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At least 1,081 records · Page 60

A Versatile Click-Compatible Monolignol Probe to Study Lignin Deposition in Plant Cell Walls

Here, lignin plays important structural and functional roles in plants by forming a hydrophobic matrix in secondary cell walls that enhances mechanical strength and resists microbial decay. While the importance of the lignin matrix is well documented and the biosynthetic pathways for monolignols are known, the process by which lignin precursors or monolignols are transported and polymerized to form this matrix remains a subject of considerable debate. In this study, we have synthesized and tested an analog of coniferyl alcohol that has been modified to contain an ethynyl group at the C-3 position. This modification enables fluorescent tagging and imaging of this molecule after its incorporation into plant tissue by click chemistry-assisted covalent labeling with a fluorescent azide dye, and confers a distinct Raman signature that could be used for Raman imaging. We found that this monolignol analog is incorporated into in vitro -polymerized dehydrogenation polymer (DHP) lignin and into root epidermal cell walls of 4-day-old Arabidopsis seedlings. Incorporation of the analog in stem sections of 6-week-old Arabidopsis thaliana plants and labeling with an Alexa-594 azide dye revealed the precise locations of new lignin polymerization. Results from this study indicate that this molecule can provide high-resolution localization of lignification during plant cell wall maturation and lignin matrix assembly.

59 BASIC BIOLOGICAL SCIENCES↗

A Diagnostic Approach for Electro-Mechanical Actuators in Aerospace Systems

Electro-mechanical actuators (EMA) are finding increasing use in aerospace applications, especially with the trend towards all all-electric aircraft and spacecraft designs. However, electro-mechanical actuators still lack the knowledge base accumulated for other fielded actuator types, particularly with regard to fault detection and characterization. This paper presents a thorough analysis of some of the critical failure modes documented for EMAs and describes experiments conducted on detecting and isolating a subset of them. The list of failures has been prepared through an extensive Failure Modes and Criticality Analysis (FMECA) reference, literature review, and accessible industry experience. Methods for data acquisition and validation of algorithms on EMA test stands are described. A variety of condition indicators were developed that enabled detection, identification, and isolation among the various fault modes. A diagnostic algorithm based on an artificial neural network is shown to operate successfully using these condition indicators and furthermore, robustness of these diagnostic routines to sensor faults is demonstrated by showing their ability to distinguish between them and component failures. The paper concludes with a roadmap leading from this effort towards developing successful prognostic algorithms for electromechanical actuators.

Balaban, Edward↗

MAVEN Information Security Governance, Risk Management, and Compliance (GRC): Lessons Learned

As the first interplanetary mission managed by the NASA Goddard Space Flight Center, the Mars Atmosphere and Volatile EvolutioN (MAVEN) had three IT security goals for its ground system: COMPLIANCE, (IT) RISK REDUCTION, and COST REDUCTION. In a multiorganizational environment in which government, industry and academia work together in support of the ground system and mission operations, information security governance, risk management, and compliance (GRC) becomes a challenge as each component of the ground system has and follows its own set of IT security requirements. These requirements are not necessarily the same or even similar to each other's, making the auditing of the ground system security a challenging feat. A combination of standards-based information security management based on the National Institute of Standards and Technology (NIST) Risk Management Framework (RMF), due diligence by the Mission's leadership, and effective collaboration among all elements of the ground system enabled MAVEN to successfully meet NASA's requirements for IT security, and therefore meet Federal Information Security Management Act (FISMA) mandate on the Agency. Throughout the implementation of GRC on MAVEN during the early stages of the mission development, the Project faced many challenges some of which have been identified in this paper. The purpose of this paper is to document these challenges, and provide a brief analysis of the lessons MAVEN learned. The historical information documented herein, derived from an internal pre-launch lessons learned analysis, can be used by current and future missions and organizations implementing and auditing GRC.

FISMA↗

Planetary Science Technology Infusion Study: Findings and Recommendations Status

The Planetary Science Division (PSD) within the National Aeronautics and Space Administrations (NASA) Science Mission Directorate (SMD) at NASA Headquarters sought to understand how to better realize a scientific return on spacecraft system technology investments currently being funded. In order to achieve this objective, a team at NASA Glenn Research Center was tasked with surveying the science and mission communities to collect their insight on technology infusion and additionally sought inputs from industry, universities, and other organizations involved with proposing for future PSD missions. This survey was undertaken by issuing a Request for Information (RFI) activity that requested input from the proposing community on present technology infusion efforts. The Technology Infusion Study was initiated in March 2013 with the release of the RFI request. The evaluation team compiled and assessed this input in order to provide PSD with recommendations on how to effectively infuse new spacecraft systems technologies that it develops into future competed missions enabling increased scientific discoveries, lower mission cost, or both. This team is comprised of personnel from the Radioisotope Power Systems (RPS) Program and the In-Space Propulsion Technology (ISPT) Program staff.The RFI survey covered two aspects of technology infusion: 1) General Insight, including: their assessment of barriers to technology infusion as related to infusion approach; technology readiness; information and documentation products; communication; integration considerations; interaction with technology development areas; cost-capped mission areas; risk considerations; system level impacts and implementation; and mission pull. 2) Specific technologies from the most recent PSD Announcements of Opportunities (AOs): The Advanced Stirling Radioisotope Generator (ASRG), aerocapture and aeroshell hardware technologies, the NASA Evolutionary Xenon Thruster (NEXT) ion propulsion system, and the Advanced Materials Bi-propellant Rocket (AMBR) engine.This report will present the teams Findings from the RFI inputs and the recommendations that arose from these findings. Methodologies on the findings and recommendations development are discussed.

technology infusion↗

HSI in NASA: From Research to Implementation

As NASA plans to send human explorers beyond low Earth orbit, onward to Mars and other destinations in the solar system, there will be new challenges to address in terms of HSI. These exploration missions will be quite different from the current and past missions such as Apollo, Shuttle, and International Space Station. The exploration crew will be more autonomous from ground mission control with delayed, and at times, no communication. They will have limited to no resupply for much longer mission durations. Systems to deliver and support extended human habitation at these destinations are extremely complex and unique, presenting new opportunities to employ HSI practices. In order to have an effective and affordable HSI implementation, both research and programmatic efforts are required. Currently, the HSI-related research at NASA is primarily in the area of space human factors and habitability. The purpose is to provide human health and performance countermeasures, knowledge, technologies, and tools to enable safe, reliable, and productive human space exploration beyond low Earth orbit, and update standards, requirements, and processes to verify and validate these requirements. In addition, HSI teams are actively engaged in technology development and demonstration efforts to influence the mission architecture and next-generation vehicle design. Finally, appropriate HSI references have been added to NASA' s systems engineering documentation, and an HSI Practitioner's Guide has been published to help design engineers consider HSI early and continuously in the acquisition process. These current and planned HSI-related activities at NASA will be discussed in this panel.

Whitmore, Mihriban↗

Quarterly Management Document – FY17, 3rd Quarter, Physics-based Creep Simulations of Thick Section Welds in High Temperature and Pressure Applications

Progress on modeling the the creep of thick sections welds in Alloy 740H is reported. Climb of dislocations during creep has been added to the model. Creep testing is continuing and stress drop testing has been initiated to determine the threshold stress of this particle-strengthened alloy. Work has also begun on generating synthetic microstructures, representative of experimental microstructures, from data collected with EBSD. This will enable incorporation of experimental microstructures into the modeling and simulation effort.

36 MATERIALS SCIENCE↗

Documentation of program COORDC to generate and coordinate system for 3D corners with or without fillet using body fitted curvilinear coordinates, part 2

The computer program COORDC generates a body fitted curvilinear coordinate system for corner geometry with or without corner fillets. It is assumed that at any given xi, x remains constant; consequently the only variation is in y and z. It is also assumed that for all xi's in the physical plane the coordinate system in y-z plane is similar. This enables solution of coordinate system for one particular xi = 1 (x for xi = 1 is arbitrarily chosen to be 0.0) and the solution for all other xi plane can be easily specified once the coordinates in the physical plane on the line 1 or = to xi or = to IMAX, eta = 1, zeta = 1 are specified.

Kumar, D.↗

Advanced Distributed Wind Turbine Controls Series: Part 1-Flatirons Campus Model Overview – Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL)

Wind turbines are typically deployed to provide energy, reduce diesel-fuel consumption, reduce carbon emissions, and reduce costs for energy and fuel transportation. However, in addition to solely providing energy to the power system, wind turbines contain rotating masses and inverter-based controls that can enable various reliability and resilience services through advance controls. As part of the Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL), it is demonstrated that advanced wind turbine controls can be employed to support higher contributions of wind, and to demonstrate ways that wind can play a role in supporting grid stability in islanded or grid-connected configurations. This paper documents models of various subsystem comprising a portion of NREL's Flatirons campus that will be used in three subsequent reports to demonstrate capabilities of advanced wind turbine controls. The series of reports will detail advanced capabilities of distributed wind turbines to provide support to isolated grids, distribution grids, and microgrids. We developed models to simulate a wind turbine (600 kW), solar PV (430 kW), battery energy storage system (1 MW/1MWh), a diesel generator (2 MW) and various types of loads (critical, dynamic). The model of the subsystems in MATLAB/Simulink are validated with available data from real-world components on NREL's Flatirons Campus. These validated models can be configured for various studies including four MIRACL use cases: 1) isolated grids, 2) microgrids, and 3) behind-the-meter, and 4) front-of-the-meter wind turbine deployments.

17 WIND ENERGY↗

Assessment of the High Flux Isotope Reactor Cybersecurity Initiative

Recent cyber-attacks on industrial control systems, and inadvertent exposure of nuclear plant systems to cyber-exploits underscore the need for plant operators to adopt and deploy cyber-security defense solutions made for industrial control systems. Of increasing concern is the fact that international cyber hackers are beginning to target critical infrastructure, and because these more modern controls systems depend on advanced use of digital systems, they are more vulnerable than ever before to cyber-attacks. Traditional cyber defense strategies and products that have been available for decades are tailored for use on IT or corporate networks but can cause interruptions and catastrophic damage when deployed on industrial control system networks. The Department of Energy (DOE) Office of Nuclear Energy established the Gateway for Accelerated Innovation in Nuclear (GAIN) program to provide private companies pursuing innovative nuclear energy technologies with access to the technical support necessary to move toward commercialization. One of these GAIN small business vouchers was awarded to Dragos, Inc. to enable collaboration with Oak Ridge National Laboratory (ORNL) to evaluate the Dragos Platform on a production nuclear reactor test bed, hence laying the path for future commercial adoption. The vision was to provide a guide for industrial operators on implementing an industrial monitoring solution and to show how these solutions can be deployed without causing safety and reliability issues. This report documents the results of the collaboration between ORNL and Dragos, Inc.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

A Roadmap for a Lightning Modeling Grand Challenge

This document is a roadmap for building an interconnected model of the physical processes that produce a lightning discharge, and its observable optical and radio signals. We call this a Lightning Modeling Grand Challenge, recognizing that significant effort and coordination of human and financial resources is required to realize the capability. The roadmap serves to outline the coordination of resources necessary to enable stitching together existing knowledge and model components to make a lightning prediction, and to test these predictions with observations. Such a capability does not currently exist. The roadmap is motivated not only by a spirit of scientific inquiry, but by practical challenges faced by US Federal and societal stakeholders. Advancements in lightning observations have outpaced our tests of integrated understanding, leaving many stakeholders unsure how to design their missions to properly detect and discriminate lightning, and unsure how to apply the sometimes-disagreeing lightning signals from diverse instruments. The time is right to connect existing theories and models to support stakeholders in understanding the signals they observe, for needs as diverse as climate monitoring, national security, weather forecasting, public safety, and protection of natural and built environments. The roadmap’s two main technical sections describe the components of a linked physical model, followed by a description of models of lightning signals and sensors that are driven by outputs from the physical model. The goal is to predict the time-varying physical properties of lightning that are self-consistent with the thunderstorm’s structure and dynamics. These lightning signals then propagate through the storm, with realistic dispersion and attenuation, to receivers on the ground or in space. At a high level, the model begins with weather (cloud) model output, including explicit prediction of the electrification of cloud particles. The cloud’s electrical structure drives a model of lightning physics, from initiation, through channel development, and discharges along those channels. Key lightning parameters, such as the temperature and currents in the channel, and their space and time distribution, are then used to produce optical and electromagnetic signal sources that propagate to modeled receivers. This architecture therefore generates a dataset suitable for comparison to existing and envisioned observing systems. The need for additional measurements and field campaigns to support model development is described. In each model sub-component, inputs, outputs, uncertainties, evaluation methods, and next steps are summarized, interleaved with references to the scientific literature. Identifying boundaries between the model sub-components aids in segmenting an integrated, complex model into practical work packages and system sub-components, allowing a diverse team to contribute and maintain the system. We estimate that at least five years of effort and a $\$$10M initial investment is necessary to make a significant step forward. Mechanisms to facilitate community coordination, including annual workshops and open-source code repositories, are described.

54 ENVIRONMENTAL SCIENCES↗

Stirling engine design manual

This manual is intended to serve both as an introduction to Stirling engine analysis methods and as a key to the open literature on Stirling engines. Over 800 references are listed and these are cross referenced by date of publication, author and subject. Engine analysis is treated starting from elementary principles and working through cycles analysis. Analysis methodologies are classified as first, second or third order depending upon degree of complexity and probable application; first order for preliminary engine studies, second order for performance prediction and engine optimization, and third order for detailed hardware evaluation and engine research. A few comparisons between theory and experiment are made. A second order design procedure is documented step by step with calculation sheets and a worked out example to follow. Current high power engines are briefly described and a directory of companies and individuals who are active in Stirling engine development is included. Much remains to be done. Some of the more complicated and potentially very useful design procedures are now only referred to. Future support will enable a more thorough job of comparing all available design procedures against experimental data which should soon be available.

Martini, W. R.↗

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.

Exploration medical system↗

Multi-Source Machine Learning and Thermoplastics Enhanced Aerostructure Manufacturing (mTEAM)

RTX Technology Research Center (RTRC), together with Collins Aerospace (Collins) and Oak Ridge National Laboratory (ORNL) has developed an Artificial Intelligence (AI) / Machine Learning (ML) guided solution to advance the manufacturing and assembly of high performance and lightweight thermoplastic composite (TPC) aerospace products. The solution aims to lower risk, cost and lead time for induction heating based welding and consolidation processes for TPC structure. The cost and lead time of part and material specific process development for induction welding (IW) and induction consolidation will be reduced by replacing traditional empirical methods with optimization methods that merge AI/ML and physics-based process simulations and process experiments with sensing and controls. TPC-IW process development is empirical in nature, and uncertainties in material & process behavior exist near & far from the induction coil. Physics-based simulations can be leveraged directly for process optimization but can be too computationally expensive to run in high fidelity and real time to do robust process optimization. The key impact of successful TPC induction consolidation and welding is cost & lead time reduction for part & material specific consolidation and welding recipes. This is an enabler for more rapid deployment of TPC structures via joining assembly, which can reduce energy & cost intensive usage of autoclaves & ovens. The solution aimed to advance the U.S. Department of Energy’s interests in using thermoplastics and automation in composite manufacturing for improvement of products for existing markets via increased production speeds, reduced costs, and lowered use of energy. Welded TPC structures can offer significant weight & energy savings for high-value commercial aerospace & industrial applications compared to metal & thermoset composite structures assembled by mechanical fastening and/or adhesive bonding. The project was organized into two Budget Periods. Budget Period 1 (BP1) was 15 months and its goal was to perform ML process optimization framework development & deployment on lab-coupon aerostructure components. A Go/No-Go Review was performed at the end of BP1 to verify fulfilment of key tasks & milestones to justify a Go Decision to move into the next Budget Period. Budget Period 2 (BP2) was 12 months and its goal was the deployment of the ML framework for ML process optimization of pilot industrial scale aerostructure components. The overall project aim was to develop & demonstrate ML-enhanced modeling framework that learns process-property mapping from multiple data sources at different fidelities. During BP1, the team accomplished key tasks & milestones to demonstrate the concept of multi-source ML for TPC aerostructure consolidation and assembly. First, the team completed documentation of induction based TPC heating requirements including baseline metrics to compare measured results against. Next the team completed demonstration of data generation from physics-based simulations for ML surrogate model generation and demonstrated the integration of physics-based simulation data into multi-source AI/ML algorithms. In parallel, the team established the lab-coupon scale induction welding system and completed a process to label and reduce generated data from physics-based simulation and experiments for ML surrogate models to enable multi-source ML model training & testing. To complete BP1, the team integrated physics-based simulation data and experimental data into multi-source ML algorithms. This was based on the team completing ML deployment of the induction welding on a lab system at RTRC and AI/ML deployment on existing induction welding line at Collins. ORNL visited both Collins and RTRC sites to witness the TPC induction welding process. Then, ORNL designed and constructed a new version of their vision-based sensing system better adapted to acquire process signals of the TPC induction welding process for process anomaly and defect detection. In BP2, the team accomplished key tasks & milestones to scale up multi-source ML for TPC aerostructure consolidation and assembly from the lab-coupon scale to the pilot-industrial scale. In BP2, the team demonstrated real time anomaly & defect detection via experiments performed by ORNL & RTRC. The team completed ML-optimization heating trials for TPC induction consolidation at Collins, and the team confirmed pilot industrial scale experimental data from Collins was compatible with the developed ML pipeline from RTRC. The team completed sub-element scale ML process optimization demonstration at RTRC, where the team leveraged RTRC’s robotic TPC welding setup to de-risk the ML process optimization by performing ML analysis of recorded temperatures to account for complex part features. Then, the team applied its ML-derived control strategies and ML process optimization framework at Collins to the pilot-industrial scale on a demo skin-stiffener part representative of a nacelle aerostructure fan cowl section. The key innovation is the AI/ML framework enabling effective process development of high performance, lightweight, energy efficient TPCs for composite aircraft structures.

36 MATERIALS SCIENCE↗

A Systems Biology Approach to Energy Flow in H 2 Producing Microbial Communities: Microbial Mats

This report describes the results of work conducted at NASA Ames Research Center, in collaboration with investigators at Lawrence Livermore National Laboratory, during the time period 12/15/2014 to 12/15/2017. The work was an extension of a collaboration with LLNL that began in 2008. Work this reporting period focused primarily on tasks related to microbial mats from both the Elkhorn Slough and Baja California field sites, including the analysis and publication of data produced prior to 12/15/2014. During this reporting period, in addition to the microbial mat work, we also conducted a series of experiments with a particular algal-bacterial association (C. sorokiniana and A. brasilense). A number of aspects of this well-characterized algal-bacterial association enabled us not only to further our understanding of interactions between these particular organisms, but to apply that knowledge and techniques to our collection of microorganisms isolated from microbial mats. Microbial mat experiments focused both on intact mat communities and on cultures of organisms isolated from the mats (the Microbial Mat Living Library). In a series of co-culture experiments, we documented both positive and negative interactions amongst heterotrophic and autotrophic isolates of microbial mat microorganisms. One particularly important and novel mat cyanobacterium (ESFC-1) was studied in detail. We developed techniques to pursue an investigation of functional redundancy (the idea that closely related organisms perform identical roles in a community) in cyanobacterial autotrophs in the Elkhorn Slough microbial mat. In those experiments, we documented numerous instances of increases in growth rate between co-cultures of two organisms (relative to their growth rate in isolation) performing what would seem to be identical functional roles. Simplified microbial mat communities consisting of organisms from the Microbial Mat Living Library were constructed and studied in laboratory experiments. The “constructed mats” were grown in standard laboratory glassware and plasticware, but cultures were also combined with artificial materials in an effort to re-create the three-dimensional structure of naturally occurring microbial mats. These constructed mats re-created a number of functions attributable to natural microbial mats (N-fixation, H2-production) and simplified their study using molecular ecological techniques due to the smaller number of microbial “species” present. Cyanobacteria which migrated in response to vertical variations in light intensity (irradiance) obtained characteristic positions in constructed mats that were similar to their positions in natural mats. A detailed investigation of nitrogen cycling in both the Baja California and Elkhorn Slough microbial mats was initiated during this reporting period. The nitrogen cycle in the microbial mats has not been studied in depth, despite the fact that nitrogen usually limits growth in marine environments. The organisms conducting nitrogen cycling in both microbial mats were studied using the genomes available from earlier work on these mats, as well as with a targeted approach using molecular ecological methods developed here. Quantitative measurements of rates of nitrogen transformations were made using stable isotopically labeled nitrogen. The processes quantified and examined using molecular ecological methods included: nitrogen fixation, ammonification, ammonium and nitrate assimilation, denitrification, anaerobic oxidation of ammonium, and dissimilatory nitrate reduction to ammonium. In a series of experiments designed to examine a potential application for microbial mats, we demonstrated that both Elkhorn Slough and Baja California microbial mats were very effective in removing large quantities of both nitrate and ammonium from waste streams containing these compounds at levels where they would be considered to be pollutants. Considerable effort was expended during this reporting period to analyze, and prepare for publication, metagenomes and metatranscriptomes collected from two experimental manipulations of microbial mats. The first, a diel study, was conducted in November 2011, while the second, an investigation of the effects of sulfate on community composition, was conducted during this reporting period. For the earlier study, reference-based and reference-free methods were used to assess microbial ecology and genetic partitioning in these complex microbial systems, and that work is available as a pre-print. Four metagenomes from the same experiment were published. In the second, longer (nearly 200 day) manipulation, rRNA iTag libraries for cDNA and DNA were analyzed to determine the effects of sulfate concentration on microbial mat community composition over the course of the experiment. Work on the algal-bacterial association (Chlorella sorokiniana and Azospirillum brasilense) focused initially on demonstrating the transfer of carbon and nitrogen between the partners, using stable isotopic labeling and the LLNL NanoSIMS. Subsequently, the potential role of diazotrophy (nitrogen fixation) by the bacterial partner in supporting the growth of the association was assessed in a series of experiments. It appears to be the case that, although the bacterial partner demonstrably increases the fitness of the algae under nitrogen limitation, and cells of C. sorokiniana receive nitrogen originally fixed from atmospheric nitrogen by A. brasilense, the amount of nitrogen obtained by diazotrophy is too small to explain the increase in fitness.

08 HYDROGEN↗

High-order algorithmic developments and optimizations for large-scale GPU-accelerated simulations (Milestone CEED-MS36)

The goal of this milestone was to improve the high-order software ecosystem for CEED-enabled ECP applications by making progress on efficient matrix-free kernels targeting forthcoming ECP architectures. These kernels included matrix-free preconditioning and the development of new set of CEED solver bake-off problems. As part of this milestone, we also released the next version of the CEED software stack, CEED-4.0, reported on results from several application collaborations, and documented the efforts of porting to AMD GPUs for Frontier and other modern architectures, such as Fugaku. The specific tasks addressed in this milestone were: (1) Port and run CEED benchmarks/miniapps on Frontier EA systems; (2) Demonstrate performant libCEED integration in MFEM, Nek and applications; (3) Matrix-free preconditioning of high-order operators; (4) Benchmark problems for fast high-order solvers on GPU platforms; and (5) Public release of CEED-4.0. The artifacts delivered include the next version of the CEED software stack, CEED-4.0, the next libCEED release, libCEED-0.8, and a number of developments integrated within applications to improve their GPU and CPU performance and capabilities. See the CEED website, https://ceed.exascaleproject.org and the CEED GitHub organization, https://github.com/ceed for more details.

97 MATHEMATICS AND COMPUTING↗

Shuttle Shaping Up

Measures to sharply curtail ana document potentially fatal launch debris similar to that which doomed Columbia and her crew should allow the space shuttle to resume flights as early as May. But it could take up to two years before a fully certified thermal protection system and wing leading edge in-orbit repair capability is ready, shuttle managers say. The overall positive safety tradeoffs, however, are enabling return-to-flight preparations to accelerate this month toward making a serious run at launching the shuttle back to space by spring.

Covault, Craig↗

Model Output Is Data, Too: And Other Futuristic Views

The NASA space science data environment has been undergoing significant changes during the past decade: Data has become significantly more voluminous and more varied. At the same time it became much more openly available to the scientific community. As a result a number of efforts have been made to document the data content at NSSDC/SPDF, PDS, the ISTP program and more recently as part of the newly developing Virtual Observatories. Concurrently, our need to access data has become much more immediate dictating a distributed environment where users can obtain their data directly from the production sites. But where does this change lead? And what more needs to be done to further enable scientific productivity? A view of our data system 5- years in the future will be offered that envisions distributed data processing services whereby the user can obtain the type of data that is needed not necessarily what is produced. Moreover, in an ideal system the means should exist to treat models as instruments allowing the ready mixing of their output with spacecraft generated data.

Szabo, A.↗

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↗