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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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At least 991 records · Page 55
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DOE OSTI2015

An ammonia spectral map of the L1495-B218 filaments in the Taurus molecular cloud. I. Physical properties of filaments and dense cores

We present deep NH{sub 3} observations of the L1495-B218 filaments in the Taurus molecular cloud covering over a 3° angular range using the K-band focal plane array on the 100 m Green Bank Telescope. The L1495-B218 filaments form an interconnected, nearby, large complex extending over 8 pc. We observed NH{sub 3} (1, 1) and (2, 2) with a spectral resolution of 0.038 km s{sup −1} and a spatial resolution of 31″. Most of the ammonia peaks coincide with intensity peaks in dust continuum maps at 350 and 500 μm. We deduced physical properties by fitting a model to the observed spectra. We find gas kinetic temperatures of 8–15 K, velocity dispersions of 0.05–0.25 km s{sup −1}, and NH{sub 3} column densities of 5 × 10{sup 12} to 1 × 10{sup 14} cm{sup −2}. The CSAR algorithm, which is a hybrid of seeded-watershed and binary dendrogram algorithms, identifies a total of 55 NH{sub 3} structures, including 39 leaves and 16 branches. The masses of the NH{sub 3} sources range from 0.05 to 9.5 M{sub ⊙}. The masses of NH{sub 3} leaves are mostly smaller than their corresponding virial mass estimated from their internal and gravitational energies, which suggests that these leaves are gravitationally unbound structures. Nine out of 39 NH{sub 3} leaves are gravitationally bound, and seven out of nine gravitationally bound NH{sub 3} leaves are associated with star formation. We also found that 12 out of 30 gravitationally unbound leaves are pressure confined. Our data suggest that a dense core may form as a pressure-confined structure, evolve to a gravitationally bound core, and undergo collapse to form a protostar.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Exploring stellar evolution models of sdB stars using MESA

Stellar evolution calculations have had great success reproducing the observed atmospheric properties of different classes of stars. Recent detections of g-mode pulsations in evolved He burning stars allow a rare comparison of their internal structure with stellar models. Asteroseismology of subdwarf B (sdB) stars suggests convective cores of 0.22–0.28 M{sub ⊙}, ≳45% of the total stellar mass. Previous studies found significantly smaller convective core masses (≲0.19 M{sub ⊙}) at a comparable evolutionary stage. We evolved stellar models with Modules for Experiments in Stellar Astrophysics (MESA) to explore how well the interior structures inferred from asteroseismology can be reproduced by standard algorithms. Our qualitative evolutionary paths, position in the logg−T{sub eff} diagram, and model timescales are consistent with previous results. The sdB masses from our full evolutionary sequences fall within the range of the empirical sdB mass distribution, but are nearly always lower than the median. Using standard MLT with atomic diffusion we find convective core masses of ∼0.17–0.18 M{sub ⊙}, averaged over the entire sdB lifetime. We can increase the convective core sizes to be as large as those inferred from asteroseismology, but only for extreme values of the overshoot parameter (overshoot gives numerically unstable and physically unrealistic behavior at the boundary). High resolution three-dimensional simulations of turbulent convection in stars suggest that the Schwarzschild criterion for convective mixing systematically underestimates the actual extent of mixing because a boundary layer forms. Accounting for this would decrease the errors in both sdB total and convective core masses.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Toward ab-initio nuclear theory calculations of 𝛿 𝐶

We propose a theory framework to study the isospin-symmetry breaking correction 𝛿 C in superallowed nuclear 𝛽 decays, crucial for the precise determination of |𝑉 𝑢⁢𝑑 |. Based on a general assumptions of the isovector dominance in isospin-symmetry breaking interactions, we construct a set of functions 𝐹 𝑇 𝑧 which involve nuclear matrix elements of isovector monopole operators and the nuclear Green's function. Via the functions 𝐹 𝑇 𝑧 , a connection of 𝛿 C to measurable electroweak nuclear radii is established, providing an experimental gauge of the theory accuracy of 𝛿 C . Here, we outline a strategy to perform ab initio calculations of 𝐹 𝑇 𝑧 based on the Lanczos algorithm, and discuss its similarity with other nuclear-structure-dependent inputs in nuclear 𝛽 decays.

Ab initio calculations↗
DOE OSTI2020

Grid-based diffusion Monte Carlo for fermions without the fixed-node approximation

A diffusion Monte Carlo algorithm is introduced that can determine the correct nodal structure of the wave function of a few-fermion system and its ground-state energy without an uncontrolled bias. This is achieved by confining signed random walkers to the points of a uniform infinite spatial grid, allowing them to meet and annihilate one another to establish the nodal structure without the fixed-node approximation. An imaginary-time propagator is derived rigorously from a discretized Hamiltonian, governing a non-Gaussian, sign-flipping, branching, and mutually annihilating random walk of particles. The accuracy of the resulting stochastic representations of a fermion wave function is limited only by the grid and imaginary-time resolutions and can be improved in a controlled manner. Here, the method is tested for a series of model problems including fermions in a harmonic trap as well as the He atom in its singlet or triplet ground state. For the latter case, the energies approach from above with increasing grid resolution and converge within 0.015 E h of the exact basis-set-limit value for the grid spacing of 0.08 a.u. with a statistical uncertainty of 10 –5 E h without an importance sampling or Jastrow factor.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Coordinate-based simulation of pair distance distribution functions for small and large molecular assemblies: implementation and applications

X-ray scattering has become a major tool in the structural characterization of nanoscale materials. Thanks to the widely available experimental and computational atomic models, coordinate-based X-ray scattering simulation has played a crucial role in data interpretation in the past two decades. However, simulation of real-space pair distance distribution functions (PDDFs) from small- and wide-angle X-ray scattering, SAXS/WAXS, has been relatively less exploited. This study presents a comparison of PDDF simulation methods, which are applied to molecular structures that range in size from β-cyclodextrin [1 kDa molecular weight (MW), 66 non-hydrogen atoms] to the satellite tobacco mosaic virus capsid (1.1 MDa MW, 81 960 non-hydrogen atoms). The results demonstrate the power of interpretation of experimental SAXS/WAXS from the real-space view, particularly by providing a more intuitive method for understanding of partial structure contributions. Furthermore, the computational efficiency of PDDF simulation algorithms makes them attractive as approaches for the analysis of large nanoscale materials and biological assemblies. The simulation methods demonstrated in this article have been implemented in stand-alone software, SolX 3.0 , which is available to download from https://12idb.xray.aps.anl.gov/solx.html.

Zuo, Xiaobing (ORCID:0000000201344804)↗
DOE OSTI2025

Desmearing two-dimensional small-angle neutron scattering data by central moment expansions

Resolution smearing is a critical challenge in the quantitative analysis of two-dimensional small-angle neutron scattering (SANS) data, particularly in studies of soft-matter flow and deformation using SANS. Here, we present a central moment expansion technique to address smearing in anisotropic scattering spectra, offering a model-free desmearing methodology. By accounting for directional variations in resolution smearing and enhancing computational efficiency, this approach reconstructs desmeared intensity distributions from smeared experimental data. Computational benchmarks using interacting hard-sphere fluids and Gaussian chain models validate the accuracy of the method, while simulated noise analyses confirm its robustness under experimental conditions. Experimental validation using rheological SANS data from shear-induced micellar structures demonstrates the practicality and effectiveness of the proposed algorithm. The desmearing technique provides a powerful tool for advancing the quantitative analysis of anisotropic scattering patterns, enabling precise insights into the interplay between material microstructure and macroscopic flow behavior.

anisotropic scattering spectra↗
DOE OSTI2018

Prescriptive provenance for streaming analysis of workflows at scale

Abstract- We extend our approach capturing and relating the provenance and performance metrics of computational workflows as a diagnostic tool for runtime optimization and placement. One important challenge is the volume of extracted data, both for performance metrics and provenance, even when specifying filters and focusing on quantities of interest in a simulation. We reduce this data by performing anomaly detection on streaming data and store provenance for the detected anomalies, an approach we call prescriptive provenance. This paper discusses the Chimbuko architecture enabling the approach. We present the use of a protein structure propagation workflow based on NWChemEx. We are testing algorithms for anomaly detection and present preliminary results here obtained with Local Outlier Factor. While scaling remains a challenge, these results show that our robust Chimbuko architecture for streaming analysis with prescriptive provenance is a promising approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Distributed Link Removal Using Local Estimation of Network Topology

In this paper, we consider the problem of network structure manipulation in the absence of information on the global network topology. In particular, the problem of removing some of links is investigated in order to slow or stop the spread of disease in a network while preserving its connectivity. Existing methods solve this combinatorial problem in a centralized manner and they require the global information of network structure. In this paper, we propose a distributed design algorithm to compute a suboptimal solution to this problem efficiently by mimicking gradient based method, namely by iteratively removing one or multiple links at a time from the network. Specifically, using matrix perturbation analysis we formulate an optimization problem involving the eigenvector associated with the largest eigenvalue of the adjacency matrix and whose solution is equal to a suboptimal solution to the original problem. This strategy also enables us to overcome the combinatorial issue of the problem. Distributed algorithms to estimate the eigenvector and to verify network’s connectivity are then proposed which facilitate us to solve the new optimization problem. In addition, topological insights into the proposed algorithm and optimality of its solution are also discussed. Lastly, the proposed distributed design method is demonstrated and evaluated via several numerical examples.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Iterative metal artifact reduction for x-ray computed tomography using unmatched projector/backprojector pairs

Purpose: Metal artifact reduction (MAR) is a major problem and a challenging issue in x-ray computed tomography (CT) examinations. Iterative reconstruction from sinograms unaffected by metals shows promising potential in detail recovery. This reconstruction has been the subject of much research in recent years. However, conventional iterative reconstruction methods easily introduce new artifacts around metal implants because of incomplete data reconstruction and inconsistencies in practical data acquisition. Hence, this work aims at developing a method to suppress newly introduced artifacts and improve the image quality around metal implants for the iterative MAR scheme. Methods: The proposed method consists of two steps based on the general iterative MAR framework. An uncorrected image is initially reconstructed, and the corresponding metal trace is obtained. The iterative reconstruction method is then used to reconstruct images from the unaffected sinogram. In the reconstruction step of this work, an iterative strategy utilizing unmatched projector/backprojector pairs is used. A ramp filter is introduced into the back-projection procedure to restrain the inconsistency components in low frequencies and generate more reliable images of the regions around metals. Furthermore, a constrained total variation (TV) minimization model is also incorporated to enhance efficiency. The proposed strategy is implemented based on an iterative FBP and an alternating direction minimization (ADM) scheme, respectively. The developed algorithms are referred to as “iFBP-TV” and “TV-FADM,” respectively. Two projection-completion-based MAR methods and three iterative MAR methods are performed simultaneously for comparison. Results: The proposed method performs reasonably on both simulation and real CT-scanned datasets. This approach could reduce streak metal artifacts effectively and avoid the mentioned effects in the vicinity of the metals. The improvements are evaluated by inspecting regions of interest and by comparing the root-mean-square errors, normalized mean absolute distance, and universal quality index metrics of the images. Both iFBP-TV and TV-FADM methods outperform other counterparts in all cases. Unlike the conventional iterative methods, the proposed strategy utilizing unmatched projector/backprojector pairs shows excellent performance in detail preservation and prevention of the introduction of new artifacts. Conclusions: Qualitative and quantitative evaluations of experimental results indicate that the developed method outperforms classical MAR algorithms in suppressing streak artifacts and preserving the edge structural information of the object. In particular, structures lying close to metals can be gradually recovered because of the reduction of artifacts caused by inconsistency effects.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Structure- and Physics-Preserving Reductions of Power Grid Models

The large size of multiscale, distribution and transmission, power grids hinders fast systemwide estimation and real-time control and optimization of operations. This paper studies graph reduction methods of power grids that are favorable for fast simulations and follow-up applications. While the classical Kron reduction has been successful in reduced order modeling of power grids with traditional, hierarchical design, the selection of reference nodes for the reduced model in a multiscale, distribution and transmission, network becomes ambiguous. In this work we extend the use of the iterative Kron reduction by utilizing the electric grid's graph topology for the selection of reference nodes, consistent with the design features of multiscale networks. Additionally, we propose further reductions by aggregation of coherent subnetworks of triangular meshes, based on the graph topology and network characteristics, in order to preserve currents and build another power-flow equivalent network. Our reductions are achieved through the use of iterative aggregation of subgraphs that include general tree structures, lines, and triangles. Important features of our reduction algorithms include that (i) the reductions are either equivalent to the Kron reduction or otherwise produce a power-flow equivalent network; (ii) due to the mentioned power-flow equivalence, the reduced network can model the dynamic of the swing equations for a lossless, inductive, steady state network; (iii) the algorithms efficiently utilize hash tables to store the sequential reduction steps. The third feature allows for easy reintroduction of detailed models into the reduced, conceptual network and makes the final reduced order model backward compatible with a sequence of intermediate, partially reduced networks with varying resolution---the ordered sequence of iterative reductions corresponds to a sequence of reduced order models. The performance of our graph reduction algorithms and features of the reduced grids are discussed on a real-word transmission and distribution grid. We produce visualizations of the reduced models through open source libraries and release our reduction algorithms with example code and toy data.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

First- and Second-Order Methods for Online Convolutional Dictionary Learning

Convolutional sparse representations are a form of sparse representation with a structured, translation-invariant dictionary. Most convolutional dictionary learning algorithms to date operate in batch mode, requiring simultaneous access to all training images during the learning process, which results in very high memory usage and severely limits the training data size that can be used. Very recently, however, a number of authors have considered the design of online convolutional dictionary learning algorithms that offer far better scaling of memory and computational cost with training set size than batch methods. This study extends our prior work, improving a number of aspects of our previous algorithm; proposing an entirely new one, with better performance, that supports the inclusion of a spatial mask for learning from incomplete data; and providing a rigorous theoretical analysis of these methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

First principles modeling of microscopic scintillation mechanisms using a Many-Body Green’s function approach (Final Report)

In 2010, we started the first lifecycle of a project on first principles modeling of microscopic unit processes that occur during scintillation in order to bring about a capability of formulating physics-based reaction-diffusion models that can predict scintillator light yield and explain their non-proportional response to the energy of incident ionizing radiation, with the hope that this will accelerate materials discovery that can mitigate this problem. During the ensuing years we focused on investigating from first principles the elementary quantum mechanical processes leading to polaron formation and exciton self-trapping in scintillators and identify the microscopic pathways leading to their transport. The effort to derive the master equation for carrier and exciton transport in realistic scintillators materials from first principles constitutes a challenge that requires an extensive background in various areas of computational physics. Previous theoretical investigations involved significant approximations and were limited in their scope. Most notably, the standard workhorse of the computational material scientist, density-functional theory, fails in describing the localized nature of self-trapped carriers as well as the electronic structure of rare-earth dopants. Advances in both algorithms and computational resources however, have rendered a comprehensive and accurate approach feasible. This has been amply demonstrated by the results produced by us during the first lifecycle of this project, which impressed upon the reviewers of the Independent Project Review: “The Review Team agreed, and commented that ’amazing and excellent progress had been made to date.’ The researchers tried and did improve the technology to advance the state of the art and show that it was adequate for the project.” In the following, we detail the progress achieved during each year of the project. We conclude by a final section where all our main achievements are summarized.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Developing a novel hierarchical approach for multiscale structural reliability predictions for ultra-high consequence applications

Microstructural variabilities are among the predominant sources of uncertainty in structural performance and reliability. We seek to develop efficient algorithms for multiscale calcu- lations for polycrystalline alloys such as aluminum alloy 6061-T6 in environments where ductile fracture is the dominant failure mode. Our approach employs concurrent multiscale methods, but does not focus on their development. They are a necessary but not sufficient ingredient to multiscale reliability predictions. We have focused on how to efficiently use concurrent models for forward propagation because practical applications cannot include fine-scale details throughout the problem domain due to exorbitant computational demand. Our approach begins with a low-fidelity prediction at the engineering scale that is sub- sequently refined with multiscale simulation. The results presented in this report focus on plasticity and damage at the meso-scale, efforts to expedite Monte Carlo simulation with mi- crostructural considerations, modeling aspects regarding geometric representation of grains and second-phase particles, and contrasting algorithms for scale coupling.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Group Structure Machine Learning Proposal

Nuclear data is the linchpin underwriting several fundamental capabilities and mission needs at LANL. New techniques such as machine learning can be brought to bear to solve old problems such as multigroup cross-section accuracy. In neutron transport, generating multigroup cross sections is a complex and arcane task, but a crucial one, as accurate solutions require appropriate cross sections. There are two key challenges when generating multigroup cross sections: (1) choosing an accurate weight function, and (2) choosing appropriate energy boundaries. Often, energy boundaries are chosen using “expert judgment” that is not documented and is difficult to replicate. The long-standing Los Alamos 30-group structure has been in use since at least 1969 and is still in use today. Simplistic attempts over the years since to improve on the 30-group structure have been met with limited success. Machine learning algorithms would enable the selection of appropriate, problem-dependent group boundaries without an inordinate investment of scientist time. We will develop workflows and tools to enable these improved group boundary choices, which will reduce uncertainty and increase predictive capability of neutron-transport applications at LANL.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Initializing BSQ with Open-Source ICCING

While it is well known that there is a significant amount of conserved charges in the initial state of nuclear collisions, the production of these due to gluon splitting has yet to be thoroughly investigated. The ICCING (Initial Conserved Charges in Nuclear Geometry) algorithm reconstructs these quark distributions, providing conserved strange, baryon, and electric charges, by sampling a given model for the g → qq¯ splitting function over the initial energy density, which is valid at top collider energies, even when µB = 0. The ICCING algorithm includes fluctuations in the gluon longitudinal momenta, a structure that supports the implementation of dynamical processes, and the c++ version is now open-source. A full analysis of parameter choices on the model has been done to quantify the effect these have on the underlying physics. We find there is a sustained difference across the different charges that indicates sensitivity to hot spot geometry.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Linear optimal power flow system and method

An electric power system or power grid is optimized using a computer-implemented tool the represents in computer memory the optimization function and at least one constraint, which the processor operates upon using a linear programming solver algorithm. The constraints are represented in memory as data structures that include both real and reactive power terms, corresponding to at least one of a power flow model and a transmission line model. The transmission line model is represented using a piecewise linear representation. The power flow model may also include for each node in the power system a real power loss term representing transmission line loss allocated to that node.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Implementation of a generalized coherent elastic scattering formulation for thermal neutron scattering analysis - 14487

The scattering interactions of thermal neutrons in matter are classified into inelastic and elastic components. In crystalline materials, coherent elastic scattering represents a dominant form of interaction. Traditionally, the treatment of this interaction in standard computer codes (e.g., the LEAPR module of the NJOY code system) was performed within the cubic approximation and restricted the analyst to a few materials that were hardwired into the code. In general, these restrictions can hinder the production of ENDF style thermal neutron scattering libraries for new materials outside the current portfolio of treated materials. In this work, a general formulation based on the exact theory of coherent elastic scattering was developed. This formulation is capable of processing the crystalline structure of any material. The cubic approximation is relaxed by accounting for the partial forces from asymmetric crystal structures in the calculation. The atom sites approximation is relaxed by utilizing a site-wise Debye-Waller factor. Specifically, the Debye-Waller factor is no longer regarded as a uniform constant across the crystal but treated as a matrix tensor that uses the integral of the partial phonon density of states. Therefore, the calculation of the coherent elastic scattering cross section is executed by applying the matrix-form of the Debye-Waller factor on each reciprocal space point and summing them up. Furthermore, the developed algorithm supports compounds with any number of elements and of any ratio to each other. This general formulation was successfully implemented and contributed to the production of ENDF style thermal neutron scattering libraries for silicon dioxide (α-SiO{sub 2}) and silicon carbide (3C-SiC). The needed input for the analysis was generated using density functional theory (DFT) atomistic simulations and dynamical matrix calculations for both materials. (authors)

42 ENGINEERING↗
DOE OSTI2016

Coupled cluster Green function: Model involving single and double excitations

In this paper, we report on the development of a parallel implementation of the coupled-cluster (CC) Green function formulation (GFCC) employing single and double excitations in the cluster operator (GFCCSD). A key aspect of this work is the determination of the frequency dependent self-energy, Σ(ω). The detailed description of the underlying algorithm is provided, including approximations used that preserve the pole structure of the full GFCCSD method, thereby reducing the computational costs while maintaining an accurate character of methodology. Furthermore, for systems with strong local correlation, our formulation reveals a diagonally dominate block structure where as the non-local correlation increases, the block size increases proportionally. Here, to demonstrate the accuracy of our approach, several examples including calculations of ionization potentials for benchmark systems are presented and compared against experiment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗