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The NASA Open Science Data Repository: Biomedical Fair Data, Analysis Tools, User Communities, Publications, and Discoveries for Deep Space Missions

Increased biomedical risks and challenges associated with deep space missions require new knowledge discovery, new health countermeasures, and development of novel ecosystems, life support, crop production, and biomedical support capabilities. To meet NASA’s Moon to Mars strategic program goals for Human and Biological Sciences, findable, accessible, interoperable, reusable (FAIR), and maximally open-access data is going to be required to enable humanity to thrive in deep space. Indeed, this cornerstone perspective on FAIR and maximally open access data was also recommended in the recent 2023-2032 Decadal Survey from the National Academies of Sciences, Engineering, and Medicine. The NASA Open Science Data Repository (OSDR) is a maximally open access and FAIR database, and meets various scientific, technical, and operational spaceflight needs. It offers public users and submitters the ability to upload, download, search, share, analyze, and visualize data across ‘omics, physiological, phenotypic, behavioral, bioimaging, video, and environmental monitoring telemetry datasets. OSDR includes NASA GeneLab, NASA Ames Life Sciences Data Archive, and the NASA Biological Institutional Scientific Collection. OSDR has >455 studies with datasets from model organisms and non-NASA human astronauts. There are ~12 datasets from the Inspiration 4 (I4) mission, spanning metagenomics, comprehensive metabolic panels, clonal hematopoiesis, spatial transcriptomics, proteomics, and cytokine panels. In the interest of data privacy, two I4 datasets have raw FASTQ and FASTA files relating to the epitranscriptome, and a new request feature is live in OSDR (with a backend review process established) which was developed based on industry norms. OSDR also recently began a collaboration with the European Space Agency (ESA) to scientifically curate and make available >200 terabytes of human and model organism space-relevant data. The OSDR submission portal is designed to ingest and curate ~25 ‘omics assay data types, and ~50 physiological-phenotypic-imaging assay data types, spanning ultrasonography, micro-computed tomography, histology, morphometric photography, rebound tonometry, gait analysis, optical coherence tomography, novel object recognition, flow cytometry, and immunohistochemistry. A suite of analysis tools are available for OSDR users including: 1) an Environmental Data Application to compare radiation, CO2, relative humidity, temperature, and other telemetry across missions and subjects, 2) the RadLab database, a collaboration between NASA, ESA, the German and Italian Space Agencies, and the Bulgarian Academy of Sciences, which compiles radiation measurements relevant to human spaceflight and provides tools for accessing and manipulating the data, and 3) a Multi-study visualization tool which enables users to look across and combine GeneLab’s omics datasets across different experiments and missions. There are ~600 volunteer OSDR Analysis Working Group (AWG) members who: 1) provide feedback on scientific standards for reuse (subject and assay metadata; processing pipelines; dataset formats and uniformed structures for machine-readability), and 2) collaborate to mine-reuse OSDR data conducting scientific analysis. OSDR has enabled 60 publications as of September 2023, many directly from AWG collaborations most notably the Cell Press package in 2020. Lastly, there are at least 15 articles which mine OSDR data part of a package of ~50 articles across Nature Portfolio with research stemming from I4, the Japan Aerospace Exploration Agency, NASA Space Biology, and the NASA Human Research Program.

space biology↗

NASA Open Science Data Repository: Biomedical FAIR Data, Analysis Tools, User Communities, and Discoveries for Deep Space Missions

Increased biomedical risks and challenges associated with deep space missions require new knowledge discovery, new health countermeasures, and development of novel ecosystems, life support, crop production, and biomedical support capabilities. To meet NASA’s Moon to Mars strategic program goals for Human and Biological Sciences, findable, accessible, interoperable, reusable (FAIR), and maximally open-access data is going to be required to enable humanity to thrive in deep space. Indeed, this cornerstone perspective on FAIR and maximally open access data was also recommended in the recent 2023-2032 Decadal Survey from the National Academies of Sciences, Engineering, and Medicine. The NASA Open Science Data Repository (OSDR) is a maximally open access and FAIR database, and meets various scientific, technical, and operational spaceflight needs. It offers public users and submitters the ability to upload, download, search, share, analyze, and visualize data across ‘omics, physiological, phenotypic, behavioral, bioimaging, video, and environmental monitoring telemetry datasets. OSDR includes NASA GeneLab, NASA Ames Life Sciences Data Archive, and the NASA Biological Institutional Scientific Collection. OSDR has >455 studies with datasets from model organisms and non-NASA human astronauts. There are ~12 datasets from the Inspiration 4 (I4) mission, spanning metagenomics, comprehensive metabolic panels, clonal hematopoiesis, spatial transcriptomics, proteomics, and cytokine panels. In the interest of data privacy, two I4 datasets have raw FASTQ and FASTA files relating to the epitranscriptome, and a new request feature is live in OSDR (with a backend review process established) which was developed based on industry norms. OSDR also recently began a collaboration with the European Space Agency (ESA) to scientifically curate and make available >200 terabytes of human and model organism space-relevant data. The OSDR submission portal is designed to ingest and curate ~25 ‘omics assay data types, and ~50 physiological-phenotypic-imaging assay data types, spanning ultrasonography, micro-computed tomography, histology, morphometric photography, rebound tonometry, gait analysis, optical coherence tomography, novel object recognition, flow cytometry, and immunohistochemistry. A suite of analysis tools are available for OSDR users including: 1) an Environmental Data Application to compare radiation, CO2, relative humidity, temperature, and other telemetry across missions and subjects, 2) the RadLab database, a collaboration between NASA, ESA, the German and Italian Space Agencies, and the Bulgarian Academy of Sciences, which compiles radiation measurements relevant to human spaceflight and provides tools for accessing and manipulating the data, and 3) a Multi-study visualization tool which enables users to look across and combine GeneLab’s omics datasets across different experiments and missions. There are ~600 volunteer OSDR Analysis Working Group (AWG) members who: 1) provide feedback on scientific standards for reuse (subject and assay metadata; processing pipelines; dataset formats and uniformed structures for machine-readability), and 2) collaborate to mine-reuse OSDR data conducting scientific analysis. OSDR has enabled 60 publications as of September 2023, many directly from AWG collaborations most notably the Cell Press package in 2020. Lastly, there are at least 15 articles which mine OSDR data part of a package of ~50 articles across Nature Portfolio with research stemming from I4, the Japan Aerospace Exploration Agency, NASA Space Biology, and the NASA Human Research Program.

open access↗

Space-based Sensor for Extreme Fire Weather Events

Catastrophic bushfires are becoming increasingly prevalent as climate change advances. Impacts extend beyond national borders. Multinational efforts can inform new science and management practices. Space-based sensors and integrated data facilities will play an important role. This paper describes a collaborative project between a consortium of Australian universities and NASA Centers to develop and implement a small satellite platform comprising highly integrated thermal and lightning sensors coupled with AI-based edge computing to help predict, detect, and track bushfires, supporting mitigation activities. This will fill an important capability gap since Australia does not currently have any sovereign Earth observation satellites. This program is enabled by and builds on Australia-NASA collaboration and will also support fire science and management activities in the broader global context.

wildfire↗

Exploring our Changing Planet through NASA’s Earth Information Center and Novel Methods for Earth Science Communication

In June 2023, NASA unveiled the Earth Information Center (EIC), an interagency initiative which invites the global community to explore how our planet is changing through interactive installations, captivating visualizations, and novel storytelling. Existing in both physical and virtual space, the EIC serves as a gateway to actionable information collected through an expanding fleet of Earth observing satellites and sensors. The EIC features data driven visualizations, near real-time information, immersive experiences, and curated stories that highlight the applications of publicly available data to address environmental challenges across nine thematic areas: agriculture, biodiversity, disasters, greenhouse gases, air quality, sea level rise, sustainable energy, water resources, and wildfires. Designed by an interdisciplinary team, EIC exhibits are developed to reach a wide base of end-users across multiple learning modalities. During the first year of operation, the inaugural location of the EIC at NASA Headquarters in Washington, DC, welcomed an estimated 24,000 visitors, hosted over 145 tours for domestic and international organizations, supported NASA’s Earth Day 2024 programming, and led six STEM programs for diverse student communities. With lessons learned from the first year of being open to the public and a variety of novel science communication tools in development, the EIC is expanding the mission’s reach by collaborating with museums and visitor centers. Through these collaborations, we aim to inform a broader demographic about the unprecedented changes observed in Earth’s climate and inspire communities to learn more about their one and only home, planet Earth.

Nicole Ramberg-Pihl↗

Terrestrial Proving Ground Capabilities Needed for Lunar In Situ Resource Utilization (ISRU) & Construction Concepts of Operation

Incorporating any new technology or system into a human exploration mission or architecture requires development well in advance of the mission to eliminate technology, cost, and schedule risk concerns. It is often stated that technologies need to be at a Technology Readiness Level (TRL) of 6, i.e. ‘system/subsystem model or prototype demonstration in a relevant environment (ground or space)’, by Authority To Proceed (ATP) or by the Preliminary Design Review (PDR) for the mission at the latest. There are two game changing capabilities for sustained human exploration of space that can have a significant effect on the overall exploration architecture and the technologies and systems included in the architecture. The first game changing capability, known as In Situ Resource Utilization (ISRU), involves the search for, acquisition, and processing of resources on the Moon and Mars into mission consumables and usable products, and the second is the ability to utilize space resources in the construction of roads, structures, and surface infrastructure. ISRU and surface construction capabilities have the potential to greatly reduce the cost and risk of human exploration while enabling sustained lunar surface and commercial operations. However, ISRU and surface construction systems are complex and must operate in extremely harsh environments, with abrasive regolith and pervasive dust, for long-periods of time, with potentially limited opportunities for maintenance and repair by humans. The complexity of these capabilities and operations also means that there are a limited number of companies that can design, build, and operate end-to-end systems on their own. The majority of the technologies being developed for these systems are by small companies and at the component or subsystem level. With the overarching strategy of the United States National Aeronautics and Space Administration (NASA) Space Technology Mission Directorate (STMD) to enable industry to implement ISRU and surface infrastructure for Artemis and space commercialization, it is therefore important to establish processes and capabilities to promote and foster collaborations among large and small companies involved in ISRU and surface infrastructure development. For ISRU and infrastructure systems and capabilities to be used in Artemis missions and future commercial lunar surface operations, a coordinated framework with virtual/physical integration and testing locations, or ‘Proving Grounds’, needs to be established and operated on a regular basis and open to all. This paper will discuss the ISRU and surface construction near and long-term concepts of operations, and review operations and lessons-learned from the previous ISRU analog field tests. From this information, requirements and capabilities will be proposed to support and enable the integration and testing of ISRU and construction systems with industry, academia, and international agencies, as well as what facilities and organizations could help establish these Proving Grounds.

ISRU↗

Collaborative Data Publication Utilizing the Open Data Repository's Data Publisher

For small communities in multidisciplinary fields such as astrobiology, publishing and sharing data can be challenging. While large, homogenous fields often have repositories and existing data standards, small groups of independent researchers have few options for publishing data that can be utilized within their community. In conjunction with teams at NASA Ames and the University of Arizona, a number of pilot studies are being conducted to assess the needs of these research groups and to guide the software development so that it allows them to publish and share their data collaboratively.

Human-readable interfaces↗

Chemochromic Indicators for the Detection of Hypergolic Fuels

The toxicity and hazard level associated with the use of hypergolic fuels necessitates the development of technology capable of detecting the presence of such fuels in a variety of different environments and conditions. The most commonly used sensors for the detection of hypergolic fuels are electrochemical in nature, which have serious limitations when used as area monitoring devices. Recent collaborative work between Kennedy Space Center and ASRC Aerospace has led to the development of indicators which exhibit a color change upon exposure to hydrazine under different conditions. The indicators under investigation on this developmental effort are para-dimethylaminobenzaldehyde (PDAB), various formulations of universal pH indicators, and potassium tetrachloroaurate (KAuCl4). These chemochromic indicators have been tested for the detection of hydrazine under various conditions: pure liquid fuel, aqueous fuel solution, saline aqueous fuel solutions, vapor fuel, and 3-month shelf life study, which included UV protection, thermal extremes, and normal storage conditions. The hypergolic fuel indicator test was conducted with the indicator impregnated into a wipe material to test the applicability of the indicator to be used to capture (absorb) and indicate the presence of hypergolic fuels. Each of the indicators performed well, with the universal pH indicator being the best candidate because of the visible response color change and the indicator stability after the shelf life study.

Santiago-Maldonado, E.↗

Hail Storm Risk Assessment Using Space-Borne Remote Sensing Observations and Reanalyses

Much of the world is impacted by severe thunderstorms, but whether they become disasters depends upon resilience--our capacity to prepare, mitigate, respond, and recover. Hail is the costliest severe weather hazard for the insurance industry, generating ~70% of severe convective storm losses due to damage to assets such as homes, businesses, agriculture, and infrastructure. Most insurance companies do not reserve enough capital to cover catastrophes, so they acquire reinsurance. The reinsurance industry uses catastrophe models (CatModels) to statistically estimate risk to an insurer’s portfolio. Hail CatModels are developed with climatologies that define hailstorm frequency and severity. Hail-prone areas can be defined using hail reports from trained spotters, the media, and the general public. Extremely severe hail (2+ inch diameter) occurs nearly every day across the world. Weather radars can detect hail because hailstones strongly reflect microwave signals that they emit. However, hail climatologies are difficult to derive because hail covers small areas and there are neither hail reporting mechanisms (e.g. website or mobile app) nor radar networks in most places outside the US and Europe. This lack of ground truth on severe hail puts society and economies at risk. Hail is generated within storms by strong updrafts. These updrafts exhibit unique signatures in NASA and other agency satellite observations, offering new opportunities for hailstorm analysis. Geostationary (GEO) visible and infrared imagery has been collected for ~15-25 years across the world (region dependent) and methods have been developed at NASA Langley Research Center (LaRC) to detect hailstorm updrafts using GEO imagery. Climatological GEO updraft data has been used by Willis Towers Watson (WTW), a leader in catastrophe risk assessment for the insurance industry, and Karlsruhe Institute of Technology to develop CatModels over Europe and Australia. Hail can also be inferred with passive microwave imagery collected by low-Earth-orbiting sensors such as the GPM GMI, TRMM TMI, AMSR-E, AMSR-2, SSM/I, and SSMIS over the last 20+ years using methods developed at the Marshall Space Flight Center (MSFC). Hailstorms generate enhanced lightning flash rates that can be tracked using new GOES-R series GEO Lightning Mapping (GLM) imagery. Atmospheric reanalyses can be used to define favorable hailstorm environments for combination with the satellite-based storm detections. This presentation will describe a framework for developing continental to global hail climatologies and CatModels based on NASA satellite data and capabilities. This is a collaboration between LaRC and MSFC, WTW, and partners in Brazil, Argentina, and South Africa. This project seeks to mitigate hail disasters by aiding development of new satellite-based severe storm nowcasting tools by regional partners and developing climatologies to improve societal understanding of hail frequency. GEOO visible and infrared metrics of storm intensity, environmental conditions based on reanalyses, spotter hail reports and radar MESH observations are intercompared to quantify the detectability of hailstorms, and our ability to discriminate hailstorms from other severe storms. We are also maturing methods using land surface imaging satellite data (e.g. MODIS, Landsat, Sentinel 1 and 2) to identify hail damage to agriculture. Work with WTW will improve socioeconomic resilience through development of new CatModels. Southern Brazil, Uruguay, Paraguay, and Argentina feature some of the most intense thunderstorms on Earth. South America and South Africa are developing insurance markets of interest to WTW clients, and is similar to other regions routinely impacted by hail that do not have comprehensive hail reporting or radars to assess hailstorm frequency. Project datasets will be made available via online GIS-enabled tools developed at the LaRC Atmospheric Science Data Center (ASDC) which will visualize data and provide it in multiple formats for use in a wide range of open source and commercial tools.

Kristopher Michael Bedka↗

Scheduler Design Criteria: Requirements and Considerations

This presentation covers fundamental requirements and considerations for developing schedulers in airport operations. We first introduce performance and functional requirements for airport surface schedulers. Among various optimization problems in airport operations, we focus on airport surface scheduling problem, including runway and taxiway operations. We then describe a basic methodology for airport surface scheduling such as node-link network model and scheduling algorithms previously developed. Next, we explain how to design a mathematical formulation in more details, which consists of objectives, decision variables, and constraints. Lastly, we review other considerations, including optimization tools, computational performance, and performance metrics for evaluation.

NASA-KAIA/KARI research collaboration↗

NASA LSII Lunar Simulant Project

Introduction: America has entered a new era of exploration. NASA’s Artemis program will lead humanity forward to the Moon and prepare us for the next giant leap, the exploration of Mars [1]. To champion technologies needed to live on and explore the Moon, NASA’s Space Technology Mission Directorate (STMD) established the Lunar Surface Innovation Initiative (LSII)[2].LSII's technology development portfolio includes: Utilizing the Moon’s resources; Establishing sustainable surface power; Building machinery and electronics that work in extreme environments, like super-chilly permanently shadowed craters; Mitigating lunar dust; Carrying out surface excavation, manufacturing and construction duties; and Extreme access which includes navigating and exploring the surface/subsurface. To support the development and testing of these technologies, LSII created the lunar simulant project, to create and/or acquire low-, medium-and high-fidelity lunar simulants to match the needs of STMD projects at all levels of technology readiness levels (TRL), as well as other NASA programs. There is not one bulk lunar simulant that will satisfy the needs of all projects. NASA's Approach to Simulants: Just as LSII's activities are being implemented through a combination of unique NASA work and public-private partnerships, NASA will work with commercial simulant providers to acquire simulants that meet NASA's needs. If warranted, NASA will develop simulants using government agencies, as was done with the NASA/USGS Lunar Highlands Type (NU-LHT)series of lunar simulants [3].NASA is also collaborating with the Johns Hopkins University Applied Physics Laboratory(JHUAPL) Lunar Surface Innovation Consortium (LSIC) in the development and characterization of lunar simulants [4]. Within NASA, a small team (< 10 people) is coordinating simulant activities across the agency, with team members located at several NASA centers. The overall objective of the project is to procure lunar simulants in sufficient amounts for earth-based testing of subsystems and systems in a variety of environments (i.e., laboratory, high-bay, thermal-vacuum chambers), required for Artemis missions to the Moon, as well as other missions carrying NASA lunar payloads, such as the Commercial Lunar Payload Services (CLPS)program [5]. Lunar Highlands Simulant: NASA's Artemis Program is targeting the lunar south pole region for initial human missions and the Artemis Base Camp. Hence, the LSII lunar simulant project is currently focusing on the mineralogy and properties of lunar highlands regolith [6 and 7]. Plagioclase-rich rocks (e.g., anorthosite, norite) are the dominant constituent in highlands simulants, with Shawmere, Stillwater, and White Mountain anorthosites being used in commercially available simulants. However, because these feedstocks are terrestrial in nature, they include hydrated minerals, carbon-bearing minerals, and other chemical signatures that are not present on the Moon, and these minor mineral assemblages need to be taken into account when trying to understand test procedures and results. Glass Component: While much attention has been placed on the rock/mineral component of lunar simulants, glass is just as important when creating simulants. The glass component in lunar regoliths is often greater than 50% by volume [8]. This component includes impact melt glass, dark matrix breccias, and agglutinates. However, this component is difficult, time-consuming and expensive to make. Most lunar simulants, past and current, have relied on basaltic cinder as a feedstock for glass. Getting better glass components at a lower cost, particularly agglutinates and glass with an anorthositic composition is a near-term objective that the NASA simulant project is trying to address . Characterization: It is extremely important for lunar simulants to be characterized by several analytical methods. Gruener et al. [9] and JHUAPL LSIC [10] conducted initial assessments of some of the commercially available simulants in 2019 and early 2020, before the global pandemic. Further analyses are needed to better quantify important parameters such as, modal mineralogy and glass content, particle shape, and particle size distribution. These quantified results can then be used in determining figures of merit (FOM) that show how well simulants compare to lunar regolith [11 and 12].

J E Gruener↗

Characterization of Machine Variability and Progressive Heat Treatment in Selective Laser Melting of Inconel 718

The absence of an economy of scale in spaceflight hardware makes additive manufacturing an immensely attractive option for propulsion components. As additive manufacturing techniques are increasingly adopted by government and industry to produce propulsion hardware in human-rated systems, significant development efforts are needed to establish these methods as reliable alternatives to conventional subtractive manufacturing. One of the critical challenges facing powder bed fusion techniques in this application is variability between machines used to perform builds. Even with implementation of robust process controls, it is possible for two machines operating at identical parameters with equivalent base materials to produce specimens with slightly different material properties. The machine variability study presented here evaluates 60 specimens of identical geometry built using the same parameters. 30 samples were produced on machine 1 (M1) and the other 30 samples were built on machine 2 (M2). Each of the 30-sample sets were further subdivided into three subsets (with 10 specimens in each subset) to assess the effect of progressive heat treatment on machine variability. The three categories for post-processing were: stress relief, stress relief followed by hot isostatic press (HIP), and stress relief followed by HIP followed by heat treatment per AMS 5664. Each specimen (a round, smooth tensile) was mechanically tested per ASTM E8. Two formal statistical techniques, hypothesis testing for equivalency of means and one-way analysis of variance (ANOVA), were applied to characterize the impact of machine variability and heat treatment on six material properties: tensile stress, yield stress, modulus of elasticity, fracture elongation, and reduction of area. This work represents the type of development effort that is critical as NASA, academia, and the industrial base work collaboratively to establish a path to certification for additively manufactured parts. For future flight programs, NASA and its commercial partners will procure parts from vendors who will use a diverse range of machines to produce parts and, as such, it is essential that the AM community develop a sound understanding of the degree to which machine variability impacts material properties.

Prater, T.↗

Characterization of Machine Variability and Progressive Heat Treatment in Selective Laser Melting of Inconel 718

The absence of an economy of scale in spaceflight hardware makes additive manufacturing an immensely attractive option for propulsion components. As additive manufacturing techniques are increasingly adopted by government and industry to produce propulsion hardware in human‐rated systems, significant development efforts are needed to establish these methods as reliable alternatives to conventional subtractive manufacturing. One of the critical challenges facing powder bed fusion techniques in this application is variability between machines used to perform builds. Even with implementation of robust process controls, it is possible for two machines operating at identical parameters with equivalent base materials to produce specimens with slightly different material properties. The machine variability study presented here evaluates 60 specimens of identical geometry built using the same parameters. 30 samples were produced on machine 1 (M1) and the other 30 samples were built on machine 2 (M2). Each of the 30‐sample sets were further subdivided into three subsets (with 10 specimens in each subset) to assess the effect of progressive heat treatment on machine variability. The three categories for post‐processing were: stress relief, stress relief followed by hot isostatic press (HIP), and stress relief followed by HIP followed by heat treatment per AMS 5664. Each specimen (a round, smooth tensile) was mechanically tested per ASTM E8. Two formal statistical techniques, hypothesis testing for equivalency of means and one‐way analysis of variance (ANOVA), were applied to characterize the impact of machine variability and heat treatment on six material properties: tensile stress, yield stress, modulus of elasticity, fracture elongation, and reduction of area. This work represents the type of development effort that is critical as NASA, academia, and the industrial base work collaboratively to establish a path to certification for additively manufactured parts. For future flight programs, NASA and its commercial partners will procure parts from vendors who will use a diverse range of machines to produce parts and, as such, it is essential that the AM community develop a sound understanding of the degree to which machine variability impacts material properties.

Prater, Tracie↗

Overview of NASA's Integrated Design and Engineering Analysis (IDEA)Environment

Historically, the design of subsonic and supersonic aircraft has been divided into separate technical disciplines (such as propulsion, aerodynamics and structures) each of which performs their design and analysis in relative isolation from others. This is possible in most cases either because the amount of interdisciplinary coupling is minimal or because the interactions can be treated as linear. The design of hypersonic airbreathing vehicles, like NASA s X-43, is quite the opposite. Such systems are dominated by strong non-linear interactions between disciplines. The design of these systems demands that a multi-disciplinary approach be taken. Furthermore, increased analytical fidelity at the conceptual design phase is highly desirable as many of the non-linearities are not captured by lower fidelity tools. Only when these systems are designed from a true multi-disciplinary perspective can the real performance benefits be achieved and complete vehicle systems be fielded. Toward this end, the Vehicle Analysis Branch at NASA Langley Research Center has been developing the Integrated Design & Engineering Analysis (IDEA) Environment. IDEA is a collaborative environment for parametrically modeling conceptual and preliminary launch vehicle configurations using the Adaptive Modeling Language (AML) as the underlying framework. The environment integrates geometry, configuration, propulsion, aerodynamics, aerothermodynamics, trajectory, closure and structural analysis into a generative, parametric, unified computational model where data is shared seamlessly between the different disciplines. Plans are also in place to incorporate life cycle analysis tools into the environment which will estimate vehicle operability, reliability and cost. IDEA is currently being funded by NASA s Hypersonics Project, a part of the Fundamental Aeronautics Program within the Aeronautics Research Mission Directorate. The environment is currently focused around a two-stage-to-orbit configuration with a turbine based combined cycle (TBCC) first stage and reusable rocket second stage. This paper provides an overview of the development of the IDEA environment, a description of the current status and detail of future plans.

Robinson, Jeffrey S.↗

Long-Term Time Series of Remote Sensing Observations for Development of Regulatory Water Quality Standards

Water quality standards in the U.S. consist of: designated uses (the services that a water body provides; e.g., drinking water, aquatic life, harvestable species, recreation) . criteria that define the environmental conditions that must be maintained to support the uses For estuaries and coastal waters in the Gulf of Mexico, there are no numeric (quantitative) criteria to protect designated uses from effects of nutrients. This is largely due to the absence of adequate data that would quantitatively link biological conditions to nutrient concentrations. The Gulf of Mexico Alliance, an organization fostering collaboration between the Gulf States and U.S. Federal agencies, has identified the development of the numeric nutrient criteria as a major step leading to reduction in MODIS Products Figure 6. Map of the Mobile Bay with a yellow patch indicating the Bon Secour Bay area selected in this study for averaging water clarity parameters retrieved from MODIS datasets. nutrient inputs to coastal ecosystems. Nutrient enrichment in estuaries and coastal waters can be quantified based on response variables that measure phytoplankton biomass and water clarity. Long-term, spatially and temporally resolved measurements of chlorophyll a concentration, total concentration of suspended solids, and water clarity are needed to establish reference conditions and to quantify stressor-response relationships.

Blonski, Slawomir↗

Open Science for Life in Space: Data Sharing and Tools for Knowledge Discovery

The fast-growing array of space biological data, which in the past was simply archived after minimal analysis, holds great potential if it can be reorganized and formatted for Open Science. Organizing the data for such analysis is a challenge because of its diverse nature (molecular, cellular, tissue, whole organism, behavior; tabular, imagery). Open Science is the concept that the more people have access to scientifically curated data, the more knowledge will be gained. This led NASA to start the development of GeneLab in 2015. GeneLab houses spaceflight and space-analog multi-omics datasets from plant, rodent, small animal, and microbial experiments. The success and knowledge gained from GeneLab led to a new alliance of NASA “Open Science Data Repositories” (OSDR), which include the Ames Life Sciences Data Archive (ALSDA) and the NASA Biological Institutional Scientific Collection (NBISC). Both are adopting the GeneLab data system, so data are more findable, accessible, interoperable, and reusable (FAIR). OSDR systems provide users the ability to upload, download, search, share, analyze, and visualize. Open Science also needs strong confidence in the data, which is gained through building science communities. With ~400 current members, GeneLab and ALSDA formed Analysis Working Groups (AWGs) to provide feedback on processing pipelines, metadata curation standards (for ‘omics and phenotypic-physiological-behavioral assays), and to collaborate in effectively reusing data. The AWG also led to the development of the Radiation Biology Ontology (RBO), ensuring radiation metadata are efficiently captured, connected, and interoperable. Feedback from the AWG provided design input toward the new single point-of-entry data submission portal for all investigators to submit, curate, and share their research data. Space biological data is now maximally open access, collected-curated with rich metadata, and formatted for interoperability to enable systems biology, meta-analysis, knowledge graphs, machine learning, modeling, and other reuse approaches. With potential for further federation of OSDR for data mining with traditional biological and medical databases (NIH, NCI, EBI, etc.), a new era for space biology has begun to support the knowledge discovery necessary for Lunar and Martian missions.

Ryan T Scott↗

The Iodine Satellite (iSAT) Hall Thruster Demonstration Mission Concept and Development

The use of iodine propellant for Hall thrusters has been studied and proposed by multiple organizations due to the potential mission benefits over xenon. In 2013, NASA Marshall Space Flight Center competitively selected a project for the maturation of an iodine flight operational feed system through the Technology Investment Program. Multiple partnerships and collaborations have allowed the team to expand the scope to include additional mission concept development and risk reduction to support a flight system demonstration, the iodine Satellite (iSAT). The iSAT project was initiated and is progressing towards a technology demonstration mission preliminary design review. The current status of the mission concept development and risk reduction efforts in support of this project is presented.

Dankanich, John W.↗

Chemical Mechanical Polishing of Silicon Carbide

The High Temperature Integrated Electronics and Sensors (HTIES) team at the NASA Lewis Research Center is developing silicon carbide (SiC) as an enabling electronic technology for many aerospace applications. The Lewis team is focusing on the chemical vapor deposition of the thin, single-crystal SiC films from which devices are fabricated. These films, which are deposited (i.e., epitaxially "grown") on commercial wafers, must consist of a single crystal with very few structural defects so that the derived devices perform satisfactorily and reliably. Working in collaboration (NASA grant) with Professor Pirouz of Case Western Reserve University, we developed a chemical-mechanical polishing (CMP) technique for removing the subsurface polishing damage prior to epitaxial growth of the single-crystal SiC films.

Powell, J. Anthony↗

[Development Of 25-Year Imp 8 Bow Shock Crossing "List, Ingestion Of This List To Cdaweb, & Enhancement"]

The MIT portion of this project was to use the plasma data from IMP 8 to identify bow shock crossings for construction of a bow shock data base. In collaboration with Goddard, we determined which shock parameters would be included in the catalog and developed a set of flags for characterizing the data. IMP 8 data from 1973-2001 were surveyed for bow shock crossings; the crossings apparent in the plasma data were compared to a list of crossing chosen in the magnetometer data by Goddard. Differences were reconciled to produce a single list. The data were then provided to the NSSDC for archiving. All the work ascribed to MIT in the proposal was completed.

Merka, J.↗