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At least 1,117 records · Page 62
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NASA NTRS2008

Non-steady Reconnection in Global Simulations of Magnetosphere Dynamics

To analyze the non-steady magnetic reconnection during quasi-steady solar wind driving we employed high resolution global MHD model BATSRUS with non-MHD corrections in diffusion regions around the reconnection sites. To clarify the role of small-scale non-MHD effects on the global magnetospheric dynamic we performed simulations with different models of dissipation. We found that magnetopause surface is not in steady state even during extended periods of steady solar wind conditions. The so-called tilted reconnection lines become unstable due to formation of pressure bubbles, strong core field flux tubes, vortices, and traveling magnetic field cavities. Non-steady dayside reconnection results in formation of flux tubes with bended axis magnetically connecting magnetic field cavities generated at flanks and strong core segments formed near the subsolar region. We found that the rate of magnetic flux loading to the tail lobes is not very sensitive to the dissipation mechanism and details of the dayside reconnection. On the other hand the magnetotail reconnection rate, the speed of the reconnection site retreat and the global magnetotail dynamics strongly depend on the model of dissipation. THEMIS and Cluster observations are consistent with signatures predicted by simulations.

Kuznetsova, M. M.↗
NASA NTRS1973

Theoretical models for electron energy relaxation in the lower ionosphere

Elastic collisions and rotation inelastic collisions involving quadrupole molecular transitions are important in energy relaxation of electrons in molecular gases. It has been customary in studying the cooling of electrons in a plasma heated by high-frequency waves to characterize this relaxation by the ionospheric G factor. The G factor is first defined in a fundamental way by use of kinetic theory. Then present models for theoretical cross sections for electron collision with O2 and N2 are used to derive expressions for the G factor in the lower ionosphere. Two models are considered: one uses Gerjuoy-Stein models for both N2 and O2; the other uses a Gerjuoy-Stein model for N2 and a Geltman-Takayanaki model for O2. Neither O2 model has been definitely established experimentally. It is found that temperature dependence of G is critically dependent on the O2 model.

Hagenbuch, K. M.↗
NASA NTRS1988

A new look at coding for APD-based direct-detection optical channels

Coding for avalanche-photodiode (APD)-based direct-detection optical channels is investigated using a simple channel model that clearly points out the difference between the signal-dependent optical noise channel model and the additive white Gaussian noise channel model. Coding and modulation are viewed as a single entity, and the coding/modulation gain (CMG) is used to analyze and construct good codes for APD-based optical receivers. It is shown that the structure of block codes, when used in conjunction with on-off keying signaling, renders these codes fairly inefficient with respect to obtaining reasonable CMG on the optical channel. In contrast, codes (or modulations) that use fewer channel ones (pulses) than information ones per block can offer substantial CMG on the optical channel. For bandwidth-constrained applications, it is proposed that pulse-position modulation be used with more than one pulse per word to obtain reasonable CMG while consuming small amounts of bandwidth.

Herro, Mark A.↗
NASA NTRS1994

Research on Orbital Plasma-Electrodynamics (ROPE)

Since the development of probe theory by Langmuir and Blodgett, the problem of current collection by a charged spherically or cylindrically symmetric body has been investigated by a number of authors. This paper overviews the development of a fully three-dimensional particle simulation code which can be used to understand the physics of current collection in three dimensions and can be used to analyze data resulting from the future tethered satellite system (TSS). According to the TSS configurations, two types of particle simulation models were constructed: a simple particle simulation (SIPS) and a super particle simulation (SUPS). The models study the electron transient response and its asymptotic behavior around a three dimensional, highly biased satellite. The potential distribution surrounding the satellite is determined by solving Laplace's equation in the SIPS model and by solving Poisson's equation in the SUPS model. Thus, the potential distribution in space is independent of the density distribution of the particles in the SUPS model but it does depend on the density distribution of the particles in the SUPS model. The evolution of the potential distribution in the SUPS model is described. When the spherical satellite is charged to a highly positive potential and immersed in a plasma with a uniform magnetic field, the formation of an electron torus in the equatorial plane (the plane in perpendicular to the magnetic field) and elongation of the torus along the magnetic field are found in both the SIPS and the SUPS models but the shape of the torus is different. The areas of high potential that exist in the polar regions in the SUPS model exaggerate the elongation of the electron torus along the magnetic field. The current collected by the satellite for different magentic field strengths is investigated in both models. Due to the nonlinear effects present in SUPS, the oscillating phenomenon of the current collection curve during the first 10 plasma periods can be seen (this does not appear in SIPS). From the parametric studies, it appears that the oscillating phenomenon of the current collection curve occurs only when the magnetic field strength is less than 0.2 gauss for the present model.

Wu, S. T.↗
NASA NTRS2017

CEDAR-GEM Challenge for Systematic Assessment of Ionosphere/Thermosphere Models in Predicting TEC During the 2006 December Storm Event

In order to assess current modeling capability of reproducing storm impacts on total electron content (TEC), we considered quantities such as TEC, TEC changes compared to quiet time values, and the maximum value of the TEC and TEC changes during a storm. We compared the quantities obtained from ionospheric models against ground-based GPS TEC measurements during the 2006 AGU storm event (14-15 December 2006) in the selected eight longitude sectors. We used 15 simulations obtained from eight ionospheric models, including empirical, physics-based, coupled ionosphere-thermosphere, and data assimilation models. To quantitatively evaluate performance of the models in TEC prediction during the storm, we calculated skill scores such as RMS error, Normalized RMS error (NRMSE), ratio of the modeled to observed maximum increase (Yield), and the difference between the modeled peak time and observed peak time. Furthermore, to investigate latitudinal dependence of the performance of the models, the skill scores were calculated for five latitude regions. Our study shows that RMSE of TEC and TEC changes of the model simulations range from about 3 TECU (total electron content unit, 1 TECU = 1016 el m2) (in high latitudes) to about 13 TECU (in low latitudes), which is larger than latitudinal average GPS TEC error of about 2 TECU. Most model simulations predict TEC better than TEC changes in terms of NRMSE and the difference in peak time, while the opposite holds true in terms of Yield. Model performance strongly depends on the quantities considered, the type of metrics used, and the latitude considered.

Shim, J. S.↗
NASA NTRS2019

Quantifying the Storm Time Thermospheric Neutral Density Variations Using Model and Observations

Accurate determination of thermospheric neutral density holds crucial importance for satellited rag calculations. The problem is twofold and involves the correct estimation of the quiet time climatology and storm time variations. In this work, neutral density estimations from two empirical and threephysics based models of the ionosphere thermosphere are compared with the neutral densities along the Challenging MicroSatellite Payload satellite track for six geomagnetic storms. Storm time variations are extracted from neutral density by (1) subtracting the mean difference between model and observation (bias),(2) setting climatological variations to zero, and (3) multiplying model data with the quiet time ratio between the model and observation. Several metrics are employed to evaluate the model performances. We find that the removal of bias or climatology reveals actual performance of the model in simulating the storm time variations. When bias is removed, depending on event and model, storm time errors in neutral density can decrease by an amount of 113% or can increase by an amount of 12% with respect to error in models with quiet time bias. It is shown that using only average and maximum values of neutral density to determine the model performances can be misleading since a model can estimate the averages fairly well but may not capture the maximum value or vice versa. Since each of the metrics used for determining model performances provides different aspects of the error, among these, we suggest employing mean absolute error, prediction efficiency, and normalized root mean square error together as a standard set ofmetrics for the neutral density.

Eyiguler, E. Ceren Kalafatoglu↗
NASA NTRSDate not supplied

Improving Multi-Model Trajectory Simulation Estimators using Model Selection and Tuning

Multi-model Monte Carlo methods have been demonstrated to be an efficient and accurate alternative to standard Monte Carlo (MC) in the model-based propagation of uncertainty in entry, descent, and landing (EDL) applications. These multi-model MC methods fuse predictions from low-fidelity models with the high-fidelity EDL model of interest to produce unbiased statistics with a fraction of the computational cost. The accuracy and efficiency of the multi-model MC methods are dependent upon the magnitude of correlations of the low-fidelity models with the high-fidelity model, but also upon the correlation amongst the low-fidelity models, and their relative computational cost. Because of this layer of complexity, the question of how to optimally select the set of low-fidelity models has remained open. In this work, methods for optimal model construction and tuning are investigated as a means to increase the speed and precision of trajectory simulation for EDL. Specifically, the focus is on the inclusion of low-fidelity model tuning within the sample allocation optimization that accompanies multi-model MC methods. Preliminary results indicate that low-fidelity model tuning can significantly improve efficiency and precision of trajectory simulations and provide an increased edge to multi-model MC methods when compared to standard MC. The challenges and potential benefits to exploring a fully iterative and comprehensive optimization strategy in future work are highlighted.

uncertainty quantification↗
NASA NTRSDate not supplied

Improving Multi-Model Trajectory Simulation Estimators using Model Selection and Tuning

Multi-model Monte Carlo methods have been demonstrated to be an efficient and accurate alternative to standard Monte Carlo (MC) in the model-based propagation of uncertainty in entry, descent, and landing (EDL) applications. These multi-model MC methods fuse predictions from low-fidelity models with the high-fidelity EDL model of interest to produce unbiased statistics with a fraction of the computational cost. The accuracy and efficiency of the multi-model MC methods are dependent upon the magnitude of correlations of the low-fidelity models with the high-fidelity model, but also upon the correlation among the low-fidelity models, and their relative computational cost. Because of this layer of complexity, the question of how to optimally select the set of low-fidelity models has remained open. In this work, methods for optimal model construction and tuning are investigated as a means to increase the speed and precision of trajectory simulation for EDL. Specifically, the focus is on the inclusion of low-fidelity model tuning within the sample allocation optimization that accompanies multi-model MC methods. Preliminary results indicate that low-fidelity model tuning can significantly improve efficiency and precision of trajectory simulations and provide an increased edge to multi-model MC methods when compared to standard MC. The challenges and potential benefits to exploring a fully iterative and comprehensive optimization strategy in future work are highlighted.

uncertainty quantification↗
NASA NTRS2017

Quantifying the Causes of Differences in Tropospheric OH Within Global Models

The hydroxyl radical (OH) is the primary daytime oxidant in the troposphere and provides the main loss mechanism for many pollutants and greenhouse gases, including methane (CH4). Global mean tropospheric OH differs by as much as 80% among various global models, for reasons that are not well understood. We use neural networks (NNs), trained using archived output from eight chemical transport models (CTMs) that participated in the Polar Study using Aircraft, Remote Sensing, Surface Measurements and Models, of Climate, Chemistry, Aerosols and Transport Model Intercomparison Project (POLMIP), to quantify the factors responsible for differences in tropospheric OH and resulting CH4 lifetime (Tau CH4) between these models. Annual average Tau CH4, for loss by OH only, ranges from 8.0 to 11.6 years for the eight POLMIP CTMs. The factors driving these differences were quantified by inputting 3-D chemical fields from one CTM into the trained NN of another CTM. Across all CTMs, the largest mean differences in Tau CH4 (Delta Tau CH4) result from variations in chemical mechanisms (Delta Tau CH4 = 0.46 years), the photolysis frequency (J) of O3 yields O(D-1) (0.31 years), local O3 (0.30 years), and CO (0.23 years). The Delta Tau CH4 due to CTM differences in NO(x) (NO + NO2) is relatively low (0.17 years), although large regional variation in OH between the CTMs is attributed to NO(x). Differences in isoprene and J(NO2) have negligible overall effect on globally averaged tropospheric OH, although the extent of OH variations due to each factor depends on the model being examined. This study demonstrates that NNs can serve as a useful tool for quantifying why tropospheric OH varies between global models, provided that essential chemical fields are archived.

Surface Measurements and Models↗
NASA NTRS1996

Gravity Induced Formation of Concentration Gradients in Supersaturated Binary Solutions

Experimental and theoretical studies of the formation of solute concentration gradient in supersaturated binary solutions in a gravitational field were carried out. The formation of solute concentration gradient was associated with the gravity induced redistribution of subcritical solute clusters. The birth-death process of the new solute-rich phase domains (subcritical solute clusters) was described in terms of the time-dependent Ginzburg Landau model developed for metastable state relaxation in binary (solute + solvent) non-critical solutions in the presence of a gravitational field. A new mathematical Ansatz was developed for solution of the model equations. This Ansatz has allowed to approach for the first time the following important problems: (1) Microstructure of solute distribution inside of the subcritical solute clusters. The analytical results obtained demonstrate that solute inside of the subcritical solute clusters is heterogeneously distributed with a spatially periodic structure. (2) Macrostructure of the solute subcritical clusters distribution in a gravitational field. The subcritical solute clusters are found to be distributed heterogeneously in a gravitational field. This heterogeneity, which is due to the heterogeneous birth-death process of the subcritical solute clusters in a gravitational field, initiates a noticeable solute concentration gradient in vertical columns of supersaturated binary solutions. An analysis and comparison of theoretical results and experimental data related to the solute concentration gradient formation in a gravitational field are presented. It is also demonstrated that the critical radius of solute clusters (radius of nucleation) and induction time are gravity-dependent.

Izmailov, Alexander F.↗
NASA NTRS2001

Results from Global Land-Surface Data Assimilation Methods

Realistic representation of the land surface is crucial in global climate modeling (GCM). Recently, the Mosaic land-surface Model (LSM) has been driven off-line using GEOS DAS (Goddard Earth Observing System Data Assimilation System) atmospheric forcing, forming the Off-line Land-surface Global Assimilation (OLGA) system. This system provides a computationally efficient test bed for land surface data assimilation. Here, we validate the OLGA simulation of surface processes and the assimilation of ISCCP surface temperatures. Another component of this study as the incorporation of the Physical-space Statistical Analysis System (PSAS) into OLGA, in order to assimilate surface temperature observations from the International Satellite Cloud Climatology Project (ISCCP). To counteract the subsequent forcing of the analyzed skin temperature back to the initial state following the analysis. incremental bias correction (IBC) was included in the assimilation. The IBC scheme effectively removed the time mean bias, but did not remove him in the mean diurnal cycle. Therefore, a diurnal him correction (DBC) scheme was developed, where the time-dependent bias was modeled with a sine wave parameterization. In addition, quality control of the ISCCP data and anisotropic temperature correction were implemented in PSAS. Preliminary results showed a substantial impact from the inclusion of PSAS and DBC that was visible in the surface meteorology fields and energy budget. Also, the monthly mean diurnal cycle from the experiment closely matched the diurnal cycle from the observations.

Radakovich, Jon D.↗
NASA NTRS1990

Fault trees and sequence dependencies

One of the frequently cited shortcomings of fault-tree models, their inability to model so-called sequence dependencies, is discussed. Several sources of such sequence dependencies are discussed, and new fault-tree gates to capture this behavior are defined. These complex behaviors can be included in present fault-tree models because they utilize a Markov solution. The utility of the new gates is demonstrated by presenting several models of the fault-tolerant parallel processor, which include both hot and cold spares.

Dugan, Joanne Bechta↗
NASA NTRS2009

Further Investigations of Gravity Modeling on Surface-Interacting Vehicle Simulations

A vehicle simulation is "surface-interacting" if the state of the vehicle (position, velocity, and acceleration) relative to the surface is important. Surface-interacting simulations perform ascent, entry, descent, landing, surface travel, or atmospheric flight. The dynamics of surface-interacting simulations are influenced by the modeling of gravity. Gravity is the sum of gravitation and the centrifugal acceleration due to the world s rotation. Both components are functions of position relative to the world s center and that position for a given set of geodetic coordinates (latitude, longitude, and altitude) depends on the world model (world shape and dynamics). Thus, gravity fidelity depends on the fidelities of the gravitation model and the world model and on the interaction of the gravitation and world model. A surface-interacting simulation cannot treat the gravitation separately from the world model. This paper examines the actual performance of different pairs of world and gravitation models (or direct gravity models) on the travel of a subsonic civil transport in level flight under various starting conditions.

Madden, Michael M.↗
NASA NTRS2010

Gravity Modeling Effects on Surface-Interacting Vehicles in Supersonic Flight

A vehicle simulation is "surface-interacting" if the state of the vehicle (position, velocity, and acceleration) relative to the surface is important. Surface-interacting simulations per-form ascent, entry, descent, landing, surface travel, or atmospheric flight. The dynamics of surface-interacting simulations are influenced by the modeling of gravity. Gravity is the sum of gravitation and the centrifugal acceleration due to the world s rotation. Both components are functions of position relative to the world s center and that position for a given set of geodetic coordinates (latitude, longitude, and altitude) depends on the world model (world shape and dynamics). Thus, gravity fidelity depends on the fidelities of the gravitation model and the world model and on the interaction of these two models. A surface-interacting simulation cannot treat gravitation separately from the world model. This paper examines the actual performance of different pairs of world and gravitation models (or direct gravity models) on the travel of a supersonic aircraft in level flight under various start-ing conditions.

Madden, Michael M.↗
NASA NTRS2023

Interactions Between Thresholds and Spatial Discretizations of Snow: Insights From Estimates of Wolverine Denning Habitat in the Colorado Rocky Mountains

Thresholds can be used to interpret environmental data in a way that is easily communicated and useful for decision making purposes. However, thresholds are often developed for specific data products and time periods, changing findings when the same threshold is applied to datasets or periods with different characteristics. Here, we test the impact of different spatial discretizations of snow on annual estimates of wolverine denning opportunities in the Colorado Rocky Mountains, defined using a snow water equivalent (SWE) threshold (0.20 m) and threshold date (15 May) from previous habitat assessments. Annual potential wolverine denning area (PWDA) was thresholded from a 36-year (1985 – 2020) snow reanalysis model with three different spatial discretizations: 1) 480 m grid cells (D480), 2) 90 m grid cells (D90), and 3) 480 m grid cells with implicit representations of subgrid snow spatial heterogeneity (S480). Relative to the D480 and S480 discretizations, D90 resolved shallower snow deposits on slopes between 3050 and 3350 m elevation, decreasing PWDA by 10%, on average. In years with warmer and/or drier winters, S480 discretizations with subgrid representations of snow heterogeneity increased PWDA, even within grid cells where mean 15 May SWE was less than the SWE threshold. These simulations increased PWDA by upwards of 30% in low snow years, as compared to the D480 and D90 simulations without subgrid snow heterogeneity. Despite PWDA sensitivity to different snow spatial discretizations, PWDA was controlled more by annual variations in winter precipitation and temperature. However, small changes to the SWE threshold (± 0.07 m) and threshold date (± 2 weeks) also affected PWDA by as much as 82%. Across these threshold ranges, PWDA was approximately 18% more sensitive to the SWE threshold than the threshold date. However, the sensitivity to the threshold date was larger in years with late spring snowfall, when PWDA depended on whether modeled SWE was thresholded before, during, or after spring snow accumulation. Our results demonstrate that snow thresholds are useful but may not always provide a complete picture of the annual variability in snow-adapted wildlife denning opportunities. Studies thresholding spatiotemporal datasets could be improved by including 1) information about the fidelity of thresholds across multiple spatial discretizations, and 2) uncertainties related to ranges of realistic thresholds.

Justin M. Pflug↗
NASA NTRS2007

A Stellar-mass Black Hole in the Ultra-luminous X-ray Source M82 X-1

We have analyzed the archival XMM-Newton data of the archetypal Ultra-Luminous X-ray Source (ULX) M82 X-1 with an LO5 ksec exposure when the source was in the steady state. Thanks to the high photon statistics from the large effective area and long exposure, we were able to discriminate different X-ray continuum spectral models. Neither the standard accretion disk model (where the radial dependency of the disk effective temperature is T(r) proportional to r(sup -3/4)) nor a power-law model gives a satisfactory fit. In fact, observed curvature of the M82 X-1 spectrum was just between those of the two models. When the exponent of the radial dependence (p in T(r) proportional to r(sup -P)) of the disk temperature is allowed to be free, we obtained p = 0.61 (sup +0.03)(sub -0.02). Such a reduction of p from the standard value 3/4 under extremely high mass accretion rates is predicted from the accretion disk theory as a consequence of the radial energy advection. Thus, the accretion disk in M82 X-1 is considered to be in the Slim disk state, where an optically thick Advection Dominant Accretion Flow (ADAF) is taking place. We have applied a theoretical slim disk spectral model to M82 X-1, and estimated the black hole mass approximately equal to 19 - 32 solar mass. We conclude that M82 X-1 is a stellar black hole which has been produced through evolution of an extremely massive star, shining at a several times the super-Eddington luminosity.

Okajima, Takashi↗
NASA NTRS1992

The abundance and distribution of water vapor in the Jovian troposphere as inferred from Voyager IRIS observations

The Voyager IRIS spectra of the Jovian North Equatorial Belt (NEB) hot spots are reanalyzed using a radiative transfer model which includes the full effects of anisotropic multiple scattering by clouds. The atmospheric model includes the three thermochemically predicted cloud layers, NH3, NH4SH, and H2O. Spectrally dependent cloud extinction is modeled using Mie theory and the refractive indices of NH3 ice, NH4SH ice, water, and H2O ice. The upper tropospheric temperature profile, gas abundances, height-dependent parahydrogen profile, and vertical distribution of NH3 cloud opacity are retrieved from an analysis of the far-infrared (180-1200/cm) IRIS observations. With these properties constrained, the 5-micron (1800-2300/cm) observations are analyzed to determine the atmospheric and cloud structure of the deeper atmosphere (P of greater than 1.5 bars). The results show that the abundance of water is at least 1.5 times solar with 2 times solar (0.00276 mixing ratio relative to H2) providing the best-fit to the Voyager IRIS hot spot observations.

Carlson, Barbara E.↗