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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.

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At least 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Campaign: Telemetry-based Biology for the Artemis Era and Beyond

We call for a major dedicated campaign to develop and fly autonomous biological payloads in lunar orbit and on the lunar surface during the next decade, followed by subsequent expansion to Martian orbit. This ambitious goal will require dedicated effort to develop hardware, biological models and data acquisition and processing techniques. We believe that it would be best achieved as a single comprehensive, NASA-led and funded mission project, analogous to planetary science missions. Furthermore, technological developments should be accompanied by collaborations within and between agencies and a robust program for acquisition and retention of talented scientists and engineers.

Egle Cekanaviciute↗
NASA NTRS2022

NASA's System-Wide Safety...A New Era in Aviation is Here!

NASA’s System-Wide Safety project is developing the concept and requirements for an assured In-Time Aviation Safety Management System (IASMS) that will: Improve the efficiency of flight, the access to airspace, and the expansion of services provided by air vehicles; Explore, discover, and understand the impact on safety from growing complexity introduced by industry modernization; Develop and demonstrate innovative solutions that enable the aviation transformation envisioned for global airspace system; Identify and proactively mitigate risks in accordance with target levels of safety; Assure safe, rapid, and repeatable access to a transformed National Airspace System (NAS)

Kyle Ellis↗
NASA NTRSDate not supplied

PAHs Near and Far: Ground and Airborne 3-5 micron observations of PAHs in Planetary Nebulae and Star Forming Regions in the Era of JWST

Polycyclic Aromatic Hydrocarbons (PAHs) exhibit bright, broad emission features throughout the infrared with main features at 3.3, 6.2, 7.7, 8.6, 11.3 and 12.7 μm. These bands arise from the UV excitation of PAHs and relaxation through the vibration, bending and/or stretching of the C–H and C–C bonds. This emission has been observed in multiple astronomical phenomena, including planetary nebulae, where they are believed to be formed, and star-forming regions, which has led to their use as a marker for estimating star formation rates in distant galaxies. Many of these bands are accessible from ground-based observatories, including 3.3 micron PAH feature and its associated aliphatic features at 3.4-3.6 microns. We used ground-based (Lick/FLITECAM and Keck/NIRSPEC) observations of the ~3-5 micron spectra of young planetary nebulae and nearby star-forming regions, to investigate the spatial distribution and spectral variation of PAH emission, and stratospheric (SOFIA/FLITECAM) observations to constrain the theoretical contribution of the 4.4-4.8 micron deuterated-PAH features and the weak 5.25 PAH emission feature. Studying young PNs and nearby star-forming regions with ground-based telescopes gives a unique opportunity for fully understanding PAH emission, processing and variation that can be used in interpreting the extra-galactic PAH spectra JWST will study.

E C Smith↗
NASA NTRS2021

Revisiting Topographic Horizons in the Era of Big Data and Parallel Computing

Widely used to calculate illumination geometry forestimates of solar and emitted longwave radiation, and forcorrecting remotely sensed data for topographic effects, digitalelevation models (DEMs) are now extensive globally at 10–30-mspatial resolution and locally at spatial resolutions down to afew centimeters. Globally, regionally, or locally, elevation datasetshave many grid points. Many software packages calculate gradi-ents over every grid cell or point, but in the mountains, shadingby nearby terrain must also be assessed. Terrain may obscure aslope that would otherwise face the Sun. Four decadesago, a fastmethod to calculate topographic horizons at every point in anelevation grid required computations related only linearly to thesize of the grid, but grids now have so many points that parallelcomputing still provides an advantage. Exploiting parallelismover terrain grids can use alternative strategies: among columnsof a rotated grid, or simultaneously at multiple rotation angles,or on different tiles of a grid. On a multi-processor machine, theimprovement in computing time approaches 2/3 the number ofprocessors deployed,

Jeff Dozier↗
NASA NTRS2021

NASA’s Deep Space Network: Automation in the Follow-the-Sun Era

The Deep Space Network (DSN) comprises three sites, located in California, Spain, and Australia; each site operates one 70m and multiple 34m antennas that provide communications and navigation services to NASA and international partners. As part of a multiyear upgrade in automation of the network, the DSN has undertaken a series of operations efficiency improvements which has fundamentally changed the operations paradigm of the network. At the start of this effort, each site operated only their local antennas and equipment 24 hours/day, 7 days/week, and each spacecraft activity (link) had a single dedicated Link Control Operator. In its final stage, realized in 2020, each one of the three sites operates the entire network during their local day shift, handing off control to the next site as their day ends, and tracks can be run in a fully automated manner with no operator intervention. This paradigm change has realized significant operations cost savings, but has posed some major challenges along the way. This paper describes the system changes that enabled the operations efficiency improvements, some the challenges, and plans for the future.

Levesque, Michael↗
NASA NTRS2022

Perspective on Satellite-Based Land Data Assimilation to Estimate Water Cycle Components in an Era of Advanced Data Availability and Model Sophistication

The beginning of the 21st century is marked by a rapid growth of land surface satellite data and model sophistication. This offers new opportunities to estimate multiple components of the water cycle via satellite-based land data assimilation (DA) across multiple scales. By resolving more processes in land surface models and by coupling the land, the atmosphere, and other Earth system compartments, the observed information can be propagated to constrain additional unobserved variables. Furthermore, access to more satellite observations enables the direct constraint of more and more components of the water cycle that are of interest to end users. However, the finer level of detail in models and data is also often accompanied by an increase in dimensions, with more state variables, parameters, or boundary conditions to estimate, and more observations to assimilate. This requires advanced DA methods and efficient solutions. One solution is to target specific observations for assimilation based on a sensitivity study or coupling strength analysis, because not all observations are equally effective in improving subsequent forecasts of hydrological variables, weather, agricultural production, or hazards through DA. This paper offers a perspective on current and future land DA development, and suggestions to optimally exploit advances in observing and modeling systems.

Data Assimilation↗
NASA NTRSDate not supplied

A New Era of Astrophysics with NASA’s JWST

JWST - launched December 25, 2021 - is poised to change the way we understand the universe, and we are already making some groundbreaking discoveries in just the first several months of operations. I will discuss the engineering milestones that made the mission possible, as well as the over-arching scientific themes/goals of the telescope: first galaxies around the time of cosmic reionization, galaxy assembly and evolution, the birth of stars & protoplanetary systems, and study of planets (both within the solar system and exoplanets). I will also discuss specific scientific programs approved for Cycle 1, as well as early results from the mission.

James Webb Space Telescope↗
NASA NTRSDate not supplied

Nanni in the SAS-2 Era

Explore the source record for details and available documents.

Dave Thompson↗
NASA NTRSDate not supplied

Science Off the Earth: an Integrated Approach to Science Operations in the Artemis Era and Beyond

Humanity is standing on the cusp of its next giant leap – an international, sustainable, and commercial return to the moon. Unlike the Apollo missions, the expectation that a permanent human presence will be established is well founded. Initially, crewed missions to the lunar surface are expected to last between 6 and 30 days and occur approximately once per year, however the robust suite of landers and orbiting assets proposed by both commercial and government entities provide an opportunity to conduct science research on the moon and in cis-lunar space, 24x7 for many years. In the 50 years since the conclusion of Apollo, NASA’s crewed space science missions have been evolving. This can be seen clearly from Skylab and the Space Shuttle’s Spacelab to the International Space Station (ISS). Presently aboard the ISS, international crews spend nearly half their time working on experiments while many payloads collect science non-stop with either very limited, or no crew interaction. Additionally, a fleet of orbiting experiments complement and validate those investigations performed on the ISS. As the number, variety, and complexity of these investigation increase, it becomes ever more necessary to integrate across the many entities involved to prevent duplication of effort, ensure complementary results, reduce cost, and create a sustainable environment to conduct groundbreaking scientific research in space. In this paper, we examine how the various elements of the Artemis program including NASA’s Lunar Gateway, Commercial Lunar Payload Services (CLPS) endeavor, the Human Landing Systems (HLS), surface habitats, rovers and many more will be operated to ensure interoperability, maximize science return, and enable success for government, commercial and private partners.

Science Operations↗