Engineering PapersSearch

SEARCH · Engineering Papers

Results for “GRAM”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4

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.

Diversity in the Common Fold: Structural Insights into Class D β-Lactamases from Gram-Negative Pathogens

Class D β-lactamases (DBLs) represent a major threat to antibiotic efficacy by hydrolyzing β-lactam drugs, including last-resort carbapenems, thereby driving antimicrobial resistance in Gram-negative bacteria. The enzymes share a structurally conserved two-domain α/β architecture with seven active-site motifs and three flexible extended loops (the P-loop, Ω-loop, and newly designated B-loop) that surround the active site. While each of these loops is known to influence enzyme function, their coordinated roles have not been fully elucidated. To investigate the significance of their interplay, we compared the sequences and crystal structures of 40 DBLs from clinically relevant Gram-negative pathogens and performed molecular dynamics simulations on selected representatives. Combined structural and dynamical analyses revealed a strong correlation between B-loop architecture and carbapenemase activity in the pathogens Klebsiella and Acinetobacter, particularly regarding loop length and spatial organization. These findings emphasize the B-loop’s critical contribution, in concert with the P- and Ω-loops, in tuning active site versatility, substrate recognition, catalytic activity, and structural stability. A deeper understanding of how these motifs and loops govern DBL function may inform the development of novel antibiotics and inhibitors targeting this class of enzymes.

antibiotic resistance

Shuttle derived atmospheric density model. Part 2: STS atmospheric implications for AOTV trajectory analysis, a proposed GRAM perturbation density model

A perturbation model to the Marshall Space Flight Center (MSFC) Global Reference Atmosphere Model (GRAM) was developed for use in the Aeroassist Orbital Transfer Vehicle (AOTV) trajectory and analysis. The model reflects NASA Space Shuttle experience over the first twelve entry flights. The GRAM was selected over the Air Force 1978 Reference Model because of its more general formulation and wider use throughout NASA. The add-on model, a simple scaling with altitude to reflect density structure encountered by the Shuttle Orbiter was selected principally to simplify implementation. Perturbations, by season, can be utilized to minimize the number of required simulations, however, exact Shuttle flight history can be exercised using the same model if desired. Such a perturbation model, though not meteorologically motivated, enables inclusion of High Resolution Accelerometer Package (HiRAP) results in the thermosphere. Provision is made to incorporate differing perturbations during the AOTV entry and exit phases of the aero-asist maneuver to account for trajectory displacement (geographic) along the ground track.

Findlay, J. T.

Utilization of Global Reference Atmosphere Model (GRAM) for shuttle entry

At high latitudes, dispersions in values of density for the middle atmosphere from the Global Reference Atmosphere Model (GRAM) are observed to be large, particularly in the winter. Trajectories have been run from 28.5 deg to 98 deg. The critical part of the atmosphere for reentry is 250,000 to 270,000 ft. 250,000 ft is the altitude where the shuttle trajectory levels out. For ascending passes the critical region occurs near the equator. For descending entries the critical region is in northern latitudes. The computed trajectory is input to the GRAM, which computes means and deviations of atmospheric parameters at each point along the trajectory. There is little latitude dispersion for the ascending passes; the strongest source of deviations is seasonal; however, very wide seasonal and latitudinal deviations are exhibited for the descending passes at all orbital inclinations. For shuttle operations the problem is control to maintain the correct entry corridor and avoid either aerodynamic skipping or excessive heat loads.

Joosten, Kent

The GRAM-3 model

The Global Reference Atmosphere Model (GRAM) is under continuous development and improvement. GRAM data were compared with Middle Atmosphere Program (MAP) predictions and with shuttle data. An important note: Users should employ only step sizes in altitude that give vertical density gradients consistent with shuttle-derived density data. Using too small a vertical step size (finer then 1 km) will result in what appears to be unreasonably high values of density shears but what in reality is noise in the model.

Justus, C. G.

The NASA/MSFC global reference atmospheric model: 1990 version (GRAM-90). Part 1: Technical/users manual

A technical description of the NASA/MSFC Global Reference Atmospheric Model 1990 version (GRAM-90) is presented with emphasis on the additions and new user's manual descriptions of the program operation aspects of the revised model. Some sample results for the new middle atmosphere section and comparisons with results from a three dimensional circulation model are provided. A programmer's manual with more details for those wishing to make their own GRAM program adaptations is also presented.

Justus, C. G.

Mars Global Reference Atmospheric Model (Mars-GRAM 3.34): Programmer's Guide

This is a programmer's guide for the Mars Global Reference Atmospheric Model (Mars-GRAM 3.34). Included are a brief history and review of the model since its origin in 1988 and a technical discussion of recent additions and modifications. Examples of how to run both the interactive and batch (subroutine) forms are presented. Instructions are provided on how to customize output of the model for various parameters of the Mars atmosphere. Detailed descriptions are given of the main driver programs, subroutines, and associated computational methods. Lists and descriptions include input, output, and local variables in the programs. These descriptions give a summary of program steps and 'map' of calling relationships among the subroutines. Definitions are provided for the variables passed between subroutines through common lists. Explanations are provided for all diagnostic and progress messages generated during execution of the program. A brief outline of future plans for Mars-GRAM is also presented.

Justus, C. G.