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ExMC Digital Engineering

Future missions beyond Artemis II will become increasingly complex as multiple vehicles (e.g., Gateway, Human Landing System (HLS), and Extravehicular Activity and Human Surface Mobility Program (EHP)), each having their own Program requirements and other associated documentation, which will need to be integrated into a single mission. Currently, the Human Health and Performance Directorate (HHPD)Program Support Teams mostly use documents to manage, perform, and archive their analyses. Identifying an opportunity for efficiency, ExMC demonstrated the ability to utilize MagicDraw, a Model-Based Systems Engineering (MBSE) tool, as a requirements database with traceability, dependencies, and relationships in one place. Rather than existing in documents, emails, and historical knowledge, ExMC pursued a Digital Engineering (DE) effort in coordination with HHPD by combining MBSE tools with other digital platforms to manage and develop user-defined databases and interfaces. This DE approach is aimed to simplify processes and reduce risk through the unification of requirements into a centralized digital network, improving collaboration, decision-making, and transparency compared to isolated documents and knowledge. However, manipulating data views and content in MagicDraw requires a steep learning curve not needed by all users and even the user-friendly web view comes with downsides due to the static views. To provide a more dynamic user interface, ExMC investigated the use of Microsoft Power Platform which does not require as steep of a learning curve to become proficient. This introduces analytics to the DE infrastructure, offering customizable and dynamic data dashboards. ExMC continues developing these dashboards and tailoring the DE infrastructure in alignment with HHPD workforce needs.

M Krihak↗

Large-scale variations in ozone and polar stratospheric clouds measured with airborne lidar during formation of the 1987 ozone hole over Antarctica

A joint field experiment between NASA and NOAA was conducted during August to September 1987 to obtain in situ and remote measurements of key gases and aerosols from aircraft platforms during the formation of the ozone (O3) hole over Antarctica. The ER-2 (advanced U-2) and DC-8 aircraft from the NASA Ames Research Center were used in this field experiment. The NASA Langley Research Center's airborne differential absorption lidar (DIAL) system was operated from the DC-8 to obtain profiles of O3 and polar stratospheric clouds in the lower stratosphere during long-range flights over Antarctica from August 28 to September 29, 1987. The airborne DIAL system was configured to transmit simultaneously four laser wavelengths (301, 311, 622, and 1064 nm) above the DC-8 for DIAL measurements of O3 profiles between 11 to 20 km ASL (geometric altitude above sea level) and multiple wavelength aerosol backscatter measurements between 11 to 24 km ASL. A total of 13 DC-8 flights were made over Antarctica with 2 flights reaching the South Pole. Polar stratospheric clouds (PSC's) were detected in multiple thin layers in the 11 to 21 km ASL altitude range with each layer having a typical thickness of less than 1 km. Two types of PSC's were found based on aerosol backscattering ratios: predominantly water ice clouds (type 2) and clouds with scattering characteristics consistent with binary solid nitric acid/water clouds (type 1). Large-scale cross sections of O3 distributions were obtained. The data provides additional information about a potentially important transport mechanism that may influence the O3 budget inside the vortex. There is also some evidence that strong low pressure systems in the troposphere are associated with regions of lower stratospheric O3. This paper discusses the spatial and temporal variations of O3 inside and outside the polar vortex region during the development of the O3 hole and relates these data to other measurements obtained during this field experiment.

Browell, Edward V.↗

Advanced Hybrid Spacesuit Concept Featuring Integrated Open Loop and Closed Loop Ventilation Systems

A document discusses the design and prototype of an advanced spacesuit concept that integrates the capability to function seamlessly with multiple ventilation system approaches. Traditionally, spacesuits are designed to operate both dependently and independently of a host vehicle environment control and life support system (ECLSS). Spacesuits that operate independent of vehicle-provided ECLSS services must do so with equipment selfcontained within or on the spacesuit. Suits that are dependent on vehicle-provided consumables must remain physically connected to and integrated with the vehicle to operate properly. This innovation is the design and prototype of a hybrid spacesuit approach that configures the spacesuit to seamlessly interface and integrate with either type of vehicular systems, while still maintaining the ability to function completely independent of the vehicle. An existing Advanced Crew Escape Suit (ACES) was utilized as the platform from which to develop the innovation. The ACES was retrofitted with selected components and one-off items to achieve the objective. The ventilation system concept was developed and prototyped/retrofitted to an existing ACES. Components were selected to provide suit connectors, hoses/umbilicals, internal breathing system ducting/ conduits, etc. The concept utilizes a lowpressure- drop, high-flow ventilation system that serves as a conduit from the vehicle supply into the suit, up through a neck seal, into the breathing helmet cavity, back down through the neck seal, out of the suit, and returned to the vehicle. The concept also utilizes a modified demand-based breathing system configured to function seamlessly with the low-pressure-drop closed-loop ventilation system.

Daniel, Brian A.↗

Collaborative WorkBench for Researchers - Work Smarter, Not Harder

It is important to define some commonly used terminology related to collaboration to facilitate clarity in later discussions. We define provisioning as infrastructure capabilities such as computation, storage, data, and tools provided by some agency or similarly trusted institution. Sharing is defined as the process of exchanging data, programs, and knowledge among individuals (often strangers) and groups. Collaboration is a specialized case of sharing. In collaboration, sharing with others (usually known colleagues) is done in pursuit of a common scientific goal or objective. Collaboration entails more dynamic and frequent interactions and can occur at different speeds. Synchronous collaboration occurs in real time such as editing a shared document on the fly, chatting, video conference, etc., and typically requires a peer-to-peer connection. Asynchronous collaboration is episodic in nature based on a push-pull model. Examples of asynchronous collaboration include email exchanges, blogging, repositories, etc. The purpose of a workbench is to provide a customizable framework for different applications. Since the workbench will be common to all the customized tools, it promotes building modular functionality that can be used and reused by multiple tools. The objective of our Collaborative Workbench (CWB) is thus to create such an open and extensible framework for the Earth Science community via a set of plug-ins. Our CWB is based on the Eclipse [2] Integrated Development Environment (IDE), which is designed as a small kernel containing a plug-in loader for hundreds of plug-ins. The kernel itself is an implementation of a known specification to provide an environment for the plug-ins to execute. This design enables modularity, where discrete chunks of functionality can be reused to build new applications. The minimal set of plug-ins necessary to create a client application is called the Eclipse Rich Client Platform (RCP) [3]; The Eclipse RCP also supports thousands of community-contributed plug-ins, making it a popular development platform for many diverse applications including the Science Activity Planner developed at JPL for the Mars rovers [4] and the scientific experiment tool Gumtree [5]. By leveraging the Eclipse RCP to provide an open, extensible framework, a CWB supports customizations via plug-ins to build rich user applications specific for Earth Science. More importantly, CWB plug-ins can be used by existing science tools built off Eclipse such as IDL or PyDev to provide seamless collaboration functionalities.

Ramachandran, Rahul↗

BioNutrients-2: Improvements to the BioNutrients-1 Nutrient Production System

The BioNutrients (BN) project aims to develop an on-demand biological production system capable of rapid and safe delivery of multiple nutrients in single-use production packs for long-duration missions. The general concept of this system is to develop edible engineered microorganisms that produce nutrients for human consumption following long-term storage, revival, and growth. BN-1 is a five-year flight project currently on the International Space Station (ISS). It is testing the long-term storage of various microorganisms for the biomanufacturing of space-relevant compounds and validating the performance of the first generation of production packs. The BN-2 project expands the BN-1 flight project scope by introducing novel products, broadening the range of microbial food sources, and improving upon production pack hardware. We are optimizing the biomanufacturing platform for in situ production of yogurt and kefir on the ISS. BN-2 also will test engineered microorganisms, including a probiotic strain, to produce carotenoids or follistatin. To improve the feasibility of this technology for mission use, we transitioned from a hard-shell pack to a second-generation fluorinated ethylene propylene (FEP) bag. The single-use FEP bioreactor facilitates growth of target organisms in a contaminant free environment, while reducing mass and volume compared to the BN-1 hardware. These bioreactors will be employed for production of additional space-relevant products in the BN-2 project. On-orbit testing of FEP production packs will enable optimization of the platform for eventual flight use by the crew.

Natalie Ball↗

Crowd Sourcing for Challenging Technical Problems and Business Model

Crowd sourcing may be defined as the act of outsourcing tasks that are traditionally performed by an employee or contractor to an undefined, generally large group of people or community (a crowd) in the form of an open call. The open call may be issued by an organization wishing to find a solution to a particular problem or complete a task, or by an open innovation service provider on behalf of that organization. In 2008, the Space Life Sciences Directorate (SLSD), with the support of Wyle Integrated Science and Engineering, established and implemented pilot projects in open innovation (crowd sourcing) to determine if these new internet-based platforms could indeed find solutions to difficult technical challenges. These unsolved technical problems were converted to problem statements, also called "Challenges" or "Technical Needs" by the various open innovation service providers, and were then posted externally to seek solutions. In addition, an open call was issued internally to NASA employees Agency wide (10 Field Centers and NASA HQ) using an open innovation service provider crowd sourcing platform to post NASA challenges from each Center for the others to propose solutions). From 2008 to 2010, the SLSD issued 34 challenges, 14 externally and 20 internally. The 14 external problems or challenges were posted through three different vendors: InnoCentive, Yet2.com and TopCoder. The 20 internal challenges were conducted using the InnoCentive crowd sourcing platform designed for internal use by an organization. This platform was customized for NASA use and promoted as NASA@Work. The results were significant. Of the seven InnoCentive external challenges, two full and five partial awards were made in complex technical areas such as predicting solar flares and long-duration food packaging. Similarly, the TopCoder challenge yielded an optimization algorithm for designing a lunar medical kit. The Yet2.com challenges yielded many new industry and academic contacts in bone imaging, microbial detection and even the use of pharmaceuticals for radiation protection. The internal challenges through NASA@Work drew over 6000 participants across all NASA centers. Challenges conducted by each NASA center elicited ideas and solutions from several other NASA centers and demonstrated rapid and efficient participation from employees at multiple centers to contribute to problem solving. Finally, on January 19, 2011, the SLSD conducted a workshop on open collaboration and innovation strategies and best practices through the newly established NASA Human Health and Performance Center (NHHPC). Initial projects will be described leading to a new business model for SLSD.

Davis, Jeffrey R.↗

Machine Learning-Based Atmospheric Phenomena Detection Platform

As the number of Earth pointing satellites has increased over the last several decades, the data volume retrieved from instruments onboard these satellites has also increased. It is expected that this trend will continue as more data intensive missions and small satellite constellations are launched. Currently, feature detection - namely atmospheric phenomena - in these datasets is performed manually and is thus not scalable with the growing data archives. Recent advancements in computational efficiency allow for the Earth science community to leverage machine learning to identify interesting atmospheric phenomena. Given the wide range of distinctive features in various atmospheric phenomena, a specialized machine learning model is required for accurate detection of these phenomena independently. The Phenomena Portal, developed at NASA IMPACT, is designed to provide visualization for the output from these machine learning models. In addition, detected events for each atmospheric phenomena are stored in a database that can be used to more easily use/subset larger spatiotemporal datasets. The user interface also incorporates additional features to enhance the user experience including spatiotemporal analysis, multiple base layer images, and a slider to filter events with lower probabilities of positive detection. Each detection supports user feedback on whether the detection is true or false that can then be stored and used to improve the machine learning model performance.

Gurung, Iksha↗

An Overview of SIMBIOS Project Activities and Accomplishments During FY00

In FY00, the Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project brought a number of activities to fruition and laid the groundwork for new initiatives in FY01 of particular importance was ensuring that the SIMBIOS program was renewed and a new science team selected in FY00. With Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) continuing to perform well, the Terra platform and Moderate Resolution Imaging Spectroradiometer (MODIS) being launched in December 1999, and several other global missions scheduled for launch (e.g., the Aqua platform with a second MODIS (2001), the ENVISAT mission with the Medium Resolution Imaging Spectrometer (2001), and Advanced Earth Observing Satellite-2 with GLI and Polarization and Directionality of the Earth's Reflectances (POLDER)), the first real opportunities to merge global data sets can be pursued. NASA Headquarters did approve a three-year continuation of the science team under an NASA Research Announcement (NRA) and the Project Office. As it is taking some time for the MODIS team to work through the initial on-orbit processing issues, merger activities within the Project Office have been a low priority with most of the emphasis being on other program objectives which will provide a broader foundation and capabilities for working with multiple global data sets in the future. These activities and accomplishments are described.

Fargion, Giulietta S.↗

In Situ Chemical Reduction Interim Measures Work Plan Hot Spot 3 Mobile Launcher Platform Rehabilitation Sites / Vehicle Assembly Building Area (SWMU 056) Kennedy Space Center, Florida

This document presents the design details of an In Situ Chemical Reduction (ISCR) Interim Measures Work Plan for Hot Spot 3 within Mobile Launcher Platform Rehabilitation Sites/Vehicle Assembly Building Area, Solid Waste Management Unit (SWMU) 056 (SWMU 056), located at the John F. Kennedy Space Center, Florida. The interim measures (IM) treatment zone encompasses an area identified as the High Concentration Plume (HCP), which is defined as the area with chlorinated volatile organic compound (CVOC) groundwater concentrations greater than their respective Natural Attenuation Default Concentration (NADC). The objective of the IM is to remove CVOC mass within the treatment area to levels that facilitate a transition to natural attenuation monitoring. The IM design consists of the selected ISCR amendment, Provect-IR, which is a mixture of solid reagents in a single product that promotes enhanced reductive dechlorination and ISCR. ProvectIR includes natural antimethanogenic compounds; multiple hydrophilic, nutrient-rich organic carbon sources; zero valent iron; chemical oxygen scavengers; and vitamin and mineral sources. The proposed treatment area for this IM encompasses less than 1 acre and includes three vertical treatment intervals to reach the NADC plumes that vary per CVOC and depth: 4 to 10 feet below land surface (bls), 10 to 18 feet bls, and 42 to 52 feet bls. The amendment will be distributed through 16 injection points (IP01 through IP16) using dosing rates ranging from 0.4% to 0.6% of soil mass within the treatment interval and a 15% or 20% slurry strength. Dosage rates and slurry strength are based on groundwater geochemistry, soil characteristics, and contaminant concentrations. To aid in the evaluation of the ISCR IM performance, six performance monitoring wells will be installed following injections and sampled semiannually. CVOC parameters will be sampled until concentrations reduce to below their NADC. Underground Injection Control parameters will be sampled until concentrations decrease to background levels or to levels that meet respective groundwater standards. Sampling frequency will be evaluated annually and modified as needed. The path forward for the ISCR IM implementation includes preparing the IM Implementation Work Plan, ISCR injections, monitoring well installation, performance monitoring, and reporting.

Randall K. Sillan↗

Supporting Global Air Quality Management Needs With A Flexible Data Fusion Tool for Estimation and Forecasting in Google Earth Engine

High spatial and temporal resolution air quality estimation and forecasting can be enhanced by combining global data sources, like chemical transport models and satellite remote sensing, with local information from regulatory and low-cost air quality monitors. Successful integration of data from these diverse sources is complicated by many factors, however, including differences in spatial and temporal resolution, data availability and latency issues, varying data quality, and large computational and data storage requirements. This presentation will provide an overview of a NASA-funded effort to develop the foundation for future operationalization of air quality forecasting for world-wide end-users and integration into their air quality management decision processes, which will be achieved in future phases of this multi-year project. We will summarize our progress in developing a data fusion system using the Google Earth Engine platform which can integrate model, satellite, and surface-level monitoring datasets to enhance estimation and forecasting of air-quality-relevant pollutants at sub-daily and sub-city scales. The tool is being developed in close cooperation with several city- and regional-level air quality managers in the USA and around the world. Our end-goal is to provide these air quality managers with the information they need to assess and anticipate the impacts of poor air quality, track changes in air quality due to ongoing mitigation efforts and land use changes, and identify ways to improve their air quality monitoring strategies. This presentation will focus on recent advances achieved through the project, including integration of multiple air quality datasets in a prototype data fusion system in Google Earth Engine, the quantification of uncertainties associated with our data fusion approach, and the development of user interfaces and visualization tools to convey air quality information in a way which best meets end-user needs.

Carl Malings↗

Supporting Global Air Quality Management Needs With A Flexible Data Fusion Tool for Estimation and Forecasting in Google Earth Engine

High spatial and temporal resolution air quality estimation and forecasting can be enhanced by combining global data sources, like chemical transport models and satellite remote sensing, with local information from regulatory and low-cost air quality monitors. Successful integration of data from these diverse sources is complicated by many factors, however, including differences in spatial and temporal resolution, data availability and latency issues, varying data quality, and large computational and data storage requirements. This presentation will provide an overview of a NASA-funded effort to develop the foundation for future operationalization of air quality forecasting for world-wide end-users and integration into their air quality management decision processes, which will be achieved in future phases of this multi-year project. We will summarize our progress in developing a data fusion system using the Google Earth Engine platform which can integrate model, satellite, and surface-level monitoring datasets to enhance estimation and forecasting of air-quality-relevant pollutants at sub-daily and sub-city scales. The tool is being developed in close cooperation with several city- and regional-level air quality managers in the USA and around the world. Our end-goal is to provide these air quality managers with the information they need to assess and anticipate the impacts of poor air quality, track changes in air quality due to ongoing mitigation efforts and land use changes, and identify ways to improve their air quality monitoring strategies. This presentation will focus on recent advances achieved through the project, including integration of multiple air quality datasets in a prototype data fusion system in Google Earth Engine, the quantification of uncertainties associated with our data fusion approach, and the development of user interfaces and visualization tools to convey air quality information in a way which best meets end-user needs.

Carl Malings↗

Parallelization of the Physical-Space Statistical Analysis System (PSAS)

Atmospheric data assimilation is a method of combining observations with model forecasts to produce a more accurate description of the atmosphere than the observations or forecast alone can provide. Data assimilation plays an increasingly important role in the study of climate and atmospheric chemistry. The NASA Data Assimilation Office (DAO) has developed the Goddard Earth Observing System Data Assimilation System (GEOS DAS) to create assimilated datasets. The core computational components of the GEOS DAS include the GEOS General Circulation Model (GCM) and the Physical-space Statistical Analysis System (PSAS). The need for timely validation of scientific enhancements to the data assimilation system poses computational demands that are best met by distributed parallel software. PSAS is implemented in Fortran 90 using object-based design principles. The analysis portions of the code solve two equations. The first of these is the "innovation" equation, which is solved on the unstructured observation grid using a preconditioned conjugate gradient (CG) method. The "analysis" equation is a transformation from the observation grid back to a structured grid, and is solved by a direct matrix-vector multiplication. Use of a factored-operator formulation reduces the computational complexity of both the CG solver and the matrix-vector multiplication, rendering the matrix-vector multiplications as a successive product of operators on a vector. Sparsity is introduced to these operators by partitioning the observations using an icosahedral decomposition scheme. PSAS builds a large (approx. 128MB) run-time database of parameters used in the calculation of these operators. Implementing a message passing parallel computing paradigm into an existing yet developing computational system as complex as PSAS is nontrivial. One of the technical challenges is balancing the requirements for computational reproducibility with the need for high performance. The problem of computational reproducibility is well known in the parallel computing community. It is a requirement that the parallel code perform calculations in a fashion that will yield identical results on different configurations of processing elements on the same platform. In some cases this problem can be solved by sacrificing performance. Meeting this requirement and still achieving high performance is very difficult. Topics to be discussed include: current PSAS design and parallelization strategy; reproducibility issues; load balance vs. database memory demands, possible solutions to these problems.

Larson, J. W.↗

Nano-Satellite Avionics

Abstract NASA's Goddard Space Flight Center (GSFC) is currently developing a new class of satellites called the nano-satellite (nano-sat). A major objective of this development effort is to provide the technology required to enable a constellation of tens to hundreds of nano-satellites to make both remote and in-situ measurements from space. The Nano-sat will be a spacecraft weighing a maximum of 10 kg, including the propellant mass, and producing at least 5 Watts of power to operate the spacecraft. The electronics are required to survive a total radiation dose rate of 100 krads for a mission lifetime of two years. There are many unique challenges that must be met in order to develop the avionics for such a spacecraft. The first challenge is to develop an architecture that will operate on the allotted 5 Watts and meet the diverging requirements of multiple missions. This architecture will need to incorporate a multitude of new advanced microelectronic technologies. The microelectronics developed must be a modular and scalable packaging of technology to solve the problem of developing a solution to both reduce cost and meet the requirements of various missions. This development will utilize the most cost effective approach, whether infusing commercially driven semiconductor devices into spacecraft applications or partnering with industry to design and develop low cost, low power, low mass, and high capacity data processing devices. This paper will discuss the nano-sat architecture and the major technologies that will be developed. The major technologies that will be covered include: (1) Light weight Low Power Electronics Packaging, (2) Radiation Hard/Tolerant, Low Power Processing Platforms, (3) High capacity Low Power Memory Systems (4) Radiation Hard reconfiguragble field programmable gate array (rFPGA)

Culver, Harry↗

Planning and Execution for Front Delineation and Tracking with Multiple Underwater Vehicles

This work describes a planning architecture for a heterogeneous fleet of marine assets as well as a method for detecting and tracking ocean fronts using multiple autonomous underwater vehicles. Multiple vehicles — equally-spaced along the expected frontal boundary — complete near parallel transects orthogonal to the front. Lateral gradients are used to determine the location of the front crossing from each individual vehicle transect by detecting a change in the observed water property. Adaptive control of the vehicles ensure they remain perpendicular to the estimated frontal boundary as it evolves over time. This method was demonstrated in several experiment periods totaling weeks, in and around Monterey Bay, California in May and June of 2017. We discuss the challenges associated with the implementation of the planning system. We show the capability of this method for repeated sampling across a dynamic two-dimensional ocean front using a fleet of three types of platforms: short-range Iver AUVs, Tethys-Class Long-Range AUVs, and Seagliders. This method extends to tracking gradients of different properties using a variety of vehicles.

Chavez, Francisco P.↗

Impact of Space Radiation with Other Combined Space Environmental Factors on Plant Seeds and Plant Development: from Arabidopsis thaliana to Crops

One of the major concerns for long-term exploration missions beyond Earth’s magnetosphere is radiation risk, primarily from solar particle events (SPE) and galactic cosmic rays (GCR). With the goal of manned Mars exploration, the production of fresh food during long-duration space missions provides critical nutritional supplementation and may also benefit astronauts’ behavioral health. However, the effects of space radiation on plants and plant propagules have not been sufficiently investigated and characterized. To evaluate the effects of space radiation on plant seeds and development, we explored several platforms, including ground-based radiation facilities, the MISSE platform outside the ISS, and other Low Earth Obit (LEO) opportunities. Radiation particle types ranged from neutrons, single charged particles, simulated galactic cosmic rays, simulated solar particle events, the radiation field outside the ISS (total 10 months on the ISS), and the field inside a LEO vehicle (over 3 years). Radiation doses ranged from around 10 cGy to 80 cGy with acute or chronic exposures. In these studies up to 15 types of model plant and crop seeds were evaluated. In addition, tests were conducted to determine whether the combination of radiation exposure and simulated microgravity could have synergetic effects. Exposure to space radiation at the levels tested had no significant impact on the germination rate in Arabidopsis and the seeds from multiple crop plants; however, radiation exposure alone or with other combined factors reduced the viability of some seed types. Overall, the changes within plants grown from irradiated seeds were dose- and ion quality- dependent, with heavier ions causing more severe damage. These changes ranged from cotyledon deformation, shortened root length, smaller seedling size, and other signs of stress, depending on the seed types. Radiation exposure also significantly altered transcriptomic profiles in seedlings grown from irradiated seeds. The impact of space radiation on seeds and plants potentially affects the ability of plants to adapt to other environmental stresses (e.g. microgravity, water stress, and hardware constraints) as well as susceptibility to plant diseases, which need to be furtherly investigated.

Y Zhang↗

Genelab: Scientific Partnerships and an Open-Access Database to Maximize Usage of Omics Data from Space Biology Experiments

NASA's mission includes expanding our understanding of biological systems to improve life on Earth and to enable long-duration human exploration of space. The GeneLab Data System (GLDS) is NASA's premier open-access omics data platform for biological experiments. GLDS houses standards-compliant, high-throughput sequencing and other omics data from spaceflight-relevant experiments. The GeneLab project at NASA-Ames Research Center is developing the database, and also partnering with spaceflight projects through sharing or augmentation of experiment samples to expand omics analyses on precious spaceflight samples. The partnerships ensure that the maximum amount of data is garnered from spaceflight experiments and made publically available as rapidly as possible via the GLDS. GLDS Version 1.0, went online in April 2015. Software updates and new data releases occur at least quarterly. As of October 2016, the GLDS contains 80 datasets and has search and download capabilities. Version 2.0 is slated for release in September of 2017 and will have expanded, integrated search capabilities leveraging other public omics databases (NCBI GEO, PRIDE, MG-RAST). Future versions in this multi-phase project will provide a collaborative platform for omics data analysis. Data from experiments that explore the biological effects of the spaceflight environment on a wide variety of model organisms are housed in the GLDS including data from rodents, invertebrates, plants and microbes. Human datasets are currently limited to those with anonymized data (e.g., from cultured cell lines). GeneLab ensures prompt release and open access to high-throughput genomics, transcriptomics, proteomics, and metabolomics data from spaceflight and ground-based simulations of microgravity, radiation or other space environment factors. The data are meticulously curated to assure that accurate experimental and sample processing metadata are included with each data set. GLDS download volumes indicate strong interest of the scientific community in these data. To date GeneLab has partnered with multiple experiments including two plant (Arabidopsis thaliana) experiments, two mice experiments, and several microbe experiments. GeneLab optimized protocols in the rodent partnerships for maximum yield of RNA, DNA and protein from tissues harvested and preserved during the SpaceX-4 mission, as well as from tissues from mice that were frozen intact during spaceflight and later dissected on the ground. Analysis of GeneLab data will contribute fundamental knowledge of how the space environment affects biological systems, and as well as yield terrestrial benefits resulting from mitigation strategies to prevent effects observed during exposure to space environments.

bioinformatics↗

GeneLab: Scientific Partnerships and an Open-Access Database to Maximize Usage of Omics Data from Space Biology Experiments

NASA's mission includes expanding our understanding of biological systems to improve life on Earth and to enable long-duration human exploration of space. The GeneLab Data System (GLDS) is NASAs premier open-access omics data platform for biological experiments. GLDS houses standards-compliant, high-throughput sequencing and other omics data from spaceflight-relevant experiments. The GeneLab project at NASA-Ames Research Center is developing the database, and also partnering with spaceflight projects through sharing or augmentation of experiment samples to expand omics analyses on precious spaceflight samples. The partnerships ensure that the maximum amount of data is garnered from spaceflight experiments and made publically available as rapidly as possible via the GLDS. GLDS Version 1.0, went online in April 2015. Software updates and new data releases occur at least quarterly. As of October 2016, the GLDS contains 80 datasets and has search and download capabilities. Version 2.0 is slated for release in September of 2017 and will have expanded, integrated search capabilities leveraging other public omics databases (NCBI GEO, PRIDE, MG-RAST). Future versions in this multi-phase project will provide a collaborative platform for omics data analysis. Data from experiments that explore the biological effects of the spaceflight environment on a wide variety of model organisms are housed in the GLDS including data from rodents, invertebrates, plants and microbes. Human datasets are currently limited to those with anonymized data (e.g., from cultured cell lines). GeneLab ensures prompt release and open access to high-throughput genomics, transcriptomics, proteomics, and metabolomics data from spaceflight and ground-based simulations of microgravity, radiation or other space environment factors. The data are meticulously curated to assure that accurate experimental and sample processing metadata are included with each data set. GLDS download volumes indicate strong interest of the scientific community in these data. To date GeneLab has partnered with multiple experiments including two plant (Arabidopsis thaliana) experiments, two mice experiments, and several microbe experiments. GeneLab optimized protocols in the rodent partnerships for maximum yield of RNA, DNA and protein from tissues harvested and preserved during the SpaceX-4 mission, as well as from tissues from mice that were frozen intact during spaceflight and later dissected on the ground. Analysis of GeneLab data will contribute fundamental knowledge of how the space environment affects biological systems, and as well as yield terrestrial benefits resulting from mitigation strategies to prevent effects observed during exposure to space environments.

spaceflight↗

The Tailoring of Traditional Systems Engineering for the Morpheus Project

NASA's Morpheus Project has developed and tested a prototype planetary lander capable of vertical takeoff and landing that is designed to serve as a testbed for advanced spacecraft technologies. The lander vehicle, propelled by a LOX/Methane engine and sized to carry a 500kg payload to the lunar surface, provides a platform for bringing technologies from the laboratory into an integrated flight system at relatively low cost. From the beginning, one of goals for the Morpheus Project was to streamline agency processes and practices. The Morpheus project accepted a challenge to tailor the traditional NASA systems engineering approach in a way that would be appropriate for a lower cost, rapid prototype engineering effort, but retain the essence of the guiding principles. The team has produced innovative ways to create an infrastructure and approach that would challenge existing systems engineering processes while still enabling successful implementation of the current Morpheus Project. This paper describes the tailored systems engineering approach for the Morpheus project, including the processes, tools, and amount of rigor employed over the project's multiple lifecycles since the project began in FY11. Lessons learned from these trials have the potential to be scaled up and improve efficiency on a larger projects or programs.

Devolites, Jennifer L.↗