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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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173 records · Page 10

Validation of Heat Transfer Correlations in Line Chill-Down Tests of Cryogenic Fluid in SINDA/FLUINT

Line chill-down is an important process in cryogenic tank propellant management, storage, and usage Complex flow dynamics during these processes: boiling heat transfer (film, transition, and nucleate) Understanding boiling phenomena can lead to efficient line chill-down systems that use less propellant, propellant stored, reducing cost for space missions Line Chill-down heat transfer was modelled using SINDA/FLUINT version 5.8 (SF) Multiple chill-down tests were modelled using: heat transfer correlations readily available in SF using HTN/HTC TIES heat transfer empiricisms developed by the University of Florida (UF) based on a series of liquid nitrogen chill-down tests using SF HTU TIES Chill-down tests modelled: liquid nitrogen tests conducted by the University of Florida horizontal flow, upward flow, and downward flow (Reynolds Numbers ranging 850-231,000)liquid hydrogen tests conducted by NASA Glenn Research Center vertical upward flow (Reynolds Number range of 18,400 - 433,000)The flow rate was measured far downstream of the test section, near the system exit. Where to set the flow rate? SF was highly sensitive, and sometime unstable, setting the test flow rate downstream (the outlet) of the test section model and setting the test pressure upstream (the inlet) of the test section model higher flow rate oscillations at the entrance of the model's test section SF was more stable setting the test flow rate upstream (than the downstream flow rate set case)test pressure was used as an inlet (SF plenum) to set the thermodynamic state (temperature and quality) coming into the system setting the appropriate downstream pressure was the unknown. The pressure drops predicted by SF for the downstream set flow rate boundary condition were much smaller than test section measured pressure drops. The multiphase pressure drop correlations used internally in SF may need to be adjusted. Models with an upstream flow rate set assumed a pressure drop that was small

cryogenic modeling↗

Curating NASA's Past, Present, and Future Extraterrestrial Sample Collections

As codified in NASA Policy Directive 7100.10F, the Astromaterials Acquisition and Curation Office at NASA Johnson Space Center (hereafter JSC Curation) is charged with curation of all extraterrestrial material under NASA control, including future NASA missions. JSC Curation curates all or part of nine astromaterial collections in seven clean room suites: (1) Apollo Samples (1969; ISO 6-7), (2) Luna Samples (from USSR; 1972; ISO 7), (3) Antarctic Meteorites (1976; ISO 7), (4) Cosmic Dust (1981; ISO 5), (5) Microparticle Impact Collection (formerly called Space Exposed Hardware; 1985; ISO 5), (6) Genesis Solar Wind Atoms (2004; ISO 4); (7) Stardust Comet Particles (2006; ISO 5), (8) Stardust Interstellar Particles (2006; ISO 5), (9) Hayabusa Asteroid Particles (from JAXA; 2010; ISO 5). In addition to the labs that house the samples, we have installed and maintained a wide variety of facilities and infrastructure required to support the clean-rooms: more than 10 different HEPA-filtered air-handling systems, ultrapure dry gaseous nitrogen systems, an ultrapure water system (UPW) and cleaning facilities to provide clean tools and equipment for the labs. We also have sample preparation facilities for making thin sections, microtome sections, and even focused ion-beam (FIB) sections to meet the research requirements of scientists. To ensure that we are keeping the samples as pristine as possible, we routinely monitor the cleanliness of our clean rooms and infrastructure systems. This monitoring includes: daily monitoring of the quality of our UPW, weekly airborne particle counts in the labs, monthly monitoring of the stable isotope composition of the gaseous N2 system, and annual measurements of inorganic or organic contamination in processing cabinets. We track within our databases the current and ever-changing characteristics of more than 250,000 individual samples across our various collections (including the 19,141 samples on loan to 433 Principal Investigators in 24 countries). The next sample return missions that NASA will participate in are Hayabusa2 and OSIRIS-REx (Origins Spectral Interpretation Resource Identification Security - Regolith Explorer). The designs for a new state-of-the-art suite of clean rooms to house these samples at JSC have been finalized. This includes separate ISO class 5 clean rooms to house each collection, a common ISO class 7 area for general use, an ISO class 7 microtome laboratory, and a separate thin section lab. Additionally, a new cleaning facility is being designed and procedures developed that will allow for enhanced cleaning of cabinets and tools in an inorganically, organically, and biologically clean manner. We are also designing a large multi-purpose Advanced Curation laboratory that will allow us to develop the techniques necessary to fully support the Hayabusa2 and OSIRIS-REx missions, as well as future possible sample return missions (e.g., Lunar Polar Volatiles, Mars, Comet Surface). A micro-CT (micro Computed Tomography) laboratory dedicated to the study of astromaterials has come online within JSC Curation, and we plan to add additional facilities that will enable non-destructive (or minimally-destructive) analyses of astromaterials in the near future (e.g., micro-XRF (micro X-Ray Fluorescence), confocal imaging Raman Spectroscopy). These facilities will be available to: (1) develop sample handling and storage techniques for future sample return missions, (2) be utilized by PET (Positron Emission Tomography) for future sample return missions, (3) for retroactive PET-style analyses of our existing collections, and (4) for periodic assessments of the existing sample collections.

Zeigler, Ryan A.↗

Validation of Heat Transfer Correlations in Line Chill-Down Tests of Cryogenic Fluid in SINDA/FLUINT

Line Chill-down heat transfer was modelled using SINDA/FLUINT. Multiple chill-down tests were modelled using the heat transfer correlations that are available in SINDA/FLUINT, as well as incorporating heat transfer empiricisms developed by the University of Florida1 based on a series of liquid nitrogen chill-down tests. The chill-down tests that were modelled were the liquid nitrogen tests conducted by the University of Florida1 as well as liquid hydrogen tests conducted by NASA Glenn Research Center2. The liquid nitrogen tests included horizontal flow, upward flow, and downward flow with the liquid Reynolds Numbers ranging 850 - 231,000. The liquid hydrogen test was vertical upward flow at a Reynolds Number range of 18,400 - 433,000. Both the University of Florida's heat transfer correlations and SINDA/FLUINT's internal correlations faired similarly to wall temperature test data. They were acceptable although improvements could be made to the University of Florida correlations as well and SINDA/FLUINT's internal correlations.

cryogenic modeling↗

Three Red Suns in the Sky: A Transiting, Terrestrial Planet in a Triple M-dwarf System at 6.9 pc

We present the discovery from Transiting Exoplanet Survey Satellite (TESS) data of LTT 1445Ab. At a distance of 6.9 pc, it is the second nearest transiting exoplanet system found to date, and the closest one known for which the primary is an M dwarf. The host stellar system consists of three mid-to-late M dwarfs in a hierarchical configuration, which are blended in one TESS pixel. We use MEarth data and results from the Science Processing Operations Center data validation report to determine that the planet transits the primary star in the system. The planet has a radius of {1.38}_{-0.12}^{+0.13} {R}_{\oplus }, an orbital period of {5.35882}_{-0.00031}^{+0.00030} days, and an equilibrium temperature of {433}_{-27}^{+28} K. With radial velocities from the High Accuracy Radial Velocity Planet Searcher, we place a 3σ upper mass limit of 8.4 {M}_{\oplus } on the planet. LTT 1445Ab provides one of the best opportunities to date for the spectroscopic study of the atmosphere of a terrestrial world. We also present a detailed characterization of the host stellar system. We use high-resolution spectroscopy and imaging to rule out the presence of any other close stellar or brown dwarf companions. Nineteen years of photometric monitoring of A and BC indicate a moderate amount of variability, in agreement with that observed in the TESS light-curve data. We derive a preliminary astrometric orbit for the BC pair that reveals an edge-on and eccentric configuration. The presence of a transiting planet in this system hints that the entire system may be co-planar, implying that the system may have formed from the early fragmentation of an individual protostellar core.

Binaries↗

Detecting water hazards for autonomous off-road navigation

Detecting water hazards for autonomous, off-road navigation of unmanned ground vehicles is a largely unexplored problem. In this paper, we catalog environmental variables that affect the difficulty of this problem, including day vs. night operation, whether the water reflects sky or other terrain features, the size of the water body, and other factors. We briefly survey sensors that are applicable to detecting water hazards in each of these conditions. We then present analyses and results for water detection for four specific sensor cases: 1) using color image classification to recognize sky reflections in water during the day, 2) using ladar to detect the presence of water bodies and to measure their depth, 3) using short-wave infrared (SWIR) imagery to detect water bodies, as well as snow and ice, and 4) using mid-wave infrared (MWIR) imagery to recognize water bodies at night. For color imagery, we demonstrate solid results with a classifier that runs at nearly video rate on a 433 MHz processor. For ladar, we present a detailed propagation analysis that shows the limits of water body detection and depth estimation as a function of look ahead distance, water depth, and ladar wavelength. For SWIR and MWIR, we present sample imagery from a variety of data collections that illustrate the potential of these sensors. These results demonstrate significant progress on this problem.

McHenry, Mike↗

The Infrared Spectrum of H 2 S from 1 to 5 µm

The absorption spectra of H 2 S from 2000 to 11 147 cm -1 have been obtained with spectral resolutions of 0.006, 0.012, and 0.021 cm -1 and optical paths of 1.5 m to 433 m using the Fourier transform spectrometer at Kitt Peak National Observatory/National Solar Observatory. The 20 new vibrational bands have been assigned for the first time and 8 others re-analyzed so that accurate energy levels, band origins, and rotational parameters could be determined for a total of 29 states. Experimental band centers have been modeled by vibrational calculations. Line intensity measurements and analysis are in progress. A prediction of the 4 µm bands of H 2 S is currently available.

absorption↗

On the Rigidity Spectrum of Cosmic-Ray Variations within Propagating InterplanetaryDisturbances: Neutron Monitor and SOHO/EPHIN Observations at∼1–10GV

The rigidity dependence of all Forbush decreases (FDs) recorded from 1995 to 2015 has been determined using neutron monitor (NM) and Solar and Heliospheric Observatory (SOHO) (EPHIN) spacecraft data, covering the energy (rigidity) range from ∼433 MeV (1GV) to 9.10 GeV (10 GV). We analyzed a total of 421 events and determined the spectrum in rigidity with an inverse power-law fit. As a result, the mean spectral index was identified to be 〈γF〉 = 0.46 ± 0.02. The majority (∼66%) of the FDs have γF within the range 0.3–0.7. The remaining one-third of the events (∼33%) have either (very) soft or hard FD spectra, with the latter being more common than the former. Significant variations of γF occur within almost every FD event. During the initial FD decay phase the spectrum becomes gradually harder, in contrast to the recovery phase, when it becomes softer. Additionally, low energies (rigidities) seem to be better suited for studying the fine structure of interplanetary disturbances (primarily interplanetary coronal mass ejections) that lead to FDs. In particular, FDs recorded by the EPHIN instrument on SOHO better capture a two-step structure than FDs observed by NMs. Finally, the ejecta of an ICME, especially when identified as a magnetic cloud, often leads to abrupt changes in the slope of γF.

Anatoly Belov↗

Astromaterial Curation and Research at NASA

Astromaterial sample return missions from other planetary bodies (e.g., the Moon, asteroids, the Sun) and astromaterial sample collection missions here on Earth (e.g., Antarctic Meteorites, Cosmic Dust) have been a vital part of NASA’s science vision since nearly its inception. Beginning with the Apollo missions to the Moon and extending to the recent successful sample collection by the OSIRIS-REx asteroid sample return mission, these astromaterials collections have been an invaluable resource to scientists and educators around the world. Sample studies continue to provide fundamental insight into how our solar system and its constituent bodies formed and evolved over the past 4.5 billion years. As evidence of their broad impact, there are over 19,141 samples on loan to 433 Principal Investigators in 24 countries [1]. As we plan for exploration missions through 2050, sample return missions will continue to play a vital role in NASA’s science vision. Returned samples truly are the gift that keeps on giving. Having the samples accessible on Earth allows new generations of scientists and new generations of instrumentation to pursue ever evolving scientific questions. For example, the Apollo samples were collected ~50 years ago, yet our views of how the Earth-Moon system formed, the role of volatiles in the early inner solar system, and even the positions of the gas giants in the outer solar system have changed dramatically as a result of Apollo sample analyses conducted very recently. Vital to the long-term viability of any sample return mission is the careful curation of the samples. Curatorial efforts need to begin early in the project lifecycle, not with the return of the samples, but at mission conception. The Astromaterials Acquisition and Curation Office at NASA Johnson Space Center is responsible for curating all of NASA’s current and future extraterrestrial samples. Looking at possible sample return missions over the next 35+ years [2], many samples would require curation efforts a step beyond current capabilities, e.g., cold or cryogenic curation, organically and biologically clean curation, curation of gases and ices, and curation of samples with extreme pressure, temperature, or redox requirements. During the lecture, we discuss the current curatorial efforts in JSC curation, as well as discoveries from the astromaterial research. [1] Zeigler, R. A. et al. (2017) Planetary Science Vision 2050 Workshop. [2] McCubbin F. M. et al. (2017) Planetary Science Vision 2050 Workshop.

astromaterial↗

A Transmission Electron Microscopy Study of a Refractory Metal Grain from a Calcium-Aluminum-Rich Inclusion in the Leoville CV3 Chondrite

Introduction: Calcium-aluminum-rich inclusions (CAIs) are an important component of chondritic meteorites. They can contain materials that are thermodynamically predicted and isotopically age dated to be among the first-formed solids in our solar system [1-5]. Observed in some CAIs are micron to sub-micron sized inclusions rich in Fe, Ni, and high-Z elements such as Pt, Os, Ir and W, in the form of refractory metal nuggets (RMNs), fremdlinges, and ‘nugget like objects’ (NLOs) [1,6]. Refractory siderophile elements such as Os, Ir and Ru are thermodynamically predicted to condense at temperatures well in excess of the major CAI phases such as melilite, perovskite, spinel and hibonite [2,7-9]. These refractory metal inclusions in CAIs can therefore serve as probes into the thermodynamic landscape of the early solar protoplanetary disk. Here we report on a refractory grain identified in a CAI of the Leoville CV3 chondrite. This work is part of an ongoing effort to gain insight into the thermochemistry of the early solar system through systematic analyses of the structure and chemistry of various components in CAIs [10-13]. Sample and Analytical Techniques: A fluffy type A CAI (Fig. 1A) was identified in a section of the Leoville, CV3 chondrite (Center for Meteorite Studies, Arizona State University collection, #821_C_3) using a JOEL-JXA 8530F electron microprobe at Arizona State University. Backscattered electron (BSE) imaging and energy-dispersive X-ray spectroscopy (EDS) were used to identify refractory metal grains in the CAI using a Thermo Fisher (formerly FEI) Helios NanoLab 660 G3 focused-ion-beam scanning-electron microscope (FIBSEM) located at the Kuiper Materials Imaging and Characterization Facility (KMICF) at the Lunar and Planetary Laboratory, University of Arizona. The FIB is equipped with an EDAX EDS system. We selected one of the larger (micron-sized) refractory metal grains, designated as ‘Spud’ (Fig. 1B) for further analysis. ‘Spud’ was extracted and thinned to electron transparency (<100 nm) using the FIB-SEM located in KMICF, following methods described by [14- 15]. The FIB section was analyzed using a 200 keV Hitachi HF5000 scanning transmission electron microscope (S/TEM) located at KMICF. The HF5000 is equipped with cold-field emission gun, 3rd-order spherical aberration corrector for STEM imaging, and an Oxford Instruments X-Max N 100 TLE energydispersive spectroscopy (EDS) system with dual 100 mm2 windowless silicon-drift detectors (Ω = 2.0 sr). Selected-area electron-diffraction (SAED) patterns were acquired to aid in determination of crystallinity and phase. Results: The mineralogy, texture, and morphology of the CAI are consistent with that of a fluffy type A (FTA) CAI [16]. BSE imaging at high magnifications revealed grains with high contrast, indicative of compositions rich in elements of higher atomic number relative to surrounding material. These high-Z grains have sizes that range from ∼250 nm to 4 µm. EDS analyses confirm that the bright grains are metal-rich inclusions. A minor fraction of the grains are composed of only Fe and Ni, but the majority (∼60%) of the identified inclusions also contained various refractory siderophiles including Os, Ru, Zr, Ir and Mo. EDS analysis on the FIB-SEM of Spud shows that it contains Fe, Ni, Mo and Ru. High-angle annular dark-field (HAAFD) imaging and EDS mapping in the TEM (Fig. 2) show that Spud occurs in melilite (Ca1.9Al1.99Si1.06O7). Spud contains a subhedral to anhedral morphology and is compositionally heterogenous (polyphasic, Fig. 2). Local spatial correlation occurs among Fe, Ni, and Pt, and also among Os, Ru, and Mo. SAED patterns show that the Fe-Ni-Pt, Fe-Os-Mo-Ru and Fe-Pt regions are crystalline. Discussion: CAIs can contain various types of inclusions rich in Fe, Ni and refractory siderophiles such as Os, Ru, W and Pt [1]. RMNs are micron-sized, single phase alloy grains and can contain Os, Ir, Ru and Rh [1,7,17]. NLOs are also micron-sized inclusions, but contain two phases, a refractory metal, and an oxide [6]. Fremdlinge are the largest of such inclusions (tens of microns in size) and are complex aggregates of Fe-Ni alloy, silicates, oxides, and sulfides [1,17]. While the size of Spud matches previous descriptions of RMNs and NLOs, Spud is neither a single-phase alloy like RMNs, nor does it contain one metal phase and one oxide like NLOs. Spud does not match the above described categories of refractory metal inclusions. The presence of refractory siderophiles such as Mo, Os, Ru, and Pt suggests a high-temperature origin. Thermodynamic modelling by [7] indicates condensation temperatures of 1917 K, 1693 K, 1613 K and 1415 K for Os, Mo, Ru and Pt respectively. These models also show that following the initial condensation of a refractory metal, alloying of solutes such as Fe, Ni and W, occurs in levels proportional to their partial pressures in the surrounding gas. Such alloying occurs at temperatures above the condensation temperatures of common CAI phases such as melilite (1529 K), perovskite (1441 K), spinel (197 K) and forsterite (1354 K) [2]. The polyphasic nature of Spud could be the result of such high-temperature alloying, possibly shortly after the condensation of Mo and Ru at 1693 K and 1613 K respectively. That Spud occurs as an inclusion is consistent with it having formed prior to and at temperature above that of its host melilite in this FTA CAI, which is qualitatively consistent with such prior thermodynamic modeling. Further, the polyphasic nature of Spud is similar to refractory grains from a FTA CAI in the Northwest Africa (NWA) 8323, CV3 chondrite [11-13]. These data suggest that such refractory metal grains could have been widespread in the inner and early solar protoplanetary disk and represent some of the earliest formed solids to have condensed. Acknowledgments: Research and instrumentation supported by NASA grants #NNX12AL47G, #NNX15AJ22G and #80NSSC19K0509, and NSF grants #1531243 and #0619599. Fig 2. STEM data on ‘Spud’. HAADF Image (Top) False-color EDS Maps (Bottom) References: [1] MacPherson G. J. (2014) T. of Geochem. Vol I: Met. And Cosmochem. Processes, 139-179. [2] Lodders K. (2003) ApJ, 591, 1220-1247. [3] Ebel D. S. (2006) Met. & the Early S. Sys. II., 253- 277. [4] Amelin Y. (2002) Science, 297, 1678-1683. [5] Connelly J.N. et.al. (2012) Science, 338, 651-655. [6] Schwander D. et al. (2015) GCA, 18, 70-87. [7] Palme H. and Wlotzka F. (1976) EPSL, 33, 45-60. [8] Berg T. et al. (2009) ApJ, 702, 172-176. [9] Liffman K. et al. (2021) Icarus, 221, 89-105. [10] Zega T.J. et al. (2021) PSJ, 2, 115. [11] Ramprasad T. et al. (2020) LPSC LI, Abstract #2472. [12] Ramprasad T. et al. (2021) Microscopy & Microanalysis, S1, 2792-2794. [13] Ramprasad T. et al. (2021) 84th MetSoc, Abstract #6123. [14] Zega T.J. et al. (2007) MAPS, 42, 1373-1386. [15] Ramprasad T. et al. (2022) MAPS, in revision. [16] Grossman L. (1975), GCA, 39, 433-454. [17] El Goresy A. et al. (1978) LPSC IX, Abstract#1100

T. Ramprasad↗

Communication-Aware Orbit Design for Small Spacecraft Swarms around Small Bodies

Exploration of small Solar System bodies has traditionally been performed by single monolithic spacecraft carrying a number of science instruments. However, science instruments typically cannot be operated simultaneously due to the instrument requirements including optimal viewing angle, surface illumination, altitude and ground resolution, power, and data constraints. This observation has motivated interest in multi-spacecraft architectures where a swarm of small spacecraft, each carrying a single science instrument, studies a small body after being deployed by a carrier spacecraft, which then collects data from the vehicles and relays it to Earth. Such architectures hold promise to yield significant improvements in mission efficiency, increases in data quality, and shorter mission duration. A key difficulty in the design of such missions is the selection of orbits for the small spacecraft, which must satisfy not only instrument requirements, but also strict inter-spacecraft communication and on-board storage constraints. To address this, in this paper, we present a novel computationally-efficient optimization algorithm for \emph{communication-aware design} of the orbits of a small spacecraft swarm orbiting a small body. The proposed approach captures constraints including instrument requirements, inter-spacecraft communication bandwidths, and on-board memory usage, and it can accommodate highly irregular gravity field models and surface geometries. We propose an efficient algorithm for optimization of instrument observations and inter-spacecraft communications; we then leverage the differentiable nature of the proposed algorithm to accelerate a gradient-based global search algorithm. Numerical simulations of a six-spacecraft swarm studying 433 Eros show that the proposed approach successfully identifies high-quality orbits, and significantly outperform communication-agnostic optimization techniques, resulting in a 10% increase in scientific returns and a 30% increase in the quality of the collected data.

Rahmani, Amir↗