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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 73 records · Page 4

Antihelium-3 sensitivity for the GRAMS experiment

The Gamma-Ray and AntiMatter Survey (GRAMS) is a next-generation balloon/satellite mission utilizing a Liquid Argon Time Projection Chamber (LArTPC) detector to measure both MeV gamma rays and antinuclei produced by dark matter annihilation or decay. The GRAMS can identify antihelium-3 events based on the measurements of X-rays and charged pions from the decay of the exotic atoms, Time of Flight (TOF), energy deposition, and stopping range. This paper shows the antihelium-3 sensitivity estimation using a GEANT4 Monte Carlo simulation. For the proposed long-duration balloon (LDB) flight program (35 days x 3 flights) and future satellite mission (2-year observation/10-year observation), the sensitivities become 1.47 × 10 −7 [m 2 s sr GeV/n] −1 and 1.55 × 10 −9 [m 2 s sr GeV/n] −1 /3.10 x 10 -10 [m 2 s sr GeV/n] −1 , respectively. The results indicate that GRAMS can extensively investigate various dark matter models through the antihelium-3 measurements.

Antihelium-3↗

An extreme-halophile archaebacterium possesses the interlock type of prephenate dehydratase characteristic of the Gram-positive eubacteria

The focal point of phenylalanine biosynthesis is a dehydratase reaction which in different organisms may be prephenate dehydratase, arogenate dehydratase, or cyclohexadienyl dehydratase. Gram-positive, Gram-negative, and cyanobacterial divisions of the eubacterial kingdom exhibit different dehydratase patterns. A new extreme-halophile isolate, which grows on defined medium and is tentatively designated as Halobacterium vallismortis CH-1, possesses the interlock type of prephenate dehydratase present in Gram-positive bacteria. In addition to the conventional sensitivity to feedback inhibition by L-phenylalanine, the phenomenon of metabolic interlock was exemplified by the sensitivity of prephenate dehydratase to allosteric effects produced by extra-pathway (remote) effectors. Thus, L-tryptophan inhibited activity while L-tyrosine, L-methionine, L-leucine and L-isoleucine activated the enzyme. L-Isoleucine and L-phenylalanine were effective at micromolar levels; other effectors operated at mM levels. A regulatory mutant selected for resistance to growth inhibition caused by beta-2-thienylalanine possessed an altered prephenate dehydratase in which a phenomenon of disproportionately low activity at low enzyme concentration was abolished. Inhibition by L-tryptophan was also lost, and activation by allosteric activators was diminished. Not only was sensitivity to feedback inhibition by L-phenylalanine lost, but the mutant enzyme was now activated by this amino acid (a mutation type previously observed in Bacillus subtilis). It remains to be seen whether this type of prephenate dehydratase will prove to be characteristic of all archaebacteria or of some archaebacterial subgroup cluster.

NASA Discipline Number 52-30↗

Venus Global Reference Atmospheric Model (GRAM) Upgrades

The inability to test planetary spacecraft in the flight environment prior to a mission requires engineers to rely on ground-based testing and models of the vehicle and expected environments. One of the most widely used engineering models of Venus’ atmosphere is the Venus Global Reference Atmospheric Model (Venus-GRAM).The Venus-GRAM upgrades are being developed by NASA Marshall Space Flight Center and NASA Langley Research Center.

atmospheric models↗

Gram-positive bacterial cell wall components inhibit herpes simplex virus infection

The role of the mucosal microbiome in viral infections remains unclear. Genital herpes, caused by herpes simplex virus 1 and 2 (HSV-1 and HSV-2), is among the most prevalent sexually transmitted infections worldwide. Despite evidence linking vaginal Lactobacillus to protection against sexually transmitted viruses, the specific microbial components and mechanisms that mediate this defense are not well understood. Here, we show that multiple cell wall components from diverse gram-positive bacteria, including lactobacilli, inhibit HSV-1 and HSV-2 infection in cells and in a mouse model of genital herpes infection. Peptidoglycan (PG) and lipoteichoic acid (LTA), both major components of the gram-positive bacterial cell wall, significantly reduced HSV infectivity in vitro and improved survival and disease outcomes in mice. We further showed that Lactobacillus crispatus surface layer proteins SlpA and SlpB bind HSV-1 and inhibit infection. Antiviral effects of cell wall components were dose-dependent, relied on intact PG structure, and, in the case of PG and LTA, were independent of TLR2-mediated host signaling. Collectively, our findings identify a species-independent antiviral function for gram-positive bacterial cell wall components against HSV and suggest that the composition of the mucosal microbiome may play an underappreciated role in suppressing mucosal herpes infection in humans.

Adams↗

Extensive middle atmosphere (20-120 KM) modification in the Global Reference Atmospheric Model (GRAM-90)

The Global Reference Atmospheric Model (GRAM) is currently available in the 'GRAM-88' version (Justus, et al., 1986; 1988), which includes relatively minor upgrades and changes from the 'MOD-3' version (Justus, et al., 1980). Currently a project is underway to use large amounts of data, mostly collected under the Middle Atmosphere Program (MAP) to produce a major upgrade of the program planned for release as the GRAM-90 version. The new data and program revisions will particularly affect the 25-90 km height range. Sources of data and preliminary results are described here in the form of cross-sectional plots.

Justus, C. G.↗

The NASA/MSFC global reference atmospheric model: 1990 version (GRAM-90). Part 2: Program/data listings

A new (1990) version of the NASA/MSFC Global Reference Atmospheric Model (GRAM-90) was completed and the program and key data base listing are presented. GRAM-90 incorporate extensive new data, mostly collected under the Middle Atmosphere Program, to produce a completely revised middle atmosphere model (20 to 120 km). At altitudes greater than 120 km, GRAM-90 uses the NASA Marshall Engineering Thermosphere model. Complete listings of all program and major data bases are presented. Also, a test case is included.

Justus, C. G.↗

Mars Global Reference Atmospheric Model (Mars-GRAM): Release No. 2 - Overview and applications

The Mars Global Reference Atmospheric Model (Mars-GRAM), a science and engineering model for empirically parameterizing the temperature, pressure, density, and wind structure of the Martian atmosphere, is described with particular attention to the model's newest version, Mars-GRAM, Release No. 2 and to the improvements incorporated into the Release No. 2 model as compared with the Release No. 1 version. These improvements include (1) an addition of a new capability to simulate local-scale Martian dust storms and the growth and decay of these storms; (2) an addition of the Zurek and Haberle (1988) wave perturbation model, for simulating tidal perturbation effects; and (3) a new modular version of Mars-GRAM, for incorporation as a subroutine into other codes.

James, B.↗

Mars Global Reference Atmospheric Model 2000 Version (Mars-GRAM 2000): Users Guide

This report presents Mars Global Reference Atmospheric Model 2000 Version (Mars-GRAM 2000) and its new features. All parameterizations for temperature, pressure, density, and winds versus height, latitude, longitude, time of day, and L(sub s) have been replaced by input data tables from NASA Ames Mars General Circulation Model (MGCM) for the surface through 80-km altitude and the University of Arizona Mars Thermospheric General Circulation Model (MTGCM) for 80 to 170 km. A modified Stewart thermospheric model is still used for higher altitudes and for dependence on solar activity. "Climate factors" to tune for agreement with GCM data are no longer needed. Adjustment of exospheric temperature is still an option. Consistent with observations from Mars Global Surveyor, a new longitude-dependent wave model is included with user input to specify waves having 1 to 3 wavelengths around the planet. A simplified perturbation model has been substituted for the earlier one. An input switch allows users to select either East or West longitude positive. This memorandum includes instructions on obtaining Mars-GRAM source code and data files and for running the program. It also provides sample input and output and an example for incorporating Mars-GRAM as an atmospheric subroutine in a trajectory code.

Justus, C. G.↗

Mars-Gram Validation with Mars Global Surveyor Data

Mars Global Reference Atmospheric Model (Mars-GRAM 2001) is an engineering-level Mars atmosphere model widely used for many b4ars mission applications. From 0-80 km, it is based on NASA Ames Mars General Circulation Model (MGCM), while above 80 km it is based on University of Arizona Mars Thermospheric General Circulation Model. Mars-GRAM 2001 and MGCM use surface topography from Mars Global Surveyor Mars Orbiting Laser Altimeter (MOLA). Validation studies are described comparing Mars-GRAM with Mars Global Surveyor Radio Science (RS) and Thermal Emission Spectrometer (TES) data. RS data from 2480 profiles were used, covering latitudes 75deg S to 72deg N, surface to approx. 40 km, for seasons ranging from areocentric longitude of Sun (Ls) = 70-160deg and 265-310deg. RS data spanned a range of local times, mostly 0-9 hours and 18-24 hours. For interests in aerocapture and precision landing, comparisons concentrated on atmospheric density. At a fixed height of 20 km, measured RS density varied by about a factor of 2.5 over the range of latitudes and Ls values observed. Evaluated at matching positions and times, average RS/Mars-GRAM density ratios were generally lf0.05, except at heights above approx. 25 km and latitudes above approx.50deg N. Average standard deviation of RS/Mars-GRAM density ratio was 6%. TES data were used covering surface to approx. 40 km, over more than a full Mars year (February, 1999 - June, 2001, just before start of Mars global dust storm). Depending on season, TES data covered latitudes 85deg S to 85deg N. Most TES data were concentrated near local times 2 hours and 14 hours. Observed average TES/Mars-GRAM density ratios were generally 1+/-0.05, except at high altitudes (15-30 km, depending on season) and high latitudes (> 45deg N), or at most altitudes in the southern hemisphere at Ls approx. 90 and 180deg). Compared to TES averages for a given latitude and season, TES data had average density standard deviation about the mean of approx. 6.5-10.5% (varying with height) for all data, or approx. 5- 12%, depending on time of day and dust optical depth. Average standard deviation of TES/Mars-GRAM density ratio was 8.9% for local time 2 hours and 7.1% for 1o:al time 14 hours. Thus standard deviation of observed TES/Mars-GRAM density ratio, evaluated at matching positions and times, is about the same as the standard deviation of TES data about the TES mean value at a given position and season.

Justus, C. G.↗

Strategies to Improve the Accuracy of Mars-GRAM Sensitivity Studies at Large Optical Depths

The poster provides an overview of techniques to improve the Mars Global Reference Atmospheric Model (Mars-GRAM) sensitivity. It has been discovered during the Mars Science Laboratory (MSL) site selection process that the Mars Global Reference Atmospheric Model (Mars-GRAM) when used for sensitivity studies for TES MapYear = 0 and large optical depth values such as tau = 3 is less than realistic. A preliminary fix has been made to Mars-GRAM by adding a density factor value that was determined for tau = 0.3, 1 and 3.

Justh, Hilary L.↗

Earth Global Reference Atmospheric Model (GRAM) Overview and Updates: DOLWG Meeting

What is Earth-GRAM (Global Reference Atmospheric Model): Provides monthly mean and standard deviation for any point in atmosphere - Monthly, Geographic, and Altitude Variation; Earth-GRAM is a C++ software package - Currently distributed as Earth-GRAM 2016; Atmospheric variables included: pressure, density, temperature, horizontal and vertical winds, speed of sound, and atmospheric constituents; Used by engineering community because of ability to create dispersions in atmosphere at a rapid runtime - Often embedded in trajectory simulation software; Not a forecast model; Does not readily capture localized atmospheric effects.

White, Patrick↗

New Efforts to Update NASA's Global Reference Atmospheric Models (GRAM)

NASA is at the forefront of planetary exploration. The inability to test planetary spacecraft in the flight environment prior to a mission requires engineers to rely on ground-based testing and models of the vehicle and expected environments. One of the most widely used engineering models of the atmosphere for many NASA projects is the Global Reference Atmospheric Model (GRAM) developed by the NASA Marshall Space Flight Center (MSFC). Over the past decade GRAM upgrades and maintenance have depended on inconsistent and waning project-specific support. Recently, the NASA Science Mission Directorate agreed to provide funding support in Fiscal Year 2018 and 2019 to upgrade the GRAMs. This poster summarizes the objectives, tasks and milestones of this effort.

Justh, Hilary↗

New Efforts to Update NASA's Global Reference Atmospheric Models (GRAM)

NASA is at the forefront of planetary exploration. The inability to test planetary space-craft in the flight environment prior to a mission requires engineers to rely on ground-based testing and models of the vehicle and expected environments. One of the most widely used engineering models of the atmosphere for many NASA projects is the Global Reference Atmospheric Model (GRAM) developed by the NASA Marshall Space Flight Center (MSFC). Over the past decade GRAM upgrades and maintenance have depended on inconsistent and waning project-specific support. Recently, the NASA Science Mission Directorate (SMD) has agreed to provide funding support in Fiscal Year 2018 and 2019 to upgrade the GRAMs.

Justh, H. L.↗

New Efforts to Update NASA's Global Reference Atmospheric Models (GRAM)

NASA is at the forefront of planetary exploration. The inability to test planetary spacecraft in the flight environment prior to a mission requires engineers to rely on ground-based testing and models of the vehicle and expected environments. One of the most widely used engineering models of the atmosphere for many NASA projects is the Global Reference Atmospheric Model (GRAM) developed by the NASA Marshall Space Flight Center (MSFC). Over the past decade GRAM upgrades and maintenance have depended on inconsistent and waning project-specific support. Recently, the NASA Science Mission Directorate agreed to provide funding support in Fiscal Year 2018 and 2019 to upgrade the GRAMs. This poster summarizes the objectives, tasks and milestones of this effort.

Dwyer Cianciolo, Alicia↗

Earth Global Reference Atmospheric Model (GRAM) Overview and Comparison to Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2)

Earth-GRAM (Earth-Global Reference Atmospheric Model) Overview: Provides monthly statistics at any point in the atmosphere; Monthly, geographic, altitude variation; Current Version - Earth-GRAM 2016, C++; Output Includes - pressure, density, temperature, horizontal and vertical winds, speed of sound, atmospheric constituents; Used by engineering community to create atmospheric dispersions at a rapid runtime; Not a forecast model. MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications, Version 2) Background: Developed by NASA Goddard Modelling and Assimilation Office; Horizontal Resolution: 0.625 degrees by 0.5 degrees longitude-by-latitude grid (NCEP (National Centers for Environmental Prediction) reanalysis I vs. 2.5 degrees by 2.5 degrees currently used in Earth-GRAM); Vertical resolution: 72 model layers or interpolated to 42 pressure levels to 0.1 hectopascals (hPa) (NCEP reanalysis I, surface to 10hPa at 17 pressure levels).

White, Patrick W.↗

Low synchronization Gram–Schmidt and generalized minimal residual algorithms

The Gram–Schmidt process uses orthogonal projection to construct the A = QR factorization of a matrix. When Q has linearly independent columns, the operator P = I - Q(QTQ)-1QT defines an orthogonal projection onto Q⊥. In finite precision, Q loses orthogonality as the factorization progresses. A family of approximate projections is derived with the form P = I - QTQT, with correction matrix T. When T = (QTQ)-1, and T is triangular, it is postulated that the best achievable orthogonality is $\mathcal{O}(ε)\mathcal{K}(A)$. We present new variants of modified (MGS) and classical Gram–Schmidt algorithms that require one global reduction step. An interesting form of the projector leads to a compact WY representation for MGS. In particular, the inverse compact WY MGS algorithm is equivalent to a lower triangular solve. Our main contribution is to introduce a backward normalization lag into the compact WY representation, resulting in a $\mathcal{O}(ε)\mathcal{K}[r_0, AV_m])$ stable Generalized Minimal Residual Method (GMRES) algorithm that requires only one global reduce per iteration. Finally, further improvements in performance are achieved by accelerating GMRES on GPUs.

97 MATHEMATICS AND COMPUTING↗

Low-synch Gram–Schmidt with delayed reorthogonalization for Krylov solvers

The parallel strong-scaling of iterative methods is often determined by the number of global reductions at each iteration. Low-synch Gram-Schmidt algorithms are applied here to the Arnoldi algorithm to reduce the number of global reductions and therefore to improve the parallel strong-scaling of iterative solvers for nonsymmetric matrices such as the GMRES and the Krylov-Schur iterative methods. In the Arnoldi context, the factorization is "left-looking" and processes one column at a time. Among the methods for generating an orthogonal basis for the Arnoldi algorithm, the classical Gram-Schmidt algorithm, with reorthogonalization (CGS2) requires three global reductions per iteration. A new variant of CGS2 that requires only one reduction per iteration is presented and applied to the Arnoldi algorithm. Delayed CGS2 (DCGS2) employs the minimum number of global reductions per iteration (one) for a one-column at-a-time algorithm. The main idea behind the new algorithm is to group global reductions by rearranging the order of operations. DCGS2 must be carefully integrated into an Arnoldi expansion or a GMRES solver. Numerical stability experiments assess robustness for Krylov-Schur eigenvalue computations. Performance experiments on the ORNL Summit supercomputer then establish the superiority of DCGS2 over CGS2.

97 MATHEMATICS AND COMPUTING↗

Novel Extracellular Electron Transfer Channels in a Gram-Positive Thermophilic Bacterium

Biogenic transformation of Fe minerals, associated with extracellular electron transfer (EET), allows microorganisms to exploit high-potential refractory electron acceptors for energy generation. EET-capable thermophiles are dominated by hyperthermophilic archaea and Gram-positive bacteria. Information on their EET pathways is sparse. Here, we describe EET channels in the thermophilic Gram-positive bacterium Carboxydothermus ferrireducens that drive exoelectrogenesis and rapid conversion of amorphous mineral ferrihydrite to large magnetite crystals. Microscopic studies indicated biocontrolled formation of unusual formicary-like ultrastructure of the magnetite crystals and revealed active colonization of anodes in bioelectrochemical systems (BESs) by C. ferrireducens . The internal structure of micron-scale biogenic magnetite crystals is reported for the first time. Genome analysis and expression profiling revealed three constitutive c -type multiheme cytochromes involved in electron exchange with ferrihydrite or an anode, sharing insignificant homology with previously described EET-related cytochromes thus representing novel determinants of EET. Our studies identify these cytochromes as extracellular and reveal potentially novel mechanisms of cell-to-mineral interactions in thermal environments.

59 BASIC BIOLOGICAL SCIENCES↗