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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Influence Metrics for Value and Utility Functions

Methods are proposed to measure the sensitivity of utility or value function to the variations of attribute values for Multi-Criteria Decision Analyses that are based on functions that cannot be expressed as a weighted sum of the attribute values. These measures, called factor Influence Metrics, can be used to examine the characteristics of the option scoring algorithm and help verify the algorithm is consistent with decision makers value structure and processes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Detailed Modeling of Physical Processes in Electron Sources for Accelerator Applications

At present, electron sources are essential in a wide range of applications – from common technical use to exploring the nature of matter. Depending on the application requirements, different methods and materials are used to generate electrons. State of-the-art accelerator applications set a number of often-contradicting requirements for electron sources (e.g., high quantum efficiency vs. high spin-polarization, high current density vs. long lifetime, etc). Development of advanced electron sources includes modeling and design of cathodes, material growth, fabrication of cathodes, and cathode testing. The detailed simulation and modeling of physical processes are required in order to shed light on the exact mechanisms of electron emission and to develop new-generation electron sources with optimized efficiency. The purpose of the present work is to study physical processes in prominent electron sources and to develop scientific tools that could be used to predict electron emission from novel nano-structured materials. In particular, the Monte Carlo model has been implemented and used to study photoemission from Negative Electron Affinity (NEA) GaAs widely used to provide spin-polarized electron beams for many accelerator facilities, including Thomas Jefferson National Accelerator Facility. According to our best knowledge, this is the first to date scientific tool to simulate the complete from-excitation-to-emission-into-vacuum photoemission of spin-polarized electrons from NEA GaAs based on the details of material band structure. Moreover, an effective image-processing algorithm has been developed and used to study field emission properties of Nitrogen-incorporated UltraNanoCrystalline Diamond ((N)UNCD) films. The algorithm processes large sets of image micrographs representing field emission sites formed on the anode plate and therefore provides significant information about the field emission area and the current density. The field emission model from convenient semiconductors has been modified and used to study the influence of the space-charge region and the electric-field-dependent electron mobility on the field emission characteristics of (N)UNCD field emitters.

Chubenko, Oksana↗
DOE OSTI2026

Quantum Computing Algorithms and Applications for Coherent and Strongly Correlated Chemical Systems

This project advanced quantum algorithms, quantum information theory, strongly correlated electronic structure methods, molecular quantum materials, and exciton transport imaging in coherent condensed phase systems. Across the award period, the team developed new methods for open-quantum-system simulation, Hamiltonian learning, state tomography, reduced-density-matrix and contracted-quantum eigensolver approaches, and quantum diagnostics for device capability and openness.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Alloy identification device

An electrochemical metal alloy identification device employing electrolytes to measure and identify different potentials of alloys is presented. This includes physical structure, disposables, electrical systems, control circuitry, and algorithms to identify alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Towards a Software Development Framework for Interconnected Science Ecosystems

The innovative science of the future must be multi-domain and interconnected to usher in the next generation of “self-driving” laboratories enabling consequential discoveries and transformative inventions. Such a disparate and interconnected ecosystem of scientific instruments will need to evolve using a system-of-systems (SoS) approach. The key to enabling application integration with such an SoS will be the use of Software Development Kits (SDKs). Currently, SDKs facilitate scientific research breakthroughs via algorithmic automation, databases and storage, optimization and structure, pervasive environmental monitoring, among others. However, existing SDKs lack instrument-interoperability and reusability capabilities, do not effectively work in an open federated architectural environment, and are largely isolated within silos of the respective scientific disciplines. Inspired by the scalable SoS framework, this work proposes the development of INTERSECT-SDK to provide a coherent environment for multi-domain scientific applications to benefit from the open federated architecture in an interconnected ecosystem of instruments. This approach will decompose functionality into loosely coupled software services for interoperability among several solutions that do not scale beyond a single domain and/or application. Furthermore, the proposed environment will allow operational and managerial inter-dependence while providing opportunities for the researchers to reuse software components from other domains and build universal solution libraries. We demonstrate this research for microscopy use-case, where we show how INTERSECT-SDK is developing the tools necessary to enable advanced scanning methods and accelerate scientific discovery.

Malviya, Addi Thakur↗
DOE OSTI2024

Get Non-Real: Randomized Sketching for High-Dimensional Non-Real Valued Data (Final Report)

In our final report for DE-C0022186, we describe the work we did on this grant towards the goals we proposed. Our first goal was characterizing fundamental limits for sketching of discrete high-dimensional matrices with low-dimensional structures. Our second main goal was designing algorithms for data reconstruction from sketches. We focus on approaches that are either specifically designed for non-real-valued data (binary, finite field) or that will translate more readily to that setting.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Classical Simulation of Boson Sampling Based on Graph Structure

Boson sampling is a fundamentally and practically important task that can be used to demonstrate quantum supremacy using noisy intermediate-scale quantum devices. In this Letter, we present classical sampling algorithms for single-photon and Gaussian input states that take advantage of a graph structure of a linear-optical circuit. The algorithms’ complexity grows as so-called treewidth, which is closely related to the connectivity of a given linear-optical circuit. Using the algorithms, we study approximated simulations for local Haar-random linear-optical circuits. For equally spaced initial sources, we show that, when the circuit depth is less than the quadratic in the lattice spacing, the efficient simulation is possible with an exponentially small error. Notably, right after this depth, photons start to interfere each other and the algorithms’ complexity becomes subexponential in the number of sources, implying that there is a sharp transition of its complexity. Finally, when a circuit is sufficiently deep enough for photons to typically propagate to all modes, the complexity becomes exponential as generic sampling algorithms. We numerically implement a likelihood test with a recent Gaussian boson sampling experiment and show that the treewidth-based algorithm with a limited treewidth renders a larger likelihood than the experimental data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Partitioned Coupling for Structural Acoustics

Here, we expand the second-order fluid–structure coupling scheme of Farhat et al. (1998, “Load and Motion Transfer Algorithms for 19 Fluid/Structure Interaction Problems With Non-Matching Discrete Interfaces: Momentum and Energy Conservation, Optimal Discretization and Application to Aeroelasticity,” Comput. Methods Appl. Mech. Eng., 157(1–2), pp. 95–114; 2006, “Provably Second-Order Time-Accurate Loosely-Coupled Solution Algorithms for Transient Nonlinear Computational Aeroelasticity,” Comput. Methods Appl. Mech. Eng., 195(17), pp. 1973–2001) to structural acoustics. The staggered structural acoustics solution method is demonstrated to be second-order accurate in time, and numerical results are compared to a monolithically coupled system. The partitioned coupling method is implemented in the Sierra Mechanics software suite, allowing for the loose coupling of time domain acoustics in SIERRA/SD to structural dynamics ( SIERRA/SD ) or solid mechanics ( SIERRA/SD ). The coupling is demonstrated to work for nonconforming meshes. Results are verified for a one-dimensional piston, and the staggered and monolithic results are compared to an exact solution. Huang, H. (1969, “Transient Interaction of Plane Acoustic Waves With a Spherical Elastic Shell,” J. Acoust. Soc. Am., 45(3), pp. 661–670) sphere scattering problem with a spherically spreading acoustic load demonstrates parallel capability on a complex problem. Our numerical results compare well for a bronze plate submerged in water and sinusoidally excited (Fahnline and Shepherd, 2017, “Transient Finite Element/Equivalent Sources Using Direct Coupling and Treating the Acoustic Coupling Matrix as Sparse,” J. Acoust. Soc. Am., 142(2), pp. 1011–1024).

42 ENGINEERING↗
DOE OSTI2019

An adaptive fast multipole method in Cartesian basis, enabled by algorithmic differentiation

A novel form of the fast multipole method is realized by the combination of adaptive data structures with implementation of the multipole expansions and their translations in Cartesian basis, and enabled by algorithmic differentiation. It may be possible to generalize it to any kernel that allows its formulation as a function of small quantities with respect to which they can be expanded. There is no hard and fast rule recipe that works for all cases. However, it is shown how to do it for the softened Coulomb kernel, which is different from the Coulomb kernel. The characteristics and performance of the method are mapped and shown to provide an attractive option for a generic fast multipole algorithm in a wide region of the parameter space. The algorithm is illustrated with a beam dynamics application.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Structural characterization of an intrinsically disordered protein complex using integrated small-angle neutron scattering and computing

Characterizing structural ensembles of intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) of proteins is essential for studying structure–function relationships. Due to the different neutron scattering lengths of hydrogen and deuterium, selective labeling and contrast matching in small-angle neutron scattering (SANS) becomes an effective tool to study dynamic structures of disordered systems. However, experimental timescales typically capture measurements averaged over multiple conformations, leaving complex SANS data for disentanglement. We hereby demonstrate an integrated method to elucidate the structural ensemble of a complex formed by two IDRs. We use data from both full contrast and contrast matching with residue-specific deuterium labeling SANS experiments, microsecond all-atom molecular dynamics (MD) simulations with four molecular mechanics force fields, and an autoencoder-based deep learning (DL) algorithm. From our combined approach, we show that selective deuteration provides additional information that helps characterize structural ensembles. We find that among the four force fields, a99SB-disp and CHARMM36m show the strongest agreement with SANS and NMR experiments. In addition, our DL algorithm not only complements conventional structural analysis methods but also successfully differentiates NMR and MD structures which are indistinguishable on the free energy surface. Finally, we present an ensemble that describes experimental SANS and NMR data better than MD ensembles generated by one single force field and reveal three clusters of distinct conformations. Our results demonstrate a new integrated approach for characterizing structural ensembles of IDPs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Filamentary Dust Polarization and the Morphology of Neutral Hydrogen Structures

Filamentary structures in neutral hydrogen (H$\tiny{I}$) emission are well aligned with the interstellar magnetic field, so H$\tiny{I}$ emission morphology can be used to construct templates that strongly correlate with measurements of polarized thermal dust emission. We explore how the quantification of filament morphology affects this correlation. We introduce a new implementation of the Rolling Hough Transform (RHT) using spherical harmonic convolutions, which enables efficient quantification of filamentary structure on the sphere. We use this Spherical RHT algorithm along with a Hessian-based method to construct H$\tiny{I}$-based polarization templates. We discuss improvements to each algorithm relative to similar implementations in the literature and compare their outputs. By exploring the parameter space of filament morphologies with the Spherical RHT, we find that the most informative H$\tiny{I}$ structures for modeling the magnetic field structure are the thinnest resolved filaments. For this reason, we find a ~10% enhancement in the B-mode correlation with polarized dust emission with higher-resolution H$\tiny{I}$ observations. We demonstrate that certain interstellar morphologies can produce parity-violating signatures, i.e., nonzero TB and EB, even under the assumption that filaments are locally aligned with the magnetic field. Finally, we demonstrate that B modes from interstellar dust filaments are mostly affected by the topology of the filaments with respect to one another and their relative polarized intensities, whereas E modes are mostly sensitive to the shapes of individual filaments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Benders Decomposition Using Graph Modeling and Multi-Parametric Programming

Benders decomposition is a widely used method for solving large and structured optimization problems, but its performance is affected by the repeated solution of subproblems. We propose a flexible and modular algorithmic framework for accelerating Benders decomposition. Specifically, we express the problem structure by using a graph-theoretic modeling abstraction in which nodes represent optimization subproblems and edges represent connectivity between subproblems. A key innovation of our approach is that we embed multiparametric programming (mp) surrogates for node subproblems, which maps the exact analytical map of the subproblem solution space. The use of mp surrogates allows us to replace subproblem solves with fast look-ups and function evaluations for primal and dual variables during the iterative Benders process. We formally show the equivalence between classical Benders cuts and those derived from the mp solution. We implement our framework in the open-source PlasmoBenders.jl software package. To demonstrate the capabilities of the proposed framework, we apply it to a two-stage stochastic programming problem, which aims to make optimal capacity expansion decisions under market uncertainty. We evaluate both single-cut and multicut variants of Benders decomposition and show that the use of mp surrogates achieves substantial speedups in subproblem solve time, while preserving the convergence guarantees of Benders decomposition. We highlight advantages in solution analysis and interpretability that is enabled by mp critical region tracking; specifically, we show that these reveal how decisions evolve geometrically across the Benders search. Our results aim to demonstrate that combining surrogate modeling with graph modeling offers a promising and extensible foundation for structure-exploiting decomposition. In addition, by decomposing the problem into more tractable subproblems, the proposed approach also aims to overcome scalability issues of mp. Finally, the use of mp surrogates provides a unifying and modular optimization framework that enables the representation of heterogeneous node subproblems as modeling objects with a homogeneous structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Computational Search for Strong Topological Insulators: An Exercise in Data Mining and Electronic Structure

In this paper, we report a data-mining investigation for the search of topological insulators by examining individual electronic structures for over 60,000 materials. Using a data-mining algorithm, we survey changes in band inversion with and without spin-orbit coupling by screening the calculated electronic band structure for a small gap and a change concavity at high-symmetry points. Overall, we were able to identify a number of topological candidates with varying structures and composition. Lastly, our overall goal is expand the realm of predictive theory into the determination of new and exotic complex materials through the data mining of electronic structure.

36 MATERIALS SCIENCE↗
DOE OSTI2015

SU-E-T-616: Plan Quality Assessment of Both Treatment Planning System Dose and Measurement-Based 3D Reconstructed Dose in the Patient

Purpose: Systematic radiotherapy plan quality assessment promotes quality improvement. Software tools can perform this analysis by applying site-specific structure dose metrics. The next step is to similarly evaluate the quality of the dose delivery. This study defines metrics for acceptable doses to targets and normal organs for a particular treatment site and scores each plan accordingly. The input can be the TPS or the measurement-based 3D patient dose. From this analysis, one can determine whether the delivered dose distribution to the patient receives a score which is comparable to the TPS plan score, otherwise replanning may be indicated. Methods: Eleven neuroblastoma patient plans were exported from Eclipse to the Quality Reports program. A scoring algorithm defined a score for each normal and target structure based on dose-volume parameters. Each plan was scored by this algorithm and the percentage of total possible points was obtained. Each plan also underwent IMRT QA measurements with a Mapcheck2 or ArcCheck. These measurements were input into the 3DVH program to compute the patient 3D dose distribution which was analyzed using the same scoring algorithm as the TPS plan. Results: The mean quality score for the TPS plans was 75.37% (std dev=14.15%) compared to 71.95% (std dev=13.45%) for the 3DVH dose distribution. For 3/11 plans, the 3DVH-based quality score was higher than the TPS score, by between 0.5 to 8.4 percentage points. Eight/11 plans scores decreased based on IMRT QA measurements by 1.2 to 18.6 points. Conclusion: Software was used to determine the degree to which the plan quality score differed between the TPS and measurement-based dose. Although the delivery score was generally in good agreement with the planned dose score, there were some that improved while there was one plan whose delivered dose quality was significantly less than planned. This methodology helps evaluate both planned and delivered dose quality. Sun Nuclear Corporation has provded a license for the software described.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

The MARS15-based FermiCORD code system for calculation of the accelerator-induced residual dose

The FermiCORD code system, a set of codes based on MARS15 that calculates the accelerator-induced residual doses at experimental facilities of arbitrary configurations, has been developed. FermiCORD is written in C++ as an add-on to Fortran-based MARS15. The FermiCORD algorithm consists of two stages: 1) simulation of residual doses on contact with the surfaces surrounding the studied location and of radionuclide inventories in the structures surrounding those locations using MARS15, and 2) simulation of the emission of the nuclear decay gamma-quanta by the residuals in the activated structures and scoring the prompt doses of these gamma-quanta at arbitrary distances from those structures. The FermiCORD code system has been benchmarked against similar algorithms based on other code systems and showed a good agreement. In conclusion, the code system has been applied for calculation of the residual dose of the target station for the Mu2e experiment and the results have been compared to approximate dosimetric approaches.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Active learning for SNAP interatomic potentials via Bayesian predictive uncertainty

Bayesian inference with a simple Gaussian error model is used to efficiently compute prediction variances for energies, forces, and stresses in the linear SNAP interatomic potential. Here, the prediction variance is shown to have a strong correlation with the absolute error over approximately 24 orders of magnitude. Using this prediction variance, an active learning algorithm is constructed to iteratively train a potential by selecting the structures with the most uncertain properties from a pool of candidate structures. The relative importance of the energy, force, and stress errors in the objective function is shown to have a strong impact upon the trajectory of their respective net error metrics when running the active learning algorithm. Batched training of different batch sizes is also tested against singular structure updates, and it is found that batches can be used to significantly reduce the number of retraining steps required with only minor impact on the active learning trajectory.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Structural hierarchy as a key to complex phase selection in Al-Sm

Investigating the unknown structure of the complex cubic phase, previously observed to crystallize from melt-spun amorphous Al–10 at.% Sm alloy, we determine the structure in full site-occupancy detail, highlighting several critical structural features that govern the far-from-equilibrium phase selection pathway. Using an efficient genetic algorithm combining molecular dynamics, density functional theory, and x-ray diffraction, the structure is clearly identified as body-centered cubic Im¯3m (No. 229) with ~140 atoms per cubic unit cell and a lattice parameter of 1.4 nm. The complex structure is further refined to elucidate the detailed site occupancy, revealing full Sm occupancy on 6b sites and split Sm/Al occupancy on 16f sites. Based on the refined site occupancy associated with the experimentally observed phase, we term this phase ε–Al 60 Sm 11 (bcc), corresponding to the limiting situation when all 16f sites are occupied by Sm. However, it should be recognized that the range of solubility enabled by split occupancy at Sm sites is an important feature in phase selection under experimental conditions, permitting an avenue for transition with little or no chemical partitioning. Our analysis shows that the ε–Al 60 Sm 11 (bcc) exhibits a “3-6-6-1” first-shell packing around Sm centers on 16f sites, the same dominant motif exhibited by the undercooled liquid. Here, the coincident motif supports the notion that liquid/glass ordering at high undercooling may give rise to topological invariants between the noncrystalline and crystalline states that provide kinetic pathways to metastable phases that are not accessible during near-equilibrium processing.

36 MATERIALS SCIENCE↗