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At least 1,693 records · Page 94

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NASA NTRS1995

Stormtime ring current and radiation belt ion transport: Simulations and interpretations

We use a dynamical guiding-center model to investigate the stormtime transport of ring current and radiation-belt ions. We trace the motion of representative ions' guiding centers in response to model substorm-associated impulses in the convection electric field for a range of ion energies. Our simple magnetospheric model allows us to compare our numerical results quantitatively with analytical descriptions of particle transport, (e.g., with the quasilinear theory of radial diffusion). We find that 10-145-keV ions gain access to L approximately 3, where they can form the stormtime ring current, mainly from outside the (trapping) region in which particles execute closed drift paths. Conversely, the transport of higher-energy ions (approximately greater than 145 keV at L approximately 3) turns out to resemble radial diffusion. The quasilinear diffusion coefficient calculated for our model storm does not vary smoothly with particle energy, since our impulses occur at specific (although randomly determined) times. Despite the spectral irregularity, quasilinear theory provides a surprisingly accurate description of the transport process for approximately greater than 145-keV ions, even for the case of an individual storm. For 4 different realizations of our model storm, the geometric mean discrepancies between diffusion coefficients D(sup sim, sub LL) obtained from the simulations and the quasilinear diffusion coefficient D(sup ql, sub LL) amount to factors of 2.3, 2.3, 1.5, and 3.0, respectively. We have found that these discrepancies between D(sup sim, sub LL) and D(sup ql, sub LL) can be reduced slightly by invoking drift-resonance broadening to smooth out the sharp minima and maxima in D(sup ql, sub LL). The mean of the remaining discrepancies between D(sup sim, sub LL) and D(sup ql, sub LL) for the 4 different storms then amount to factors of 1.9, 2.1, 1.5, and 2.7, respectively. We find even better agreement when we reduce the impulse amplitudes systematically in a given model storm (e.g., reduction of all the impulse amplitudes by half reduces the discrepancy factor by at least its square root) and also when we average our results over an ensemble of 20 model storms (agreement is within a factor of 1.2 without impulse-amplitude reduction). We use our simulation results also to map phase-space densities f in accordance with Liouville's theorem. We find that the stormtime transport of approximately greater than 145-keV ions produces little change in f-bar the drift-averaged phase-space density on any drift shell of interest. However, the stormtime transport produces a major enhancement from the pre-storm phase-space density at energies approximately 30-145 keV, which are representative of the stormtime ring current.

Lyons, Larry R.↗

DOE OSTI2026

Automated and Accelerated Continuum Model Development for Electrochemical Systems (Abbreviated Report)

Despite the availability of computational resources and advancements in numerical computing capabilities, the multiscale models core to understanding, predicting the behaviors of, and designing energy and environmental systems involving porous media are still 1.) developed through by-hand derivations and 2.) limited by many methodological assumptions employed during model derivation. As a result, the advancement of effective media models for engineering DOE mission-critical systems (e.g., batteries, flow batteries, electrolyzers, geothermal systems, subsurface chemical storage systems, etc.) is slow (i.e., it takes years for models to traverse from stages of “development” to “practical utilization”), hindering our ability to effectively optimize such systems and stay at the cutting-edge of the energy frontier. In this work, we aimed to address these limitations by 1.) automating and accelerating multiscale model derivation via symbolic computing and 2.) develop a novel multiscale modeling methodology for flow and transport through porous media that avoids the typical assumptions hindering previous models. As a result of our efforts, we 1.) developed a hybrid symbolic-numeric code called Fouriera for fully-automating the implementation of multiphysical and phase-field models via the Fourier spectral method for materials science research, and 2.) advanced a multiscale modeling methodology called The Method of Finite Averages that rigorously predicts the behaviors of flow and transport through heterogeneous porous media under the influence of non-local effects and strong advection. Ultimately, these deliverables provide strong foundations from which further efforts can advance multiscale modeling tools and capabilities that do not intrinsically rely on 1.) the speed and mathematical capabilities of humans, nor 2.) the methodological assumptions limiting current models.

36 MATERIALS SCIENCE↗

NASA NTRS1980

Seasonal and daily snowmelt runoff estimates utilizing satellite data

Methods using snowcovered area to update seasonal forecasts as snowmelt progresses are also being used in quasi-operational situations. The input of snowcovered area to snowmelt models for short term perdictions was attempted in two ways; namely, the modification of existing hydrologic models and/or the use of models that were specifically designed to use snowcovered area. A daily snowmelt runoff model was used with LANDSAT data to simulate discharge on remote basins in the Wind River Mountains of Wyoming. Daily predicted and actual flows compare closely, and, summarized over the entire snowmelt season (April 1 - September 30), the average difference is only three percent. The model and snowcovered area data are currently being tested on additional watersheds to determine the method's transferability.

Source record↗

NASA NTRS2013

Modeling X-Ray Binary Evolution in Normal Galaxies: Insights from SINGS

We present the largest-scale comparison to date between observed extragalactic X-ray binary (XRB) populations and theoretical models of their production. We construct observational X-ray luminosity functions (oXLFs) using Chandra observations of 12 late-type galaxies from the Spitzer Infrared Nearby Galaxy Survey (SINGS). For each galaxy, we obtain theoretical XLFs (tXLFs) by combining XRB synthetic models, constructed with the population synthesis code StarTrack, with observational star formation histories (SFHs). We identify highest-likelihood models both for individual galaxies and globally, averaged over the full galaxy sample. Individual tXLFs successfully reproduce about half of oXLFs, but for some galaxies we are unable to find underlying source populations, indicating that galaxy SFHs and metallicities are not well matched and/or XRB modeling requires calibration on larger observational samples. Given these limitations, we find that best models are consistent with a product of common envelope ejection efficiency and central donor concentration approx.. = 0.1, and a 50% uniform - 50% "twins" initial mass-ratio distribution. We present and discuss constituent subpopulations of tXLFs according to donor, accretor and stellar population characteristics. The galaxy-wide X-ray luminosity due to low-mass and high-mass XRBs, estimated via our best global model tXLF, follows the general trend expected from the L(sub X) - star formation rate and L(sub X) - stellar mass relations of Lehmer et al. Our best models are also in agreement with modeling of the evolution both of XRBs over cosmic time and of the galaxy X-ray luminosity with redshift.

Normal Galaxies↗

DOE OSTI2020

Using Thermodynamic Availability to Predict the Transitional Film Reynolds Number between the Droplet and Jet Modes in Falling Liquid between Horizontal Tubes

The objective of this paper is to propose and validate a model for predicting the transitional film Reynolds number between the droplet and jet modes of falling film flows. The proposed model relies on thermodynamic availability with no fitting to mode transition data. The model directly predicts the numerical values of the transitional film Reynolds numbers at different operating conditions. The results of the model are validated against 43 experimental data points from the literature, which cover 10 working fluids and a wide range of tube geometries. The accuracy of the proposed model in predicting the validation data is -on average- more than 20 % better than that of the widely used Re = a (Ga) b and Re = a (Ga) b (S/ξ) c models. The model also achieves low computation time (less than 30 seconds for the 43 validation data points). The model presented in this paper has the potential of integration with heat transfer, mass transfer, and pressure drop models for optimizing the design and operation of falling film heat and mass exchangers.

42 ENGINEERING↗

DOE OSTI2024

A novel conditional generative model for efficient ensemble forecasts of state variables in large-scale geological carbon storage

Integrating monitoring data to efficiently update reservoir pressure and CO 2 plume distribution forecasts presents a significant challenge in geological carbon storage (GCS) applications. Inverse modeling techniques are commonly used to fuse observational data and refine reservoir model parameters, thereby improving state variable forecasts. However, these techniques often rely on linear or Gaussian assumptions, which can limit their effectiveness in accurately predicting state variables. Moreover, simulating large-scale three-dimensional (3D) GCS problems is computationally expensive, making iterative runs in inverse problems prohibitive. To address these challenges, we propose a conditional generative model utilizing the score-based diffusion method for real-time 3D pressure and saturation field distribution predictions. Our approach involves solving the score function with a mini-batch-based Monte Carlo estimator to generate labeled data. This data is subsequently employed to train a fully connected neural network, enabling it to learn the conditional sample generator within a supervised learning framework. This method enables the rapid generation of a large ensemble of predictions, facilitating comprehensive uncertainty quantification of state variables. Here we applied our method to forecast the dynamic 3D distributions of pressure and saturation fields over a 30-year injection period. The statistical assessment with low root mean square error (RMSE) values demonstrates that our method can accurately predict the spatiotemporal distributions of both pressure and saturation fields. Moreover, the developed conditional generative model shows high computational efficiency by generating 100 ensemble forecasts of 3D state variables in less than 10 min. The consistency between ensemble averages and ground truth values further illustrates the model’s capability to capture state variable dynamics during the CO 2 plume injection process. Notably, the ground truth values fall within the ensemble forecasts, indicating that our uncertainty quantification effectively captures variability and potential noise in the observations. Thus, the developed conditional generative model proves to be a more efficient, accurate, and practical tool for GCS applications, facilitating timely risk analysis and informed decision-making.

58 GEOSCIENCES↗

NASA NTRS1979

Prediction of the acoustic environment in the Space Shuttle payload bay

An analytical model has been developed to predict space-averaged sound levels in the payload bay of the Space Shuttle when the bay is empty or when a payload is present. The model utilizes the power flow concept and takes into account net power flow from the exterior, flow between subvolumes surrounding a payload, and power dissipation in the subvolumes. The characteristics of the model are described and its application to the Spacelab Configuration 1 payload is presented to illustrate the type of results obtained.

Wilby, J. F.↗

NASA NTRS1989

Geoid height versus topography for oceanic plateaus and swells

Gridded geoid height data (Marsh et al.l, 1986) and gridded bathymetry data (Van Wykhouse, 1973) are used to estimate the average compensation depths of 53 oceanic swells and plateaus. The relationship between geoid height and topography is examined using Airy and thermal compensation models. It is shown that geoid height is linearly related to topography between wavelengths of 400 and 4000 m as predicted by isostatic compensation models. The geoid/topography ratio is dependent on the average depth of compensation. The intermediate geoid/topography ratios of most thermal swells are interpreted as a linear combination of the decaying thermal swell signature and that of the persisting Airy-compensated volcanic edifice.

Sandwell, David T.↗

NASA NTRS2018

Analysis of the Two-Level NO PLIF Model for Low-Temperature High-Speed Flow Applications

The current work compares experimentally obtained nitric oxide (NO) laser-induced fluorescence (LIF) spectra with the equivalent spectra obtained analytically. The experimental spectra are computed from captured images of fluorescence in a gas cell and from a laser sheet passing through the fuel-air mixing flowfield produced by a high-speed fuel injector. The fuel injector is a slender strut that is currently being studied as a part of the Enhanced Injection and Mixing Project (EIMP) at the NASA Langley Research Center. This injector is placed downstream of a Mach 6 facility nozzle, which simulates the high Mach number airflow at the entrance of a scramjet combustor, and injects helium, which is used as an inert substitute for hydrogen fuel. Experimental planar (P) LIF is obtained by using a UV laser to excite fluorescence from the NO molecules that are present in either a gas cell or the facility air used for the EIMP experiments. The experimental data are obtained for several segments of the NO fluorescence spectrum. The selected segments encompass LIF lines with rotational quantum numbers appropriate for low-to-moderate temperature flows similar to those corresponding to the nominal experimental flow conditions. The experimental LIF spectra are then evaluated from the data and compared with those obtained from the theoretical models. The theoretical spectra are obtained from LIFBASE and LINUS software, and from a simplified version of the two-level fluorescence model. The equivalent analytic PLIF images are also obtained by applying only the simplified model to the results of the Reynolds-averaged simulations (RAS) of the mixing flowfield. Good agreement between the experimental and theoretical results provides increased confidence in both the simplified LIF modeling and CFD simulations for further investigations of high-speed injector performance using this approach.

Drozda, Tomasz G.↗

NASA NTRS2018

Analysis of the Two-Level NO PLIF Model for Low-Temperature High-Speed Flow Applications

Tomasz G Drozda↗

NASA NTRS2004

A Two-Stage Procedure Toward the Efficient Implementation of PANS and Other Hybrid Turbulence Models

The main objective of this article is to introduce and to show the implementation of a novel two-stage procedure to efficiently estimate the level of scale resolution possible for a given flow on a given grid for Partial Averaged Navier-Stokes (PANS) and other hybrid models. It has been found that the prescribed scale resolution can play a major role in obtaining accurate flow solutions. The first step is to solve the unsteady or steady Reynolds Averaged Navier-Stokes (URANS/RANS) equations. From this preprocessing step, the turbulence length-scale field is obtained. This is then used to compute the characteristic length-scale ratio between the turbulence scale and the grid spacing. Based on this ratio, we can assess the finest scale resolution that a given grid for a given flow can support. Along with other additional criteria, we are able to analytically identify the appropriate hybrid solver resolution for different regions of the flow. This procedure removes the grid dependency issue that affects the results produced by different hybrid procedures in solving unsteady flows. The formulation, implementation methodology, and validation example are presented. We implemented this capability in a production Computational Fluid Dynamics (CFD) code, PAB3D, for the simulation of unsteady flows.

Abdol-Hamid, Khaled S.↗

DOE OSTI2024

CovTransformer: A transformer model for SARS-CoV-2 lineage frequency forecasting

With hundreds of SARS-CoV-2 lineages circulating in the global population, there is an ongoing need for predicting and forecasting lineage frequencies and thus identifying rapidly expanding lineages. Accurate prediction would allow for more focused experimental efforts to understand pathogenicity of future dominating lineages and characterize the extent of their immune escape. Here, we first show that the inherent noise and biases in lineage frequency data make a commonly-used regression-based approach unreliable. To address this weakness, we constructed a machine learning model for SARS-CoV-2 lineage frequency forecasting, called CovTransformer, based on the transformer architecture. We designed our model to navigate challenges such as a limited amount of data with high levels of noise and bias. We first trained and tested the model using data from the UK and the USA, and then tested the generalization ability of the model to many other countries and US states. Remarkably, the trained model makes accurate predictions two months into the future with high levels of accuracy both globally (in 31 countries with high levels of sequencing effort) and at the US-state level. Our model performed substantially better than a widely used forecasting tool, the multinomial regression model implemented in Nextstrain, demonstrating its utility in SARS-CoV-2 monitoring. Assuming a newly emerged lineage is identified and assigned, our test using retrospective data shows that our model is able to identify the dominating lineages 7 weeks in advance on average before they became dominant. Overall, our work demonstrates that transformer models represent a promising approach for SARS-CoV-2 forecasting and pandemic monitoring.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1981

The Lyman-alpha/H-alpha ratio in solar flares and quasars

Constant temperature and density solar flare models are constructed with temperature and hydrogen density values that reflect reasonable nonlinear averages of those parameters in the depth dependent solar flare chromosphere models of Lites and Cook (1979). Acceptable values of the intensity ratios L-alpha/H-alpha and H-beta/H-alpha correspond to temperatures from about 9000 to 13,000 K, and hydrogen densities from 10 to the 11th to 10 to the 15th cu cm. The H-alpha and Ly-alpha source functions are thermalized at depths consistent with those inferred from independent studies, although the observed Ly-alpha/H-alpha ratio does not necessarily imply an electron temperature appropriate to the Planck function ratio. It is also shown that the value of Ly-alpha/H-alpha depends on the temperature, hydrogen density, and the optical depth of the emitting chromospheric layer.

Canfield, R. C.↗

NASA NTRS1986

The average magnetic field draping and consistent plasma properties of the Venus magnetotail

The detailed average draping pattern of the magnetic field in the deep Venus magnetotail is examined. The variability of the data ordered by spatial location is studied, and the groundwork is laid for developing a coordinate system which measured locations with respect to the tail structures. The reconstruction of the tail in the presence of flapping using a new technique is shown, and the average variations in the field components are examined, including the average field vectors, cross-tail current density distribution, and J x B forces as functions of location across the tail. The average downtail velocity is derived as a function of distance, and a simple model based on the field variations is defined from which the average plasma acceleration is obtained as a function of distance, density, and temperature.

Mccomas, D. J.↗

NASA NTRS1998

A Simple Model of Cirrus Horizontal Inhomogeneity and Cloud Fraction

A simple model of horizontal inhomogeneity and cloud fraction in cirrus clouds has been formulated on the basis that all internal horizontal inhomogeneity in the ice mixing ratio is due to variations in the cloud depth, which are assumed to be Gaussian. The use of such a model was justified by the observed relationship between the normalized variability of the ice water mixing ratio (and extinction) and the normalized variability of cloud depth. Using radar cloud depth data as input, the model reproduced well the in-cloud ice water mixing ratio histograms obtained from horizontal runs during the FIRE2 cirrus campaign. For totally overcast cases the histograms were almost Gaussian, but changed as cloud fraction decreased to exponential distributions which peaked at the lowest nonzero ice value for cloud fractions below 90%. Cloud fractions predicted by the model were always within 28% of the observed value. The predicted average ice water mixing ratios were within 34% of the observed values. This model could be used in a GCM to produce the ice mixing ratio probability distribution function and to estimate cloud fraction. It only requires basic meteorological parameters, the depth of the saturated layer and the standard deviation of cloud depth as input.

Smith, Samantha A.↗

NASA NTRS1998

Depth dependence of absorbed dose, dose equivalent and linear energy transfer spectra of galactic and trapped particles in polyethylene and comparison with calculations of models

A matched set of five tissue-equivalent proportional counters (TEPCs), embedded at the centers of 0 (bare), 3, 5, 8 and 12-inch-diameter polyethylene spheres, were flown on the Shuttle flight STS-81 (inclination 51.65 degrees, altitude approximately 400 km). The data obtained were separated into contributions from trapped protons and galactic cosmic radiation (GCR). From the measured linear energy transfer (LET) spectra, the absorbed dose and dose-equivalent rates were calculated. The results were compared to calculations made with the radiation transport model HZETRN/NUCFRG2, using the GCR free-space spectra, orbit-averaged geomagnetic transmission function and Shuttle shielding distributions. The comparison shows that the model fits the dose rates to a root mean square (rms) error of 5%, and dose-equivalent rates to an rms error of 10%. Fairly good agreement between the LET spectra was found; however, differences are seen at both low and high LET. These differences can be understood as due to the combined effects of chord-length variation and detector response function. These results rule out a number of radiation transport/nuclear fragmentation models. Similar comparisons of trapped-proton dose rates were made between calculations made with the proton transport model BRYNTRN using the AP-8 MIN trapped-proton model and Shuttle shielding distributions. The predictions of absorbed dose and dose-equivalent rates are fairly good. However, the prediction of the LET spectra below approximately 30 keV/microm shows the need to improve the AP-8 model. These results have strong implications for shielding requirements for an interplanetary manned mission.

Flight Experiment↗

NASA NTRS2017

Electron Drift Resonance in the MHD-Coupled Comprehensive Inner Magnetosphere-Ionosphere Model

Relativistic electrons in the outer radiation belt are highly dynamic and respond to interplanetary solar wind structures interacting with the Earth's magnetic field. A known mechanism dictating electron dynamics is the drift-resonant interaction with ultralow frequency (ULF) waves. The present work simulates the ring current and radiation belt electron populations in the bounce-averaged, kinetic Comprehensive Inner Magnetosphere-Ionosphere model coupled with the Block Adaptive Tree Solar Wind Roe-type Upwind Scheme global magnetospheric magnetohydrodynamic (MHD) code using an idealized ULF wave solar wind density driver. ULF waves generated with 10 min periods (at 1.67 mHz frequencies) in the MHD model are characterized and the corresponding energization of electrons and radial transport of electron phase space density is presented. The drift-resonant electron energy is determined in the simulation and is consistent with the electron resonance conditions in dipolar magnetic fields. The present results will be an important component of understanding inner magnetospheric dynamics and how these inner magnetospheric populations interact with ULF waves resulting from interplanetary solar wind structures.

Komar, C. M.↗

NASA NTRS2004

Computation of a Synthetic Jet in a Turbulent Cross-Flow Boundary Layer

A series of unsteady Reynolds-averaged Navier-Stokes computations are performed for the flow of a synthetic jet issuing into a turbulent boundary layer through a circular orifice. This is one of the validation test cases from a synthetic jet validation workshop held in March 2004. Several numerical parameters are investigated, and the effects of three different turbulence models are explored. Both long-time-averaged and time-dependent phase-averaged results are compared to experiment. On the whole, qualitative comparisons of the mean flow quantities are fairly good. There are many differences evident in the quantitative comparisons. The calculations do not exhibit a strong dependence on the type of turbulence model employed.

Rumsey, Christopher L.↗