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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

MATRIX-VBS Condensing Organic Aerosols in an Aerosol Microphysics Model

The condensation of organic aerosols is represented in a newly developed box-model scheme, where its effect on the growth and composition of particles are examined. We implemented the volatility-basis set (VBS) framework into the aerosol mixing state resolving microphysical scheme Multiconfiguration Aerosol TRacker of mIXing state (MATRIX). This new scheme is unique and advances the representation of organic aerosols in models in that, contrary to the traditional treatment of organic aerosols as non-volatile in most climate models and in the original version of MATRIX, this new scheme treats them as semi-volatile. Such treatment is important because low-volatility organics contribute significantly to the growth of particles. The new scheme includes several classes of semi-volatile organic compounds from the VBS framework that can partition among aerosol populations in MATRIX, thus representing the growth of particles via condensation of low volatility organic vapors. Results from test cases representing Mexico City and a Finish forrest condistions show good representation of the time evolutions of concentration for VBS species in the gas phase and in the condensed particulate phase. Emitted semi-volatile primary organic aerosols evaporate almost completely in the high volatile range, and they condense more efficiently in the low volatility range.

Aerosols↗
NASA NTRS1988

Correlation studies on surface particle detection methods

The accurate determination of dust levels on optical surfaces is necessary to assess sensor system performance. A comparison study was made on several particle measurement methods including those based on direct imaging and light scattering. The effectiveness of removing the particles from the surface prior to determining particle size distributions was also assessed. These studies revealed that some methods, especially those requiring particle removal before analysis, are subject to large systematic errors affecting particle size distributions. Thus, an understanding of the particle measurement methods employed is necessary before any surface cleanliness or obstruction value assignments are accepted as true representations of an optical surface contamination condition.

Peterson, Ronald V.↗
NASA NTRS2013

Influence of Computational Drop Representation in LES of a Droplet-Laden Mixing Layer

Multiphase turbulent flows are encountered in many practical applications including turbine engines or natural phenomena involving particle dispersion. Numerical computations of multiphase turbulent flows are important because they provide a cheaper alternative to performing experiments during an engine design process or because they can provide predictions of pollutant dispersion, etc. Two-phase flows contain millions and sometimes billions of particles. For flows with volumetrically dilute particle loading, the most accurate method of numerically simulating the flow is based on direct numerical simulation (DNS) of the governing equations in which all scales of the flow including the small scales that are responsible for the overwhelming amount of dissipation are resolved. DNS, however, requires high computational cost and cannot be used in engineering design applications where iterations among several design conditions are necessary. Because of high computational cost, numerical simulations of such flows cannot track all these drops. The objective of this work is to quantify the influence of the number of computational drops and grid spacing on the accuracy of predicted flow statistics, and to possibly identify the minimum number, or, if not possible, the optimal number of computational drops that provide minimal error in flow prediction. For this purpose, several Large Eddy Simulation (LES) of a mixing layer with evaporating drops have been performed by using coarse, medium, and fine grid spacings and computational drops, rather than physical drops. To define computational drops, an integer NR is introduced that represents the ratio of the number of existing physical drops to the desired number of computational drops; for example, if NR=8, this means that a computational drop represents 8 physical drops in the flow field. The desired number of computational drops is determined by the available computational resources; the larger NR is, the less computationally intensive is the simulation. A set of first order and second order flow statistics, and of drop statistics are extracted from LES predictions and are compared to results obtained by filtering a DNS database. First order statistics such as Favre averaged stream-wise velocity, Favre averaged vapor mass fraction, and the drop stream-wise velocity, are predicted accurately independent of the number of computational drops and grid spacing. Second order flow statistics depend both on the number of computational drops and on grid spacing. The scalar variance and turbulent vapor flux are predicted accurately by the fine mesh LES only when NR is less than 32, and by the coarse mesh LES reasonably accurately for all NR values. This is attributed to the fact that when the grid spacing is coarsened, the number of drops in a computational cell must not be significantly lower than that in the DNS.

Bellan, Josette↗
NASA NTRS1972

Interplanetary gas dynamics.

Observations of the interplanetary medium are considered together with the structure of the solar atmosphere and the kinetic properties of the interplanetary plasma. Methods of gas kinetics and continuum flows are examined, taking into account microscopic and macroscopic representations, the kinetic flow equations, the formal solution of the Vlasov equation, and the continuum flow equations. The collective particle behavior of that interplanetary gas is discussed along with the hydrodynamic coronal expansion, a wave-pump problem, the free expansion phenomenon, and a generalized free expansion problem.

Liu, V. C.↗
NASA NTRS1984

A Lagrangian method for a two layer shallow water model

One of the biggest drawbacks of Eulerian methods is the presence of the nonlinear convective terms which leads to inaccurate representations of advection and fronts. An alternative and conceptually simpler approach is the Lagrangian approach in which the fluid particles themselves are tracked and equations are derived based on local spatial interaction. In this formulation the nonlinear convective terms do not appear. The main drawback with the Lagrangian formulation, however, is that the local spatial interactions are time dependent. That is, at each time level, one must know the current neighbors of a given particle to accurately compute the forces acting on the particle. The Voroni Mesh which is continuously deforming and always linking nearest neighbors is needed. The effectiveness of a simple Lagrangian method for simulating the onset of a Kelvin-Helmholtz instability in a 2 layer fluid is demonstrated.

Augenbaum, J. M.↗
NASA NTRS2018

Impact of the Ozone Monitoring Instrument Row Anomaly on the Long-Term Record of Aerosol Products

Since about three years after the launch the Ozone Monitoring Instrument (OMI) on the EOS-Aura satellite, the sensor's viewing capability has been affected by what is believed to be an internal obstruction that has reduced OMI's spatial coverage. It currently affects about half of the instrument's 60 viewing positions. In this work we carry out an analysis to assess the effect of the reduced spatial coverage on the monthly average values of retrieved aerosol optical depth (AOD), single scattering albedo (SSA) and the UV Aerosol Index (UVAI) using the 2005-2007 three-year period prior to the onset of the row anomaly. Regional monthly average values calculated using viewing positions 1 through 30 were compared to similarly obtained values using positions 31 through 60, with the expectation of finding close agreement between the two calculations. As expected, mean monthly values of AOD and SSA obtained with these two scattering-angle dependent subsets of OMI observations agreed over regions where carbonaceous or sulphate aerosol particles are the predominant aerosol type. However, over arid regions, where desert dust is the main aerosol type, significant differences between the two sets of calculated regional mean values of AOD were observed. As it turned out, the difference in retrieved desert dust AOD between the scattering-angle dependent observation subsets was due to the incorrect representation of desert dust scattering phase function. A sensitivity analysis using radiative transfer calculations demonstrated that the source of the observed AOD bias was the spherical shape assumption of desert dust particles. A similar analysis in terms of UVAI yielded large differences in the monthly mean values for the two sets of calculations over cloudy regions. On the contrary, in arid regions with minimum cloud presence, the resulting UVAI monthly average values for the two sets of observations were in very close agreement. The discrepancy under cloudy conditions was found to be caused by the parameterization of clouds as opaque Lambertian reflectors. When properly accounting for cloud scattering effects using Mie theory, the observed UVAI angular bias was significantly reduced. The analysis discussed here has uncovered important algorithmic deficiencies associated with the model representation of the angular dependence of scattering effects of desert dust aerosols and cloud droplets. The resulting improvements in the handling of desert dust and cloud scattering have been incorporated in an improved version of the OMAERUV algorithm.

Atmospheric Chemistry↗
NASA NTRS1970

The viscous magnetopause

Magnetopause representation by mixing region of plasma streams with different velocities and magnetic fields, assuming hydromagnetic viscosity caused by wave-particle interactions

Cassen, P.↗
NASA NTRS2020

Global Airborne Sampling Reveals a Previously Unobserved Dimethyl Sulfide Oxidation Mechanism in the Marine Atmosphere

Dimethyl sulfide (DMS), emitted from the oceans, is the most abundant biological source of sulfur to the marine atmosphere. Atmospheric DMS is oxidized to condensable products that form secondary aerosols that affect Earth’s radiative balance by scattering solar radiation and serving as cloud condensation nuclei. We report the atmospheric discovery of a previously unquantified DMS oxidation product, hydroperoxymethyl thioformate (HPMTF, HOOCH2SCHO), identified through global-scale airborne observations that demonstrate it to be a major reservoir of marine sulfur. Observationally constrained model results show that more than 30% of oceanic DMS emitted to the atmosphere forms HPMTF. Coincident particle measurements suggest a strong link between HPMTF concentration and new particle formation and growth. Analyses of these observations show that HPMTF chemistry must be included in atmospheric models to improve representation of key linkages between the biogeochemistry of the ocean, marine aerosol formation and growth, and their combined effects on climate.

DMS gas-phase oxidation product↗
NASA NTRS2024

A Multi‐Probe Automated Classification of Ice Crystal Habits During the IMPACTS Campaign

Although all ice crystals are unique, many can be grouped together by shape or habit, with members of a habit class sharing similar representations of properties such as fall velocity and growth rate. A decision tree algorithm designed to be adaptable to any particle imaging probe, thus enabling the creation of habit size distributions over a size range larger than that of any probe on its own, is used to classify ice crystals imaged by three airborne cloud probes in mid-latitude winter cyclones during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign. Crystals are sorted into seven habit classes based on their morphological properties: sphere, column/needle, plate, graupel, dendrite, aggregate, and irregular. Although adaptability was its primary goal, the algorithm was found to be moderately skillful for identifying idealized habit images. Quantitative tests of the algorithm’s adaptability displayed mixed results, as Two-Dimensional Stereo Probe (2DS) classifications showed moderate correlation with Particle Habit Imaging and Polar Scattering Probe (PHIPS) classifications, but only weak correlation with High Volume Precipitation Spectrometer (HVPS) classifications. The algorithm was applied to random sets of images from each probe in a case study of a mesoscale snow band sampled on 7 February 2020. In the case study, qualitative analysis of particle images revealed general agreement on classifications among the probes, supporting the algorithm’s applicability to multiple cloud probes. Most classifications appeared correct upon manual inspection, suggesting that in practical use, the algorithm is reasonably able to classify non-idealized images.

Julian Schima↗
NASA NTRS2013

Forecasting Propagation and Evolution of CMEs in an Operational Setting: What Has Been Learned

One of the major types of solar eruption, coronal mass ejections (CMEs) not only impact space weather, but also can have significant societal consequences. CMEs cause intense geomagnetic storms and drive fast mode shocks that accelerate charged particles, potentially resulting in enhanced radiation levels both in ions and electrons. Human and technological assets in space can be endangered as a result. CMEs are also the major contributor to generating large amplitude Geomagnetically Induced Currents (GICs), which are a source of concern for power grid safety. Due to their space weather significance, forecasting the evolution and impacts of CMEs has become a much desired capability for space weather operations worldwide. Based on our operational experience at Space Weather Research Center at NASA Goddard Space Flight Center (http://swrc.gsfc.nasa.gov), we present here some of the insights gained about accurately predicting CME impacts, particularly in relation to space weather operations. These include: 1. The need to maximize information to get an accurate handle of three-dimensional (3-D) CME kinetic parameters and therefore improve CME forecast; 2. The potential use of CME simulation results for qualitative prediction of regions of space where solar energetic particles (SEPs) may be found; 3. The need to include all CMEs occurring within a ~24 h period for a better representation of the CME interactions; 4. Various other important parameters in forecasting CME evolution in interplanetary space, with special emphasis on the CME propagation direction. It is noted that a future direction for our CME forecasting is to employ the ensemble modeling approach.

forecasting↗
NASA NTRS2012

Large Eddy Simulation (LES) of Particle-Laden Temporal Mixing Layers

High-fidelity models of plume-regolith interaction are difficult to develop because of the widely disparate flow conditions that exist in this process. The gas in the core of a rocket plume can often be modeled as a time-dependent, high-temperature, turbulent, reacting continuum flow. However, due to the vacuum conditions on the lunar surface, the mean molecular path in the outer parts of the plume is too long for the continuum assumption to remain valid. Molecular methods are better suited to model this region of the flow. Finally, granular and multiphase flow models must be employed to describe the dust and debris that are displaced from the surface, as well as how a crater is formed in the regolith. At present, standard commercial CFD (computational fluid dynamics) software is not capable of coupling each of these flow regimes to provide an accurate representation of this flow process, necessitating the development of custom software. This software solves the fluid-flow-governing equations in an Eulerian framework, coupled with the particle transport equations that are solved in a Lagrangian framework. It uses a fourth-order explicit Runge-Kutta scheme for temporal integration, an eighth-order central finite differencing scheme for spatial discretization. The non-linear terms in the governing equations are recast in cubic skew symmetric form to reduce aliasing error. The second derivative viscous terms are computed using eighth-order narrow stencils that provide better diffusion for the highest resolved wave numbers. A fourth-order Lagrange interpolation procedure is used to obtain gas-phase variable values at the particle locations.

Bellan, Josette↗
NASA NTRS1978

Quantum mechanical theory of collisional ionization in the presence of intense laser radiation

The paper presents a quantum mechanical formalism for treating ionizing collisions occurring in the presence of an intense laser field. Both the intense laser radiation and the internal electronic continuum states associated with the emitted electrons are rigorously taken into account by combining discretization techniques with expansions in terms of electronic-field representations for the quasi-molecule-plus-photon system. The procedure leads to a coupled-channel description of the heavy-particle dynamics which involves effective electronic-field potential surfaces and continua. It is suggested that laser-influenced ionizing collisions can be studied to verify the effects of intense laser radiation on inelastic collisional processes. Calculation procedures for electronic transition dipole matrix elements between discrete and continuum electronic states are outlined.

Bellum, J. C.↗
NASA NTRS1982

Rational engineering correlations of diffusional and inertial particle deposition behavior in non-isothermal forced convection environments

A multiparameter correlation approach to the study of particle deposition rates in engineering applications is discussed with reference to two specific examples, one dealing with thermophoretically augmented small particle convective diffusion and the other involving larger particle inertial impaction. The validity of the correlations proposed here is demonstrated through rigorous computations including all relevant phenomena and interactions. Such representations are shown to minimize apparent differences between various geometric, flow, and physicochemical parameters, allowing many apparently different physicochemical situations to be described in a unified way.

Rosner, D. E.↗
NASA NTRS1999

Can A "Hyperspace" Really Exist?

The idea of "hyperspace" is suggested as a possible approach to faster-than-light (FTL) motion. A brief summary of a 1986 study on the Euclidean representation of space-time by the author is presented. Some new calculations on the relativistic momentum and energy of a free particle in Euclidean "hyperspace" are now added and discussed. The superimposed Energy-Momentum curves for subluminal particles, tachyons, and particles in Euclidean "hyperspace" are presented. It is shown that in Euclidean "hyperspace", instead of a relativistic time dilation there is a time "compression" effect. Some fundamental questions are presented,

Zampino, Edward J.↗
NASA NTRS1982

Solid particle dynamic behavior through twisted blade rows

The particle trajectory calculations provide the essential information which is required for predicting the pattern and intensity of turbomachinery erosion. Consequently, the evaluation of the machine performance deterioration due to erosion is extremely sensitive to the accuracy of the flow field and blade geometry representation in the trajectory computational model. A model is presented that is simple and efficient yet versatile and general to be applicable to axial, radial and mixed flow machines, and to inlets, nozzles, return passages and separators. The results of the computations are presented for the particle trajectories through a row of twisted vanes in the inlet flow field. The effect of the particle size on their trajectories, blade impacts, and on their redistribution and separation are discussed.

Hamed, A.↗
NASA NTRS1977

Adiabatic particle motion in a nearly drift-free magnetic field: Application to the geomagnetic tail

The guiding center motion of particles in a nearly drift free magnetic field is analyzed in order to investigate the dependence of mean drift velocity on equatorial pitch angle, the variation of local drift velocity along the trajectory, and other properties. The mean drift for adiabatic particles is expressed by means of elliptic integrals. Approximations to the twice-averaged Hamiltonian W near z = O are derived, permitting simple representation of drift paths if an electric potential also exists. In addition, the use of W or of expressions for the longitudinal invariant allows the derivation of the twice averaged Liouville equation and of the corresponding Vlasov equation. Bounce times are calculated (using the drift-free approximation), as are instantaneous guiding center drift velocities, which are then used to provide a numerical check on the formulas for the mean drift.

Stern, D. P.↗
NASA NTRS1994

Empirical models of the magnetospheric magnetic field

A general overview of magnetospheric modeling is given, along with a more detailed discussion of several empirical models which are widely used. These models are composed of representations of the Earth's main internal field (basically a bipolar field), plus external field contributions due to ring currents (carried by the particles in the Van Allen radiation belts), magnetopause currents (the boundary surface between the Earth's magnetic field and interplanetary magnetic field carried by the solar wind), and tail currents (carried by particles in the neutral sheet of the magnetotail). The empirical models presented here are the Mead-Fairfield, Olsen-Pfitzer tilt-dependent (1977), Tsyganenko-Usamo, Tsyganenko (1987), Olsen-Pfitzer dynamic (1988), Tsyganenko (1989), and Hilmer-Voight models. The derivations, agreement with quiet time and storm time data from the two satellite programs, Spacecraft Charging at High Altitudes (SCATHA) and Combined Release Radiation Effects Satellite (CRRES), and computational requirements of these models are compared.

Jordan, C. E.↗