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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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NASA NTRS1990

Interaction of a neutral cloud moving through a magnetized plasma

Current collection by outgassing probes in motion relative to a magnetized plasma may be significantly affected by plasma processes that cause electron heating and cross field transport. Simulations of a neutral gas cloud moving across a static magnetic field are discussed. The authors treat a low-Beta plasma and use a 2-1/2 D electrostatic code linked with the authors' Plasma and Neutral Interaction Code (PANIC). This study emphasizes the understanding of the interface between the neutral gas cloud and the surrounding plasma where electrons are heated and can diffuse across field lines. When ionization or charge exchange collisions occur a sheath-like structure is formed at the surface of the neutral gas. In that region the crossfield component of the electric field causes the electron to E times B drift with a velocity of the order of the neutral gas velocity times the square root of the ion to electron mass ratio. In addition a diamagnetic drift of the electron occurs due to the number density and temperature inhomogeneity in the front. These drift currents excite the lower-hybrid waves with the wave k-vectors almost perpendicular to the neutral flow and magnetic field again resulting in electron heating. The thermal electron current is significantly enhanced due to this heating.

Goertz, C. K.↗
NASA NTRS1990

Theoretical predictions

In order to understand the impact of man made chemicals on the atmospheric ozone layer, it is essential to develop models that can perform long term predictions of future ozone changes. An advantage of using two dimensional models is that they can be used to predict latitudinal and seasonal changes in ozone. The formulation and recent improvements are described in 2-D models, which are used herein, along with the three dimensional models that are currently being developed to better simulate transport of chemically active trace gases, especially in polar regions. The range in 2-D model calculations is described. Selected fields calculated by these models are compared with observations. A number of scenarios have been defined, which encompass possible emission rates of different halocarbons. Because of the large uncertainties in the rates for heterogeneous processes, the calculated responses of the models include only the effects of homogeneous chemistry. One important distinction among the models is their ability to account for temperature feedbacks on the calculated ozone changes.

Brasseur, G.↗
NASA NTRS1997

Neutron Induced Backgrounds In the MIXE X-Ray Detector at Balloon Altitudes

The MIXE detector developed at NASA/MSFC is designed for x-ray astronomy and consists of a multiwire proportional counter sensitive to photons less than 150 keV. The detector has been flown on several balloon flights with higher than expected background levels observed. Previous predictions of the detector background due to atmospheric gamma-ray and cosmic diffuse sources were much less (factor of 3) than flight background measurements. The work reported here was undertaken to determine if the additional contribution from gamma-rays generated by albedo and cosmic-ray induced neutrons in the detector and payload assembly could account for the background levels observed. Monte Carlo nuclear interaction and radiation transport simulations were made for the ambient cosmic-ray environment corresponding to a previous MEE balloon flight at 3 g/cm(exp 2) residual atmosphere and 42 N geomagnetic latitude. The omnidirectional albedo neutron spectrum and the GCR proton spectrum which were used as input to the calculations are shown. For the albedo angular distribution, the predicted up/down flux ratio of 2.5 was used together with the angular dependence measured by Preszler, et al.

Armstrong, T. W.↗
NASA NTRS2000

Near-Simultaneous POLAR and DMSP Measurements of Topside Ionospheric Up and Down Flows at High Latitudes

We will present what we believe to be the first reported observations of up- and downflows of topside ionospheric thermal plasmas from multiple near-simultaneous tracks through the high-latitude topside ionosphere. From several Southern polar passes, it has been possible to construct plots of field-aligned flows of 0+ observed by the Thermal Ion Dynamics Experiment(TIDE) on the POLAR spacecraft near 5000 km altitude together with vertical ion flow observations from one or more DMSP spacecraft near 800 km altitude. These observations provide a glimpse of the wide-spread upward and downward ionospheric ion flows over the broad polar region along multiple distinct satellite tracks. For the instances where DMSP and POLAR cross nearly the same field lines at the 800 and 5000 kin altitudes, we will show ion parameter measurements at these to altitudes in comparison to Dynamic Fluid-Kinetic(DyFK) transport simulations of anticipated altitude profiles of these parameters.

Zeng, W.↗
NASA NTRS2001

Near-simultaneous Polar and DMSP Measurements of Topside Ionospheric Field-Aligned Flows at High Latitudes

Near-simultaneous observations of topside O(+) parallel flows are presented for four periods of measurement by the Polar and DMSP satellites during April 1996. The Polar measurements were from southern perigee measurements near 5000 km altitude, while the DMSP measurements were from 840 km altitude. In general, the velocities were upward at expected cleft and auroral latitudes, typically about 2-10 km per second at 5000 km altitude, and 0-2 km per second at 840 km altitude. At the highest, polar cap latitudes, downward velocities were more frequent at both altitudes, but especially at the lower 840 km altitude. The downward velocities were typically a few hundred meters per second at 840 km altitude, and 0-1 km per second at 5000 km altitude. In some instances, downward velocities were observed at 840 km altitude while upward O(+) flows were observed at 5000 km altitude, possibly on the same flux tube. The O(+) densities were characteristically 10(exp 3) - 10(exp 4) O(+) at 5000 km altitude and 10(exp 3) - 10(exp 4) O(+) cm (exp -3) at 840 km altitude, while the O(+) fluxes were characteristically 10(exp 5) - 10(exp 7) O(+) cm(exp -2) per second at 5000 km altitude and characteristically 10(exp 7) - 10(exp 9) O(+) cm(exp -2) per second at 840 km altitude. We have also examined the dual-altitude parameter measurements for a polar cap field line, the Polar and DMSP measurements approximately 30 min apart, and compared them with results from a transport simulation. The simulated high-altitude velocity altitude profiles for the period during and after the initiation of the auroral processes generally bracketed the observations, but the observed downward velocities (500 - 600 m per second) at 840 km altitude were much larger in magnitude than those observed at both altitudes.

Zeng, W.↗
NASA NTRS2003

The NASA/Ames Mars General Circulation Model: Model Improvements and Comparison with Observations

For many years, the NASA/Ames Mars General Circulation Model (GCM) has been built around the UCLA B-grid dynamical core. An attached tracer transport scheme based on the aerosol microphysical model of Toon et al. (1988) provided a tool for studying dust storm transport and feedbacks (Murphy et al., 1995). While we still use a B-grid version of the model, the Ames group is now transitioning to the ARIES/GEOS Goddard C-grid dynamical core (Suarez and Takacs, 1995). The C-grid produces smoother fields when the model top is raised above 50 km, and has a built in transport scheme for an arbitrary number of tracers. All of our transport simulations are now carried out with the C-grid. We have also been updating our physics package. Several years ago we replaced our bulk boundary layer scheme with a level 2 type diffusive scheme, and added a multi-level soil model (Haberle et al., 2000). More recently we replaced our radiation code with a more generalized two-stream code that accounts for aerosol multiple scattering and gaseous absorption. This code gives us much more flexibility in choosing aerosol optical properties and radiatively active gases.

Haberle, R. M.↗
NASA NTRS2004

CFD Support for STS-107 Ascent Investigation

The research described in this viewgraph presentation investigates the ascent of STS-107 and foam-debris impact, and contributes to understanding of the STS-107 accident using CFD tools. The goals of the research are to: 1) Quantify loads on foam bipod ramp during ascent; 2) Provide steady-state flow-fields to debris-transport simulations; 3) Simulate flight of foam debris using unsteady six-degree-of-freedom calculations; 4) Provide estimates of foam mass, velocity, and impact angle which correlate with video and film evidence.

Rogers, Stuart E.↗
NASA NTRS2006

NAS Demand Predictions, Transportation Systems Analysis Model (TSAM) Compared with Other Forecasts

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler s purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized and various demand sensitivities can be predicted for future travel. These resulting demand scenarios can be incorporated into future flight schedules, therefore providing a quantifiable demand for flights in the NAS for a range of futures. In addition, new future airline business scenarios are investigated that illustrate when direct flights can replace connecting flights and larger aircraft can be substituted, only when justified by demand.

Viken, Jeff↗
NASA NTRS2006

Utilizing Traveler Demand Modeling to Predict Future Commercial Flight Schedules in the NAS

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler s purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized and various demand sensitivities can be predicted for future travel. These resulting demand scenarios can be incorporated into future flight schedules, therefore providing a quantifiable demand for flights in the NAS for a range of futures. In addition, new future airline business scenarios are investigated that illustrate when direct flights can replace connecting flights and larger aircraft can be substituted, only when justified by demand.

Viken, Jeff↗
NASA NTRS2007

Optimization of Crew Shielding Requirement in Reactor-Powered Lunar Surface Missions

On the surface of the moon -and not only during heightened solar activities- the radiation environment As such that crew protection will be required for missions lasting in excess of six months. This study focuses on estimating the optimized crew shielding requirement for lunar surface missions with a nuclear option. Simple, transport-simulation based dose-depth relations of the three (galactic, solar, and fission) radiation sources am employed in a 1-dimensional optimization scheme. The scheme is developed to estimate the total required mass of lunar-regolith separating reactor from crew. The scheme was applied to both solar maximum and minimum conditions. It is shown that savings of up to 30% in regolith mass can be realized. It is argued, however, that inherent variation and uncertainty -mainly in lunar regolith attenuation properties in addition to the radiation quality factor- can easily defeat this and similar optimization schemes.

Barghouty, Abdulnasser F.↗
NASA NTRS2007

Optimization of Crew Shielding Requirement in Reactor-Powered Lunar Surface Missions

On the surface of the moon and not only during heightened solar activities the radiation environment is such that crew protection will be required for missions lasting in excess of six months. This study focuses on estimating the optimized crew shielding requirement for lunar surface missions with a nuclear option. Simple, transport-simulation based dose-depth relations of the three radiation sources (galactic, solar, and fission) are employed in a one-dimensional optimization scheme. The scheme is developed to estimate the total required mass of lunar regolith separating reactor from crew. The scheme was applied to both solar maximum and minimum conditions. It is shown that savings of up to 30% in regolith mass can be realized. It is argued, however, that inherent variation and uncertainty mainly in lunar regolith attenuation properties in addition to the radiation quality factor can easily defeat this and similar optimization schemes.

Barghouty, A. F.↗
NASA NTRS2000

Near-Simultaneous Polar and DMSP Measurements of Topside Ionosphere Field - Aligned Flows at High Latitudes

Near-simultaneous observations of topside 0' parallel flows are presented for four periods of measurement by POLAR and DMSP satellites during April 1996. The POLAR measurements are from Southern perigee measurements near 5000 km altitude, while the DMSP measurements were from 840 km altitude. These observations provide a view of wide-spread upward/downward ionospheric O(+) flows over the broad polar region along extended and multiple distinct satellite tracks. In general, the velocities are upward toward expected cleft and auroral latitudes, typically about a 2-10 km/s at 5000 km altitude, and 0-2 km/s at 840 km altitudes. At the highest, polar cap latitudes, downward velocities are more frequent at both altitudes, but especially at the lower 840 km altitude. The downward velocities were typically a few hundred d s at 840 altitude, and 0-1 km/s at 5000 km altitude. In some instances, apparently downward velocities were observed at 840 km altitudes while upward 0' flows were observed at 5000 km altitude on the same flux tube. The O+ density were characteristically 1-10 O(+)/cu cm at 5000 km altitude and 10(exp 3) - 10(exp 40 O(+)/cu cm at 840 km altitude, while the O(+) flux were characteristically 1 10(exp 5) - 10(exp 7) O(+)+/sq cm -sec at 5000 km altitudes and characteristically 10(exp 7) - 10(exp 9) O(+)/sq cm -sec at 840 km altitude. We have also examined the dual altitude parameter measurements for a polar cap field line, the POLAR and DMSP measurements approximately 30 minutes apart, and compared them with results from a transport simulation in which a flux tube was subjected to a brief pulse of soft electron precipitation and topside transverse ion heating. The simulated density and velocity altitude profiles for 5 minutes later generally matched the observations, except that the observed downward velocities (500 - 600 m/s) at 840 km altitude were much larger than those simulated.

Zeng, W.↗
NASA NTRS2013

Diary of a Wimpy Cycle

The cause of the low and extended minimum in solar activity between Sunspot Cycles 23 and 24 was the small size of Sunspot Cycle 24 itself - small cycles start late and leave behind low minima. Cycle 24 is small because the polar fields produced during Cycle 23 were substantially weaker than those produced during the previous cycles and those (weak) polar fields are the seeds for the activity of the following cycle. Here we discuss the observed characteristics of Cycle 24 and contrast them to the characteristics of previous cycles. We present observations and Magnetic Flux Transport simulations with data assimilated from SOHO/MDI and SDO/HMI that help to explain these differences and point the way to predictions of future activity levels.

Hathaway, David↗
NASA NTRS2009

Heavy Ion Testing at the Galactic Cosmic Ray Energy Peak

A 1 GeV/u 5 6Fe ion beam allows for true 90deg tilt irradiations of various microelectronic c-0mponents and reveals relevant upset trends at the GCR Hux energy peak. Three SRAMs and an SRAM-based FPGA evaluated at the NASA Space Radiation Effects Laboratory demonstrate that a 90deg tilt irradiation yields a unique device response. These tilt angle effects need t-0 be screened for, and if found, pursued with radiation transport simulations to quantify their impact on event rate calculations.

Pellish, Jonathan A.↗
NASA NTRS2018

GMI-IPS: Python Processing Software for Aircraft Campaigns

NASA's Atmospheric Tomography Mission (ATom) seeks to understand the impact of anthropogenic air pollution on gases in the Earth's atmosphere. Four flight campaigns are being deployed on a seasonal basis to establish a continuous global-scale data set intended to improve the representation of chemically reactive gases in global atmospheric chemistry models. The Global Modeling Initiative (GMI), is creating chemical transport simulations on a global scale for each of the ATom flight campaigns. To meet the computational demands required to translate the GMI simulation data to grids associated with the flights from the ATom campaigns, the GMI ICARTT Processing Software (GMI-IPS) has been developed and is providing key functionality for data processing and analysis in this ongoing effort. The GMI-IPS is written in Python and provides computational kernels for data interpolation and visualization tasks on GMI simulation data. A key feature of the GMI-IPS, is its ability to read ICARTT files, a text-based file format for airborne instrument data, and extract the required flight information that defines regional and temporal grid parameters associated with an ATom flight. Perhaps most importantly, the GMI-IPS creates ICARTT files containing GMI simulated data, which are used in collaboration with ATom instrument teams and other modeling groups. The initial main task of the GMI-IPS is to interpolate GMI model data to the finer temporal resolution (1-10 seconds) of a given flight. The model data includes basic fields such as temperature and pressure, but the main focus of this effort is to provide species concentrations of chemical gases for ATom flights. The software, which uses parallel computation techniques for data intensive tasks, linearly interpolates each of the model fields to the time resolution of the flight. The temporally interpolated data is then saved to disk, and is used to create additional derived quantities. In order to translate the GMI model data to the spatial grid of the flight path as defined by the pressure, latitude, and longitude points at each flight time record, a weighted average is then calculated from the nearest neighbors in two dimensions (latitude, longitude). Using SciPya's Regular Grid Interpolator, interpolation functions are generated for the GMI model grid and the calculated weighted averages. The flight path points are then extracted from the ATom ICARTT instrument file, and are sent to the multi-dimensional interpolating functions to generate GMI field quantities along the spatial path of the flight. The interpolated field quantities are then written to a ICARTT data file, which is stored for further manipulation. The GMI-IPS is aware of a generic ATom ICARTT header format, containing basic information for all flight campaigns. The GMI-IPS includes logic to edit metadata for the derived field quantities, as well as modify the generic header data such as processing dates and associated instrument files. The ICARTT interpolated data is then appended to the modified header data, and the ICARTT processing is complete for the given flight and ready for collaboration. The output ICARTT data adheres to the ICARTT file format standards V1.1. The visualization component of the GMI-IPS uses Matplotlib extensively and has several functions ranging in complexity. First, it creates a model background curtain for the flight (time versus model eta levels) with the interpolated flight data superimposed on the curtain. Secondly, it creates a time-series plot of the interpolated flight data. Lastly, the visualization component creates averaged 2D model slices (longitude versus latitude) with overlaid flight track circles at key pressure levels. The GMI-IPS consists of a handful of classes and supporting functionality that have been generalized to be compatible with any ICARTT file that adheres to the base class definition. The base class represents a generic ICARTT entry, only defining a single time entry and 3D spatial positioning parameters. Other classes inherit from this base class; several classes for input ICARTT instrument files, which contain the necessary flight positioning information as a basis for data processing, as well as other classes for output ICARTT files, which contain the interpolated model data. Utility classes provide functionality for routine procedures such as: comparing field names among ICARTT files, reading ICARTT entries from a data file and storing them in data structures, and returning a reduced spatial grid based on a collection of ICARTT entries. Although the GMI-IPS is compatible with GMI model data, it can be adapted with reasonable effort for any simulation that creates Hierarchical Data Format (HDF) files. The same can be said of its adaptability to ICARTT files outside of the context of the ATom mission. The GMI-IPS contains just under 30,000 lines of code, eight classes, and a dozen drivers and utility programs. It is maintained with GIT source code management and has been used to deliver processed GMI model data for the ATom campaigns that have taken place to date.

Damon, M. R.↗
NASA NTRS2018

The Ozone Water-Land Environmental Transition Study: An Innovative Strategy for Understanding Chesapeake Bay Pollution Events

Coastal regions have historically represented a significant challenge for air quality investigations because of water-land boundary transition characteristics and a paucity of measurements available over water. Prior studies have identified the formation of high levels of ozone over water bodies, such as the Chesapeake Bay, that can potentially recirculate back over land to significantly impact populated areas. Earth-observing satellites and forecast models face challenges in capturing the coastal transition zone where small-scale meteorological dynamics are complex and large changes in pollutants can occur on very short spatial and temporal scales. An observation strategy is presented to synchronously measure pollutants “over land” and “over water” to provide a more complete picture of chemical gradients across coastal boundaries for both the needs of state and local environmental management and new remote sensing platforms. Intensive vertical profile information from ozone lidar systems and ozonesondes, obtained at two main sites, one over land and the other over water, are complemented by remote sensing and in situ observations of air quality from ground-based, airborne (both personned and unpersonned), and shipborne platforms. These observations, coupled with reliable chemical transport simulations, such as the National Oceanic and Atmospheric Administration (NOAA) National Air Quality Forecast Capability (NAQFC), are expected to lead to a more fully characterized and complete land–water interaction observing system that can be used to assess future geostationary air quality instruments, such as the National Aeronautics and Space Administration (NASA) Tropospheric Emissions: Monitoring of Pollution (TEMPO), and current low-Earth-orbiting satellites, such as the European Space Agency’s Sentinel-5 Precursor (S5-P) with its Tropospheric Monitoring Instrument (TROPOMI).

Forecast Models↗
NASA NTRSDate not supplied

Overview of Large-Scale Transport into the Arctic in the Chemistry Climate Model Initiative (CCMI) Simulations

The transport of trace gases and aerosols is a major uncertainty in the modeling of Arctic tropospheric composition. Here we compare the large-scale midlatitude-to-Arctic transport properties among different models participating in the Chemistry Climate Modeling Initiative (CCMI). Among simulations of the recent past (1980-2010) we show that there are substantial (~30-45%) differences in transport to the Arctic free troposphere, as diagnosed through use of idealized tracers emitted over the Northern Hemisphere (NH) midlatitude surface and subject to prescribed uniform loss. In addition, we show that the spread among tracers with predominantly land-based sources is correlated with the spread in the location of the Hadley Cell edge, while the spread in tracers with zonally uniform sources is also related to differences in (parameterized) convection over oceans. Interestingly, comparisons with simulations constrained with analysis fields reveal similar, if not larger, transport differences, compared to the free-running simulations, indicating that caution should be taken when interpreting simulations constrained with analyzed winds. Finally, among simulations of the 21st century we show that models project a consistent, albeit small (~5-10%), increase in transport from the NH midlatitude surface to the Arctic upper troposphere.

Large-Scale Transpor↗