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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Continuous momentum dependence in the dynamical cluster approximation

The dynamical cluster approximation (DCA) is a quantum cluster extension to the single-site dynamical mean-field theory that incorporates spatially nonlocal dynamic correlations systematically and nonperturbatively. The DCA + algorithm addresses the cluster shape dependence of the DCA and improves the convergence with cluster size by introducing a lattice self-energy with continuous momentum dependence. However, we show that the DCA + algorithm is plagued by a fundamental problem when its self-consistency equations are formulated using the bare Green's function of the cluster. This problem is most severe in the strongly correlated regime at low doping, where the DCA + self-energy becomes overly metallic and local, and persists to cluster sizes where the standard DCA has long converged. In view of the failure of the DCA + algorithm, we propose to complement DCA simulations with a post-interpolation procedure for single-particle and two-particle correlation functions to preserve continuous momentum dependence and the associated benefits in the DCA. We demonstrate the effectiveness of this practical approach with results for the half-filled and hole-doped two-dimensional Hubbard model.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

A New Equivalence Theory Method for Treating Doubly Heterogeneous Fuel - I. Theory

A new methodology has been developed to treat resonance self-shielding in doubly heterogeneous very high temperature gas-cooled reactor systems in which the fuel compact region of a reactor lattice consists of small fuel grains dispersed in a graphite matrix. This new method first homogenizes the fuel grain and matrix materials using an analytically derived disadvantage factor from a two-region problem with equivalence theory and intermediate resonance method. This disadvantage factor accounts for spatial self-shielding effects inside each grain within the framework of an infinite array of grains. Then the homogenized fuel compact is self-shielded using a Bondarenko method to account for interactions between the fuel compact regions in the fuel lattice. In the final form of the equations for actual implementations, the double-heterogeneity effects are accounted for by simply using a modified definition of a background cross section, which includes geometry parameters and cross sections for both the grain and fuel compact regions. With the new method, the doubly heterogeneous resonance self-shielding effect can be treated easily even with legacy codes programmed only for a singly heterogeneous system by simple modifications in the background cross section for resonance integral interpolations. This paper presents a detailed derivation of the new method and a sensitivity study of double-heterogeneity parameters introduced during the derivation. The implementation of the method and verification results for various test cases are presented in the companion paper.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

A HPC Theory-Guided Machine Learning Cyberinfrastructure for Communicating Hydrometeorological Data Across Scales

High-resolution predictions of hydrometeorological variables are critical for supporting hydropower generation decisions and flood control at hydroelectric power plants. Traditional climate and hydrologic models rely on the numerical simulation of detailed physical processes. Therefore, running these simulations is time-, labor-, and computation-intensive. Improving the spatial and temporal resolution in these modeling outputs could lead to cubic increases in both the simulation time and computational demands, rendering high-resolution hydrometeorological predictions expensive and impractical. Many past studies apply the super resolution (SR) technique to downscale climate models using deep learners. However, deep learners are deemed “black-boxes,” as their derivation processes from low-resolution outputs to high-resolution outputs are often hidden. Their results are difficult for domain scientists to interpret and validate. Thus, there is a need for an exploratory machine learning approach that can partially integrate domain-specific theory and knowledge into the data-driven mapping process between simulation outputs of different spatial scales. The domain-specific theory and knowledge can be incorporated into the data model through an inductive approach in which process-related environmental variables are used and analyzed as key drivers (i.e., environmental surrogates) to reflect the complex physical processes. Many of these variables, such as land use land cover, soil types, topography, digital elevation, air temperature, and various watershed characteristics, can be directly measured through sensors or remote sensing techniques. Additionally, SR applications that can downscale hydrological and hydrodynamics models to efficiently produce high-resolution (1 m) flood depth grids are still rare. Since the flood depth grid can be used to support critical decisions for flood control operation at hydroelectric power plants, it is crucial to enable an SR-based capability for interpolating high-resolution flood inundation maps.

13 HYDRO ENERGY↗
DOE OSTI2026

HostSub_GP: Precise Galaxy Background Subtraction in Transient Long-slit Spectroscopy with Gaussian Processes

We present a novel host galaxy subtraction technique in long-slit spectroscopy for extragalactic transients. Unlike classic methods which generally estimate the background using simple interpolation of local galaxy flux in the 2D spectrum, our approach leverages multi-band archival images of the host galaxies to model the background emission from the galaxy in the 2D spectrum. Such imaging encodes the wavelength-dependent galaxy profile along the slit, and is readily accessible through wide-field imaging surveys. We construct a smooth prior for the 2D galaxy profile with a Gaussian process (GP) based on these reference images, and use another GP to model the correlated deviations from the prior in the observed spectrum. This enables accurate inference of the galaxy flux blended with the transient. On synthetic long-slit data of a spiral galaxy extracted from a Multi Unit Spectroscopic Explorer hyper-spectral cube, the GP method remains robust as long as the host galaxy is spatially resolved and consistently outperforms classic methods. We apply the method to archival Keck spectra of two real transients, SN 2019eix and AT 2019qiz, to further demonstrate how the method uniquely recovers weak spectral features amid strong galaxy contamination, enabling refined constraints on the properties of both transients. We have released the software implementation, HostSub_GP, a scalable toolkit that leverages JAX, with an MIT license.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Disparities in the air quality monitoring stations and PM₂.₅ in Chicago’s air quality landscape

Fine particulate matter (PM₂.₅) poses significant public and environmental health risks in urban areas. Chicago’s dense industry and traffic create variable air quality, yet monitoring is unevenly distributed, resulting in undersampling of air quality data in some city areas. This study applied a hybrid approach using GIS-based kernel density mapping, interpolation modeling (IDW, Spline, Kriging) of USEPA monitoring data, multi-scale temporal trend analyses (hourly to annual), and ESDA. Accordingly, the density surface showed that monitors are concentrated in the affluent north, northwest, and southwest sides of Chicago (up to ~ 0.07 stations per sq mile), while the south and southeast regions, with predominantly minority communities, have virtually no coverage. Overall, citywide coverage is minimal (~ 4–5 monitors total; ~0.02 per sq mile; ≈1 per 600,000 residents). Temporal analyses showed that the city’s mean annual PM₂.₅ (~ 10.8 µg/m³) exceeds USEPA/WHO standards (9 µg/m³), with summer means (~ 17.1 µg/m³) significantly higher than other seasons. Diurnally, a clear pattern was observed, with PM₂.₅ concentrations peaking overnight (00:00–03:00) and during the morning rush hours, and dipping during midday to late afternoon. Spatial distribution of PM₂.₅ identified hotspots near O’Hare Airport, the downtown Loop area, and south-side neighborhoods, contrasting with lower concentrations on the north side, revealing Chicago’s socioeconomic divides and resulting environmental inequities. The findings underscore the need for expanded monitoring and targeted interventions in under-monitored, high-pollution communities to advance equitable community health.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Using Temporal Deep Learning Models to Estimate Daily Snow Water Equivalent Over the Rocky Mountains

Abstract In this study we construct and compare three different deep learning (DL) models for estimating daily snow water equivalent (SWE) from high‐resolution gridded meteorological fields over the Rocky Mountain region. To train the DL models, Snow Telemetry (SNOTEL) station‐based SWE observations are used as the prediction target. All DL models produce higher median Nash‐Sutcliffe Efficiency (NSE) values than a conceptual SWE model and interpolated gridded data sets, although mean squared errors also tend to be higher. Sensitivity of the SWE prediction to the model's input variables is analyzed using an explainable artificial intelligence (XAI) method, yielding insight into the physical relationships learned by the models. This method reveals the dominant role precipitation and temperature play in snowpack dynamics. In applying our models to estimate SWE throughout the Rocky Mountains, an extrapolation problem arises since the statistical properties of SWE (e.g., annual maximum) and geographical properties of individual grid points (e.g., elevation) differ from the training data. This problem is solved by normalizing the SWE with its historical maximum value to alleviate extrapolation for all tested DL models. Our work shows that the DL models are promising tools for estimating SWE, and sufficiently capture relevant physical relationships to make them useful for spatial and temporal extrapolation of SWE values.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A Block-Structured Adaptive Mesh Framework to Solve Radiation Transfer Equation in Irregular Embedded Geometries

Radiation transport arises in various scientific, industrial, and medical fields, and understanding its effect in applications is needed to make accurate predictions, safety assessments and performance optimizations. Solving the Radiation Transport Equation (RTE) is challenging due to its integro-differential nature, which involves both differential and integral terms. The differential term describes the change in radiation intensity due to absorption and emission, while the integral term accounts for scattering. The accurate modeling of radiation is further complicated in many applications due to the complex, irregular geometries. Various methods exist for solving the RTE, including the zonal, Monte Carlo, spherical harmonics, discrete ordinates, and finite volume methods. Traditional mesh-based approaches, which rely on structured or unstructured meshes, struggle with irregular geometries due to: a) the difficulty of conforming structured grids to irregular domains, b) challenges in enforcing boundary conditions correctly, and c) the additional computational cost of unstructured mesh methods. This work presents a second-order accurate method for solving the RTE in irregular geometries. The radiation intensity is discretized using the finite-volume method in both spatial and angular directions on regular Cartesian grid blocks. Leveraging the block-structured adaptive mesh refinement (AMR) framework provided by AMReX, our method refines the grid locally to reduce spatial discretization error, ensuring a converged numerical solution while minimizing computational costs elsewhere. A two-stage deferred correction approach is employed: First, a first-order discretization on grid blocks is solved using an algebraic multigrid method in HYPRE. Second, a correction term is applied explicitly to achieve second-order accuracy. The correction term is calculated by approximating the radiation flux on cell faces using a Total Variation Diminishing (TVD) scheme. This approach ensures quick convergence of the multigrid method while preserving higher-order accuracy of the numerical solution. Irregular geometries are resolved as embedded boundaries (EB), resulting in both cut cells and regular cells. In cut cells, we modify the fluxes using face fractions and incorporate additional contributions from EB boundary conditions. To ensure higher-order convergence near the EB interface, the correction term is modified by interpolating the radiation intensity to fictitious ghost points. The implementation takes advantage of modern supercomputers by leveraging AMReX’sMPI/X parallelization strategy where X can be MPI or a GPU accelerator including CUDA, HIP and DPC++. We validate our solver using classical test cases, both with and without EB, demonstrating accuracy and efficiency. Additionally, we analyze the impact of adaptive mesh refinement on solution accuracy and computational cost, highlighting the advantages of our approach for high-resolution radiation transport simulations.

computational fluid dynamics (CFD)↗
DOE OSTI2014

SU-E-J-14: A Novel Approach to Evaluate the Dosimetric Effect of Rectal Variation During Image Guided Prostate Radiotherapy

Purpose: Deformable registration establishes the spatial correspondence back to the reference image in order to accumulate dose. However, in prostate radiotherapy the changing shape and volume of the rectum present a challenge to accurate deformable registration and consequently calculation of delivered dose. We explored an alternative approach to calculating accumulated dose to the rectum, independent of deformable registration. Methods: This study was performed on three patients who received online image-guided radiotherapy (IGRT) with daily CBCT (XVI-system,Elekta) and target localization using intraprostatic fiducials. On each CBCT, the rectum was manually contoured and bulk density assignments were made allowing dose to be calculated for each fraction. Dose-surface maps (DSM) were generated (MATLAB,Mathworks,Natick,MA) by considering the rectum as a cylinder and sampling the dose at 21-equispaced points on each CT slice. The cylinder was “cut” at the posterior-most position on each CT and unfolded to generate a DSM. These were normalised in the longitudinal direction by interpolation creating maps of 21×21 pixels. A DSM was produced for each CBCT and the dose was accumulated. Results: The mean accumulated delivered rectal surface dose was on average 7.5(+/−3.5)% lower than the planned dose. The dose difference maps consistently show that the greatest variation in dose between planned and delivered dose is away from where the rectal surface is adjacent to the prostate. Conclusion: Estimation of dose accumulation using DSM provides an alternative method for determining actual delivered dose to the rectum. The dose difference is greatest in areas away from the region where the rectal surface abuts the prostate, the region where set-up is verified. The change in size and shape of the rectum was shown to resultin a change in the accumulated dose compared to the planned dose and this will have an impact on determining the relationships between dose delivered and toxicity. We acknowledge funding from CRUK and acknowledge NHS funding to the NIHR Biomedical Research Centre for Cancer. Patients were treated within the CHHiP IGRT sub-study (CRUK/06/016, ISRCTN:97182923) funded by CRUK. RayStation was used under an evaluation agreement with RaySearch Laboratories AB.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Non-intrusive reduced-order modeling for dynamical systems with spatially localized features

This work presents a non-intrusive reduced-order modeling framework for dynamical systems with spatially localized features characterized by slow singular value decay. The proposed approach builds upon two existing methodologies for reduced and full-order non-intrusive modeling, namely Operator Inference (OpInf) and sparse Full-Order Model (sFOM) inference. We decompose the domain into two complementary subdomains that exhibit fast and slow singular value decay. The dynamics of the subdomain exhibiting slow singular value decay are learned with sFOM while the dynamics with intrinsically low dimensionality on the complementary subdomain are learned with OpInf. The resulting, coupled OpInf-sFOM formulation leverages the computational efficiency of OpInf and the high resolution of sFOM, and thus enables fast non-intrusive predictions for conditions beyond those sampled in the training data set. A novel regularization technique with a closed-form solution based on the Gershgorin disk theorem is introduced to promote stable sFOM and OpInf models. We also provide a data-driven indicator for subdomain selection and ensure solution smoothness over the interface via a post-processing interpolation step. We evaluate the efficiency of the approach in terms of offline and online speedup through a quantitative, parametric computational cost analysis. We demonstrate the coupled OpInf-sFOM formulation for two test cases: a one-dimensional Burgers’ model for which accurate predictions beyond the span of the training snapshots are presented, and a two-dimensional parametric model for the Pine Island Glacier ice thickness dynamics, for which the OpInf-sFOM model achieves an average prediction error on the order of 1% with an online speedup factor of approximately 8$\times$ compared to the numerical simulation.

42 ENGINEERING↗
DOE OSTI2019

Scalable Matrix-Free Adaptive Product-Convolution Approximation for Locally Translation-Invariant Operators

We present an adaptive grid matrix-free operator approximation scheme based on a "product-convolution" interpolation of convolution operators. This scheme is appropriate for operators that are locally translation-invariant, even if these operators are high rank or full rank. Such operators arise in Schur complement methods for solving partial differential equations (PDEs), as Hessians in PDE-constrained optimization and inverse problems, as integral operators, as covariance operators, and as Dirichlet-to-Neumann maps. Constructing the approximation requires computing the impulse responses of the operator to point sources centered on nodes in an adaptively refined grid of sample points. A randomized a posteriori error estimator drives the adaptivity. Once constructed, the approximation can be efficiently applied to vectors using the fast Fourier transform. The approximation can be efficiently converted to hierarchical matrix (H-matrix) format, then inverted or factorized using scalable H-matrix arithmetic. The quality of the approximation degrades gracefully as fewer sample points are used, allowing cheap lower quality approximations to be used as preconditioners. Furthermore, this yields an automated method to construct preconditioners for locally translation-invariant Schur complements. We directly address issues related to boundaries and prove that our scheme eliminates boundary artifacts. We test the scheme on a spatially varying blurring kernel, on the nonlocal component of an interface Schur complement for the Poisson operator, and on the data misfit Hessian for an advection dominated advection-diffusion inverse problem. Numerical results show that the scheme outperforms existing methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Emulation of dynamic simulators with application to hydrology

Many simulation-intensive tasks in the applied sciences, such as sensitivity analysis, parameter inference or real time control, are hampered by slow simulators. Emulators provide the opportunity of speeding up simulations at the cost of introducing some inaccuracy. An emulator is a fast approximation to a simulator that interpolates between design input–output pairs of the simulator. Increasing the number of design data sets is a computationally demanding way of improving the accuracy of emulation. We investigate the complementary approach of increasing emulation accuracy by including knowledge about the mechanisms of the simulator into the formulation of the emulator. To approximately reproduce the output of dynamic simulators, we consider emulators that are based on a system of linear, ordinary or partial stochastic differential equations with a noise term formulated as a Gaussian process of the parameters to be emulated. This stochastic model is then conditioned to the design data so that it mimics the behavior of the nonlinear simulator as a function of the parameters. The drift terms of the linear model are designed to provide a simplified description of the simulator as a function of its key parameters so that the required corrections by the conditioned Gaussian process noise are as small as possible. The goal of this paper is to compare the gain in accuracy of these emulators by enlarging the design data set and by varying the degree of simplification of the linear model. We apply this framework to a simulator for the shallow water equations in a channel and compare emulation accuracy for emulators based on different spatial discretization levels of the channel and for a standard non-mechanistic emulator. Our results indicate that we have a large gain in accuracy already when using the simplest mechanistic description by a single linear reservoir to formulate the drift term of the linear model. Adding some more reservoirs does not lead to a significant improvement in accuracy. However, the transition to a spatially continuous linear model leads again to a similarly large gain in accuracy as the transition from the non-mechanistic emulator to that based on one reservoir.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Growth of organized flow coherent motions within a single-stream shear layer: 4D-PTV measurements

Abstract This study investigates the evolution of a single-stream shear layer (SSSL) originating from a wall boundary layer past a backward-facing step. Utilizing a time-resolved 3D-Particle Tracking Velocimetry (4D-PTV) technique, we track the trajectories of fluorescent particles to gain insight into the flow characteristics of the SSSL. A compact water tunnel facility ( $$\textrm{Re}_\tau =1\,240$$ Re τ = 1 240 ) is fabricated to obtain an SSSL with a perpendicular slow entrainment stream past the separation edge. A hybrid interpolation approach that combines ensemble binning and Gaussian weighting is implemented to derive minimally filtered mean and instantaneous lower- and higher-order flow field parameters. Spanwise-dominant coherent motion accompanied by finer flow scales is observed to grow due to flow entrainment through “nibbling” actions of small-scale vortices, “engulfing” by large-scale vortices, and vortex pairing events. Furthermore, the non-zero-speed stream edge grows relatively faster than the zero-speed stream edge, showing a strong asymmetry in mixing composition across a mixing layer. The SSSL reaches self-similarity at a streamwise distance of $$\approx 55\,\theta _{0}$$ ≈ 55 θ 0 , where $$\theta _0$$ θ 0 is the initial momentum thickness from the separation edge, i.e., considerably shorter than reported in previous studies. A literature comparison of growth rate parameters raises intriguing questions regarding a potential inclusive growth scaling unifying the free shear layers. A turbulent kinetic energy (TKE) budget analysis reveals a negative production region immediately downstream of the separation edge attributed to a large positive streamwise gradient of streamwise velocity. In the self-similar region, the phase-averaged flow mapping demonstrates a larger concentration of turbulence production rate around the outer edges of spanwise vortices, specifically at the intersection of braids and vortices. Furthermore, a spatial separation exists in the regions of peak production and dissipation rates within the vortex core region favoring dissipation. The braids exhibit a larger concentration of turbulence diffusion rates, indicating their function as a conduit for exchanging turbulence between neighboring coherent motions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2013

4D tumor centroid tracking using orthogonal 2D dynamic MRI: Implications for radiotherapy planning

Purpose: Current pretreatment, 4D imaging techniques are suboptimal in that they sample breathing motion over a very limited “snapshot” in time. Heretofore, long-duration, 4D motion characterization for radiotherapy planning, margin optimization, and validation have been impractical for safety reasons, requiring invasive markers imaged under x-ray fluoroscopy. To characterize 3D tumor motion and associated variability over durations more consistent with treatments, the authors have developed a practical dynamic MRI (dMRI) technique employing two orthogonal planes acquired in a continuous, interleaved fashion.Methods: 2D balanced steady-state free precession MRI was acquired continuously over 9–14 min at approximately 4 Hz in three healthy volunteers using a commercial 1.5 T system; alternating orthogonal imaging planes (sagittal, coronal, sagittal, etc.) were employed. The 2D in-plane pixel resolution was 2 × 2 mm{sup 2} with a 5 mm slice profile. Simultaneous with image acquisition, the authors monitored a 1D surrogate respiratory signal using a device available with the MRI system. 2D template matching-based anatomic feature registration, or tracking, was performed independently in each orientation. 4D feature tracking at the raw frame rate was derived using spline interpolation.Results: Tracking vascular features in the lung for two volunteers and pancreatic features in one volunteer, the authors have successfully demonstrated this method. Registration error, defined here as the difference between the sagittal and coronal tracking result in the SI direction, ranged from 0.7 to 1.6 mm (1σ) which was less than the acquired image resolution. Although the healthy volunteers were instructed to relax and breathe normally, significantly variable respiration was observed. To demonstrate potential applications of this technique, the authors subsequently explored the intrafraction stability of hypothetical tumoral internal target volumes and 3D spatial probability distribution functions. The surrogate respiratory information allowed the authors to show how this technique can be used to study correlations between internal and external (surrogate) information over these prolonged durations. However, compared against the gold standard of the time stamps in the dMRI frames, the temporal synchronization of the surrogate 1D respiratory information was shown to be likely unreliable.Conclusions: The authors have established viability of a novel and practical pretreatment, 4D tumor centroid tracking method employing a commercially available dynamic MRI sequence. Further developments from the vendor are likely needed to provide a reliably synchronized surrogate 1D respiratory signal, which will likely broaden the utility of this method in the pretreatment radiotherapy planning context.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Mapping the monoceros ring in 3D with Pan-STARRS1

Using the Pan-STARRS1 survey, we derive limiting magnitude, spatial completeness, and density maps that we use to probe the three-dimensional structure and estimate the stellar mass of the so-called Monoceros Ring. The Monoceros Ring is an enormous and complex stellar sub-structure in the outer Milky Way disk. It is most visible across the large Galactic Anticenter region, 120{sup ∘}<l<240{sup ∘}, −30{sup ∘}<b<+40{sup ∘}. We estimate its stellar mass density profile along every line of sight in 2° × 2° pixels over the entire 30,000 deg{sup 2} Pan-STARRS1 survey using the previously developed match software. By parsing this distribution into a radially smooth component and the Monoceros Ring, we obtain its mass and distance from the Sun along each relevant line of sight. The Monoceros Ring is significantly closer to us in the south (6 kpc) than in the north (9 kpc). We also create 2D cross-sections parallel to the Galactic plane that show 135° of the Monoceros Ring in the south and 170° of the Monoceros Ring in the north. We show that the northern and southern structures are also roughly concentric circles, suggesting that they may be waves rippling from a common origin. Excluding the Galactic plane ∼±4{sup ∘}, we observe an excess mass of 4×10{sup 6}M{sub ⊙} across 120{sup ∘}<l<240{sup ∘}. If we interpolate across the Galactic plane, we estimate that this region contains 8×10{sup 6}M{sub ⊙}. If we assume (somewhat boldly) that the Monoceros Ring is a set of two Galactocentric rings, its total mass is 6×10{sup 7}M{sub ⊙}. Finally, if we assume that it is a set of two circles centered at a point 4 kpc from the Galactic center in the anti-central direction, as our data suggests, we estimate its mass to be 4×10{sup 7}M{sub ⊙}.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Material point methods applied to one-dimensional shock waves and dual domain material point method with sub-points

Here, using a simple one-dimensional shock problem as an example, the present paper investigates numerical properties of the original material point method (MPM), the generalized interpolation material point (GIMP) method, the convected particle domain interpolation (CPDI) method, and the dual domain material point (DDMP) method. For a weak isothermal shock of ideal gas, the MPM cannot be used with accuracy. With a small number of particles per cell, GIMP and CPDI produce reasonable results. However, as the number of particles increases the methods fail to converge and produce pressure spikes. The DDMP method behaves in an opposite way. With a small number of particles per cell, DDMP results are unsatisfactory. As the number of particles increases, the DDMP results converge to correct solutions, but the large number of particles needed for convergence makes the method very expensive to use in these types of shock wave problems in two- or three-dimensional cases. The cause for producing the unsatisfactory DDMP results is identified. A simple improvement to the method is introduced by using sub-points. With this improvement, the DDMP method produces high quality numerical solutions with a very small number of particles. Although in the present paper, the numerical examples are one-dimensional, all derivations are for multidimensional problems. With the technique of approximately tracking particle domains of CPDI, the extension of this sub-point method to multidimensional problems is straightforward. Finally, this new method preserves the conservation properties of the DDMP method, which conserves mass and momentum exactly and conserves energy to the second order in both spatial and temporal discretizations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Modeling and observations of an elevated, moving infrasonic source: Eigenray methods

In this paper, the acoustic ray tracing relations are extended by the inclusion of auxiliary parameters describing variations in the spatial ray coordinates and eikonal vector due to changes in the initial conditions. Computation of these parameters allows one to define the geometric spreading factor along individual ray paths and assists in identification of caustic surfaces so that phase shifts can be easily identified. A method is developed leveraging the auxiliary parameters to identify propagation paths connecting specific source-receiver geometries, termed eigenrays. The newly introduced method is found to be highly efficient in cases where propagation is non-planar due to horizontal variations in the propagation medium or the presence of cross winds. Finally, the eigenray method is utilized in analysis of infrasonic signals produced by a multi-stage sounding rocket launch with promising results for applications of tracking aeroacoustic sources in the atmosphere and specifically to analysis of motor performance during dynamic tests.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

A new method for analyzing and visualizing plasma simulations using a phase-space tessellation

We apply a novel phase-space interpolation technique referred to as the simplex-in-cell (SIC) method to analyze two- and three-dimensional particle-in-cell (PIC) simulations of electromagnetic plasmas. SIC relies on a discretization of the initial phase-space distribution function into simplices, which allows an approximation to the full, continuously defined distribution function to be constructed at any later time in the simulation. This allows densities, currents, and even full momentum distribution functions to be measured at any point in the simulation domain without averaging over control volumes. The SIC approach applies to any PIC simulation for which a tessellation of the initial particle distribution can be constructed. In this study, we use outputs from standard PIC simulations of the Weibel instability and compare physical quantities such as charge and current densities calculated in postprocessing using SIC and standard particle deposits. Using 2D simulations with 1–65 536 particles-per-cell, we find that SIC eliminates discrete particle noise and in some cases can reach a given noise level using ~1000 times fewer simulation particles than with standard particle deposition schemes. In regions of low density, such as between current filaments, SIC is able to capture small amplitude features even with fewer particles than gridpoints due to the deformable nature of the SIC volume elements. Here, by calculating momentum distributions, we show how SIC can capture low density tails in the spectrum using far fewer particles than are necessary for standard particle deposits. We calculate the charge density on spatial grids of increasing resolution to demonstrate the ability of SIC to reveal fine-scale details that are not accessible with standard particle deposits. Finally, we show how SIC can be extended to 3D and give an example of its use to calculate the charge density from 3D PIC simulations of the Weibel instability. These results motivate the future implementation of SIC directly in the simulation force calculation for a novel low-noise electromagnetic plasma simulation method.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

SPECTROSCOPIC METALLICITY DETERMINATIONS FOR W UMa-TYPE BINARY STARS

This study is the first attempt to determine the metallicities of W UMa-type binary stars using spectroscopy. We analyzed about 4500 spectra collected at the David Dunlap Observatory. To circumvent problems caused by the extreme spectral line broadening and blending and by the relatively low quality of the data, all spectra were subject to the same broadening function (BF) processing to determine the combined line strength in the spectral window centered on the Mg I triplet between 5080 A and 5285 A. All individual integrated BFs were subsequently orbital-phase averaged to derive a single line-strength indicator for each star. The star sample was limited to 90 W UMa-type (EW) binaries with the strict phase-constancy of colors and without spectral contamination by spectroscopic companions. The best defined results were obtained for an F-type sub-sample (0.32 < (B - V){sub 0} < 0.62) of 52 binaries for which integrated BF strengths could be interpolated in the model atmosphere predictions. The logarithmic relative metallicities, [M/H], for the F-type sub-sample indicate metal abundances roughly similar to the solar metallicity, but with a large scatter which is partly due to combined random and systematic errors. Because of the occurrence of a systematic color trend resulting from inherent limitations in our approach, we were forced to set the absolute scale of metallicities to correspond to that derived from the m{sub 1} index of the Stroemgren uvby photometry for 24 binaries of the F-type sub-sample. The trend-adjusted metallicities [M/H]{sub 1} are distributed within -0.65 < [M/H]{sub 1} < +0.50, with the spread reflecting genuine metallicity differences between stars. One half of the F-sub-sample binaries have [M/H]{sub 1} within -0.37 < [M/H]{sub 1} < +0.10, a median of -0.04 and a mean of -0.10, with a tail toward low metallicities, and a possible bias against very high metallicities. A parallel study of kinematic data, utilizing the most reliable and recently obtained proper motion and radial velocity data for 78 binaries of the full sample, shows that the F-type sub-sample binaries (44 stars with both velocities and metallicity determinations) have similar kinematic properties to solar-neighborhood, thin-disk dwarfs with space velocity component dispersions: {sigma}U = 33 km s{sup -1}, {sigma}V = 23 km s{sup -1} and {sigma}W = 14 km s{sup -1}. FU Dra with a large spatial velocity, V{sub tot} = 197 km s{sup -1} and [M/H]{sub 1} = -0.6 {+-} 0.2, appears to be the only thick-disk object in the F-type sub-sample. The kinematic data indicate that the F-type EW binaries are typical, thin-disk population stars with ages about 3-5.5 Gyr. The F-type binaries that appear to be older than the rest tend to have systematically smaller mass ratios than most of the EW binaries of the same period.

79 ASTRONOMY AND ASTROPHYSICS↗