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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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Enabling Nuclear and Solar Thermal Propulsion with the Computational Laboratory: Faster and Cheaper Materials Characterization
Nuclear and solar thermal propulsion offer enhanced efficiencies for in-space travel which may open up the outer Solar System to both crewed and automated craft. However, these advanced propulsion systems require cutting-edge materials which are often not easily tested in the laboratory. Ab initio thermodynamics and other computational methods offer a way to test materials at high pressures and temperatures more quickly, and with reduced cost. Here, several case studies are presented which highlight the utility of modern simulation techniques. First, an extensive thermodynamic study was performed at the ab initio level to elucidate the role of hot hydrogen flow on the erosion of four refractory carbides to examine their appropriateness for use as channel coatings. A detailed analysis of reaction products informs estimates of erosion which are validated in comparison with heritage NERVA data. Specific material suggestions are made for both nuclear and solar designs. Secondly, we examined the mechanical behavior and chemical stability of various components of an idealized nuclear cermet core design using techniques spanning from the atomic to microscale. Next, the mechanical and chemical behavior of tungsten (a potential matrix material) and the stability of uranium mononitride (a potential ceramic fuel element), are characterized in the presence of hydrogen and at elevated temperatures with ab initio thermodynamics. Finally, the mechanical response and failure of tungsten under tensile strain is simulated at the micron scale with a combined finite element and dislocation dynamics approach. The resultant stress-strain data agrees well with experiments and leads to a workflow which can incorporate ab initio thermodynamic data into micron-scale simulations and thus provide real-world relevant estimates of erosion and stress-strain behavior. The power of this framework and our plans to use it in the future will be discussed.
The Experiment for Cryogenic Large-aperture Intensity Mapping (EXCLAIM)
Submillimeter and far-IR spectroscopy provides insight into galaxy evolution through measurement of atomic and molecular line emission. The EXperiment for Cryogenic Large-Aperture Intensity Mapping (EXCLAIM) is a cryogenic balloon-borne instrument designed to carry out intensity mapping to measure the cumulative redshifted line emission from carbon monoxide and singly-ionized carbon to probe star formation in windows from the present to z=3.5. During this time, the rate of star formation dropped dramatically, while dark matter continued to cluster. Intensity mapping permits a blind and complete survey of emitting gas through statistics of cumulative brightness fluctuations. EXCLAIM achieves high sensitivity using a cryogenic telescope coupled to six integrated spectrometers with spectral resolving power R=512 and employing microwave kinetic inductance detectors. Here we summarize the status of the mission.
Commercial Smallsat Data Acquisition (CSDA) Program Update
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The Experiment for Cryogenic Large-aperture Intensity Mapping (EXCLAIM)
Submillimeter and far-IR spectroscopy provides insight into galaxy evolution through atomic and molecular line emission. The EXperiment for Cryogenic Large-Aperture Intensity Mapping (EXCLAIM) is a cryogenic balloon-borne instrument designed to carry out an intensity mapping to measure the cumulative redshifted line emission from carbon monoxide and singly-ionized carbon to probe star formation in windows from the present to z=3.5. During this time, the rate of star formation dropped dramatically, while dark matter continued to cluster. Intensity mapping permits a blind and complete survey of emitting gas through statistics of cumulative brightness fluctuations. EXCLAIM achieves high sensitivity using a cryogenic telescope coupled to six integrated spectrometers with spectral resolving power R = 512 and employing kinetic inductance detectors. Here we summarize the status of the mission.
The impacts of warming on rapidly retreating high-altitude, low-latitude glaciers and ice core-derived climate records
Alpine glaciers in the low- and mid-latitudes respond more quickly than large polar ice sheets to changes in temperature, precipitation, cloudiness, humidity, and radiation. Many high-altitude glaciers are monitored by ground observations, aerial photography, and satellite-borne sensors. Regardless of latitude and elevation, nearly all nonpolar glaciers and ice caps are undergoing mass loss, which compromises the records of past climate preserved within them. Almost without exception, the retreat of these ice fields is persistent, and a very important driver is the recent warming of the tropical troposphere and oceans. Here we present data on the decrease in the surface area of four glaciers from low- to mid-latitude mountainous regions: the Andes of Peru and northern Bolivia, equatorial east Africa, equatorial Papua, Indonesia, and the western Tibetan Plateau. Climate records based on oxygen isotopic ratios (δ18O) measured in ice cores drilled from several glaciers in these regions reveal that the records from elevations below ~6000 m above sea level have been substantially modified by seasonal melting and the movement of meltwater through porous upper firn layers. Fortunately, δ18O records recovered from higher altitude sites still contain well-preserved seasonal variations to the surface; however, the projected increase in the rate of atmospheric warming implies that climate records from higher elevation glaciers will eventually also be degraded. A long-term ice core collection program on the Quelccaya ice cap in Peru, Earth's largest tropical ice cap, illustrates that the deterioration of its climate record is concomitant with the increase in mid-troposphere temperatures. The melting ice and resulting growth of proglacial lakes presents an imminent hazard to nearby communities. The accelerating melting of glaciers, if sustained, ensures the eventual loss of unique and irreplaceable climate histories, as well as profound economic, agricultural, and cultural impacts on local communities.
Assembly of the IXPE Mirror Modules
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Computational Materials Modeling
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2021 Intern Experience: NASA Armstrong Flight Research Center
A collection of intern abstracts from the Summer 2021 Cohort at NASA Armstrong Flight Research Center.
Climate Drivers of Arctic Tundra Variability and Change Using an Indicators Framework
This study applies an indicators framework to investigate climate drivers of tundra vegetation trends and variability over the 1982–2019 period. Previously known indicators relevant for tundra productivity (summer warmth index (SWI), coastal spring sea-ice (SI) area, coastal summer open-water (OW)) and three additional indicators (continentality, summer precipitation, and the Arctic Dipole (AD): second mode of sea level pressure variability) are analyzed with maximum annual Normalized Difference Vegetation Index (MaxNDVI) and the sum of summer bi-weekly (time-integrated) NDVI (TI-NDVI) from the Advanced Very High Resolution Radiometer time-series. Climatological mean, trends, and correlations between variables are presented. Changes in SI continue to drive variations in the other indicators. As spring SI has decreased, summer OW, summer warmth, MaxNDVI, and TI-NDVI have increased. However, the initial very strong upward trends in previous studies for MaxNDVI and TI-NDVI are weakening and becoming spatially and temporally more variable as the ice retreats from the coastal areas. TI-NDVI has declined over the last decade particularly over High Arctic regions and southwest Alaska. The continentality index (CI) (maximum minus minimum monthly temperatures) is decreasing across the tundra, more so over North America than Eurasia. The relationship has weakened between SI and SWI and TI-NDVI, as the maritime influence of OW has increased along with total precipitation. The winter AD is correlated in Eurasia with spring SI, summer OW, MaxNDVI, TI-NDVI, the CI and total summer precipitation. This winter connection to tundra emphasizes the role of SI in driving the summer indicators. The winter (DJF) AD drives SI variations which in turn shape summer OW, the atmospheric SWI and NDVI anomalies. The winter and spring indicators represent potential predictors of tundra vegetation productivity a season or two in advance of the growing season.
Assembly of the IXPE Mirror Modules
Expected to launch in December 2021, the Imaging X-ray Polarimetry Explorer (IXPE) is a NASA Astrophysics Small Explorer Mission with significant contributions from the Italian space agency (ASI). Three identical x-ray telescopes combine to form the IXPE Observatory. Each is comprised of a 4-m-focal length mirror module assembly (MMA, provided by Marshall Space Flight Center) that focuses x-rays onto a polarization-sensitive, imaging detector (contributed by ASI-funded institutions). This paper describes the now-completed assembly process for the 3 flight and one spare mirror modules, and compares as-tested calibrated performance with as-built metrology data. Unexpected challenges and lessons-learned are also discussed.
Non-Equilibrium Matter - The Next Decade and Beyond in Space Materials Research
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Experiment for Cryogenic Large-Aperture Intensity Mapping: Instrument Design
The EXperiment for Cryogenic Large-Aperture Intensity Mapping (EXCLAIM) is a balloon-borne tele-33scope designed to survey star formation in windows from the present to z=3.5. During this time, the rate of star34formation dropped dramatically, while dark matter continued to cluster. EXCLAIM maps the redshifted emission35of singly-ionized carbon lines and carbon monoxide using intensity mapping, which permits a blind and complete36survey of emitting gas through statistics of cumulative brightness fluctuations. EXCLAIM achieves high sensitivity37using a cryogenic telescope coupled to six integrated spectrometers employing kinetic inductance detectors covering38420540GHz with spectral resolving power R=512and angular resolution⇡40. The spectral resolving power and39cryogenic telescope allow the survey to access dark windows in the spectrum of emission from the upper atmosphere.40EXCLAIM will survey305 deg2in the Sloan Digital Sky Survey Stripe 82 field from a conventional balloon flight41in 2023. EXCLAIM will also map several galactic fields to study carbon monoxide and neutral carbon emission as42tracers of molecular gas. Here, we summarize the design phase of the mission.
Elevating the Use of Genetic Engineering to Support Sustainable Plant Agriculture for Human Space Exploration
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USA Crop Yield Estimation with MODIS NDVI: Are Remotely Sensed Models Better Than Simple Trend Analyses?
Crop yield forecasting is performed monthly during the growing season by the United States Department of Agriculture’s National Agricultural Statistics Service. The underpinnings are long-established probability surveys reliant on farmers’ feedback in parallel with biophysical measurements. Over the last decade though, satellite imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) has been used to corroborate the survey information. This is facilitated through the Global Inventory Modeling and Mapping Studies/Global Agricultural Monitoring system, which provides open access to pertinent real-time normalized difference vegetation index (NDVI) data. Hence, two relatively straightforward MODIS-based modeling methods are employed operationally. The first model constitutes mid-season timing based on the maximum peak NDVI value, while the second is reflective of late-season timing by integrating accumulated NDVI over a threshold value. Corn model results nationally show the peak NDVI method provides a R^(2) of 0.88 and a coefficient of variation (CV) of 3.5%. The accumulated method, using an optimally derived 0.58 NDVI threshold, improves the performance to 0.93 and 2.7%, respectively. Both these models outperform simple trend analysis, which is 0.48 and 7.4%, correspondingly. For soybeans the R^(2) results of the peak NDVI model are 0.62, and 0.73 for the accumulated using a 0.56 threshold. CVs are 6.8% and 5.7%, respectively. Spring wheat’s R2performance with the accumulated NDVI model is 0.60 but just 0.40 with peak NDVI. The soybean and spring wheat models perform similarly to trend analysis. Winter wheat and upland cotton show poor model performance, regardless of method. Ultimately, corn yield forecasting derived from MODIS imagery is robust, and there are circumstances when forecasts for soybeans and spring wheat have merit too.
Fast Assessment of Metal Performance through Dislocation Physics and Machine Learning
The microstructure of metals is key to their mechanical properties. The types, density, composition and morphology of crystal defects all have pronounced impact on the properties. Changes to the microstructure occurring during processing and use can be very striking. The emerging technology additive manufacturing (AM) has the potential to improve performance by allowing optimized designs, but the process and environments can lead to unusual microscale features whose properties must be understood and characterized to enable higher technological readiness levels and application. Experimentally, an extensive evaluation of mechanical properties of 3D printed metals is a challenge, and anomalous effects related to the AM process add complexity. We present a new machine learning (ML) model predicting mechanical response based on dislocation mediated plasticity simulations. A large set of 3D discrete dislocation dynamics simulations with wide ranges of loading conditions is transformed to preprocessed data ready for training with the ML model. The trained model can predict the mechanical response of Mo30W for a given microstructure evolution, providing key information essential for optimization of AM processing.
Evaluation of Extreme Soil Moisture Patterns over the Sahel during the 2020 Growing Season
The African Sahel is an ecologically and climatically sensitive region, and thus is a valuable test case for examination of climate extremes. Above-average rainfall during the 2020 growing season (June-October) led to flooding in the West, Central and East Sahel, with implications for infrastructure, agriculture and disease outbreaks. In this study, we evaluate soil moisture patterns in the region during 2020 to assess and quantify the extremeness of the event. The primary tool is the NASA Soil Moisture Active Passive (SMAP) Level 4 surface soil moisture data. Daily, monthly, and seasonal anomalies are computed relative to SMAP’s long-term mean (2015-2021). Additional comparisons are made with longer-time-series data sets, including surface soil moisture from NASA’s Modern-Era Retrospective analysis for Research and Applications, Version 2(MERRA-2; 1981-present) and precipitation from the African Rainfall Climatology, Version 2 (ARC2; 1983-present).Possible drivers of the extreme wet event are examined, including potential links to the concurrent 2020-21 La Niña event. Finally, we explore the connections between the extreme soil moisture and vector-borne disease outbreaks in the region in2020, namely, Rift Valley Fever in Mauritania and Chikungunya in Chad.