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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Efficiency of a statistical transport model for turbulent particle dispersion

In developing its theory for turbulent dispersion transport, the Litchford and Jeng (1991) statistical transport model for turbulent particle dispersion took a generalized approach in which the perturbing influence of each turbulent eddy on consequent interactions was transported through all subsequent eddies. Nevertheless, examinations of this transport relation shows it to be able to decay rapidly: this implies that additional computational efficiency may be obtained via truncation of unneccessary transport terms. Attention is here given to the criterion for truncation, as well as to expected efficiency gains.

Litchford, Ron J.↗
NASA NTRS2020

Ensemble PM2.5 Forecasting during the 2018 Camp Fire Event Using the HYSPLIT Transport and Dispersion Model

Biomass burning releases a vast amount of aerosols into the atmosphere, often leading to severe air quality and health problems. Prediction of the air quality effects from biomass burning emissions is challenging due to uncertainties in fire emission, plume rise calculation, and other model inputs/processes. Ensemble forecasting is increasingly used to represent model uncertainties. In this paper, an ensemble forecast was conducted to predict surface PM2.5 during the 2018 California Camp Fire event using the NOAA HYSPLIT dispersion model at 0.1- degree horizontal resolution. Different combinations of four satellite-based fire emission datasets (FEER, FLAMBE, GBBEPx and GFAS), two plume rise schemes (Briggs and Sofiev), various meteorology inputs and model setup options were used to create the forecast ensemble, for a total of 112 experiments. The performance of each ensemble member and the ensemble mean were evaluated using ground-based observations, with four statistical metrics and an overall rank. The ensemble spread of the 112 members reached 1000 μg/m3, highlighting the large uncertainty in wildfire forecast. The ensemble mean displayed the best performance. Each fire emission product contributed to one or more members among the top ten performers, revealing the forecasting dependence on both the quality of fire emissions data and model representation of emission, transport and removal processes. In addition, an ensemble size reduction technique was introduced. With the help of this technique, the ensemble size was reduced from 112 to 28 members and still produced an ensemble mean that yielded comparable or even better performance to that of the full ensemble.

Biomass Burning↗
NASA NTRS1978

Status of aerial applications research in the Langley vortex research facility and the Langley full-scale wind tunnel

Small scale models of agricultural airplanes were tested and numerical methods were utilized to study interactions between the airplane wake and the dispersed spray and granular materials. Methods were developed to measure and predict dispersal transport and wake characteristics and dispersal techniques to obtain interactions more favorable to wide, uniform deposition patterns and reduced drift. In the full scale wind tunnel, full scale agricultural airplanes and dispersal systems for both liquid and solid applications were evaluated to improve aircraft aerodynamics and dispersal systems efficiency. The program status in these two facilities is reported with emphasis on wake interactions and dispersal systems research.

Jordan, F. L., Jr.↗
NASA NTRS1974

Diffusion algorithms and data reduction routine for onsite launch predictions for the transport of Titan 3 C exhaust effluents

The NASA/MSFC multilayer diffusion algorithms have been specialized for the prediction of the surface impact for the dispersive transport of the exhaust effluents from the launch of a Titan 3 vehicle. This specialization permits these transport predictions to be made at the launch range in real time so that the effluent monitoring teams can optimize their monitoring grids. Basically, the data reduction routine requires just the meteorology profiles for the thermodynamics and kinematics of the atmosphere as an input. These profiles are graphed along with the resulting exhaust cloud rise history, the center line concentrations and dosages, and the hydrogen chloride isopleths.

Stephens, J. B.↗
NASA NTRS1976

Diffusion algorithms and data reduction routine for onsite real-time launch predictions for the transport of Delta-Thor exhaust effluents

The National Aeronautics and Space Administration/Marshall Space Flight Center multilayer diffusion algorithms have been specialized for the prediction of the surface impact for the dispersive transport of the exhaust effluents from the launch of a Delta-Thor vehicle. This specialization permits these transport predictions to be made at the launch range in real time so that the effluent monitoring teams can optimize their monitoring grids. Basically, the data reduction routine requires only the meteorology profiles for the thermodynamics and kinematics of the atmosphere as an input. These profiles are graphed along with the resulting exhaust cloud rise history, the centerline concentrations and dosages, and the hydrogen chloride isopleths.

Stephens, J. B.↗
NASA NTRS1974

Atmospheric diffusion predictions for the exhaust effluents from the launch of a Titan 3C, December 13, 1973

Results for the predictions with the NASA/MSFC Multilayer Diffusion Model for the dispersive transport of the Titan 3C rocket exhaust effluents for the 1857 EST launch on December 13, 1973, from the Eastern Test Range at Cape Canaveral Air Force Station are presented. An atmospheric assessment is made in support of the joint Marshall Space Flight Center, Langley Research Center, and Kennedy Space Center rocket exhaust prediction and measurement program. The predictions are primarily intended to define a monitoring grid and for a postflight assessment of the field measurements in order to improve diffusion prediction techniques.

Stephens, J. B.↗
NASA NTRS1991

Annealing characteristics of amorphous silicon alloy solar cells irradiated with 1.00 MeV protons

Amorphous Si:H and amorphous Si sub x, Ge sub (1-x):H solar cells were irradiated with 1.00 MeV proton fluences in the range of 1.00E14 to 1.25E15 cm (exp -2). Annealing of the short circuit current density was studied at 0, 22, 50, 100, and 150 C. Annealing times ranged from an hour to several days. The measurements confirmed that annealing occurs at 0 C and the initial characteristics of the cells are restored by annealing at 200 C. The rate of annealing does not appear to follow a simple nth order reaction rate model. Calculations of the short-circuit current density using quantum efficiency measurements and the standard AM1.5 global spectrum compare favorably with measured values. It is proposed that the degradation in J sub sc with irradiation is due to carrier recombination through the fraction of D (o) states bounded by the quasi-Fermi energies. The time dependence of the rate of annealing of J sub sc does appear to be consistent with the interpretation that there is a thermally activated dispersive transport mechanism which leads to the passivation of the irradiation induced defects.

Abdulaziz, Salman S.↗
NASA NTRS2000

Ozone and Water Vapor Measurements by Raman Lidar in the Planetary Boundary Layer: Error Sources and Field Measurements

Why do we need time series of ozone and water vapor profiles at low altitude? The degradation of air quality is a very serious environmental problem that affects urban and industrial areas worldwide. Air pollution injures human health and ecosystems, diminishes crop yield, and spoils patrimony and materials. The phenomena involved in air pollution are very complex. Once emitted into the atmosphere, (primary) pollutants are transported, dispersed, transformed by gas/solid phase change and chemical reaction, and finally removed by dry and wet deposition. Most challenging is the fact that the health and environmental impacts of secondary pollutants (formed in the atmosphere) are frequently more severe than those of their precursors (primary pollutants). This is the case of ozone and other photochemical pollutants, such as peroxyacetil nitrate (PAN) and secondary particles, produced in the atmosphere by the photo-oxidation volatile organic compounds (VOC) catalyzed by nitrogen oxides (NO(sub x)). Photochemical air pollution is a complex science because of the non-linearity of its response to changes in primary emission.

Lazzarotto, Benoit↗
NASA NTRS2000

Electrostatics of Granular Material (EGM): Space Station Experiment

Aggregates were observed to form very suddenly in a lab-contained dust cloud, transforming (within seconds) an opaque monodispersed cloud into a clear volume containing rapidly-settling, long hair-like aggregates. The implications of such a "phase change" led to a series of experiments progressing from the lab, to KC-135, followed by micro-g flights on USML-1 and USML-2, and now EGM slated for Space Station. We attribute the sudden "collapse" of a cloud to the effect of dipoles. This has significant ramifications for all types of cloud systems, and additionally implicates dipoles in the processes of cohesion and adhesion of granular matter. Notably, there is the inference that like-charged grains need not necessarily repel if they are close enough together: attraction or repulsion depends on intergranular distance (the dipole being more powerful at short range), and the D/M ratio for each grain, where D is the dipole moment and M is the net charge. We discovered that these ideas about dipoles, the likely pervasiveness of them in granular material, the significance of the D/M ratio, and the idea of mixed charges on individual grains resulting from tribological processes --are not universally recognized in electrostatics, granular material studies, and aerosol science, despite some early seminal work in the literature, and despite commercial applications of dipoles in such modern uses as "Krazy Glue", housecleaning dust cloths, and photocopying. The overarching goal of EGM is to empirically prove that (triboelectrically) charged dielectric grains of material have dipole moments that provide an "always attractive" intergranular force as a result of both positive and negative charges residing on the surfaces of individual grains. Microgravity is required for this experiment because sand grains can be suspended as a cloud for protracted periods, the grains are free to rotate to express their electrostatic character, and Coulombic forces are unmasked. Suspended grains will be "interrogated" by applied electrical fields. In one module, grains will be immersed in an inhomogeneous electric field and allowed to be attracted towards or repelled from the central electrode of the module: part of the grain's speed will be a function of its net charge (monopole), part will be a function of the dipole. Observed grain position vs. time will provide a curve that can be deconvolved into the dipole and monopole forces responsible, since both have distinctive radial dependencies. In a second approach, the inhomogeneous field will be alternated at low frequency (e.g., every 5-10 seconds) so that the grains are alternately attracted and repelled from the center of the field. The resulting "zigzag" grain motion will gradually drift inwards, then suddenly change to a unidirectional inward path when a critical radial distance is encountered (a sort of "Coulombic event horizon") at which the dipole strength supersedes the monopole strength --thus proving the presence of a dipole, while also quantifying the D/M ratio. In a second module, an homogeneous electric field eliminates dipole effects (both Coulombic and induced) to provide calibration of the monopole and to more readily evaluate net charge statistical variance. In both modules, the e-fields will be exponentially step-ramped in voltage during the experiment, so that the field "nominalizes" grain speed while spreading the response time --effectively forcing each grain to "wait its turn" to be measured. In addition to rigorously quantifying M, D, and the D/M ratio for many hundreds of grains, the experiment will also observe gross electrometric and RF discharge phenomena associated with grain activity. The parameter space will encompass grain charging levels (via intentional triboelectrification), grain size, cloud density, and material type. Results will prove or disprove the dipole hypothesis. In either case, light will be shed on the role of electrostatic forces in governing granular systems. Knowledge so gained can be applied to natural clouds such as protostellar and protoplanetary dust and debris systems, planetary rings, planetary dust palls and aerosols created by volcanic, impact, aeolian, firestorm, or nuclear winter processes. The data are also directly applicable to adhesion, cohesion, transport, dispersion, and collection of granular materials in industrial, agricultural, pharmaceutical applications, and in fields as diverse as dust contamination of space suits on Mars and crop spraying on Earth.

Marshall, J.↗
NASA NTRS2012

Total Dose Effects on Bipolar Integrated Circuits at Low Temperature

Total dose damage in bipolar integrated circuits is investigated at low temperature, along with the temperature dependence of the electrical parameters of internal transistors. Bandgap narrowing causes the gain of npn transistors to decrease far more at low temperature compared to pnp transistors, due to the large difference in emitter doping concentration. When irradiations are done at temperatures of -140 deg C, no damage occurs until devices are warmed to temperatures above -50 deg C. After warm-up, subsequent cooling shows that damage is then present at low temperature. This can be explained by the very strong temperature dependence of dispersive transport in the continuous-time-random-walk model for hole transport. For linear integrated circuits, low temperature operation is affected by the strong temperature dependence of npn transistors along with the higher sensitivity of lateral and substrate pnp transistors to radiation damage.

linear integrated circuits↗
NASA NTRS2021

Planetary Boundary Layer Height Estimates From ICESat-2 and CATS Backscatter Measurements

The lowest layer of the atmosphere in which all human activity occurs is called the Planetary Boundary Layer (PBL). All physical interactions with the surface, such as heat and moisture transport, pollution dispersion and transport happen in this relatively shallow layer. The ability to understand and model the complex interactions that occur in the PBL is very important to air quality, weather prediction and climate modeling. A fundamental and physically important property of the PBL is its thickness or height. This work presents two methods to obtain global PBL height using satellite lidar data from the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) and the Cloud-Aerosol Transport System (CATS). The first method is a straightforward backscatter threshold technique and the second is a machine learning approach known as a Convolutional Neural Network. The PBL height retrievals from the two methods are compared with each other and with PBL height from the NASA GEOS MERRA-2 reanalysis. The lidar-retrieved PBL heights have a high degree of spatial correlation with the model heights but are generally higher over ocean (∼400 m) and over northern hemisphere high latitude regions (∼1,000 m). Over mid-latitude and tropical land areas, the satellite estimated PBL heights agree well with model mid-day estimates. This work demonstrates the feasibility of using satellite lidar backscatter measurements to obtain global PBL height estimates, as well as determining seasonal and regional variability of PBL height.

Stephen P Palm↗
NASA NTRS1973

Retrieval of dispersive and convective transport phenomena in fluids using stationary and nonstationary time domain analysis

Simultaneously occuring dispersive and convective components of fluid kinematics are obtained by a time domain analysis of optically retrieved temporal histories of the transport phenomena. Utilizing triangulation of collimated optical fields of view from two radiometers to obtain the temporal histories of the intensity fluctuations associated with the transport phenomena has enabled investigators to retrieve the local convective transport by employing correlation statistics. The location of the peak in the covariance curve determines the transit time from which the convection velocity is calculated; whereas, the change in shape of the peak in the covariance curve determines the change in average frequency of the wave packet from which the dispersion velocity is calculated. Thus, two-component analysis requires the maximum possible enhancement of the delineation for the transport. The convection velocity is the result of a fixed reference frame calculation whereas, the dispersion velocity is the result of a moving reference frame calcuation.

Stephens, J. B.↗
NASA NTRS2004

Direct Measurements of Eddy Transport and Thermal Dispersion in a High Porosity Matrix

Thermal losses from the hot end to the cold end of a Stirling cycle regenerator due to thermal dispersion through the regenerator matrix may significantly degrade the performance of the machine. Because of poor access to the void spaces within the porous medium, no direct measurements of thermal dispersion have been made and dispersion models have been derived indirectly. This is done by measuring the overall thermal performance of the regenerator and subtracting off the energy transfer caused by molecular conduction and advected enthalpy flows computed from volume-averaged fluid velocity and temperature. In the current program, a large-scale porous matrix consisting of stacked wire screens with a porosity of 90% is installed in a flow rig which is operated in a Reynolds number range that represents Stirling engine regenerator flow. Experiments are conducted to measure turbulent transport of momentum at the exit phase using hot-wires. The relationship of such turbulent transport terms to the thermal dispersion term in the volumetric-averaged energy equation for the regenerator matrix is developed and the measurements are used to determine cross-stream thermal dispersion. A dispersion model based upon the measurements is proposed and compared with models documented in the literature.

Niu, Yi↗
NASA NTRS2019

Investigating Sources of Variability and Error in Simulations of Carbon Dioxide in an Urban Region

Greenhouse gas (GHG) emissions estimation methods that use atmospheric trace gas observations, including inverse modeling techniques, perform better when carbon dioxide (CO2) fluxes are more accurately transported and dispersed in the atmosphere by a numerical model. In urban areas, transport and dispersion is particularly difficult to simulate using current mesoscale meteorological models due, in part, to added complexity from surface heterogeneity and fine spatial/temporal scales. It is generally assumed that the errors in GHG estimation methods in urban areas are dominated by errors in transport and dispersion. Other significant errors include, but are not limited to, those from assumed emissions magnitude and spatial distribution. To assess the predictability of simulated trace gas mole fractions in urban observing systems using a numerical weather prediction model, we employ an Eulerian model that combines traditional meteorological variables with multiple passive tracers of atmospheric CO2 from anthropogenic inventories and a biospheric model. The predictability of the Eulerian model is assessed by comparing simulated atmospheric CO2 mole fractions to observations from four in situ tower sites (three urban and one rural) in the Washington DC/Baltimore, MD area for February 2016. Four different gridded fossil fuel emissions inventories along with a biospheric flux model are used to create an ensemble of simulated atmospheric CO2 observations within the model. These ensembles help to evaluate whether the modeled observations are impacted more by the underlying emissions or transport. The spread of modeled observations using the four emission fields indicates the model's ability to distinguish between the different inventories under various meteorological conditions. Overall, the Eulerian model performs well; simulated and observed average CO2 mole fractions agree within 1% when averaged at the three urban sites across the month. However, there can be differences greater than 10% at any given hour, which are attributed to complex meteorological conditions rather than differences in the inventories themselves. On average, the mean absolute error of the simulated compared to actual observations is generally twice as large as the standard deviation of the modeled mole fractions across the four emission inventories. This result supports the assumption, in urban domains, that the predicted mole fraction error relative to observations is dominated by errors in model meteorology rather than errors in the underlying fluxes in winter months. As such, minimizing errors associated with atmospheric transport and dispersion may help improve the performance of GHG estimation models more so than improving flux priors in the winter months. We also find that the errors associated with atmospheric transport in urban domains are not restricted to certain times of day. This suggests that atmospheric inversions should use CO2 observations that have been filtered using meteorological observations rather than assuming that meteorological modeling is most accurate at certain times of day (such as using only mid-afternoon observations).

CO2↗
DOE OSTI2025

The QUIC Start Guide (V.6.4.9)

QUIC stands for the Quick Urban & Industrial Complex (QUIC) dispersion modeling system. QUIC is a fast response urban dispersion model that runs on a laptop. QUIC is comprised of a 3D wind field model called QUIC-URB, a transport and dispersion model called QUIC-PLUME, and graphical user interface called QUIC-GUI. QUIC also includes QUIC-PRESSURE to solve for pressure fields in and around buildings, a population exposure assessment tool called QUIC-POP, and an indoor infiltration calculator for computing indoor concentrations. Transport and dispersion for different types of airborne contaminants can be computed on building to neighborhood scales in tens of seconds to tens of minutes. QUIC will never give perfect answers, but it will account for the effects of buildings in an approximate way and provide more realism than non-building aware dispersion models.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1989

The effect of dispersion upon charged particle transport in random magnetic fields

Shortly after a strongly anisotropic beam is injected along a guiding magnetic field on which is superposed a small random component, the charged-particle density can be represented by a Gaussian profile whose center moves with the coherent velocity and whose width increases with time at a rate controlled by the coefficient of dispersion. Both parameters of this coherent mode of propagation depend upon the mean free path, which characterizes scattering by the random fields, and the focusing length, which characterizes spatial variations of the guiding field. These dependences are known explicitly for the coherent velocity, but expressions for the coefficient of dispersion are available only in the limits of very weak and very strong focusing. To span this gap, a more comprehensive analytic description of focused transport has been developed. This description includes dispersion and is valid for arbitrary spatial dependences of both the scattering mean free path and the focusing length.

Earl, James A.↗
NASA NTRS1991

Evaluation of an efficient statistical transport model for turbulent droplet dispersion in dilute combusting sprays

Evaluation of an efficient statistical transport model for turbulent droplet dispersion is made for a dilute spray of methanol droplets injected into a turbulent, axisymmnetric methane-fuelled diffusion flame burning in stagnant air. In the dispersion model, a computational parcel representing a group of physical particles (droplets) is considered to have a normal probability density function (pdf) in space. The mean is determined by Lagrangian tracking through a sequence of stochastically generated turbulent eddies and the variance is evaluated from a statistical formulation based on the linearized particle equations of motion. The basic validity of this model is established through comparison with available experimental data and with theoretical predictions using a conventional stochastic direct modeling approach. The conclusion of the evaluation is that the proposed dispersion model compares favorably with experimental data and provides a valid technique for simulating turbulent combusting sprays with significant computational savings over conventional methods.

Litchford, Ron J.↗