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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 NTRS1977

Dynamic crystallization experiments bearing on the origin of textures in impact-generated liquids

Dynamic crystallization experiments on a synthetic glass of 14310 composition show that the density and distribution of crystals present at the initiation of cooling can drastically affect the texture of the crystallized product. Experiments were performed in one-atmosphere gas-mixing furnaces at an oxygen fugacity slightly below iron-wustite, and precooling crystallization, cooling history, and melt history were systematically varied. When cooled from a complete liquid, the experimental charges were porphyritic with 1-2 mm phenocrysts set in a very fine-grained matrix (less than 0.1 mm). This result suggests that 14310 did not cool from a complete melt. When cooled from a crystal-liquid mixture, the experimental charges had widely varying textures depending on the density and distribution of crystals that act as nucleation sites. It is suggested that the close spatial association of widely divergent textures in the matrices of some breccias and rocks might arise in this manner; local variations in cooling rates are not required.

Lofgren, G. E.↗
NASA NTRS1995

The effects of pure density evolution on the brightness distribution of cosmological gamma-ray bursts

In this work, we explore the effects of burst rate density evolution on the observed brightness distribution of cosmological gamma-ray bursts. Although the brightness distribution of gamma-ray bursts observed by the BATSE experiment has been shown to be consistent with a nonevolving source population observed to redshifts of order unity, evolution of some form is likely to be present in the gamma-ray bursts. Additionally, nonevolving models place significant constraints on the range of observed burst luminosities, which are relaxed if evolution of the burst population is present. In this paper, three analytic forms of density evolution are examined. In general, forms of evolution with densities that increase monotonically with redshift require that the BATSE data correspond to bursts at larger redshifts, or to incorporate a wider range of burst luminosities, or both. Independent estimates of the maximum observed redshift in the BATSE data and/or the range of luminosity from which a large fraction of the observed bursts are drawn therefore allow for constraints to be placed on the amount of evolution that may be present in the burst population. Specifically, if recent measurements obtained from analysis of the BATSE duration distribution of the actual limiting redshift in the BATSE data at z(sub lim) = 2 are correct, the BATSE N(P) distribution in a Lambda = 0 universe is inconsistent at a level of approximately 3 alpha with nonevolving gamma-ray bursts and some form of evolution in the population is required. The sense of this required source evolution is to provide a higher density, larger luminosities, or both with increasing redshift.

Horack, J. M.↗
NASA NTRS1973

Ring current particle distributions during the magnetic storms of December 16-18, 1971.

Proton density energy distributions during two magnetic storms on Dec. 16 and 18, 1971, are derived from proton detector data of the S3-A satellite and are analyzed to show the contrast in the ring current developments during the two events. Ground magnetograms are also used in the analysis to show the magnetic field variations during the storms. Satellite orbits 97 through 103 are covered.

Smith, P. H.↗
NASA NTRS1979

Solar Mesosphere Explorer mission

The Solar Mesosphere Explorer (SME) satellite experiments will provide a comprehensive study of atmospheric ozone and the processes which form and destroy it. Five instruments to be carried on the spacecraft will measure the ozone density and altitude distribution, monitor the incoming solar radiation, and measure other atmospheric constituents which affect ozone. The first objective of the SME satellite experiments is to determine what changes occur in the ozone distribution as a result of changes in the incoming solar radiation. A second objective is to measure all changes in the ozone density distribution in the altitude range of 30 to 80 km and to determine the causes of these changes.

Stuart, J. R.↗
NASA NTRS2016

Effect of Surface Pressure Integration Methodology on Launch Vehicle Buffet Forcing Functions

The 2014 test of the Space Launch System (SLS) Rigid Buffet Model conducted at the NASA Langley Transonic Dynamics Tunnel employed an extremely high number of unsteady pressure transducers. The high channel count provided an opportunity to examine the effect of transducer placement on the resulting buffet forcing functions (BFFs). Rings of transducers on the forward half of the model were employed to simulate a single-body vehicle. The impact of transducer density, circumferential distribution, and loss of a single transducer on the resulting BFFs were examined. Rings of transducers on the aft half of the SLS model were employed to examine the effect of transducer density and circumferential distribution on BFFs for a multi-body configuration. Transducer placement considerations with respect to model size, facility infrastructure, and data acquisition system capabilities, which affect the integration process, are also discussed.

Sekula, Martin K.↗
NASA NTRS1931

Airfoil Pressure Distribution Investigation in the Variable Density Wind Tunnel

Report presents the results of wind tunnel tests of pressure distribution measurements over one section each of six airfoils. Pressure distribution diagrams, as well as the integrated characteristics of the airfoils, are given for both a high and a low dynamic scale or, Reynolds number VL/V, for comparison with flight and other wind-tunnel tests, respectively. It is concluded that the scale effect is very important only at angles of attack near the burble. The distribution of pressure over an airfoil having a Joukowski section is compared with the theoretically derived distribution. A further study of the distribution of pressure over all of the airfoils resulted in the development of an approximate method of predicting the pressure distribution along the chord of any normal airfoil for all attitudes within the working range if the distribution at one attitude is known.

Jacobs, Eastman N↗
NASA NTRS1984

Transient behavior of flare-associated solar wind. II - Gas dynamics in a nonradial open field region

Transient behavior of flare-associated solar wind in the nonradial open field region is numerically investigated, taking into account the thermal and dynamical coupling between the chromosphere and the corona. A realistic steady solar wind is constructed which passes through the inner X-type critical point in the rapidly diverging region. The wind speed shows a local maximum at the middle, O-type, critical point. The wind's density and pressure distributions decrease abruptly in the rapidly diverging region of the flow tube. The transient behavior of the wind following flare energy deposition includes ascending and descending conduction fronts. Thermal instability occurs in the lower corona, and ascending material flows out through the throat after the flare energy input ceases. A local density distribution peak is generated at the shock front due to the pressure deficit just behind the shock front.

Nagai, F.↗
NASA NTRS2010

Improving the Representation of Snow Crystal Properties Within a Single-Moment Microphysics Scheme

As computational resources continue their expansion, weather forecast models are transitioning to the use of parameterizations that predict the evolution of hydrometeors and their microphysical processes, rather than estimating the bulk effects of clouds and precipitation that occur on a sub-grid scale. These parameterizations are referred to as single-moment, bulk water microphysics schemes, as they predict the total water mass among hydrometeors in a limited number of classes. Although the development of single moment microphysics schemes have often been driven by the need to predict the structure of convective storms, they may also provide value in predicting accumulations of snowfall. Predicting the accumulation of snowfall presents unique challenges to forecasters and microphysics schemes. In cases where surface temperatures are near freezing, accumulated depth often depends upon the snowfall rate and the ability to overcome an initial warm layer. Precipitation efficiency relates to the dominant ice crystal habit, as dendrites and plates have relatively large surface areas for the accretion of cloud water and ice, but are only favored within a narrow range of ice supersaturation and temperature. Forecast models and their parameterizations must accurately represent the characteristics of snow crystal populations, such as their size distribution, bulk density and fall speed. These properties relate to the vertical distribution of ice within simulated clouds, the temperature profile through latent heat release, and the eventual precipitation rate measured at the surface. The NASA Goddard, single-moment microphysics scheme is available to the operational forecast community as an option within the Weather Research and Forecasting (WRF) model. The NASA Goddard scheme predicts the occurrence of up to six classes of water mass: vapor, cloud ice, cloud water, rain, snow and either graupel or hail.

Molthan, Andrew L.↗
NASA NTRSDate not supplied

An Updated Secondary Lunar Meteoroid Ejecta Model for Engineering Design

Introduction: The surface of the Moon is constantly being bombarded by a flux of meteoroids of various sizes. Impacts due to these meteoroids produce secondary ejecta material at much lower speeds but with a total mass larger than the original impactor. Details about the secondary ejecta are important for planning missions on the lunar surface. In this work, an updated ejecta model is presented called the Meteoroid Model of Secondary Ejecta (MeMoSeE), to re-place the Apollo-era ejecta model, NASA SP-8013 [1], in the SLS-SPEC 159 Design Specification for Natural Environments (DSNE) [2]. The model pro-duces secondary ejecta flux environments for a user-specified location on the lunar surface, and sorts the incoming secondary flux by angular direction and speed. Methods: MeMoSeE is separated into three parts: the inputs, the conversion step, and the integration of fluxes. Inputs to the model include the primary meteoroid fluxes and the primary near-Earth object (NEO) fluxes. Meteoroid fluxes, both asteroidal and cometary, are calculated using the Meteoroid Engineering Model (MEM3) [3] for different locations on the Moon. For each surface location, an ephemeris is generated using the JPL HORIZONS System [4] that feeds into MEM3. The NEO fluxes are approximated by the high-density population of MEM3 (i.e., only the directionality), where the speed distribution of the NEO fluxes is renormalized to match observations [5]. The regolith properties are used as defined in the DSNE [2]. The conversion step utilizes scaling laws given by Housen & Holsapple 2011 [6] to convert the primary impactor flux to the total mass of secondary ejecta. The ejecta distribution, at the point-of-impact (POI), is separated into a zenith angle and azimuthal angle distribution. The zenith angle distribution follows a beta distribution where the peak depends on the impact altitude angle and the impact azimuth [7]. We employ an ejecta azimuth distribution that is based on Rival & Mandeville 1999 [8] which focuses ejecta in the downstream direction for more oblique impacts. Finally, during the integration step, we sum secondary ejecta number fluxes at a particular region-of-interest (ROI) that originated from many POI locations over the entire surface of the Moon. We keep track of both altitude and azimuth angle bins as well as a range of speed bins, following the igloo gridding as done in MEM3 [9]. The ejecta particle size distribution and density is assumed to be the same as the lunar regolith [10, 2]. Results: The primary fluxes are computed for one Metonic cycle (19 years) for various locations over the lunar surface with a fixed orientation. Both the angular and speed distributions of the primary fluxes are dependent on the latitude and longitude. The over-all primary fluxes show a roughly 13% increase from the eastern limb to the western limb. In general, the speed distribution of the secondary fluxes span from a user-defined minimum speed to the escape speed of the Moon (2.38 km/s), roughly following a power-law relation [6]. Different parts of the speed distribution come from different primary impact locations on the Moon. The secondary ejecta is dominated by the slowest speeds, where these particles originate nearby the ROI. For speeds around 71% of the escape speed, the secondary ejecta originates from locations near the antipodal point. On the other hand, for secondary ejecta speeds that exceed roughly 90% the escape speed, the ejecta particles come from all over the lunar surface to the ROI. Comparing the secondary ejecta fluxes from MeMoSeE with NASA SP-8013 [1], there is a reduction by about 2-3 orders of magnitude for secondary ejecta particles greater than 1 µg. These estimates agree with recent findings from Bjorkman & Christiansen 2019 [11]. The secondary ejecta fluxes are also compared with the primary fluxes, where the ejecta fluxes are roughly an order of magnitude greater than the primary fluxes. References: [1] Cour-Palais, B. G., (1969) NASA SP-8013. [2] NASA SLS-SPEC-159 Rev. H (2020). [3] Moorhead, A. V., et al. (2019) JS&R, 1-17. [4] Giorgini, J. D., (2015) IAUGA, 29, 2256293. [5] Moorhead, A. V., (2020) Memo OSMA/MEO/Lunar-001. [6] Housen, K. R., and Holsapple, K. A., (2011) Icarus, 211(1), 856-875. [7] Gault, D. E., and Wedekind, J. A., (1978) L&PSCP, 9, 3843-3875. [8] Rival, M., and Mandeville, J., (1999) Space Debris, 1(1), 45-57. [9] Moorhead, A. V., (2019) MEM3 User Guide. [10] Carrier, W. D., (1973) The Moon, 6(3-4), 250-263. [11] Bjorkman, M. D. & Christiansen, E. L., (2019) ODC

impacts↗
NASA NTRS2023

Data-constrained Solar Modeling with GX Simulator

To facilitate the study of solarflares and active regions, we have created a modeling framework, the freelydistributed GX Simulator IDL package, that combines 3D magnetic and plasma structures with thermal andnonthermal models of the chromosphere, transition region, and corona. Its object-based modular architecture,which runs on Windows, Mac, and Unix/Linux platforms, offers the ability to either import 3D density andtemperature distribution models, or to assign numerically defined coronal or chromospheric temperatures anddensities, or their distributions, to each individual voxel. GX Simulator can apply parametric heating modelsinvolving average properties of the magneticfield lines crossing a given voxel, as well as compute and investigatethe spatial and spectral properties of radio,(sub)millimeter, EUV, and X-ray emissions calculated from the model,and quantitatively compare them with observations. The package includes a fully automatic model productionpipeline that, based on minimal users input, downloads the required SDO/HMI vector magneticfield data,performs potential or nonlinear force-freefield extrapolations, populates the magneticfield skeleton withparameterized heated plasma coronal models that assume either steady-state or impulsive plasma heating, andgenerates non-LTE density and temperature distribution models of the chromosphere that are constrained byphotospheric measurements. The standardized models produced by this pipeline may be further customizedthrough specialized IDL scripts, or a set of interactive tools provided by the graphical user interface. Here, wedescribe the GX Simulator framework and its applications.

Solar active regions↗
DOE OSTI2021

From noise to information: The transfer function formalism for uncertainty quantification in reconstructing the nuclear density

The neutron distribution of neutron-rich nuclei provides critical information on the structure of finite nuclei and neutron stars. Parity violating experiments—such as PREX and CREX—provide a clean and largely model-independent determination of neutron densities. Such experiments, however, are challenging and expensive, which is why sound statistical arguments are required to maximize the information gained. We introduce a new framework, the “transfer function formalism,” aimed at uncertainty quantification, model selection, and experimental design in the context of neutron densities. The transfer functions (TFs) are built analytically by expressing the linear response of the objective function (e.g., χ2) to small perturbations of the data. Using the TF formalism, we are able to analyze the expected overall uncertainty—quantified in terms of bias and variance—of the mean square radius and interior density of 48 Ca and 208 Pb. Using relativistic mean field models as a proxy for the weak-charge density—and assuming that a total of five measurements could be performed on the weak form factor of 48 Ca and 208 Pb—we identify the optimal models and experimental locations that minimize the uncertainty in the extraction of the radius and interior density. We also explore the use of the TF formalism to understand the influence of prior distributions for the model parameters, as well as the optimization of model hyperparameters not constrained by the data. Here,we establish how the choice of experimental locations and the model that is used can have a significant impact on the final uncertainties of the extracted quantities of interest. For challenging experiments such as CREX and PREX, a proper quantification of such uncertainties is critical. We have demonstrated how the TF formalism provides several advantages for this type of analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1966

Plasma probe

Mariner IV plasma probe to measure density, velocity distribution, and bulk direction of proton flux component of solar plasma - components, operation, and performance

MARINER IV SPACE PROBE↗
DOE OSTI2021

Survey on stochastic distribution systems: A full probability density function control theory with potential applications

Complex systems seen either in general engineering practice or economics are subjected to ever increased uncertainties that are mostly represented as random variables or parameters, and the characteristics of random variables are represented by their probability density functions (PDFs). Controlling their PDFs means to shape their stochastic distributions and in general it would provide a full treatment for system analysis and operational control and optimization. This leads to the development of stochastic distribution control (SDC) systems theory in the past decades, where the original aim of the controller design is to realize a shape control of the distributions of certain random variables in their PDFs sense for some engineering processes. Indeed, once the PDFs of these random variables or parameters are used to describe their distribution characters, the control task is to obtain control signals so that the output PDFs of stochastic systems are made to follow their target PDFs. The subject of SDC was initially originated for non-Gaussian stochastic control systems design but has found a wide spectrum of applications in general systems in terms of data-driven modeling, analysis, signal processing (filtering), data mining via multivariable statistics, decision-making (optimization) for systems subjected to uncertainties and even in economics. In this context, SDC constitutes an effective primer tool for complex system analysis, control and operational optimizations. In this review paper, a detailed survey of the developments on the research of SDC systems will be made together with their wide spectrum applications and future perspectives.

42 ENGINEERING↗
NASA NTRS2001

Investigation of Thermospheric and Ionospheric Changes during Ionospheric Storms with Satellite and Ground-Based Data and Modeling

The purpose of this proposed research is to improve our basic understanding of the causes of ionospheric storm behavior in the midlatitude F region ionosphere. This objective will be achieved by detailed comparisons between ground based measurements of the peak electron density (N(sub m)F(sub 2)), Atmosphere Explorer satellite measurements of ion and neutral composition, and output from the Field Line Interhemispheric Plasma (FLIP) model. The primary result will be a better understanding of changes in the neutral densities and ion chemistry during magnetic storms that will improve our capability to model the weather of the ionosphere which will be needed as a basis for ionospheric prediction. Specifically, this study seeks to answer the following questions: (1) To what extent are negative ionospheric storm phases caused by changes in the atomic to molecular ratio? (2) Are the changes in neutral density ratio due to increased N2, or decreased O, or both? (3) Are there other chemical processes (e.g., excited N2) that increase O+ loss rates during negative storms? (4) Do neutral density altitude distributions differed from hydrostatic equilibrium? (5) Why do near normal nighttime densities often follow daytime depletions of electron density; and (6) Can changes in h(sub m)F2 fully account for positive storm phases? To answer these questions, we plan to combine ground-based and space-based measurements with the aid of our ionospheric model which is ideally suited to this purpose. These proposed studies will lead to a better capability to predict long term ionospheric variability, leading to better predictions of ionospheric weather.

Richards, Philip G.↗
DOE OSTI2021

Initial hydration process of calcium silicates in Portland cement: A comprehensive comparison from molecular dynamics simulations

As the main components of Portland cement, calcium silicates show substantial differences in their hydration reactivity which have not been fully explained. A comprehensive comparison of the initial hydration process of calcium silicates, namely dicalcium silicate (C{sub 2}S) and tricalcium silicate (C{sub 3}S), was conducted using molecular dynamics simulations. The initial hydration process was divided into three stages using cut-off times of 0.001 ns and 3 ns. The hydration of M{sub 3}-C{sub 3}S (010) was more evident than that of β-C{sub 2}S (100), supported by the hydroxylation degree, radial distribution function, atomic density profile, etc. The coordination number of the surface Ca atoms might be the underlying reason for such a difference. Interactions between cement surfaces and water molecules were mainly characterised by solid OH bonding and Ca-water O bonding. Dissolution of Ca atoms was observed, although quite scarce, while no dissolution of Si atoms was observed.

36 MATERIALS SCIENCE↗