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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 NTRS2020

Dynamic Medical Risk Assessment Supported by Inference Networks

The Human Research Program's next generation risk model, the Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT), provides researchers with estimates of astronaut medical and health risk. MEDPRATs Susceptibility Inference Network (SIN) facilitates the dynamic component of this tool. The SIN provides MEDPRAT with a "memory" that allows the system to use knowledge of what simulation events have occurred to alter the representative probability that future simulation events will occur during a given trial. The SIN allows for the medical events being simulated to be related to, and influence the likelihood of one another, providing a more robust risk estimate. We present initial work of our efforts to mathematically quantify and represent these dependent relationships between medical events.

McIntyre, L.↗
NASA NTRS2011

Large Eddy Simulation Study for Fluid Disintegration and Mixing

A new modeling approach is based on the concept of large eddy simulation (LES) within which the large scales are computed and the small scales are modeled. The new approach is expected to retain the fidelity of the physics while also being computationally efficient. Typically, only models for the small-scale fluxes of momentum, species, and enthalpy are used to reintroduce in the simulation the physics lost because the computation only resolves the large scales. These models are called subgrid (SGS) models because they operate at a scale smaller than the LES grid. In a previous study of thermodynamically supercritical fluid disintegration and mixing, additional small-scale terms, one in the momentum and one in the energy conservation equations, were identified as requiring modeling. These additional terms were due to the tight coupling between dynamics and real-gas thermodynamics. It was inferred that if these terms would not be modeled, the high density-gradient magnitude regions, experimentally identified as a characteristic feature of these flows, would not be accurately predicted without the additional term in the momentum equation; these high density-gradient magnitude regions were experimentally shown to redistribute turbulence in the flow. And it was also inferred that without the additional term in the energy equation, the heat flux magnitude could not be accurately predicted; the heat flux to the wall of combustion devices is a crucial quantity that determined necessary wall material properties. The present work involves situations where only the term in the momentum equation is important. Without this additional term in the momentum equation, neither the SGS-flux constant-coefficient Smagorinsky model nor the SGS-flux constant-coefficient Gradient model could reproduce in LES the pressure field or the high density-gradient magnitude regions; the SGS-flux constant- coefficient Scale-Similarity model was the most successful in this endeavor although not totally satisfactory. With a model for the additional term in the momentum equation, the predictions of the constant-coefficient Smagorinsky and constant-coefficient Scale-Similarity models were improved to a certain extent; however, most of the improvement was obtained for the Gradient model. The previously derived model and a newly developed model for the additional term in the momentum equation were both tested, with the new model proving even more successful than the previous model at reproducing the high density-gradient magnitude regions. Several dynamic SGS-flux models, in which the SGS-flux model coefficient is computed as part of the simulation, were tested in conjunction with the new model for this additional term in the momentum equation. The most successful dynamic model was a "mixed" model combining the Smagorinsky and Gradient models. This work is directly applicable to simulations of gas turbine engines (aeronautics) and rocket engines (astronautics).

Bellan, Josette↗
NASA NTRS2005

Bayesian Inference in Satellite Gravity Inversion

To solve a geophysical inverse problem means applying measurements to determine the parameters of the selected model. The inverse problem is formulated as the Bayesian inference. The Gaussian probability density functions are applied in the Bayes's equation. The CHAMP satellite gravity data are determined at the altitude of 400 kilometer altitude over the South part of the Pannonian basin. The model of interpretation is the right vertical cylinder. The parameters of the model are obtained from the minimum problem solved by the Simplex method.

Kis, K. I.↗
NASA NTRS2007

Nonequilibrium Stagnation-Line Radiative Heating for Fire II

This paper presents a detailed analysis of the shock-layer radiative heating to the Fire II vehicle using a new air radiation model and a viscous shock-layer flowfield model. This new air radiation model contains the most up-to-date properties for modeling the atomic-line, atomic photoionization, molecular band, and non-Boltzmann processes. The applied viscous shock-layer flowfield analysis contains the same thermophysical properties and nonequilibrium models as the LAURA Navier-Stokes code. Radiation-flowfield coupling, or radiation cooling, is accounted for in detail in this study. It is shown to reduce the radiative heating by about 30% for the peak radiative heating points, while reducing the convective heating only slightly. A detailed review of past Fire II radiative heating studies is presented. It is observed that the scatter in the radiation predicted by these past studies is mostly a result of the different flowfield chemistry models and the treatment of the electronic state populations. The present predictions provide, on average throughout the trajectory, a better comparison with Fire II flight data than any previous study. The magnitude of the vacuum ultraviolet (VUV) contribution to the radiative flux is estimated from the calorimeter measurements. This is achieved using the radiometer measurements and the predicted convective heating. The VUV radiation predicted by the present model agrees well with the VUV contribution inferred from the Fire II calorimeter measurement, although only when radiation-flowfield coupling is accounted for. This agreement provides evidence that the present model accurately models the VUV radiation, which is shown to contribute significantly to the Fire II radiative heating.

Johnston, Christopher O.↗
NASA NTRS1990

The ionosphere of Triton

A model of the atmospheric temperature structure and composition inferred from the Voyager (UVS) solar occultations was used together with a one-dimensional chemical diffusive model to interpret the Voyager Radio Science Spectrometer (RSS) ingress measurements of Triton's electron density. Although N2(+) is the major ion created, N(+) produced by dissociative ionization is the dominant ion. Reaction of thermospheric H2, produced by Lyman-alpha dissociation of CH4 in the lower atmosphere, is the major loss for N(+) ions and maintains these ions in PCSS below 600 km. Solar EUV ionization cannot generate electron densities at the magnitude measured by the RSS experiment and an additional ionization source about 3 x 10 to the 8th ions/sq cm per sec is required. The ionosphere may undergo a transition from PCSS to diffusive control if the N(+) ion production rates were greater than the H2 flux derived from CH4. In this case, the upward flowing H2 is totally converted to H by reaction with N(+) and the remaining N(+) ions recombine radiatively to create an ionosphere under diffusive control above the peak.

Majeed, T.↗
NASA NTRS1984

Discrete Random Media Techniques for Microwave Modeling of Vegetated Terrain

Microwave remote sensing of agricultural crops and forested regions is studied. Long term goals of the research involve modeling vegetation so that radar signatures can be used to infer the parameters which characterize the vegetation and underlying ground. Vegetation is modeled by discrete scatterers viz, leaves, stems, branches and trunks. These are replaced by glossy dielectric discs and cylinders. Rough surfaces are represented by their mean and spectral characteristics. Average scattered power is then calculated by employing discrete random media methodology such as the distorted Born approximation or transport theory. Both coherent and incoherent multiple scattering techniques are explored. Once direct methods are developed, inversion techniques can be investigated.

Lang, R. H.↗
NASA NTRS1985

Discrete Random Media Techniques for Microwave Modeling of Vegetated Terrain

Microwave remote sensing of vegetated terrain has been studied. Vegetation is modeled so that backscattered radar signals can be used to infer parameters which characterize the vegetation and underlying ground. The vegetation is modeled by discrete lossy dielectric scatterers with prescribed characteristics. The goal of the modeling effort is to remotely sense vegetation type (classification), growth stage, and plant/ground moisture. This information can then be used as input into agricultural, forestry and global circulation models. The microwave frequency spectrum, particularly L and C bands, are especially appropriate for this purpose since the wavelength is comparable to plant leaf and stem size. The resulting resonant interaction leads to backscattered data highly depend on plant shape and orientation. In addition, the transparent nature of the atmosphere in this frequency regime allows for algorithm development which requires no atmospheric correction.

Lang, R. H.↗
NASA NTRS2002

A statistical model for interpreting computerized dynamic posturography data

Computerized dynamic posturography (CDP) is widely used for assessment of altered balance control. CDP trials are quantified using the equilibrium score (ES), which ranges from zero to 100, as a decreasing function of peak sway angle. The problem of how best to model and analyze ESs from a controlled study is considered. The ES often exhibits a skewed distribution in repeated trials, which can lead to incorrect inference when applying standard regression or analysis of variance models. Furthermore, CDP trials are terminated when a patient loses balance. In these situations, the ES is not observable, but is assigned the lowest possible score--zero. As a result, the response variable has a mixed discrete-continuous distribution, further compromising inference obtained by standard statistical methods. Here, we develop alternative methodology for analyzing ESs under a stochastic model extending the ES to a continuous latent random variable that always exists, but is unobserved in the event of a fall. Loss of balance occurs conditionally, with probability depending on the realized latent ES. After fitting the model by a form of quasi-maximum-likelihood, one may perform statistical inference to assess the effects of explanatory variables. An example is provided, using data from the NIH/NIA Baltimore Longitudinal Study on Aging.

NASA Discipline Neuroscience↗
NASA NTRS1977

Behavior of volatiles in Mars' polar areas - A model incorporating new experimental data

A model has been developed to explain the north polar water vapor results obtained by the Viking orbiter Mars atmospheric water detector; it has also been used to compute the thickness of seasonally deposited CO2 frost, the variation of the total atmospheric pressure, and wind velocities due to mass motions associated with CO2 condensation. A north polar water ice thickness in excess of 1 m and an ice albedo a of 0.34(+0.06,-0.03) are inferred from a comparison of the model and experimental data. The model results confirm an earlier conclusion that the atmosphere over the ice is saturated. It is suggested that concentration of the atmospheric inert gases in the polar region, combined with local topography and arctic circulation patterns, could be responsible for the south remnant cap not being at the south pole

Davies, D. W.↗
NASA NTRS1994

Vertical ocean loading amplitudes from VLBI measurements

Vertical ocean loading amplitudes are determined by analysis of IRIS geodetic Very Long Baseline Interferometry (VLBI) data. The 4 nearly diurnal (K(sub 1), P(sub 1), O(sub 1), Q(sub 1)) and 4 nearly semidiurnal (K(sub 2), S(sub 2), M(sub 2), and N(sub 2)) component amplitudes can be inferred from the data with accuracies of 1-2 mm. Uncertainties of total displacements can approach 1 cm. Empirically determined total displacements are considerably larger than the values calculated from two geophysical models. The Scherneck model is found to give a better representation of VLBI delay data than the model of Pagiatakis by about 3 mm in residuals at 6 sites. Empirical estimation of the ocean loading amplitudes reduces Chi squared by 3067 for the 96 additional degrees of freedom in a fit to 273,000 IRIS VLBI observations, and reduces the RMS residuals by 3 mm relative to a fit using the fixed Scherneck model. Vertical ocean loading amplitudes can thus be inferred from VLBI data at a level which improves the overall model, but detailed assessment of individual tidal components is presently obscured by incomplete modeling at the tidal frequencies.

Sovers, O. J.↗
NASA NTRS1997

Large Volcanic Rises on Venus

Large volcanic rises on Venus have been interpreted as hotspots, or the surface manifestation of mantle upwelling, on the basis of their broad topographic rises, abundant volcanism, and large positive gravity anomalies. Hotspots offer an important opportunity to study the behavior of the lithosphere in response to mantle forces. In addition to the four previously known hotspots, Atla, Bell, Beta, and western Eistla Regiones, five new probable hotspots, Dione, central Eistla, eastern Eistla, Imdr, and Themis, have been identified in the Magellan radar, gravity and topography data. These nine regions exhibit a wider range of volcano-tectonic characteristics than previously recognized for venusian hotspots, and have been classified as rift-dominated (Atla, Beta), coronae-dominated (central and eastern Eistla, Themis), or volcano-dominated (Bell, Dione, western Eistla, Imdr). The apparent depths of compensation for these regions ranges from 65 to 260 km. New estimates of the elastic thickness, using the 90 deg and order spherical harmonic field, are 15-40 km at Bell Regio, and 25 km at western Eistla Regio. Phillips et al. find a value of 30 km at Atla Regio. Numerous models of lithospheric and mantle behavior have been proposed to interpret the gravity and topography signature of the hotspots, with most studies focusing on Atla or Beta Regiones. Convective models with Earth-like parameters result in estimates of the thickness of the thermal lithosphere of approximately 100 km. Models of stagnant lid convection or thermal thinning infer the thickness of the thermal lithosphere to be 300 km or more. Without additional constraints, any of the model fits are equally valid. The thinner thermal lithosphere estimates are most consistent with the volcanic and tectonic characteristics of the hotspots. Estimates of the thermal gradient based on estimates of the elastic thickness also support a relatively thin lithosphere (Phillips et al.). The advantage of larger estimates of the thermal lithospheric thickness is that they provide an explanation for the apparently modest levels of geologic activity on Venus over the last half billion years.

Smrekar, Suzanne E.↗
NASA NTRSDate not supplied

Linear Mixed-Effects Models for Human-in-the-Loop Tracking Experiment Data

Linear mixed-effects models provide several benefits over more traditional statistical inference tests that are particularly useful for most human-in-the-loop tracking experiment data. However, surprisingly, mixed models are virtually not used for the analysis of tracking experiment data. This paper uses of linear mixed-effects models to analyze combined tracking data from two previous human-in-the-loop roll tracking experiments that compared control behavior metrics collected in both a research aircraft and a motion-base simulator. In the experiments, pilots' behavior under 10 different motion configurations with varying motion filter gains and break frequencies was evaluated and compared to that in the real aircraft. The linear mixed-effects model analysis on the combined dataset confirmed the main statistical outcomes of the individual experiments. The main benefits of mixed models for this type of data were demonstrated by successfully combining data from two experiments that used different experimental conditions and of which one had an additional apparatus and the other a missing participant. Finally, the mixed-model analysis was able to explicitly test for scientifically relevant statistical differences in the dependent measures between the aircraft and simulator, as well as both experiments.

manual control↗
NASA NTRS1989

The effects of viewing angle on the inference of magnetic shear in preflare active regions

Analytic models for nonpotential force-free fields representative of preflaring active regions have been used to determine the degree of magnetic shear along the magnetic neutral line of these fields as a function of location and orientation of the active region on the solar disk. The results indicate that, with the exception of regions close to the disk center, the position of the inferred neutral line differs significantly from the actual neutral line. It is suggested that the significant variation of the inferred degree of shear with the position and orientation of the region is due to such factors as geometric projection effects, the shift of the inferred neutral line relative to its true position, and the variations in the reference potential field.

Wilkinson, Ladye Kathryn↗
NASA NTRS1972

Hydrodynamic prediction of peak pool-boiling heat fluxes from finite bodies.

Previous theoretical models are considered, giving attention to the original formulation proposed by Zuber (1959), an infinite horizontal flat plate, a horizontal cylinder, and a sphere. Some general features of any hydrodynamic prediction are inferred by examining the characteristics of the models. It is found possible to eliminate the need for observed values of the vapor-blanket thickness. The concepts obtained are utilized in the derivation of expressions for the prediction of the peak pool-boiling heat flux in the case of some new configurations.

Lienhard, J. H.↗
NASA NTRS2003

A Test of Maxwell's Z Model Using Inverse Modeling

In modeling impact craters a small region of energy and momentum deposition, commonly called a "point source", is often assumed. This assumption implies that an impact is the same as an explosion at some depth below the surface. Maxwell's Z Model, an empirical point-source model derived from explosion cratering, has previously been compared with numerical impact craters with vertical incidence angles, leading to two main inferences. First, the flowfield center of the Z Model must be placed below the target surface in order to replicate numerical impact craters. Second, for vertical impacts, the flow-field center cannot be stationary if the value of Z is held constant; rather, the flow-field center migrates downward as the crater grows. The work presented here evaluates the utility of the Z Model for reproducing both vertical and oblique experimental impact data obtained at the NASA Ames Vertical Gun Range (AVGR). Specifically, ejection angle data obtained through Three-Dimensional Particle Image Velocimetry (3D PIV) are used to constrain the parameters of Maxwell's Z Model, including the value of Z and the depth and position of the flow-field center via inverse modeling.

Anderson, J. L. B.↗
NASA NTRS2019

A Fast Vector Radiative Transfer Model for the Atmosphere-Ocean Coupled System

To infer atmospheric and oceanic constituent properties from polarimetric observations, an efficient and accurate retrieval algorithm is desirable. In-line radiative transfer calculations are indispensable if a large state vector, including both atmospheric profiles and surface properties, is used to improve retrieval accuracy. However, in-line radiative transfer calculations are usually not computationally efficient for remote sensing applications. Therefore, there is a pressing need to develop an accurate and fast vector radiative transfer model (RTM) to fully utilize satellite polarimetric observations. This paper reports on a fast vector RTM, referred to as TAMU-VRTM, in support of polarimetric remote sensing, which is capable of simulating the Stokes vector values observed at the top of the atmosphere and at the surface by fully considering absorption, scattering, and emission in the atmosphere and ocean. Gaseous absorption is parameterized with respect to gas concentration, temperature, and pressure, by using a regression method applicable to an inhomogeneous atmospheric path. An efficient two-component approach combining the small angle approximation and the adding-doubling method is utilized to solve the vector radiative transfer equation (RTE). The thermal emission component of the RTE solution is obtained by an efficient doubling process. The air-sea interface is treated as a wind-ruffled rough surface in the model to mimic a realistic ocean surface. Several oceanic optical property models are introduced to model ocean inherent optical properties. To demonstrate the applicability of the TAMUVRTM, simulations are compared with satellite observations, and results from other vector radiative transfer methods including benchmarks.

radiative transfer in coupled atmosphere-ocean sys↗
NASA NTRS2019

ESD Reviews: Model Dependence in Multi-Model Climate Ensembles: Weighting, Sub-Selection and Out-Of-Sample Testing

The rationale for using multi-model ensembles in climate change projections and impacts research is often based on the expectation that different models constitute independent estimates; therefore, a range of models allows a better characterisation of the uncertainties in the representation of the climate system than a single model. However, it is known that research groups share literature, ideas for representations of processes, parameterisations, evaluation data sets and even sections of model code. Thus, nominally different models might have similar biases because of similarities in the way they represent a subset of processes, or even be near-duplicates of others, weakening the assumption that they constitute independent estimates. If there are near-replicates of some models, then treating all models equally is likely to bias the inferences made using these ensembles. The challenge is to establish the degree to which this might be true for any given application. While this issue is recognised by many in the community, quantifying and accounting for model dependence in anything other than an ad-hoc way is challenging. Here we present a synthesis of the range of disparate attempts to define, quantify and address model dependence in multi-model climate ensembles in a common conceptual framework, and provide guidance on how users can test the efficacy of approaches that move beyond the equally weighted ensemble. In the upcoming Coupled Model Intercomparison Project phase 6 (CMIP6), several new models that are closely related to existing models are anticipated, as well as large ensembles from some models. We argue that quantitatively accounting for dependence in addition to model performance, and thoroughly testing the effectiveness of the approach used will be key to a sound interpretation of the CMIP ensembles in future scientific studies.

Abramowitz, Gab↗