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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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Photos in each group are in chronological order as captured: Group I Tank Platform Setup, November 14, 2017; Group II Tank Setup, November 15, 2017; Group III Aboveground Injestion System (AIS) Setup, November 20, 2017; Group IV Chemical Mixing, November 21, 2017; Group V KB-1 Bacteria Injection, November 27, 2017; Group VI Miscellaneous.
Dynamic and static testing of selected plastics for determination of mechanical properties
NASA's Office of Space Science and Applications (OSSA) gave a select group of scientists the opportunity to test and implement their computational algorithms on the Massively Parallel Processor (MPP) located at Goddard Space Flight Center, beginning in late 1985. One year later, the Working Group presented its report, which addressed the following: algorithms, programming languages, architecture, programming environments, the way theory relates, and performance measured. The findings point to a number of demonstrated computational techniques for which the MPP architecture is ideally suited. For example, besides executing much faster on the MPP than on conventional computers, systolic VLSI simulation (where distances are short), lattice simulation, neural network simulation, and image problems were found to be easier to program on the MPP's architecture than on a CYBER 205 or even a VAX. The report also makes technical recommendations covering all aspects of MPP use, and recommendations concerning the future of the MPP and machines based on similar architectures, expansion of the Working Group, and study of the role of future parallel processors for space station, EOS, and the Great Observatories era.
The primary goal of this project was to improve constraints on dark energy measurements by improving our ability to extract cosmological information from low redshift large-scale structures. PI Clowe's project's primary aim was to reduce the bias in measurements of the masses of clusters of galaxies to a level where the evolution of the cluster mass function can be used in the Vera Rubin Observatory's Legacy Survey of Space and Time Dark Energy Science Collaboration survey to improve the accuracy of the measurement of dark energy and other cosmological parameters. Co-PI Seo's project studied observational systematics affecting large-scale clustering of galaxies, which will be used to improve dark energy constraints from the Dark Energy Spectroscopic Instrument (DESI). The cluster lensing project employed a series of simulations and observations of clusters of galaxies to test numerous potential systematic errors in cluster mass measurements using weak gravitational lensing as the accuracy of current weak lensing measurements are more than order of magnitude worse than what is required to use clusters of galaxies for accurate determination of dark energy parameters. PI Clowe and group developed and analyzed simulations to test for, and correct biases introduced in, the weak lensing measurement process. Finally, PI Clowe and group developed a method of detecting clusters using galaxy overdensities and applied the method to the BLISS and DES surveys. The success of spectroscopic dark energy mission such as the extended Baryon Oscillation Spectroscopic Survey (eBOSS) and the Dark Energy Spectroscopic Instrument (DESI) will depend on a thorough understanding of various observational systematics in the target density fluctuations that would give rise to spurious, non-cosmological signals. PI Seo and group developed a deep learning, artificial neural network (ANN) technique that modeled and mitigated such effects, aimed at deriving more robust galaxy clustering signals not only for the baryon acoustic oscillation feature and redshift-space distortions but also for primordial non-Gaussianity constraint.
Neutron transport simulations are ubiquitous in nuclear engineering because they allow one to model experimental systems and render a model platform for easy perturbation of experimental designs. In addition, simulations allow one to gain experimental insight without actually having to go through the trouble of building a physical experiment. Neutron transport simulations can be stochastic or deterministic based. Stochastic neutron transport simulations are typically simulated using the Monte Carlo method and yield very accurate solutions but are computationally expensive, while deterministic methods are typically faster but can be less accurate. Here we focus on optimizing the accuracy of deterministic neutron transport simulations for radiotherapy simulations. Deterministic neutron transport requires discretization of angle, energy, and space to appropriately analyze the system one is trying to model. Discretization of energy is challenging because of the highly variable neutron flux at certain neutron energies. Improper discretization of energy in the transport model can lead to erroneous results and therefore inaccurate interpretations of the solution. In this study, we evaluate Particle Swarm Optimization (PSO) as a mechanism for selecting optimal group structures for radiotherapy shielding. We tested the particle swarm optimization algorithm on radiotherapy shielding problems using Los Alamos National Laboratory's (LANL) main deterministic transport code PARTISN. Results show that the optimized energy group structures generated from the optimization algorithm outperformed LANL's standard energy group structures, and therefore demonstrate utility in using PSO to expedite computation times due to the increased accuracy obtained with a smaller but optimized group structure. (authors)
A comprehensive examination of cardiovascular autonomic response to motion sickness was studied and whether differences in cardiopulmonary function exist in high and low susceptibility groups were determined. Measurement techniques were developed as was test equipment for its ability to provide accurately new measures of interest and to test the adequately of these new measures in differentiating between susceptibility groups. It was concluded that these groups can be differentiated using simple, brief stressors and measurements of cardiodynamic function.
A second experimental Round Robin on the measurement of the crack opening load in fatigue crack growth tests has been completed by the ASTM Task Group E24.04.04 on Crack Closure Measurement and Analysis. Fourteen laboratories participated in the testing of aluminum alloy compact tension specimens. Opening-load measurements were made at three crack lengths during constant Delta K, constant stress ratio tests by most of the participants. Four participants made opening-load measurements during threshold tests. All opening-load measurements were based on the analysis of specimens compliance behavior, where the displacement/strain was measured either at the crack mouth or the mid-height back face location. The Round Robin data were analyzed for opening load using two non-subjective analysis methods: the compliance offset and the correlation coefficient methods. The scatter in the opening load results was significantly reduced when some of the results were excluded from the analysis population based on an accept/reject criterion for raw data quality. The compliance offset and correlation coefficient opening load analysis methods produced similar results for data populations that had been screened to eliminate poor quality data.
Recovery of lithium from brines by liquid-liquid solvent extraction (LLE) with diketones and synergistic co-ligands has been investigated for decades, but industrial application has been limited. In pursuit of a ligand with improved properties, a series of ketonamides with beta-carbonyl groups were designed, synthesized, and tested in extraction of lithium from sulfate and carbonate simulants of clay mineral tailing leachates. The best performing ligand, a novel tricarbonyl amide, was characterized for lithium extraction with and without four synergistic co-ligands. Further, the tricarbonyl amide combined with the synergistic co-ligand Cyanex-923 was absorbed on a resin support. The ligand-modified resin was tested for performance in extraction of dilute brine simulants and up to 60 % recovery of lithium was achieved.
Highlights: • TDAG51 expression is low but detectable in undamaged skeletal muscle. • Muscle expression of TDAG51 increases significantly in response to damage and insulin-like growth factor 1 (IGF-1). • Mice lacking TDAG51 display reduced functional capacity and a delay in the early regenerative phases of muscle repair. • Despite early delays in regeneration, TDAG51null mice can compensate and normalize muscle repair by 10 days post injury. The capacity for skeletal muscle to repair from daily insults as well as larger injuries is a vital component to maintaining muscle health over our lifetime. Given the importance of skeletal muscle for our physical and metabolic well-being, identifying novel factors mediating the growth and repair of skeletal muscle will thus build our foundational knowledge and help lead to potential therapeutic avenues for muscle wasting disorders. To that end, we investigated the expression of T-cell death associated gene 51 (TDAG51) during skeletal muscle repair and studied the response of TDAG51 deficient (TDAG51{sup -/-}) mice to chemically-induced muscle damage. TDAG51 mRNA and protein expression within uninjured skeletal muscle is almost undetectable but, in response to chemically-induced muscle damage, protein levels increase by 5 days post-injury and remain elevated for up to 10 days of regeneration. To determine the impact of TDAG51 deletion on skeletal muscle form and function, we compared adult male TDAG51{sup -/-} mice with age-matched wild-type (WT) mice. Body and muscle mass were not different between the two groups, however, in situ muscle testing demonstrated a significant reduction in force production both before and after fatiguing contractions in TDAG51{sup -/-} mice. During the early phases of the regenerative process (5 days post-injury), TDAG51{sup -/-} muscles display a significantly larger area of degenerating muscle tissue concomitant with significantly less regenerating area compared to WT (as demonstrated by embryonic myosin heavy chain expression). Despite these early deficits in regeneration, TDAG51{sup -/-} muscles displayed no morphological deficits by 10 days post injury compared to WT mice. Taken together, the data presented herein demonstrate TDAG51 expression to be upregulated in damaged skeletal muscle and its absence attenuates the early phases of muscle regeneration.
Plasma simulations involving collisional-radiative processes present many computational challenges because of the wide range in scales spanned by the governing set of plasma physics equations. These numerical challenges are primarily caused by limitations in resources such as memory and computational time. Collisional-radiative models deliver a part of the challenge because of the large number of levels and transitions that are associated with atomic plasmas. Multiple complexity reduction techniques have been introduced in the past to overcome this obstacle, including the quasi-steady-state solution, uniform grouping, and the recently-devised Boltzmann grouping. These reduction schemes were tested against full numerical simulations of a simplified, time-dependent argon model, with and without an external Planckian radiation field. Lastly, results will show the advantages and disadvantages of using complexity reduction techniques when employed in various plasma regimes.
The Sixth Assessment Report (AR6) of the Intergovernmental Panel on Climate Change (IPCC) has adopted the FAIR Guiding Principles. We present the Atlas chapter of Working Group I (WGI) as a test case. We describe the application of the FAIR principles in the Atlas, the challenges faced during its implementation, and those that remain for the future. We introduce the open source repository resulting from this process, including coding (e.g., annotated Jupyter notebooks), data provenance, and some aggregated datasets used in some figures in the Atlas chapter and its interactive companion (the Interactive Atlas), open to scrutiny by the scientific community and the general public. We describe the informal pilot review conducted on this repository to gather recommendations that led to significant improvements. Finally, a working example illustrates the re-use of the repository resources to produce customized regional information, extending the Interactive Atlas products and running the code interactively in a web browser using Jupyter notebooks.
The ability to rapidly screen material performance in the vast space of high entropy alloys is of critical importance to efficiently identify optimal hydride candidates for various use cases. Given the prohibitive complexity of first principles simulations and large-scale sampling required to rigorously predict hydrogen equilibrium in these systems, we turn to compositional machine learning models as the most feasible approach to screen on the order of tens of thousands of candidate equimolar high entropy alloys (HEAs). Critically, we show that machine learning models can predict hydride thermodynamics and capacities with reasonable accuracy (e.g. a mean absolute error in desorption enthalpy prediction of ~5 kJ mol H 2 –1 ) and that explainability analyses capture the competing trade-offs that arise from feature interdependence. We can therefore elucidate the multi-dimensional Pareto optimal set of materials, i.e., where two or more competing objective properties can't be simultaneously improved by another material. This provides rapid and efficient down-selection of the highest priority candidates for more time-consuming density functional theory investigations and experimental validation. Various targets were selected from the predicted Pareto front (with saturation capacities approaching two hydrogen per metal and desorption enthalpy less than 60 kJ mol H 2 –1 ) and were experimentally synthesized, characterized, and tested amongst an international collaboration group to validate the proposed novel hydrides. Finally, additional top-predicted candidates are suggested to the community for future synthesis efforts, and we conclude with an outlook on improving the current approach for the next generation of computational HEA hydride discovery efforts.
Abstract The common dolphinfish (Coryphaena hippurus) is an epipelagic, mid-trophic level, highly migratory species distributed throughout the world’s tropical and subtropical oceans in waters greater than 20°C. Life-history variables, migratory behaviour, and genetic markers have been used to define major stocks in the central Atlantic Ocean and Mediterranean Sea. Here, we used the mitochondrial DNA gene NADH subunit 1 (688 bp) to test for differences between population groups. A total of 103 haplotypes were detected among 203 fish. Gene diversities in samples were large and similar among populations (mean h = 0.932; range 0.894–0.987), but nucleotide diversities varied widely among samples (range π = 0.004–0.034) and appear to reflect population histories. Principal component analysis revealed two large populations groups, and the analysis of molecular variation and pairwise values of ΦST resolved population structure within these groups. Populations in the eastern Atlantic and Mediterranean showed the largest amounts of divergence from one another (ΦCT = 0.331). Adult movement and biophysical barriers to larval dispersal may explain contemporary differences between stocks, but the divergent populations in the Mediterranean Sea are likely due to isolations by cold temperature barriers during Pleistocene glaciations. The geographically large stock groupings require international cooperation in the harvest management and conservation of local dolphinfish populations.
Among the most critical water contaminants of concern affecting wide geographical regions and a number of industries and natural systems is selenium. Selenium found in surface, ground and wastewater in originates from natural sources, as well as industrial sources such as petroleum refineries, electronics manufacturing, pesticides, and coal power plants and mining also contribute to selenium contamination in water in the US. At high concentrations, selenium is toxic to human and wildlife. There are a number of technologies that have been used to treat selenium and other similar contaminants in water. Biological treatment of selenium has been used in the past to reduce soluble SeVI and/or SeIV to insoluble Se0, which is then filtered in the same vessel. The insoluble selenium (Se0) is then backwashed from the system and solids are separated for subsequent disposal, if they meet the leaching and water content criteria. In order to promote biological reduction to insoluble Se0, heating of bioreactor is needed in some applications, and excess food source (electron donor) is added so that all selenium can be filtered. An additional disadvantage of these systems is the significant amount of water lost due to extensive and frequent backwash and rinse cycles. When comparing the advantages and energy requirements of the various treatment technologies, RO membrane filtration immediately stands out due to the excessive energy expenditure needed to pump water across the membrane although RO is an effective way to remove selenium. In addition, RO requires extensive pretreatment, such as MF membrane, and frequent maintenance, rendering it an expensive option that may be out of reach for certain applications. In fact, although the performance was good during the pilot testing by the NSMP Working Group for treatment naturally occurring selenium in the surface water, the high electricity requirements and significant reject water stream made it an infeasible alternative. While conventional ion exchange maybe an effective treatment option, it requires frequent regeneration of the resin when applied to highly contaminated water, which leads to several tons of contaminant-laden, high-salinity brine that needs to be disposed off-site each day. One of the water systems in the west coast currently uses ion exchange for selenium treatment and has been trucking selenium laden hazardous brine waste weekly in the last several years. Pneumatic pumping and rinse water pumping required for ion exchange also increase the energy usage. In comparison, adsorption process is a passive treatment system where contaminated water comes in contact with an adsorption media in a vessel. Typically, there is no mixing, backwash, or recycle pumping required, thus significantly reducing the energy usage. A passive single-use adsorption system does not require backwash, thereby generating small amount of process waste, and producing the highest water yield among the alternatives. The energy and water efficiencies, and applicability for SeVI and SeIV are summarized in Table 1. Despite these benefits though, adsorption typically does not work for the most oxidized form of selenium (SeVI). The innovative biosorption process integrates both process to increase the treatment efficiency while minimizing energy, chemical, and time required to treat both SeVI and SeIV. Additional advantages include simple partial biological reduction with reduced on-site waste generation, which lead to water and electricity savings, and less operational need compared to biological treatment alone. This makes biosorption especially suitable for remote areas, where liquid backwash and brine disposal may be cost prohibitive or infeasible.
Bright Lyα blobs (LABs)—extended nebulae with sizes of ∼100 kpc and Lyα luminosities of ∼10{sup 44} erg s{sup −1}—often reside in overdensities of compact Lyα emitters (LAEs) that may be galaxy protoclusters. The number density, variance, and internal kinematics of LABs suggest that they themselves trace group-like halos. Here, we test this hierarchical picture, presenting deep, wide-field Lyα narrowband imaging of a 1° × 0.°5 region around a LAB pair at z = 2.3 discovered previously by a blind survey. We find 183 Lyα emitters, including the original LAB pair and three new LABs with Lyα luminosities of (0.9--1.3)×10{sup 43} erg s{sup −1} and isophotal areas of 16–24 arcsec{sup 2}. Using the LAEs as tracers and a new kernel density estimation method, we discover a large-scale overdensity (Boötes J1430+3522) with a surface density contrast of δ{sub Σ}=2.7, a volume density contrast of δ ∼10.4, and a projected diameter of ≈20 comoving Mpc. Comparing with cosmological simulations, we conclude that this LAE overdensity will evolve into a present-day Coma-like cluster with log(M/M{sub ⊙}) ∼ 15.1 ± 0.2. In this and three other wide-field LAE surveys re-analyzed here, the extents and peak amplitudes of the largest LAE overdensities are similar, not increasing with survey size, and implying that they were indeed the largest structures then and today evolve into rich clusters. Intriguingly, LABs favor the outskirts of the densest LAE concentrations, i.e., intermediate LAE overdensities of δ{sub Σ}=1--2. We speculate that these LABs mark infalling protogroups being accreted by the more massive protocluster.
In the assembly of hybrid microcircuits, passive and active discrete chip components are attached by epoxy cements and by solders. This study was initiated to determine the integrity of such attachments. Alumina substrates were subjected to a group of thermal and mechanical test environments defined by test methods in MIL-STD-883. Lot samples of substrates with assembly variations were subjected to separately applied testing and to serial testing. These test methods were applied sequentially to the same lot of substrates. Epoxy cements were generally satisfactory with respect to separate tests, although sequential tests severely degraded epoxy bond strengths of all types. Bond strengths to unglazed substrates were slightly superior to those of the same components on glazed types. Solder joints were vulnerable to catastrophic failure in several environments, especially temperature cycling and thermal shock. Vibration and impact shock also produced solder joint failures.
Tests were conducted with two groups of 8.89-centimeter (3.5-in.) pitch diameter spur gears with standard 20 deg involute profile with tip relief made of CVM Super-Nitralloy (5Ni-2Al) and CVM AISI M-50 at a temperature of 350 K (170 F). Super-Nitralloy gears with tip relief had a life 150 percent that of gears without tip relief. An increased scoring phenomenon was noted with the Super-Nitralloy gears with tip relief. Through-hardened AISI M-50 gears with tip relief failed due to tooth fracture. AISI M-50 gears without tip relief had a life approximately 40 times greater than the AISI M-50 gears with tip relief.
The Land Use Management Information System (LUMIS) consists of a methodology of compiling land use maps by means of air photo interpretation techniques, digitizing these and other maps into machine-readable form, and numerically overlaying these various maps in two computer software routines to provide land use and natural resource data files referenced to the individual census block. The two computer routines are the Polygon Intersection Overlay System (PIOS) and an interactive graphics APL program. A block referenced file of land use, natural resources, geology, elevation, slope, and fault-line items has been created and supplied to the Los Angeles Department of City Planning for the City's portion of the Santa Monica Mountains. In addition, the interactive system contains one hundred and seventy-three socio-economic data items created by merging the Third Count U.S. Census Bureau tapes and the Los Angeles County Secured Assessor File. This data can be graphically displayed for each and every block, block group, or tract for six test tracts in Woodland Hills, California. Other benefits of LUMIS are the knowledge of air photo availability, flight pattern coverage and frequencies, and private photogrammetry companies flying Southern California, as well as a formal Delphi study of relevant land use informational needs in the Santa Monicas.