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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Machine learning assisted bayesian inference of mix and hot-spot conditions in NIF implosions

Experiments on the National Ignition Facility (NIF) have provided clear evidence of ablator material mixing into the Hot-Spot, leading to degraded performance. However, inferring the amount of mix and Hot-Spot conditions from typical experimental observations (e.g. x-ray spectra and images) is highly challenging. Here, we have developed an analysis method that utilizes machine learning assisted Bayesian inference to find the probability distributions of the Hot-Spot and mix conditions. This approach uses a neural network, trained on an idealized 2-dimensional representation of the Hot-Spot and mix distribution, and Bayesian inference to find the statistical distributions of Hot-Spot conditions that provide a match with observations. We have tested this method with synthetic data from simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

X-ray digital industrial radiography (DIR) for local liquid velocity (V{sub LL}) measurement in trickle bed reactors (TBRs): Validation of the technique

Local liquid velocity measurements in Trickle Bed Reactors (TBRs) are one of the essential components in its hydrodynamic studies. These measurements are used to effectively determine a reactor's operating condition. This study was conducted to validate a newly developed technique that combines Digital Industrial Radiography (DIR) with Particle Tracking Velocimetry (PTV) to measure the Local Liquid Velocity (V{sub LL}) inside TBRs. Three millimeter-sized Expanded Polystyrene (EPS) beads were used as packing material. Three validation procedures were designed to test the newly developed technique. All procedures and statistical approaches provided strong evidence that the technique can be used to measure the V{sub LL} within TBRs.

42 ENGINEERING↗
NASA NTRS2001

A Hydrodynamic Theory for Spatially Inhomogeneous Semiconductor Lasers: Numerical Results - 2

We present numerical results of the diffusion coefficients (DCs) in the coupled diffusion model derived in the preceding paper for a semiconductor quantum well. These include self and mutual DCs in the general two-component case, as well as density- and temperature-related DCs under the single-component approximation. The results are analyzed from the viewpoint of free Fermi gas theory with many-body effects incorporated. We discuss in detail the dependence of these DCs on densities and temperatures in order to identify different roles played by the free carrier contributions including carrier statistics and carrier-LO phonon scattering, and many-body corrections including bandgap renormalization and electron-hole (e-h) scattering. In the general two-component case, it is found that the self- and mutual- diffusion coefficients are determined mainly by the free carrier contributions, but with significant many-body corrections near the critical density. Carrier-LO phonon scattering is dominant at low density, but e-h scattering becomes important in determining their density dependence above the critical electron density. In the single-component case, it is found that many-body effects suppress the density coefficients but enhance the temperature coefficients. The modification is of the order of 10% and reaches a maximum of over 20% for the density coefficients. Overall, temperature elevation enhances the diffusive capability or DCs of carriers linearly, and such an enhancement grows with density. Finally, the complete dataset of various DCs as functions of carrier densities and temperatures provides necessary ingredients for future applications of the model to various spatially inhomogeneous optoelectronic devices.

Li, Jianzhong↗
DOE OSTI2012

CONSERVATIVE CASCADE OF KINETIC ENERGY IN COMPRESSIBLE TURBULENCE

The physical nature of compressible turbulence is of fundamental importance in a variety of astrophysical settings. We investigate the question: 'At what scales does the mechanism of pressure-dilatation operate?' and present the first direct evidence that mean kinetic energy cascades conservatively beyond a transitional 'conversion' scale range despite not being an invariant of the dynamics. We use high-resolution 1024{sup 3} subsonic and transonic simulations. The key quantity we measure is the pressure-dilatation cospectrum, E{sup PD}(k), where we show that it decays at a rate faster than k{sup -1} in wavenumber in at least the subsonic and transonic regimes. This is sufficient to imply that mean pressure-dilatation acts primarily at large scales and that kinetic and internal energy budgets statistically decouple beyond a transitional scale range. However, we observe that small-scale dynamics remains highly compressible locally in space and that the statistical decoupling in the energy budgets is unrelated to the existence of a subsonic scale range. Our results suggest that an extension of Kolmogorov's inertial-range theory to compressible turbulence is possible.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

Hydrodynamic Modeling Analysis of Tidal Wetland Restoration in Snohomish River, Washington

To re-establish the intertidal wetlands with full tidal interaction and improve salmonid rearing habitat in the Lower Snohomish River estuary, a diked wetland along Union Slough of the Snohomish River was restored by breaching the existing dike and constructing bridges across the breaches. However, post-restoration monitoring indicated that the restored project site could not drain as efficiently as desired. To improve the drainage conditions at the restoration site during low tides, a modeling study was conducted to evaluate additional restoration scenarios and to provide recommendations for finish-grade ground elevations to achieve the desired drainage. To accurately simulate the drainage of the project site, an unstructured-grid hydrodynamic model with fine-grid resolution down to a few meters was used in this study. The model was first validated with observed water level data collected in the project site and then applied to assess the feasibility of different proposed restoration scenarios. A spatial varying bottom roughness option in the model is also implemented to better represent the high roughness due to the presence of dense vegetation in the project site. The methodology, error statistics of model validation and uncertainty of the modeling analysis are presented and discussed.

Yang, Zhaoqing↗
DOE OSTI2022

An Open-Source Frequency-Domain Model for Floating Wind Turbine Design Optimization

A new frequency-domain dynamics model has been developed that uses open-source components to efficiently represent a complete floating wind turbine system. The model, called RAFT (Response Amplitudes of Floating Turbines), incorporates quasi-static mooring reactions, strip-theory and potential-flow hydrodynamics, blade-element-momentum aerodynamics, and linear turbine control. The formulation is compatible with a wide variety of support structure configurations and no manual or time-domain preprocessing steps are required, making RAFT very practical in design and optimization workflows. The model is applied to three reference floating wind turbine designs and its predictions are compared with results from time-domain OpenFAST simulations. There is good agreement in mean offsets as well the statistics and spectra of the dynamic response, verifying RAFT’s general suitability for floating wind analysis. Follow-on work will include verification of potential-flow and turbine-control features and application to optimization problems.

17 WIND ENERGY↗
DOE OSTI2023

Domain Adaptive Graph Neural Networks for Constraining Cosmological Parameters Across Multiple Data Sets

Deep learning models have been shown to outperform methods that rely on summary statistics, like the power spectrum, in extracting information from complex cosmological data sets. However, due to differences in the subgrid physics implementation and numerical approximations across different simulation suites, models trained on data from one cosmological simulation show a drop in performance when tested on another. Similarly, models trained on any of the simulations would also likely experience a drop in performance when applied to observational data. Training on data from two different suites of the CAMELS hydrodynamic cosmological simulations, we examine the generalization capabilities of Domain Adaptive Graph Neural Networks (DA-GNNs). By utilizing GNNs, we capitalize on their capacity to capture structured scale-free cosmological information from galaxy distributions. Moreover, by including unsupervised domain adaptation via Maximum Mean Discrepancy (MMD), we enable our models to extract domain-invariant features. We demonstrate that DA-GNN achieves higher accuracy and robustness on cross-dataset tasks. Using data visualizations, we show the effects of domain adaptation on proper latent space data alignment. This shows that DA-GNNs are a promising method for extracting domain-independent cosmological information, a vital step toward robust deep learning for real cosmic survey data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Bridging the Gap between Cosmological Simulations with Graph Neural Networks and Domain Adaptation

Deep learning models have been shown to outperform methods that rely on summary statistics, like the power spectrum, in extracting information from complex cosmological data sets. However, due to differences in the subgrid physics implementation and numerical approximations across different simulation suites, models trained on data from one cosmological simulation show a drop in performance when tested on another. Similarly, models trained on any of the simulations would also likely experience a drop in performance when applied to observational data. Training on data from two different suites of the CAMELS hydrodynamic cosmological simulations, we examine the generalization capabilities of Domain Adaptive Graph Neural Networks (DA-GNNs). By utilizing GNNs, we capitalize on their capacity to capture structured scale-free cosmological information from galaxy distributions. Moreover, by including unsupervised domain adaptation via Maximum Mean Discrepancy (MMD), we enable our models to extract domain-invariant features. We demonstrate that DA-GNN achieves higher accuracy and robustness on cross dataset tasks (up to 28% better relative error and up to almost an order of magnitude better χ 2 ). Using data visualizations, we show the effects of domain adaptation on proper latent space data alignment. This shows that DA-GNNs are a promising method for extracting domain-independent cosmological information, a vital step toward robust deep learning for real cosmic survey data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Domain Adaptive Graph Neural Networks for Constraining Cosmological Parameters Across Multiple Data Sets

Deep learning models have been shown to outperform methods that rely on summary statistics, like the power spectrum, in extracting information from complex cosmological data sets. However, due to differences in the subgrid physics implementation and numerical approximations across different simulation suites, models trained on data from one cosmological simulation show a drop in performance when tested on another. Similarly, models trained on any of the simulations would also likely experience a drop in performance when applied to observational data. Training on data from two different suites of the CAMELS hydrodynamic cosmological simulations, we examine the generalization capabilities of Domain Adaptive Graph Neural Networks (DA-GNNs). By utilizing GNNs, we capitalize on their capacity to capture structured scale-free cosmological information from galaxy distributions. Moreover, by including unsupervised domain adaptation via Maximum Mean Discrepancy (MMD), we enable our models to extract domain-invariant features. We demonstrate that DA-GNN achieves higher accuracy and robustness on cross-dataset tasks (up to $28\%$ better relative error and up to almost an order of magnitude better $\chi^2$). Using data visualizations, we show the effects of domain adaptation on proper latent space data alignment. This shows that DA-GNNs are a promising method for extracting domain-independent cosmological information, a vital step toward robust deep learning for real cosmic survey data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Experimentally Inferred Fusion Yield Dependencies of OMEGA Inertial Confinement Fusion Implosions

Statistical modeling of experimental and simulation databases has enabled the development of an accurate predictive capability for deuterium-tritium layered cryogenic implosions at the OMEGA laser. Here, a physics-based statistical mapping framework is described and used to uncover the dependencies of the fusion yield. This model is used to identify and quantify the degradation mechanisms of the fusion yield in direct-drive implosions on OMEGA. The yield is found to be reduced by the ratio of laser beam to target radius, the asymmetry in inferred ion temperatures from the $l$ = 1 mode, the time span over which tritium fuel has decayed, and parameters related to the implosion hydrodynamic stability. When adjusted for tritium decay and $l$ = 1 mode, the highest yield in OMEGA cryogenic implosions is predicted to exceed 2 × 10 14 fusion reactions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Quantitative Constraints on the Reionization History from the IGM Damping Wing Signature in Two Quasars at z > 7

During reionization, neutral hydrogen in the intergalactic medium (IGM) imprints a damping wing absorption feature on the spectrum of high-redshift quasars. A detection of this signature provides compelling evidence for a significantly neutral universe, and enables measurements of the hydrogen neutral fraction x HI (z) at that epoch. Obtaining reliable quantitative constraints from this technique, however, is challenging due to stochasticity induced by the patchy inside-out topology of reionization, degeneracies with quasar lifetime, and the unknown unabsorbed quasar spectrum close to rest-frame Lyα. Here, we combine a large-volume semi-numerical simulation of reionization topology with 1D radiative transfer through high-resolution hydrodynamical simulations of the high-redshift universe to construct models of quasar transmission spectra during reionization. Our state-of-the-art approach captures the distribution of damping wing strengths in biased quasar halos that should have reionized earlier, as well as the erosion of neutral gas in the quasar environment caused by its own ionizing radiation. Combining this detailed model with our new technique for predicting the quasar continuum and its associated uncertainty, we introduce a Bayesian statistical method to jointly constrain the neutral fraction of the universe and the quasar lifetime from individual quasar spectra. We apply this methodology to the spectra of the two quasars with the highest redshifts known, ULAS J1120+0641 and ULAS J1342+0928, and measure volume-averaged neutral fractions {x HI }(Z = 7.09) = 0.48 $+0.26\atop{-0.26}$and {x HI }(Z = 7.54) = 0.60 $+0.20\atop{-0.23}$ (posterior medians and 68% credible intervals) when marginalized over quasar lifetimes of 10 3 ≤ t q ≤ 10 8 yr.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Spectral form factor of a quantum spin glass

It is widely expected that systems which fully thermalize are chaotic in the sense of exhibiting random-matrix statistics of their energy level spacings, whereas integrable systems exhibit Poissonian statistics. In this paper, we investigate a third class: spin glasses. These systems are partially chaotic but do not achieve full thermalization due to large free energy barriers. We examine the level spacing statistics of a canonical infinite-range quantum spin glass, the quantum p-spherical model, using an analytic path integral approach. We find statistics consistent with a direct sum of independent random matrices, and show that the number of such matrices is equal to the number of distinct metastable configurations — the exponential of the spin glass “complexity” as obtained from the quantum Thouless-Anderson-Palmer equations. We also consider the statistical properties of the complexity itself and identify a set of contributions to the path integral which suggest a Poissonian distribution for the number of metastable configurations. Our results show that level spacing statistics can probe the ergodicity-breaking in quantum spin glasses and provide a way to generalize the notion of spin glass complexity beyond models with a semi-classical limit.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2001

Fluid Physics Under a Stochastic Acceleration Field

The research summarized in this report has involved a combined theoretical and computational study of fluid flow that results from the random acceleration environment present onboard space orbiters, also known as g-jitter. We have focused on a statistical description of the observed g-jitter, on the flows that such an acceleration field can induce in a number of experimental configurations of interest, and on extending previously developed methodology to boundary layer flows. Narrow band noise has been shown to describe many of the features of acceleration data collected during space missions. The scale of baroclinically induced flows when the driving acceleration is random is not given by the Rayleigh number. Spatially uniform g-jitter induces additional hydrodynamic forces among suspended particles in incompressible fluids. Stochastic modulation of the control parameter shifts the location of the onset of an oscillatory instability. Random vibration of solid boundaries leads to separation of boundary layers. Steady streaming ahead of a modulated solid-melt interface enhances solute transport, and modifies the stability boundaries of a planar front.

Vinals, Jorge↗
DOE OSTI2012

Theory of electron-ion energy transfer applied to laser ablation

Electron-ion temperature equilibration will be considered for states of matter typically occurring during laser ablation that is for strongly heated electrons and densities similar and lower than the one in the solid. The focus will be on fluid systems after the melt of the lattice as these dominate the hydrodynamic phase of the ablation process. It is shown that simple expressions derived for dilute gases and plasmas become highly questionable for solid-density fluids whereas the electron-phonon picture is inapplicable as well. Instead, one has to consider the collective behavior of electrons and ions in the strongly coupled fluid. The strong inter-ionic forces also strongly affect the heat capacities applied in a two-temperature model. The results presented here are based on a quantum-statistical approach applying nonequilibrium Green's functions.

36 MATERIALS SCIENCE↗
DOE OSTI2017

On the galaxy–halo connection in the EAGLE simulation

Empirical models of galaxy formation require assumptions about the correlations between galaxy and halo properties. These may be calibrated against observations or inferred from physical models such as hydrodynamical simulations. In this Letter, we use the EAGLE simulation to investigate the correlation of galaxy size with halo properties. We motivate this analysis by noting that the common assumption of angular momentum partition between baryons and dark matter in rotationally supported galaxies overpredicts both the spread in the stellar mass–size relation and the anticorrelation of size and velocity residuals, indicating a problem with the galaxy–halo connection it implies. We find the EAGLE galaxy population to perform significantly better on both statistics, and trace this success to the weakness of the correlations of galaxy size with halo mass, concentration and spin at fixed stellar mass. Here by, using these correlations in empirical models will enable fine-grained aspects of galaxy scalings to be matched.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Effects of Riser Diameter on Solids Holdup and Particle Velocity Profiles in Circulating Fluidized Bed Riser Systems

Tests were performed in a 0.1-m diameter small circulating fluidized bed (SCFB) and 0.3 m diameter cold flow circulating fluidized bed (CFCFB) riser systems located at the National Energy Technology Laboratory (NETL) to study the effects of riser diameter on the riser hydrodynamics. These tests were performed at solids circulation rates of G s = 20 and 75 kg/m 2 s and superficial gas velocities of U g = 5.8 and 6.5 m/s using high-density polyethylene (HDPE) pellets with a density of 0.863 g/cm 3 , particle size range of 600–1400 µm (with a Sauter mean diameter of 871 µm, placing them in the Geldart B classification). Comparisons of riser axial pressure and solids fraction profiles, radial particle velocity profiles, and radial profiles of higher statistical moments and select chaos analysis parameters were considered. The results showed that for a given U g and G s , the smaller diameter riser exhibited characteristics associated with more dilute solids flow than that observed in the larger diameter riser. Additionally, the larger diameter riser exhibited a downward flow of solids near the wall under all test conditions, whereas the smaller diameter riser data exhibited little or no indications of solids downflow near the wall. Overall, these findings suggest that, from an industrial standpoint, a direct scaleup of small-scale tests cannot readily be accomplished as the solids holdup and the solids velocity profiles in small units (those normally tested in the laboratory) are not similar to those of large units and the performance of large units can therefore not be predicted from small-scale tests.

42 ENGINEERING↗
DOE OSTI2016

THE TURBULENT ORIGIN OF OUTFLOW AND SPIN MISALIGNMENT IN MULTIPLE STAR SYSTEMS

The protostellar outflows of wide-separation forming binaries frequently appear misaligned. We use magneto-hydrodynamic simulations to investigate the alignment of protostellar spin and molecular outflows for forming binary pairs. We show that the protostellar pairs, which form from turbulent fragmentation within a single parent core, have randomly oriented angular momentum. Although the pairs migrate to closer separations, their spins remain partially misaligned. We produce {sup 12}CO(2-1) synthetic observations of the simulations and characterize the outflow orientation in the emission maps. The CO-identified outflows exhibit a similar random distribution and are also statistically consistent with the observed distribution of molecular outflows. We conclude that the observed misalignment provides a clear signature of binary formation via turbulent fragmentation. The persistence of misaligned outflows and stellar spins following dynamical evolution may provide a signature of binary origins for more evolved multiple star systems.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1993

Testing the pressure-confined Ly alpha cloud model

The Ly-alpha absorption line forest, seen in quasar spectra, is generally interpreted as being due to cosmologically distributed 'clouds' of primordial gas. Analyses of the observations reveal that the number distribution can be described by power laws: dN/dz is proportional to (1 + z)(sup gamma) and dN/dN(sub HI) is proportional to N(sub HI)(sup -beyda), where N(sub HI) is the HI column density. The typical values for power law indices range between 2 is approximately less than gamma is approximately less than 2.6 and 1.7 is approximately less than gamma is approximately less than 1.9. One model postulates that the Ly-alpha clouds are optically thin entities, photoionized by the background UV flux, J(sub nu) is proportional to (1 + z)(sup j), and confined by an adiabatically evolving intercloud medium (ICM): P(z) is proportional to (1 + z)(sup 5). Analytic studies of this model suggest that the ensuing Ly-alpha line statistics can account for the observations (in particular, the dN/dz and the dN/dN(sub HI) distributions) if the cloud mass spectrum is a power law dN/dN is proportional to M(sup -delta), delta is approximately 1.9, and j is approximately 4. One of the simplifying assumptions incorporated into these studies is the existence of a large mass range for the clouds at all epochs, the validity of which is questionable. The pressure-confined model is investigated using a 1-D spherically symmetric hydrodynamical code to simulate cloud evolution over the epoch 1.8 less than z less than 6. This enables us to relax many of the assumptions incorporated in the analytic studies.

Babul, Arif↗