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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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NASA NTRS2018

NASA Armstrong Flight Research Center Summer 2018 Abstracts

Student internships provide the opportunity for students to work side by side with a mentor to contribute to the NASA mission. During Fiscal Year 2018, NASA Armstrong welcomed students from universities in states ranging from Washington to Massachusetts. Student interns were represented in different organizations across NASA Armstrong and supported exciting projects such as SOFIA, X-57 Maxwell, UASNAS, FOSS, X-59 QueSST, TGALS, PRANDTL - M, and PRANDTL-D3c.

internship experience↗
NASA NTRS2018

Leverage Your Science Data Return by Flying with the International Earth Science Constellation (ESC)

Constellations have proven to be an effective and efficient way to acquire earth science data. By flying together, sensors on all satellites in a constellation take measurements of the same air, water, or land mass at essentially the same time. The sensors form a single "virtual satellite". The key to making a constellation effective and efficient is keeping the operations as independent as possible in order to minimize the operational burden and costs. The Earth Science Constellation (ESC) has been successful on all counts and continues to welcome new missions to continue its 18+ year record of coincidental earth science observations. The ESC also serves as a model for future constellation designs. This paper describes the ESC and its evolution from its initial launches in 1999 through the present and how new missions might benefit from joining the ESC.

Morning Constellation; Afternoon Constellation; Ea↗
NASA NTRS2018

GrassPlot - a Database of Multi-Scale Plant Diversity in Palaearctic Grasslands

GrassPlot is a collaborative vegetation-plot database organised by the Eurasian Dry Grassland Group (EDGG)and listed in the Global Index of Vegetation-Plot Databases (GIVD ID EU-00-003). GrassPlot collects plot records (releves) from grasslands and other open habitats of the Palaearctic biogeographic realm. It focuses on precisely delimited plots of eight standard grain sizes (0.0001; 0.001; ... 1,000 m_) and on nested-plot series withat least four different grain sizes. The usage of GrassPlot is regulated through Bylaws that intend to balance the interests of data contributors and data users. The current version (v. 1.00) contains data for approximately 170,000 plots of different sizes and 2,800 nested-plot series. The key components are richness data and metadata.However, most included datasets also encompass compositional data. About 14,000 plots have near-complete records of terricolous bryophytes and lichens in addition to vascular plants. At present, GrassPlot contains data from 36 countries throughout the Palaearctic, spread across elevational gradients and major grassland types. GrassPlot with its multi-scale and multi-taxon focus complements the larger international vegetation plot databases, such as the European Vegetation Archive (EVA) and the global database "sPlot". Its main aim is to facilitate studies on the scale- and taxon-dependency of biodiversity patterns and drivers along macroecological gradients. GrassPlot is a dynamic database and will expand through new data collection coordinated by the elected Governing Board. We invite researchers with suitable data to join GrassPlot. Researchers with project ideas addressable with GrassPlot data are welcome to submit proposals to the Governing Board.

Dengler, Jurgen↗
NASA NTRS2018

What-If System

The What-If System is meant to be a "sandbox" to be able to view the potential impact of system wide changes on the tower side and metering decisions on the ramp side without actually making changes to the system. The What-If System is a tool within which with STBO, RMTC and DASH may be used such that proposed changes and updates can be made to determine their impact in isolation. The What-If System is a prototype tool, we welcome suggestions for improving the What-If utility. Improvements will be incorporated in later builds beyond phase-1 of ATD-2.

User Manual↗
NASA NTRS2018

Leverage Your Science Data Return by Flying with the International Earth Science Constellation (ESC)

Constellations have proven to be an effective and efficient way to acquire earth science data. By flying together, sensors on all satellites in a constellation take measurements of the same air, water, or land mass at essentially the same time. The sensors form a single "virtual satellite". The key to making a constellation effective and efficient is keeping the operations as independent as possible in order to minimize the operational burden and costs. The Earth Science Constellation (ESC) has been successful on all counts and continues to welcome new missions to continue its 18+ year record of coincidental earth science observations. The ESC also serves as a model for future constellation designs. This paper describes the ESC and its evolution from its initial launches in 1999 through the present and how new missions might benefit from joining the ESC.

leverage data↗
NASA NTRS2016

Uncertainty Assessment of the NASA Earth Exchange Global Daily Downscaled Climate Projections (NEX-GDDP) Dataset

The NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset is comprised of downscaled climate projections that are derived from 21 General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 5 (CMIP5) and across two of the four greenhouse gas emissions scenarios (RCP4.5 and RCP8.5). Each of the climate projections includes daily maximum temperature, minimum temperature, and precipitation for the periods from 1950 through 2100 and the spatial resolution is 0.25 degrees (approximately 25 km by 25 km). The GDDP dataset has received warm welcome from the science community in conducting studies of climate change impacts at local to regional scales, but a comprehensive evaluation of its uncertainties is still missing. In this study, we apply the Perfect Model Experiment framework (Dixon et al. 2016) to quantify the key sources of uncertainties from the observational baseline dataset, the downscaling algorithm, and some intrinsic assumptions (e.g., the stationary assumption) inherent to the statistical downscaling techniques. We developed a set of metrics to evaluate downscaling errors resulted from bias-correction ("quantile-mapping"), spatial disaggregation, as well as the temporal-spatial non-stationarity of climate variability. Our results highlight the spatial disaggregation (or interpolation) errors, which dominate the overall uncertainties of the GDDP dataset, especially over heterogeneous and complex terrains (e.g., mountains and coastal area). In comparison, the temporal errors in the GDDP dataset tend to be more constrained. Our results also indicate that the downscaled daily precipitation also has relatively larger uncertainties than the temperature fields, reflecting the rather stochastic nature of precipitation in space. Therefore, our results provide insights in improving statistical downscaling algorithms and products in the future.

general circulation model (GCM)↗
NASA NTRS2017

Observations, Modeling, and Predictions of Solar Activity From the Deep Interior to the Corona

Solar activity is a manifestation of magnetic self-organization processes that involve complex dynamical coupling of various layers of the Sun acting over a broad range of spatial and temporal scales. Synergy of observational, theoretical, and modeling efforts is key to understanding solar activity variation, dynamics, and evolution and to developing reliable physics-based forecasts of long-term solar cycles and short-term activity manifestations, “seasons of solar activity”, such as periods of enhanced flaring and CME activity. The session welcomes observers, modelers, and theoreticians to share their results and ideas and to discuss current challenges, development of emerging fields (such as data assimilation), and the analysis of historical and modern observational data using theoretical modeling, interpretations, and predictions.

Deep Interior↗
NASA NTRS2014

Atmospheric Research 2013 Technical Highlights

Welcome to the Atmospheric Research 2013 Atmospheric Research Highlights report. This report, as before, is intended for a broad audience. Our readers include colleagues within NASA, scientists outside the Agency, science graduate students, and members of the general public. Inside are descriptions of atmospheric research science highlights and summaries of our education and outreach accomplishments for calendar year 2013.This report covers research activities from the Mesoscale Atmospheric Processes Laboratory, the Climate and Radiation Laboratory, the Atmospheric Chemistry and Dynamics Laboratory, and the Wallops Field Support Office under the Office of Deputy Director for Atmospheres (610AT), Earth Sciences Division in the Sciences and Exploration Directorate of NASAs Goddard Space Flight Center.

Atmospheric Research↗
NASA NTRS2016

NASA Ames Space Science and Astrobiology: 4th Annual Jamboree

Welcome to the Fourth Annual Ames Space Sciences and Astrobiology Jamboree! The Space Science and Astrobiology Division at NASA Ames Research Center consists of over 50 civil servants and more than 110 contractors, co-­‐ops, post-­‐docs and associates. Researchers in the division are pursuing investigations in a variety of fields including exoplanets, planetary science, astrobiology and astrophysics. In addition, division personnel support a wide variety of NASA missions including (but not limited to) Kepler, SOFIA, LADEE, JWST, and New Horizons. With such a wide variety of interesting research going on, distributed among three branches in at least 5 different buildings, it can be difficult to stay abreast of what one’s fellow researchers are doing. Our goal in organizing this symposium is to facilitate communication and collaboration among the scientists within the division, and to give center management and other ARC researchers and engineers an opportunity to see what scientific research and science mission work is being done in the division. We are also continuing the tradition within the Space Science and Astrobiology Division to honor one senior and one early career scientist with the Pollack Lecture and the Early Career Lecture, respectively. With the Pollack Lecture, our intent is to select a senior researcher who has made significant contributions to any area of research within the space sciences, and we are pleased to honor Dr. David DesMarais this year. With the Early Career Lecture, our intent is to select a young researcher within the division who, by their published scientific papers, shows great promise for the future in any area of space science research, and we are pleased to honor Dr. Christiaan Boersma this year.

Dotson, Jessie↗
NASA NTRS2019

Setting Sail for the Sun: The NEA Scout & Solar Cruiser Missions

Join HAL5 as we welcome back Les Johnson, who will talk about his work on developing solar sails at Marshall Space Flight Center and its role in propulsion and exploration of the Sun. With the successful flights of NASA's NanoSail-D and the Planetary Society's LightSail, solar sails are making the transition from an interesting idea to be demonstrated to technology ready for use on space missions. Scientists and engineers here in Huntsville are doing just that with the development of the Near Earth Asteroid Scout's 925 square foot solar sail that will fly in 2020. And that's not all, in August, a team led by NASA MSFC was selected as a finalist to develop an 18,000 square foot solar sail for a project called, Solar Cruiser, that may fly as early as 2024. If you would like to learn the fundamentals of solar sailing and get the scoop on these two innovative and exciting missions, then hang on as we "Set Sail for the Sun!"

Heliophysics↗
NASA NTRS2020

LUNAR SURFACE GEOSCIENCE TRAINING FOR ASTRONAUTS

Geoscientists have been training and preparing astronauts to observe the Earth from space and explore other planetary surfaces with a legacy that reaches back to the early days of the space program. Continuing this legacy and critical function, a core NASA team has been closely coordinating with the Johnson Space Center (JSC) Flight Operations Directorate (FOD) as well as academic, research institutions, and other governmental partners to conduct a comprehensive geoscience training program that ranges from initial astronaut candidate training to preparing assigned crew for future lunar surface missions. Described below are the three program training phases (summarized in Figure 1), along with recent program highlights and forward planning. Given NASA’s increased planning and development efforts regarding near-term lunar surface science activities, we welcome ideas, concepts, capabilities, collaborations, and innovations to this astronaut training program.

T. G. Graff↗
NASA NTRS2017

TPSAS-NF1676L-26965-DND

A comprehensive understanding of the spatial and temporal distributions of clouds on a global scale can be best achieved when the vertical distributions and multi-layer occurrence frequencies obtained from active remote sensors are fully integrated with the horizontal distributions currently provided by passive sensors. The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) satellite lidar onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) spacecraft was specially designed to acquire aerosol and cloud profiles with unprecedented high vertical resolution and accuracy. As a part of the A-Train satellite constellation, CALIPSO has been operating routinely for more than 10 years and continues to provide a wealth of cloud observations to describe the mean state and inter-annual variability. Recently a suite of level 3 (L3) cloud products has been under development by the CALIPSO lidar science working group at the NASA Langley Research Center. These products describe 3-dimensional (3D) cloud occurrence and 3D ice cloud extinction coefficients and ice water content. Future evolution of the products will add observations from the Imaging Infrared Radiometer onboard CALIPSO. Here we present a brief introduction and provide results from a product prototype. We will characterize the inter-annual vertical variability of zonal cloud occurrence and ice water content during the last 10 years. Suggestions and comments are welcome to help us design and provide better cloud climatology products using CALIOP observations for our cloud community.

Xia Cai↗
NASA NTRS2020

Technical Risks Associated with Heat Melt Compaction Systems

The processing of trash and waste is a welcome and valuable addition to humans living and working in space. Besides the obvious desire to have a pleasant and productive habitation environment, trash management has many practicalbenefits for crew health, resource recovery, and volume reclamation through garbage compaction. The Trash Compaction and Processing System (TCPS), which is a NASA project to develop a trash processing system for long-duration spaceflight, is currently undergoing concept development with engineering prototype validation through two contracted efforts. The development efforts are being supported with activities associated with the NASA Generation 2 Heat Melt Compactor (HMC). The HMC is a facility that compacts trash, recovers water, heats the trash to eliminate biological activity, and manages gas and vapor effluents. The resulting residual processed trash is a compact tile that is free of biological growth and that can be used for augmenting radiation shields. The work being conducted with the HMC focuses on high risk technical areas with respect to operations, subsystem performance, and ISS effluent management interface requirements. This paper gives an overview of the technical risks and the current use of the HMC as a facility for reducing risk.

HMC↗
NASA NTRSDate not supplied

Dust Mitigation: Impacts & Opportunities for Science on the Lunar South Pole

Lunar dust will be a feature of all lunar surface science investigations, whether welcome or not. While lunar dust may pose problems for some investigations, it is also the subject of many critical scientific discoveries made since the Apollo days. Dust mitigation, or learning how to work with and around the inevitable dust we will encounter on the surface, is not a new concept. However, new initiatives throughout NASA are underway in an effort to tackle dust mitigation strategically for the Artemis program. Dust mitigation efforts and technologies will enable successful lunar surface science investigations.

lunar dust↗
NASA NTRSDate not supplied

3-Dimensional Advanced Workflow

Have you ever been frustrated with the 2-dimensional nature of implementing complex Advanced Workflows (AWF) in your RSA Archer environment? Does the lack of concurrent, parallel workflows make you scratch your head and ask, ‘Why?’ Has your AWF gotten so complicated and convoluted that navigating through a maze-like plate of spaghetti looks simple and straightforward by comparison? If so, come listen to how NASA leverages Questionnaires to add an extra dimension and welcome simplification to complex Advanced Workflow configurations!

RSA Archer↗
NASA NTRSDate not supplied

Common Scientific and Technological Interests Between Astrobiology and Space Biology

The disciplines of astrobiology (AB) and space biology (SB) clearly have common interests, however they have not been pursued jointly. SB and AB are inextricably linked, both intellectually and technologically. They can now be effectively linked operationally. Cross-cutting joint collaborations will enhance innovation and increase cost effectiveness. Session topics include joint science questions, technologies, instrumentation, and missions. Examples include life detection, overlapping planetary protection concerns, biofilms, radiation, hyper- and hypogravity, applications of artificial intelligence and machine learning, interoperable databases, facilities (i.e., spacecraft, lunar surface efforts, simulation chambers, analog sites, etc.), training opportunities, and other topics relevant to AB and SB joint ventures. We welcome contributions on this very broad topical area to facilitate cross-fertilization of these disciplines that are of great importance to NASA.

astrobiology↗
NASA NTRSDate not supplied

Transforming Science Prioritization Processes Using Artificial Intelligence

Artificial Intelligence (AI) and Machine Learning (ML) have potential to augment significantly the current labor-intensive processes of science prioritization, specifically by the National Academies’ Decadal Survey on behalf of NASA and NSF. Here we summarize what we believe to be the first exploratory demonstration-of-concept results from an application of AI/ML to Survey science prioritization. Specifically, we applied Latent Dirichlet Allocation (LDA) and Natural Language Processing (NLP) to reveal trends in published astrophysics research that may indicate science priorities and which could be applied to strategic planning. For the purpose of the work that we summarize here, AI/ML is able to analyze – that is, to “understand,” in a manner of speaking – a vast amount of text to reveal complex relationships among research topics, including the growth or decline of science community activities in those topics over time. We trained ourselves and AI/ML algorithms by using ~400,000 abstracts in the period 1998 to 2010 to “forecast” the Academies’ Astro2010 recommendations and compare with the solicited white papers. Comparing our results with actual Astro2010 recommendations allowed us to identify candidate metrics that better predicted the actual results of the Survey. We found, for example, that Compound Annual Growth Rate (CAGR) of papers published in a topic area is a good proxy measure for importance of this topic area of research. With this training complete, we identified candidate astrophysics astrophysics science priorities for the 2021+ period using the research during 2007 - 2019 . We conclude that appropriate application of AI can potentially significantly reduce the current workload of the Decadal Survey processes and reveal otherwise unrecognized characteristics in the body of astronomical research. We emphasize throughout the exploratory nature of our work, encouraging colleagues to pursue promising results further. Our most critical governing assumption was that increased (or decreased) research activity can be used to identify scientific or technology topic areas worthy of increased (or decreased) future emphasis. We discuss advantages, limitations, and recognize the “black box” nature of our technique. We note ethics issues associated, for example, with using AI/ML to reveal “hidden” meanings and biases in published work. Furthermore, inevitable improvements in AI may soon enable widespread and welcome identification of and advocacy for science and technology priorities by disparate and diverse groups and organizations. Consequently, we continue to urge a near-term, in-depth evaluation of appropriate applications of AI, including implications and consequences, as well as support for multiple follow-on assessments, of which ours is only a beginning.

Artificial Intelligence↗
NASA NTRSDate not supplied

Assimilating Lessons Learned – From URGE to NASA's Student Airborne Science Activation (SaSa) Project

In the first half of 2021, formal and informal pods at several universities and NASA Center affiliates participated in the Unlearning Racism in Geosciences (URGE) curriculum and deliverables. As a result, several members from different URGE pods are propagating and applying the URGE lessons learned to the new 5-year NASA Student Airborne Science Activation project (SaSa). Starting in the Summer of 2022, SaSa will provide an 8-week summer Earth Science research experience focused on attracting and retaining early undergraduate students from historically underrepresented groups from minority-serving institutions (MSIs). The multicenter and field-based research experience will provide the students access to and experience with NASA airborne resources. Additionally, integrating NASA material into the MSI curricula and providing student mentorship at both MSIs and NASA Centers will enhance students' exposure to Earth Science research. The objectives of URGE and SaSa are highly compatible with one another, and the project timing allows for the integration of URGE lessons early in the SaSa curriculum design phase. As of December 2021, the first SaSa summer program application will be open and the first SaSa semester at the host MSIs will be completed. This presentation will discuss the assimilation of URGE lessons learned from our respective pods into the first SaSa academic semester and into the preparations for the first SaSa summer cohort. We will welcome additional feedback from the broader URGE community in advance of SaSa's first summer session.

Kristina Pistone↗