Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “BRIDGE project”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3

AmeriFlux FLUXNET-1F US-Ced Cedar Bridge

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Ced Cedar Bridge. This is the FLUXNET version of the carbon flux data for the site US-Ced Cedar Bridge produced by applying the standard ONEFlux (1F) software. Site Description - Wildfires and prescribed fires are a common occurrence in the NJ Pinelands. Prior to a 1995 nonstand replacing wildfire, the stand was last burned in the very large wildfire in 1963. Plow lines were installed for fire control in December of 2007, followed by a prescribed burns in 2008 and 2013, conducted by the New Jersey Forest Fire Service. Pine looper defoliated the stand in 1998, and Gypsy moth defoliated the understory and deciduos oaks in 2007. Pitch Pines are largely unaffected by defoliation by Gypsy moth.

Skowronski, Nicholas S.↗

Enabling Predictive Scale-Bridging Simulations through Active Learning (Institutional Computing Annual Report (Project w21_alscalebridging)) [Slides]

The goal of this project was to develop, demonstrate, and provide a new capability to achieve greater physical fidelity in large-scale simulations, rather than the usual brute-force increases in the number of mesh elements or particles. Transport in nanoporous media, critical to hydrocarbon extraction from tight shale formations, is affected by molecular-level interactions. Several coarse-scale Lattice Boltzmann model (LBM) parameters cannot be directly computed, so instead we calibrate them to molecular dynamics (MD) simulations, by building emulators that mimic MD and LBM behavior and then training an upscaler. The resulting machine learning (ML)-based scale-bridging framework is up to 7 orders of magnitude faster than direct MD.

74 ATOMIC AND MOLECULAR PHYSICS↗

The MY NASA DATA Project

On the one hand, locating the right dataset, then figuring out how to use it, is a daunting task that is familiar to almost any scientist or graduate student in the fields of Earth system science. On the other hand, the ability to explore authentic Earth system science data, through inquiry-based education, is an important goal in US national education standards. Fortunately, in the digital age, tools are emerging that can make such data exploration commonplace at all educational levels. This paper describes the conception and development of one project that aims to bridge this gap: Mentoring and inquiry using NASA Data on Atmospheric and Earth science for Teachers and Amateurs (MY NASA DATA; mynasadata.larc.nasa.gov). With funding from NASA's Science Mission Directorate, this project was launched in early 2004 with the aim of developing microsets and identifying other enablers for making data accessible. A key feature of the project is a Live Access Server, the first educational implementation of this open source software, developed by NOAA, that makes it possible to explore multiple data formats through a single interface. This powerful tool is made more useful to the primary target audiences (K-12 and amateur scientists) through careful selection of the data offered, user-friendly explanations of the tool itself, and age-appropriate explanations of the parameters. However experience already shows that graduate students and even practicing scientists can also make use of this resource. The website also hosts teacher-contributed lesson plans, and seeks to feature reports of research projects that use the data.

Chambers, Lin H.↗

Enabling Predictive Scale-Bridging Simulations through Active Learning (Institutional Computing Annual Report (Project w20_alscalebridging)) [Slides]

The goal of this project was to develop, demonstrate, and provide a new capability to achieve greater physical fidelity in large-scale simulations, rather than the usual brute-force increases in the number of mesh elements or particles. This was done by using machine learning (ML) techniques to develop emulators for subscale physics that can be used in coarse-scale continuum simulations, trained on fine-scale molecular dynamics (MD) simulations that are launched on-the-fly via active learning. raditional inertial confinement fusion (ICF) simulations rely on numerical diffusion to simulate molecular effects such as non-local transport and mixing without truly accounting for molecular interactions; our approach directly accounts for this physics.

74 ATOMIC AND MOLECULAR PHYSICS↗

Scaling Equitable Finance

Driven by dramatic declines in up-front cost, the U.S. solar photovoltaics (PV) industry has taken off over the past decade, growing from 1 gigawatt of installed capacity in 2009 to 89 gigawatts in 2020—or enough capacity to power roughly 19 million homes. The industry is expected to double in size over just the next 5 years.1 Much of the growth has been driven by large, utility-scale projects that can produce 5 mega- watts or more of power—enough to power at least 1,000 homes. The cost of electricity produced by these projects has decreased by more than 70 percent since 2010. As of Q3 2020, development costs of large, util- ity-scale solar PV power plants were under $1 per watt, down by more than 70 percent from 2010.2 A robust array of investors has come forward to efficiently deliver capital to these kinds of utility-scale projects including large banks, insurance companies, pension funds, and others. But low- and moderate-income communities, including communities of color, are at risk of being left behind in the transition to clean energy. Mission- driven solar project developers and financial institu- tions have been working alongside energy justice advocates to open up solar access for these communi- ties, using strategies ranging from community solar, to solar installations on affordable multifamily housing, to distributed solar and storage programs, and more. Their goals go beyond simply generating more green energy to advancing social equity by: • empowering communities to control their energy future • stabilizing energy prices, saving money, and build- ing wealth for low-income families • creating quality jobs • improving health by reducing pollution • providing energy resilience for vulnerable communities Mission-driven actors are successfully deploying a wide variety of strategies to meet these goals, from helping low-income homeowners get solar—and some- times battery storage, to developing solar projects serv- ing affordable rental housing and community facilities, to building larger “shared solar” projects to which households from across the community can subscribe. However, the financing ecosystem does not work nearly as well for these “mission driven” solar proj- ects as it does for utility-scale projects. For home rooftop solar, even if low-income consumers have a home and suitable roof, they may fail to qualify for federal tax incentives, lack adequate credit to qualify for a loan—or the mission-driven lenders seeking to serve them may not be adequately capitalized to make long-term loans. For mission-driven commercial or community-scale projects, assembling nearly every component of the project capital stack—whether bridging early-stage costs, attracting tax credit equity investors, securing long-term debt, or coming up with sponsor equity and filling gaps—can present challenges. A variety of obstacles contribute to the scarcity of financing for low-income solar, including small project sizes, lack of developer balance sheet capacity, both real and perceived issues with credit risk, elevated technical assistance needs, and greater subsidy requirements to pursue goals such as deep energy affordability, climate resilience, or job creation. Still other obstacles are regulatory: for example, not all states allow community solar projects or Power Purchase Agreements, common strategies used for providing low-income solar—and the potential for regulations to shift over time creates risks that mission-driven projects can ill afford. This report synthesizes information garnered from 47 key informant interviews, four focus group discus- sions involving 60 stakeholders, and a review of the substantial existing literature on low-income solar finance to assess the current landscape of mission- driven solar development in the United States, examine the roles that community-based financial institutions could play, and recommend public invest- ments and policy changes that could help to scale the provision of equitable solar finance. Key recommen- dations for policymakers and funders in the renew- able energy and community development fields that emerge from this process include the following: • Help to capitalize and support community-based lenders to provide flexible, low-cost, and long- term financing to mission-driven solar projects— including providing guarantees or other forms of credit enhancement. • Provide federal support for equitable solar, including a grant-in-lieu-of-credits option for the Investment Tax Credit to improve access to this critical government subsidy. • Develop pools of government and philanthropic support that can complement financing from community-based lenders to complete the capi- tal stack for mission-driven projects, as well as to support education and technical assistance to both consumers and potential project sponsors. • Create a national Renewable Energy Credits pro- gram that includes social equity targets to provide a baseline of support for clean energy generation. • Change utility regulations to remove barriers to low-income solar projects; lower permitting costs; provide greater certainty for developers, consumers and owners; and measure progress toward equity in renewable energy policy implementation.

14 SOLAR ENERGY↗

NASA POWER: Providing Analysis-Ready, Cloud-Optimized Data for AI /ML Training and Applications in Earth Science

As global demand for sustainable development grows, the integration of Earth Observation (EO) data into decision making frameworks has become a primary objective for the scientific community. The NASA Prediction of Worldwide Energy Resources (POWER) project serves as a bridge between NASA EO data and the specialized needs of the renewable energy, sustainable infrastructure and agroclimatology communities. In this poster presentation we will present an overview of POWER data products and services along with its use in diverse research to decision-making workflows. By providing over 40 years of high-resolution historical, hourly and daily solar and meteorological data, POWER transforms satellite observations and global model reanalysis into actionable, Analysis-Ready Dataset (ARD). Currently, the project delivers over 250 industry-friendly parameters to the users from different NASA datasets like CERES SYN1Deg, MERRA-2, and IMERG alongside downscaled CMIP6 climate model data, fulfilling over 16 million requests from 50,000 unique users monthly. To ensure data quality and traceability, these parameters are rigorously validated against the ground-based observations from the Baseline Surface Radiation Network (BSRN) and the Global Surface Summary of the Day (GSOD) – these results will be discussed in the presentation. A newly introduced web-based PaRameter Uncertainty ViEwer (PRUVE) tool will be presented that provides an online validation platform to the users that benchmarks satellite-based and assimilation data products against these surface measurements. To reduce technical barriers to data adoption, POWER data is accessible through RESTful APIs, ESRI ArcGIS Image Services, a web-based Data Access Viewer tool, allowing users to visualize, validate and apply the dataset. For efficient data delivery POWER data is cloud-optimized into Zarr datastore accessible through NASA managed Amazon S3 ensures high-performance allowing users to integrate EO directly into operational pipelines. These customized services will be presented. Use cases from application will be presented from the energy sector - such as for design of generation systems, performance monitoring of solar power plants, in infrastructure sector- optimizing building energy efficiency and thermal comfort, in agriculture – such as driving crop simulation and yield forecasting models to enable climate resilient farming. Furthermore, the shift toward machine learning (ML) in EO research that has positioned POWER as a key provider for training datasets which will be discussed. Use-cases will be presented to showcase how NASA data is enabling the development of predictive tools for climate variability and resource management. The poster will present POWER’s future plans including technology development to enhance data traceability and reproducibility and improving I/O performance to support the rapid integration of new EO products, ensuring that POWER remains a robust scalable backend for the evolving landscape of AI-driven Earth Science. Additionally, POWER is developing an AI Agent and an MCP-Server to enable industry AI-Agentic workflows.

Neha Khadka↗

The NASA CSTI High Capacity Power Program

The SP-100 program was established in 1983 by DOD, DOE, and NASA as a joint program to develop the technology necessary for space nuclear power systems for military and civil applications. During 1986 and 1987, the NASA Advanced Technology Program was responsible for maintaining the momentum of promising technology advancement efforts started during Phase 1 of SP-100 and to strengthen, in key areas, the chances for successful development and growth capability of space nuclear reactor power systems for future space applications. In 1988, the NASA Advanced Technology Program was incorporated into NASA's new Civil Space Technology Initiative (CSTI). The CSTI program was established to provide the foundation for technology development in automation and robotics, information, propulsion, and power. The CSTI High Capacity Power Program builds on the technology efforts of the SP-100 program, incorporates the previous NASA advanced technology project, and provides a bridge to the NASA exploration technology programs. The elements of CSTI high capacity power development include conversion systems: Stirling and thermoelectric, thermal management, power management, system diagnostics, and environmental interactions. Technology advancement in all areas, including materials, is required to provide the growth capability, high reliability, and 7 to 10 year lifetime demanded for future space nuclear power systems. The overall program will develop and demonstrate the technology base required to provide a wide range of modular power systems while minimizing the impact of day/night operations as well as attitudes and distance from the Sun. Significant accomplishments in all of the program elements will be discussed, along with revised goals and project timelines recently developed.

Winter, Jerry M.↗

Machine-Learning-Based Mapping and Modeling of Solar Energy with Ultra-High Spatiotemporal Granularity

Despite the rapid growth of solar energy, we still lack a dynamic, high-fidelity database that tracks the spatiotemporal variations of solar PVs and their associated infrastructures across different places at a spatially resolved scale. The absence of such data presents a barrier to various applications such as solar PV growth projection, solar energy integration, solar incentive design, and climate risk assessment. In this project, we aim to bridge this gap by developing AI-based algorithms to extract granular information about solar PV installations and their associated infrastructures (i.e., distribution grids) from widely available unstructured data like remote sensing images and street views. As a result, we have built the Solar Energy Atlas, a fine-grained, large-scale geospatial overlay of distributed solar PVs and distribution grids. On top of it, we have advanced the understanding of solar adoption and distribution grid vulnerability to climate-induced extremes. Our major contributions can be summarized as follow: (1) By developing new AI algorithms, we have built the most comprehensive solar PV spatiotemporal database covering the entire US. This is the first time we obtained the exact GPS locations, size, subtype, and installation year information for rooftop solar PVs across the US. This database can be used for solar PV growth projection, solar energy integration, solar energy policy analysis and design, and spatially-resolved climate risk assessment. (2) Leveraging this database, we have uncovered the socioeconomic driving factors that are correlated with earlier onset of solar adoption and higher saturated adoption levels. We have identified the heterogeneity in the effects of different types of financial incentives on solar adoption and provided implications for tailoring incentive design based on local income levels to promote equitable solar adoption. (3) We have developed a distribution grid GIS mapping algorithm which can obtain granular geospatial and topology information about distribution grids using multi-modal open data, reducing the dependency on hard-to-obtain smart meter data of conventional approaches. It shows effectiveness in both the U.S. and Sub-Saharan Africa. Using this algorithm, we have uncovered the non-uniform vulnerability of distribution grids to wildfires in California in the aspects of undergrounding protection and Distributed Energy Resources (DER) preparedness. This has provided important implications for improving the affordability and equity of grid adaptation approaches. (3) We have made our produced database publicly available and provided user-friendly interface to enable various stakeholders and the general public to interact with the data. We have also integrated the produced data into the Data Commons platform to enable the public to access the data and correlate it with other location-specific characteristics simply using natural language as queries. The impact of our project is three-fold: (1) New algorithms for mapping solar PVs and distribution grids across space and time, which are open source to facilitate researchers and industry; (2) New databases of solar PVs and distribution grids that have been made publicly available for engineering, social, and policy applications; (3) New understandings and actionable insights on the potential approaches to promoting solar adoption and reducing energy infrastructure vulnerabilities. In this report, we start by discussing the project background and motivation (section 5), followed by the overview of project objectives (section 6). Results and discussion for each task are presented in section 7. Significant accomplishments are summarized in section 8. This report will be concluded by discussing the paths forwards (section 9), products (section 10), and team roles (section 11).

14 SOLAR ENERGY↗

The scheme machine: A case study in progress in design derivation at system levels

The Scheme Machine is one of several design projects of the Digital Design Derivation group at Indiana University. It differs from the other projects in its focus on issues of system design and its connection to surrounding research in programming language semantics, compiler construction, and programming methodology underway at Indiana and elsewhere. The genesis of the project dates to the early 1980's, when digital design derivation research branched from the surrounding research effort in programming languages. Both branches have continued to develop in parallel, with this particular project serving as a bridge. However, by 1990 there remained little real interaction between the branches and recently we have undertaken to reintegrate them. On the software side, researchers have refined a mathematically rigorous (but not mechanized) treatment starting with the fully abstract semantic definition of Scheme and resulting in an efficient implementation consisting of a compiler and virtual machine model, the latter typically realized with a general purpose microprocessor. The derivation includes a number of sophisticated factorizations and representations and is also deep example of the underlying engineering methodology. The hardware research has created a mechanized algebra supporting the tedious and massive transformations often seen at lower levels of design. This work has progressed to the point that large scale devices, such as processors, can be derived from first-order finite state machine specifications. This is roughly where the language oriented research stops; thus, together, the two efforts establish a thread from the highest levels of abstract specification to detailed digital implementation. The Scheme Machine project challenges hardware derivation research in several ways, although the individual components of the system are of a similar scale to those we have worked with before. The machine has a custom dual-ported memory to support garbage collection. It consists of four tightly coupled processes--processor, collector, allocator, memory--with a very non-trivial synchronization relationship. Finally, there are deep issues of representation for the run-time objects of a symbolic processing language. The research centers on verification through integrated formal reasoning systems, but is also involved with modeling and prototyping environments. Since the derivation algebra is basd on an executable modeling language, there is opportunity to incorporate design animation in the design process. We are looking for ways to move smoothly and incrementally from executable specifications into hardware realization. For example, we can run the garbage collector specification, a Scheme program, directly against the physical memory prototype, and similarly, the instruction processor model against the heap implementation.

Johnson, Steven D.↗

NASA/JSC ISSLive!

Just 150 miles above us, the International Space Station (ISS) is orbiting. Each day, the astronauts on board perform a variety of activities from exercise, science experiments, and maintenance. Yet, many on the ground do not know about these daily activities. National Aeronautics Space Agency/ Johnson Space Center (NASA/JSC) innovation creation ISSLive! - an education project - is working to bridge this knowledge gap with traditional education channels such as schools, but also non-traditional channels with the non-technical everyday public. ISSLive! provides a website that seamlessly integrates planning and telemetry data, video feeds, 3D models, and iOS and android applications. Through the site, users are able to view astronauts daily schedules, in plain English alongside the original data. As an example, when an astronaut is working with a science experiment, a user will be able to read about the activity and for more detailed activities follow provided links to view more information all integrated into the same site. Live telemetry data from a predefined set can also be provided alongside the activities. For users to learn more, 3D models of the external and internal parts of the ISS are available, allowing users to explore the station and even select sensors, such as temperature, and view a real-time chart of the data. Even ground operations are modeled with a 3D mission control center, providing users information on the various flight control disciplines and showing live data that they would be monitoring. Some unique activities are also highlighted and have dedicated spaces to explore in more detail. Education is the focus of ISSLive!, even from the beginning when university students participated in the development process as part of their master s projects. Focus groups at a Houston school showed interest in the project and excitement towards including ISSLive! in their classroom. Through this inclusion, students' knowledge can be assessed with projects, oral presentations, and other assignments. For the public citizens outside of the traditional education system, ISSLive! provides a single, interactive, and engaging experience to learn about the ISS and its role in space exploration, international collaboration, and science. While traditional students are using ISSLive! in the classroom, their parents, grandparents, and friends are using it at home. ISSLive! truly brings the daily operations of the ISS into the daily lives of the public from every generation.

Harris, Philip D.↗

ISSLIVE! Bringing the Space Station to Every Generation

Just 200 miles above us, the International Space Station (ISS) is orbiting. Each day, the astronauts on board perform a variety of activities from exercise, science experiments, and maintenance. Yet, many on the ground don?t know about these daily activities. ISSLive! - an education project - is working to bridge this knowledge gap with traditional education channels such as schools, but also non-traditional channels with the non-technical everyday public. ISSLive! provides a website that seamlessly integrates planning and telemetry data, video feeds, 3D models, and iOS and android applications. Through the site, users are able to view astronauts? daily schedules, in plain English alongside the original data. As an example, when an astronaut is working with a science experiment, a user will be able to read about the activity and for more detailed activities follow provided links to view more information -- all integrated into the same site. Live telemetry data from a predefined set can also be provided alongside the activities. For users to learn more, 3D models of the external and internal parts of the ISS are available, allowing users to explore the station and even select sensors, such as temperature, and view a real-time chart of the data. Even ground operations are modelled with a 3D mission control center, providing users information on the various flight control disciplines and showing live data that they would be monitoring. Some unique activities are also highlighted, and have dedicated spaces to explore in more detail. Education is the focus of ISSLive!, even from the beginning when university students participated in the development process as part of their master?s projects. Focus groups at a Houston school showed interest in the project, and excitement towards including ISSLive! in their classroom. Through this inclusion, student?s knowledge can be assessed with projects, oral presentations, and other assignments. For the public citizens outside of the traditional education system, ISSLive! provides a single, interactive, and engaging experience to learn about the ISS and its role in space exploration, international collaboration, and science. While traditional students are using ISSLive! in the classroom, their parents, grandparents, and friends are using it at home. ISSLive! truly brings the daily operations of the ISS into the daily lives of the public from every generation.

Harris, Philip D.↗

Emerging Propulsion Technologies

The Emerging Propulsion Technologies (EPT) investment area is the newest area within the In-Space Propulsion Technology (ISPT) Project and strives to bridge technologies in the lower Technology Readiness Level (TRL) range (2 to 3) to the mid TRL range (4 to 6). A prioritization process, the Integrated In-Space Transportation Planning (IISTP), was developed and applied in FY01 to establish initial program priorities. The EPT investment area emerged for technologies that scored well in the IISTP but had a low technical maturity level. One particular technology, the Momentum-eXchange Electrodynamic-Reboost (MXER) tether, scored extraordinarily high and had broad applicability in the IISTP. However, its technical maturity was too low for ranking alongside technologies like the ion engine or aerocapture. Thus MXER tethers assumed top priority at EPT startup in FY03 with an aggressive schedule and adequate budget. It was originally envisioned that future technologies would enter the ISP portfolio through EPT, and EPT developed an EPT/ISP Entrance Process for future candidate ISP technologies. EPT has funded the following secondary, candidate ISP technologies at a low level: ultra-lightweight solar sails, general space/near-earth tether development, electrodynamic tether development, advanced electric propulsion, and in-space mechanism development. However, the scope of the ISPT program has focused over time to more closely match SMD needs and technology advancement successes. As a result, the funding for MXER and other EPT technologies is not currently available. Consequently, the MXER tether tasks and other EPT tasks were expected to phased out by November 2006. Presentation slides are presented which provide activity overviews for the aerocapture technology and emerging propulsion technology projects.

Keys, Andrew S.↗

Human Factors Research for Space Exploration: Measurement, Modeling, and Mitigation

As part of NASA's Human Research Program, the Space Human Factors Engineering Project serves as the bridge between Human Factors research and Human Spaceflight applications. Our goal is to be responsive to the operational community while addressing issues at a sufficient level of abstraction to ensure that our tools and solutions generalize beyond the point design. In this panel, representatives from four of our research domains will discuss the challenges they face in solving current problems while also enabling future capabilities. Historically, engineering-dominated organizations have tended to view good Human Factors (HF) as a desire rather than a requirement in system design and development. Our field has made significant gains in the past decade, however; the Department of Defense, for example, now recognizes Human-System Integration (HSI), of which HF is a component, as an integral part of their divisions hardware acquisition processes. And our own agency was far more accepting of HF/HSI requirements during the most recent vehicle systems definition than in any prior cycle. Nonetheless, HF subject matter experts at NASA often find themselves in catch up mode... coping with legacy systems (hardware and software) and procedures that were designed with little regard for the human element, and too often with an attitude of we can deal with any operator issues during training. Our challenge, then, is to segregate the true knowledge gaps in Space Human Factors from the prior failures to incorporate best (or even good) HF design principles. Further, we strive to extract the overarching core HF issues from the point-design-specific concerns that capture the operators (and managers) attention. Generally, our approach embraces a 3M approach to Human Factors: Measurement, Modeling, and Mitigation. Our first step is to measure human performance, to move from subjective anecdotes to objective, quantified data. Next we model the phenomenon, using appropriate methods in our field, modifying them to suit the unique aspects of the space environment. Finally, we develop technologies, tools, and procedures to mitigate the decrements in human performance and capabilities that occur in space environments. When successful, we decrease risks to crew safety and to mission success. When extremely successful (or lucky), we devise generalizable solutions that advance the state of our practice. Our panel is composed of researchers from diverse domains of our project... from different boxes, if you will, of the Human Factors Analysis and Classification System (HFACS).

Kaiser, Mary K.↗

Representing spatial information in a computational model for network management

While currently available relational database management systems (RDBMS) allow inclusion of spatial information in a data model, they lack tools for presenting this information in an easily comprehensible form. Computer-aided design (CAD) software packages provide adequate functions to produce drawings, but still require manual placement of symbols and features. This project has demonstrated a bridge between the data model of an RDBMS and the graphic display of a CAD system. It is shown that the CAD system can be used to control the selection of data with spatial components from the database and then quickly plot that data on a map display. It is shown that the CAD system can be used to extract data from a drawing and then control the insertion of that data into the database. These demonstrations were successful in a test environment that incorporated many features of known working environments, suggesting that the techniques developed could be adapted for practical use.

Blaisdell, James H.↗

The Advanced Pair Telescope (APT) Mission Concept

We present a mission concept for the Advanced Pair Telescope (APT), a high-energy gamma-ray instrument with an order of magnitude improvement in sensitivity, 6 sr field of view, and angular resolution a factor of 3-10 times that of GLAST. With its very wide instantaneous field-of-view and large effective area, this instrument would be capable of detecting GRBs at very large redshifts, would enable a very high resolution study of SNRs and PWN, and could provide hour-scale temporal resolution of transients from many AGN and galactic sources. The APT instrument will consist of a Xe time-projection-chamber tracker that bridges the energy regime between Compton scattering and pair production and will provide an unprecedented improvement in angular resolution; a thick scintillating-fiber trackerlcalorimeter that will provide sensitivity and energy resolution to higher energies and will possess a factor of 10 improvement in geometric factor over GLAST; and an anticoincidence detector using scintillator-tiles to reject charged particles. After the anticipated 10-years of GLAST operation , the APT instrument would provide continued coverage of the critial high-energy gamma-ray band (between 30 MeV to 100 GeV), providing an essential component of broad-band multiwavelength studies of the high-energy universe.

Hunter, Stanley↗

Human Factors Research for Space Exploration: Measurement, Modeling, and Mitigation

As part of NASA's Human Research Program, the Space Human Factors Engineering Project serves as the bridge between Human Factors research and Human Spaceflight applications. Our goal is to be responsive to the operational community while addressing issues at a sufficient level of abstraction to ensure that our tools and solutions generalize beyond the point design. In this panel, representatives from four of our research domains will discuss the challenges they face in solving current problems while also enabling future capabilities.

Kaiser, Mary K.↗

Early Assessment of VIIRS On-Orbit Calibration and Support Activities

The Suomi National Polar-orbiting Partnership (S-NPP) satellite, formally the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP), provides a bridge between current and future low-Earth orbiting weather and environmental observation satellite systems. The NASA s NPP VIIRS Characterization Support Team (VCST) is designed to assess the long term geometric and radiometric performance of the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument onboard the S-NPP spacecraft and to support NPP Science Team Principal Investigators (PI) for their independent evaluation of VIIRS Environmental Data Records (EDRs). This paper provides an overview of Suomi NPP VIIRS on-orbit calibration activities and examples of sensor initial on-orbit performance. It focuses on the radiometric calibration support activities and capabilities provided by the NASA VCST.

Xiong, Xiaoxiong↗

Composites for Exploration Upper Stage

The Composites for Exploration Upper Stage (CEUS) was a 3-year, level III project within the Technology Demonstration Missions program of the NASA Space Technology Mission Directorate. Studies have shown that composites provide important programmatic enhancements, including reduced weight to increase capability and accelerated expansion of exploration and science mission objectives. The CEUS project was focused on technologies that best advanced innovation, infusion, and broad applications for the inclusion of composites on future large human-rated launch vehicles and spacecraft. The benefits included near- and far-term opportunities for infusion (NASA, industry/commercial, Department of Defense), demonstrated critical technologies and technically implementable evolvable innovations, and sustained Agency experience. The initial scope of the project was to advance technologies for large composite structures applicable to the Space Launch System (SLS) Exploration Upper Stage (EUS) by focusing on the affordability and technical performance of the EUS forward and aft skirts. The project was tasked to develop and demonstrate critical composite technologies with a focus on full-scale materials, design, manufacturing, and test using NASA in-house capabilities. This would have demonstrated a major advancement in confidence and matured the large-scale composite technology to a Technology Readiness Level 6. This project would, therefore, have bridged the gap for providing composite application to SLS upgrades, enabling future exploration missions.

composites↗