchange rates and biomass accumulation over the growth period of several crop plants grown sequentially from seed to harvest. To better understand the systems needed to support plants and maintain the evironmental conditions required by CTF, an Engineering Development Unit (EDU) is being constructed at NASA Ames Research Center (ARC) in the Advanced Life Support Division. The EDU will provide the means of testing and evaluating hardware solutions to CTF requirements. This paper reviews the CTF science and functional requirements, and provides a description of the EDU objectives, design approach, subsystem descriptions, and some of the technology tools employed in accomplishing the design.

Kliss, M.↗

NASA NTRS2001

Workshop on Science and the Human Exploration of Mars

The exploration of Mars will be a multi-decadal activity. Currently, a scientific program is underway, sponsored by NASA's Office of Space Science in the United States, in collaboration with international partners France, Italy, and the European Space Agency. Plans exist for the continuation of this robotic program through the first automated return of Martian samples in 2014. Mars is also a prime long-term objective for human exploration, and within NASA, efforts are being made to provide the best integration of the robotic program and future human exploration missions. From the perspective of human exploration missions, it is important to understand the scientific objectives of human missions, in order to design the appropriate systems, tools, and operational capabilities to maximize science on those missions. In addition, data from the robotic missions can provide critical environmental data - surface morphology, materials composition, evaluations of potential toxicity of surface materials, radiation, electrical and other physical properties of the Martian environment, and assessments of the probability that humans would encounter Martian life forms. Understanding of the data needs can lead to the definition of experiments that can be done in the near-term that will make the design of human missions more effective. This workshop was convened to begin a dialog between the scientific community that is central to the robotic exploration mission program and a set of experts in systems and technologies that are critical to human exploration missions. The charge to the workshop was to develop an understanding of the types of scientific exploration that would be best suited to the human exploration missions and the capabilities and limitations of human explorers in undertaking science on those missions.

Duke, M. B.↗

NASA NTRS1998

Information Systems for NASA's Aeronautics and Space Enterprises

The aerospace industry is being challenged to reduce costs and development time as well as utilize new technologies to improve product performance. Information technology (IT) is the key to providing revolutionary solutions to the challenges posed by the increasing complexity of NASA's aeronautics and space missions and the sophisticated nature of the systems that enable them. The NASA Ames vision is to develop technologies enabling the information age, expanding the frontiers of knowledge for aeronautics and space, improving America's competitive position, and inspiring future generations. Ames' missions to accomplish that vision include: 1) performing research to support the American aviation community through the unique integration of computation, experimentation, simulation and flight testing, 2) studying the health of our planet, understanding living systems in space and the origins of the universe, developing technologies for space flight, and 3) to research, develop and deliver information technologies and applications. Information technology may be defined as the use of advance computing systems to generate data, analyze data, transform data into knowledge and to use as an aid in the decision-making process. The knowledge from transformed data can be displayed in visual, virtual and multimedia environments. The decision-making process can be fully autonomous or aided by a cognitive processes, i.e., computational aids designed to leverage human capacities. IT Systems can learn as they go, developing the capability to make decisions or aid the decision making process on the basis of experiences gained using limited data inputs. In the future, information systems will be used to aid space mission synthesis, virtual aerospace system design, aid damaged aircraft during landing, perform robotic surgery, and monitor the health and status of spacecraft and planetary probes. NASA Ames through the Center of Excellence for Information Technology Office is leading the effort in pursuit of revolutionary, IT-based approaches to satisfying NASA's aeronautics and space requirements. The objective of the effort is to incorporate information technologies within each of the Agency's four Enterprises, i.e., Aeronautics and Space Transportation Technology, Earth, Science, Human Exploration and Development of Space and Space Sciences. The end results of these efforts for Enterprise programs and projects should be reduced cost, enhanced mission capability and expedited mission completion.

Kutler, Paul↗

NASA NTRS2002

The Extension of ISS Resources for Multi-Discipline Subrack Payloads

The EXpedite the processing of Experiments to Space Station or EXPRESS Rack System was developed to provide Space Station accommodations for subrack payloads. The EXPRESS Rack accepts Space Shuttle middeck locker type payloads and International Subrack Interface Standard (ISIS) Drawer payloads, allowing previously flown payloads an opportunity to transition to the International Space Station. The EXPRESS Rack provides power, data command and control, video, water cooling, air cooling, vacuum exhaust, and Nitrogen supply to payloads. The EXPRESS Rack system also includes transportation racks to transport payloads to and from the Space Station, Suitcase Simulators to allow a payload developer to verify data interfaces at the development site, Functional Checkout Units to allow payload checkout at KSC prior to launch, and trainer racks for the astronauts to learn how to operate the EXPRESS Racks prior to flight. Standard hardware and software interfaces provided by the EXPRESS Rack simplify the integration processes, and facilitate simpler ISS payload development. Whereas most ISS Payload facilities are designed to accommodate one specific type of science, the EXPRESS Rack is designed to accommodate multi-discipline research within the same rack allowing for the independent operation of each subrack payload. On-orbit operations began with the EXPRESS Rack Project on April 24, 2001, with one rack operating continuously to support long-running payloads. The other on-orbit EXPRESS Racks operate based on payload need and resource availability. Sustaining Engineering and Logistics and Maintenance functions are in place to maintain operations and to provide software upgrades.

Sledd, Annette M.↗

NASA NTRS2002

EXPRESS Rack: The Extension of International Space Station Resources for Multi-Discipline Subrack Payloads

The EXpedite the PRocessing of Experiments to Space Station or EXPRESS Rack System was developed to provide Space Station accommodations for subrack payloads. The EXPRESS Rack accepts Space Shuttle middeck locker type payloads and International Subrack Interface Standard (ISIS) Drawer payloads, allowing previously flown payloads an opportunity to transition to the International Space Station. The EXPRESS Rack provides power, data command and control, video, water cooling, air cooling, vacuum exhaust, and Nitrogen supply to payloads. The EXPRESS Rack system also includes transportation racks to transport payloads to and from the Space Station, Suitcase Simulators to allow a payload developer to verify data interfaces at the development site, Functional Checkout Units to allow payload checkout at KSC prior to launch, and trainer racks for the astronauts to learn how to operate the EXPRESS Racks prior to flight. Standard hardware and software interfaces provided by the EXPRESS Rack simplify the integration processes, and facilitate simpler ISS payload development. Whereas most ISS Payload facilities are designed to accommodate one specific type of science, the EXPRESS Rack is designed to accommodate multi-discipline research within the same rack allowing for the independent operation of each subrack payload. On-orbit operations began with the EXPRESS Rack Project on April 24, 2001, with one rack operating continuously to support long-running payloads. The other on-orbit EXPRESS Racks operate based on payload need and resource availability. Sustaining Engineering and Logistics and Maintenance functions are in place to maintain operations and to provide software upgrades.

Sledd, Annette↗

NASA NTRSDate not supplied

Enabling Space Biological Knowledge Discovery Through Image and Video Data Sharing

Increased biomedical risks and challenges associated with deep space missions and experiments (cis-Lunar, Mars transit/surface) require new knowledge discovery and development of novel ecosystems. Supporting distant and long-duration missions and experiments requires biological data (from yeast, microbes, fruit flies, C. elegans, plants, crops, rodents, humans) be findable, accessible, interoperable, reusable (FAIR), and maximally open-access. As data-intensive, bioinformatic, meta-analytical, and computer-assisted approaches continue to be a centerpiece of modern research, the NASA Biological and Physical Sciences division is expanding its Open Science capabilities beyond NASA GeneLab. The NASA Ames Life Sciences Data Archive (ALSDA) is a repository which is responsible for collecting and access to space biological imagery and video, alongside tabular and environmental data. In this presentation, we will discuss strategies dealing with archiving, curating, and accessibility of images from very distinct imaging modalities (e.g., micro-computed tomography, magnetic resonance imaging, photographic images of plants, fluorescence microscopy, behavioral videos, etc.). There are two main challenges: 1. Open-source data storage and 2. Metadata related to the imagery-video. Both have been solved by leveraging two existing open-source systems. For data storage, ALSDA is utilizing components through the Open Microscopy Environment (OME), which can read most imaging proprietary formats and display on a web interface complex multidimensional images (Z stack, multi-channel, temporal, spectral). Most technical metadata from imaging modalities are captured seamlessly. For metadata capturing experimental details, ALSDA (like GeneLab) uses the ISA-Tab specification which relies on the ISA data model to order and classify metadata. The ISA data model uses a tree structure with three files to capture the metadata: The top layer is the Investigations file, the second layer is the Study file(s), and the last layer is the Assay file(s). We believe such an approach may be useful for other types of image research data from other investigators in the AGU community.

imaging↗

NASA NTRSDate not supplied

Preliminary Assessment of the Impact on the V-Band Oxygen Channels From Satellite Communication Uplinks

We calculate the percentage of time that an ATMS-like instrument [1] will be illuminated by the uplink beam of one of the proposed V-band communication system and estimate the damage resulting from such exposure. Using a combination of openly available information and educated guesses about the location and characteristics of the up/down link terminals, we constructed the ground segment of a hypothetical high-speed communication network. The space segment of the network was constructed from the orbital data of the existing Starlink constellation [2] of 6223 communication satellites (comsats) which is used as strawman to represent any other possible constellation of communication satellites. It is shown that without a very delicate balance of frequency allocations (science vs telecommunications), coupled with extremely steep and deep bandpass-defining filters, and strict adherence to the agreed limits (i.e. no out-of-band transmissions) the deployment of the telecommunication network leads to almost-complete loss of some important geophysical data. For the analysis we use the spectral characteristics of the ATMS instrument with the ephemeris for the NOAA-21 satellite [3]. The analysis is conducted for the USA and the simulation covers 8 consecutive days in July 2024. Effective and accurate microwave remote sensing of the atmosphere depends on the availability of interference-free spectrum windows at frequencies which are prescribed by physical processes [e.g. 4]. The family of resonant lines of the oxygen molecule near 60 GHz provides a unique opportunity to sample the vertical distribution of temperature and density from space, and it has been exploited for weather and climate studies from polar-orbiting satellites since 1978 (MSU on TIROS-N [5]). It remains a staple in the payloads operated by Russia, China, USA, Japan, France, India, UK, Ukraine [6] which are built around a common blueprint: a few wide-band (hundreds of MHz) channels around 50 GHz to sample the atmosphere and the surface while several more channels with high spectral resolution (few MHz) sample the individual resonant lines. Accurate retrieval of the environmental parameters depends upon the data provided by both sets of channels, and the their location in frequency space is not arbitrary and cannot be altered at will [7, 8]. The introduction of 5G technology in 2019 has driven telecommunication companies to request more bandwidth to be dedicated to their devices. This additional bandwidth is only available in spectral regions traditionally reserved for environmental and astrophysical research, such as the V-band between 50 and 60 GHz for up/downlink between satellites in low-earth orbits and terminals connected to fiberoptics network for distribution to high-speed local internet services. The power broadcast by the uplink communication leg is many orders of magnitude greater than the natural thermal signal emitted from the Earth scene. If the ground antenna were to perfectly align with the passive instrument’s antenna, the spaceborne receiver would suffer permanent, irreparable damage. While a direct boresight-to-boresight conjunction is extremely unlikely (even with a large constellation of satellites the fraction of the celestial sphere occupied by the satellites remains minuscule) the finite size of the ground station’s antenna beam in the sky suggests that the ATMS will be in the near background (as seen from the ground station) of one of the communication satellites and will be illuminated by either the main lobe or the near sidelobes of the uplink antenna more often than it is desirable. For our analysis we first calculate the position of the ATMS with respect to each of the ground stations at a resolution of 0.2 sec, then calculate the position of each of the comsats which are at least 25 deg above the station’s local horizon; finally we calculate the angle between the line-of-sight of the ATMS and the line-of-sight of the comsat. We assume that the gain pattern of the ground station is circularly symmetric; the angle-off-station-boresight then provides an attenuation of the uplink power which we use to assess the likely effect upon the passive instrument’s operations. We assume that each ground station can communicate with all the comsats in its field of view; this implies that, on average, a ground station can engage with 46 comsats simultaneously. The analysis is repeated for the case when the uplink broadcast within the ATMS passive channels (in-band scenario) and for the case when the uplink is limited to frequencies adjacent to the ATMS channels (out-of-band scenario). The antenna of the ground station is modelled as having a HPBW (Half-Power Beam Width) of 0.16 deg and EIRP (Equivalent Isotropic Radiated Power) of 70 dBW. We account for the geometric dissipation of the signal caused by the satellite orbital altitude, the attenuation induced by atmospheric gasses at 51 GHz and the mismatch between the circular polarization of the ground-based transmitting antenna and the linear polarization of the satellite-borne receiving antenna. The damages on ATMS are estimated from bench-level measurement conducted at the ATMS’ manufacturer facilities [unpublished].

passive microwave↗

NASA NTRS2008

An Overview of the Microgravity Science Glovebox (MSG) Facility, and the Gravity-Dependent Phenomena Research Performed in the MSG on the International Space Station (ISS)

The Microgravity Science Glovebox (MSG) is a double rack facility aboard the International Space Station (ISS) designed for gravity-dependent phenomena investigation handling. The MSG has been operating in the ISS US Laboratory Module since July 2002. The MSG facility provides an enclosed working area for investigation manipulation and observation, The MSG's unique design provides two levels of containment to protect the ISS crew from hazardous operations. Research investigations operating inside the MSG are provided a large 255 liter work volume, 1000 watts of dc power via a versatile supply interface (120, 28, +/-12, and 5 Vdc), 1000 watts of cooling capability, video and data recording and real time downlink, ground commanding capabilities, access to ISS Vacuum Exhaust and Vacuum Resource Systems, and gaseous nitrogen supply. With these capabilities, the MSG is an ideal platform for research required to advance the technology readiness levels (TRL) needed for the Crew Exploration Vehicle and the Exploration Initiative. Areas of research that will benefit from investigations in the MSG include thermal management, fluid physics, spacecraft fire safety, materials science, combustion, reaction control systems, in situ fabrication and repair, and advanced life support technologies. This paper will provide a detailed explanation of the MSG facility, a synopsis of the research that has already been accomplished in the MSG and an overview of investigations planning to operate in the MSG. In addition, this paper will address possible changes to the MSG utilization process that will be brought about by the transition to ISS as a National Laboratory.

Spivey, Reggie A.↗

NASA NTRSDate not supplied

Nearest-Neighbor Machine Learning Feature Selection for Interpretation of Microbial Molecular Signatures from Isotope Ratio Mass Spectrometry Data

Mass spectrometry (MS) promises to be a powerful tool for potential biosignature detection during astrobiological missions on ocean worlds in our solar system. Accurate and generalizable machine learning methods could enhance science return on investment by predicting seawater chemistry and classifying isotopic biosignatures, either as a signature consistent with microbial life (biotic) or as a novelty (unclassified/unique). However, machine learning models are likely to be complex and involve interactions between MS features, making biosignatures difficult to interpret. Feature selection methods provide biological and chemical context that help interpret the mechanisms of machine learning models, but these methods also need the ability to detect complex interactions. Previously, we developed a machine learning feature selection algorithm called nearest-neighbor projected distance regression (NPDR) that has the ability to identify important model features that involve complex interactions and automatically reduce correlation and the dimensionality in a high-dimensional variable space. The standard distance metrics used in NPDR – Manhattan and Euclidean – assume the multivariate data are isotropic, which is often violated in real data due to differences in the covariance between variables. Thus, we extend NPDR to include a random forest distance, and other anisotropic distance metrics, for computing nearest neighbors. We also augment the isotope-ratio MS data with time-series features from the raw MS signal to improve biotic classification. We test NPDR on our novel experimental ocean world seawater analog MS data. We measure isotope fractionations of volatile CO 2 that could be measured in exospheres or plumes. Samples include baseline abiotic conditions using a range of possible seawater chemistry consistent with Europa and Enceladus, and biotic samples that include microbes in these seawaters. We use penalized NPDR with random forest proximity to identify interpretable microbial molecular signatures. We compare features with random forest importance, and we train a classifier that discriminates between biotic and abiotic samples with high accuracy. These ML-trained ocean-world analog MS data could be used to assist in identifying biosignatures during future missions.

geochemistry↗