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At least 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Split representation of adaptively compressed polarizability operator

The polarizability operator plays a central role in density functional perturbation theory and other perturbative treatment of first principle electronic structure theories. The cost of computing the polarizability operator generally scales as O(Ne4) where Ne is the number of electrons in the system. The recently developed adaptively compressed polarizability operator (ACP) formulation [L. Lin, Z. Xu and L. Ying, Multiscale Model. Simul. 2017] reduces such complexity to O(Ne 3 ) in the context of phonon calculations with a large basis set for the first time, and demonstrates its effectiveness for model problems. In this paper, we improve the performance of the ACP formulation by splitting the polarizability into a near singular component that is statically compressed, and a smooth component that is adaptively compressed. The new split representation maintains the O(Ne 3 ) complexity, and accelerates nearly all components of the ACP formulation, including Chebyshev interpolation of energy levels, iterative solution of Sternheimer equations, and convergence of the Dyson equations. For simulation of real materials, we discuss how to incorporate nonlocal pseudopotentials and finite temperature effects. In this work, we demonstrate the effectiveness of our method using one-dimensional model problem in insulating and metallic regimes, as well as its accuracy for real molecules and solids.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Neural network interatomic potential-driven analysis of phase stability in Ti–V alloys at the atomistic scale

The evolution of the ω phase in titanium–vanadium (Ti–V) alloys is critical for their mechanical properties, particularly in aerospace and biomedical applications. Here, this study employs a Rapid Artificial Neural Network (RANN) potential to model the ω phase evolution at the atomistic level, demonstrating a high degree of consistency with experimental observations, unlike the Modified Embedded Atom Method (MEAM), which fails to capture this phase transformation accurately. RANN simulations replicate key phenomena such as the nucleation of α precipitates at ω/β interfaces and accurate lattice orientations, enhancing our understanding of phase stability and transformation kinetics. The findings affirm that RANN potentials can significantly improve the prediction accuracy of complex material behaviors, offering a powerful tool for designing advanced materials with tailored properties such as solute effect in various stacking fault energies. This approach not only bridges the gap between theoretical predictions and empirical data but also sets a new direction for future research in materials science, emphasizing the integration of machine learning techniques in the development and optimization of new alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2016

West Flank Coso FORGE: 3D Temperature Model

x,y,z data of the 3D temperature model for the West Flank Coso FORGE site. Model grid spacing is 250m. The temperature model for the Coso geothermal field used over 100 geothermal production sized wells and intermediate-depth temperature holes. At the near surface of this model, two boundary temperatures were assumed: (1) areas with surface manifestations, including fumaroles along the northeast striking normal faults and northwest striking dextral faults with the hydrothermal field, a temperature of ~104 deg C was applied to datum at +1066 meters above sea level elevation, and (2) a near-surface temperature at about 10 meters depth, of 20 deg C was applied below the diurnal and annual conductive temperature perturbations. These assumptions were based on heat flow studies conducted at the CVF and for the Mojave Desert. On the edges of the hydrothermal system, a 73 deg C/km temperature gradient contour was established using conductive gradient data from shallow and intermediate-depth temperature holes. This contour was continued to all elevation datums between the 20 deg C surface and -1520 meters below mean sea level. Because the West Flank is outside of the geothermal field footprint, during Phase 1, the three wells inside the FORGE site were incorporated into the preexisting temperature model. To ensure a complete model was built based on all the available data sets, measured bottom-hole temperature gradients in certain wells were downward extrapolated to the next deepest elevation datum (or a maximum of about 25% of the well depth where conductive gradients are evident in the lower portions of the wells). After assuring that the margins of the geothermal field were going to be adequately modelled, the data was contoured using the Kriging method algorithm. Although the extrapolated temperatures and boundary conditions are not rigorous, the calculated temperatures are anticipated to be within ~6 deg C (20 deg F), or one contour interval, of the observed data within the Coso geothermal field. Based on a lack of temperature data west of 74-2TCH, the edges of this model still seem to have an effect on West Flank modeled temperatures.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Advanced Hydropower and PSH Capacity Expansion Modeling (Final Report on HydroWIRES D1 Improvements to Capacity Expansion Modeling)

Hydropower and pumped-storage hydropower (PSH) have played a key role in providing flexible, low-carbon electricity to the U.S. electricity system for over a century. As variable generation (VG) deployment increases the demand for flexible, dispatchable generation, it is important to use all available methods for understanding how hydropower and PSH interfaces with VG in a future low-carbon grid. Capacity expansion models (CEMs) of electricity systems are often used to study future electricity scenarios, but these tools often have difficulty representing site- and technology-details of hydropower and PSH due to limited spatial, temporal, or process resolution. This report demonstrates a set of model advancements to improve hydropower and PSH representations in CEMs and other models that consider hydropower and PSH's role in electricity systems. Model advancements include new data integration to define closed-loop PSH resource availability and cost, along with site-level parameterizations of existing PSH capacity and energy storage specifications. Shifting energy across seasons for both hydropower and PSH is explored to demonstrate the potential value of long-duration storage. New representations of hydropower upgrades offer opportunities to increase dispatchability, add pumps, or independently add capacity or energy depending on what is most valuable. New model structures and data are demonstrated individually and in combination to observe their impact on model results and provide initial insights into what is most important for analysts, electricity system planners, and hydropower decision-makers to consider when assessing future roles of hydropower. Improving flexibility of existing hydropower assets has the potential to reduce CO 2 emissions through complementing VG technologies and/or improve electricity system economics by reducing the need to deploy higher-cost systems. Large-scale energy storage is also shown to provide opportunities for balancing seasonal differences in VG, particularly solar photovoltaics (PV). Initial analysis with a new closed-loop PSH resource and cost dataset also demonstrate the potential for new PSH deployment to offer new grid flexibility opportunities. Future analysis and modeling of hydropower's role in the U.S. and other electricity systems could include methodological improvements based on those discussed here along with sensitivity analysis to better represent current and future potential hydropower and PSH flexibility. Improvements to geospatial and site-level data can further improve the understanding of how hydropower and PSH can be upgraded and operated in response to future electricity system needs. This work lays the groundwork to use advanced planning models to explore the range of roles hydropower and PSH can play in the grid of the future.

13 HYDRO ENERGY↗
DOE OSTI2017

Critical Assessment of Metagenome Interpretation—a benchmark of metagenomics software

Methods for assembly, taxonomic profiling and binning are key to interpreting metagenome data, but a lack of consensus about benchmarking complicates performance assessment. The Critical Assessment of Metagenome Interpretation (CAMI) challenge has engaged the global developer community to benchmark their programs on highly complex and realistic data sets, generated from ~700 newly sequenced microorganisms and ~600 novel viruses and plasmids and representing common experimental setups. Assembly and genome binning programs performed well for species represented by individual genomes but were substantially affected by the presence of related strains. Taxonomic profiling and binning programs were proficient at high taxonomic ranks, with a notable performance decrease below family level. Parameter settings markedly affected performance, underscoring their importance for program reproducibility. The CAMI results highlight current challenges but also provide a roadmap for software selection to answer specific research questions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Machine learning molecular dynamics simulations toward exploration of high-temperature properties of nuclear fuel materials: case study of thorium dioxide

Predicting materials properties of nuclear fuel compounds is a challenging task in materials science. Their thermodynamical behaviors around and above the operational temperature are essential for the design of nuclear reactors. However, they are not easy to measure, because the target temperature range is too high to perform various standard experiments safely and accurately. Moreover, theoretical methods such as first-principles calculations also suffer from the computational limitations in calculating thermodynamical properties due to their high calculation-costs and complicated electronic structures stemming from f-orbital occupations of valence electrons in actinide elements. Here, we demonstrate, for the first time, machine-learning molecular-dynamics to theoretically explore high-temperature thermodynamical properties of a nuclear fuel material, thorium dioxide. The target compound satisfies first-principles calculation accuracy because f-electron occupation coincidentally diminishes and the scheme meets sampling sufficiency because it works at the computational cost of classical molecular-dynamics levels. We prepare a set of training data using first-principles molecular dynamics with small number of atoms, which cannot directly evaluate thermodynamical properties but captures essential atomistic dynamics at the high temperature range. Then, we construct a machine-learning molecular-dynamics potential and carry out large-scale molecular-dynamics calculations. Consequently, we successfully access two kinds of thermodynamic phase transitions, namely the melting and the anomalous λ transition induced by large diffusions of oxygen atoms. Furthermore, we quantitatively reproduce various experimental data in the best agreement manner by selecting a density functional scheme known as SCAN. Our results suggest that the present scale-up simulation-scheme using machine-learning techniques opens up a new pathway on theoretical studies of not only nuclear fuel compounds, but also a variety of similar materials that contain both heavy and light elements, like thorium dioxide.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2018

Search for gamma-ray emission from Galactic novae with the Fermi -LAT

Context. A number of novae have been found to emit high-energy gamma rays (>100 MeV). However, the origin of this emission is not yet understood. We report on the search for gamma-ray emission from 75 optically detected Galactic novae in the first 7.4 years of operation of the Fermi Large Area Telescope using the Pass 8 data set. Aims. We compile an optical nova catalog including light curves from various resources and estimate the optical peak time and optical peak magnitude in order to search for gamma-ray emission to determine whether all novae are gamma-ray emitters. Methods. We repeated the analysis of the six novae previously identified as gamma-ray sources and developed a unified analysis strategy that we then applied to all novae in our catalog. We searched for emission in a 15 day time window in two-day steps ranging from 20 days before to 20 days after the optical peak time. We performed a population study with Monte Carlo simulations to set constraints on the properties of the gamma-ray emission of novae. Results. Two new novae candidates have been found at ~ 2σ global significance. Although these two novae candidates were not detected at a significant level individually, taking them together with the other non-detected novae, we found a sub-threshold nova population with a cumulative 3σ significance. We report the measured gamma-ray flux for detected sources and flux upper limits for novae without significant detection. Lastly, our results can be reproduced by several gamma-ray emissivity models (e.g., a power-law distribution with a slope of 2), while a constant emissivity model (i.e., assuming novae are standard candles) can be rejected.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

A theoretical study on 2-amino-5-nitroprydinium trifluoroaceta

The geometry optimization of 2-amino-5-nitroprydinium trifluoroacetate molecule was carried out by using Becke’s three-parameter exchange functional in conjunction with the Lee-Yang-Parr correlation functional (B3LYP) level of density functional theory (DFT) and 6-311++G(d,p) basis set at GAUSSIAN 09 program. The vibration spectrum of the title compound was simulated to predict the presence of functional groups and their vibrational modes. The highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energies were calculated at the same level, and the obtained small energy gap shows that charge transfer occurs in the title compound. The molecular dipole moment, polarizability and hyperpolarizability parameters were determined to evaluate nonlinear optical efficiency of the title compound. Finally, the {sup 13}C and {sup 1}H Nuclear Magnetic Resonance (NMR) chemical shift values were calculated by the application of the gauge independent atomic orbital (GIAO) method. All of the calculations were carried out by using GAUSSIAN 09 program.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Direct Reading Particle Counters: Calibration Verification and Multiple Instrument Agreement via Bump Testing

We examined the calibration records of two direct reading instruments designated as condensation particle counters in order to determine the number of times they were found to be out of tolerance at annual manufacturer's recalibration. For both instruments were found to be out of tolerance more times than within tolerance. And, it was concluded that annual calibration alone was insufficient to provide operational confidence in an instrument's response. Thus, a method based on subsequent agreement with data gathered from a newly calibrated instrument was developed to confirm operational readiness between annual calibrations, hereafter referred to as bump testing. The method consists of measuring source particles produced by a gas grille spark igniter in a gallon-size jar. Sampling from this chamber with a newly calibrated instrument to determine the calibrated response over the particle concentration range of interest serves as a reference. Agreement between this reference response and subsequent responses at later dates implies that the instrument is performing as it was at the time of calibration. Side-by-side sampling allows the level of agreement between two or more instruments to be determined. This is useful when simultaneously collected data are compared for differences, i.e., background with process aerosol concentrations. A reference set of data was obtained using the spark igniter. The generation system was found to be reproducible and suitable to form the basis of calibration verification. Finally, the bump test is simple enough to be performed periodically throughout the calibration year or prior to field monitoring.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

A study on the statistical significance of mutual information between morphology of a galaxy and its large-scale environment

ABSTRACT A non-zero mutual information between morphology of a galaxy and its large-scale environment is known to exist in Sloan Digital Sky Survey (SDSS) upto a few tens of Mpc. It is important to test the statistical significance of these mutual information if any. We propose three different methods to test the statistical significance of these non-zero mutual information and apply them to SDSS and Millennium run simulation. We randomize the morphological information of SDSS galaxies without affecting their spatial distribution and compare the mutual information in the original and randomized data sets. We also divide the galaxy distribution into smaller subcubes and randomly shuffle them many times keeping the morphological information of galaxies intact. We compare the mutual information in the original SDSS data and its shuffled realizations for different shuffling lengths. Using a t-test, we find that a small but statistically significant (at $99.9{{\ \rm per\ cent}}$ confidence level) mutual information between morphology and environment exists upto the entire length-scale probed. We also conduct another experiment using mock data sets from a semi-analytic galaxy catalogue where we assign morphology to galaxies in a controlled manner based on the density at their locations. The experiment clearly demonstrates that mutual information can effectively capture the physical correlations between morphology and environment. Our analysis suggests that physical association between morphology and environment may extend to much larger length-scales than currently believed, and the information theoretic framework presented here can serve as a sensitive and useful probe of the assembly bias and large-scale environmental dependence of galaxy properties.

Sarkar, Suman↗
DOE OSTI2020

Lighting Control in Patient Rooms: Understanding Nurses’ Perceptions of Hospital Lighting Using Qualitative Methods

Here, this study differs in its methodological approach from previously published research by interpreting qualitative results against existing literature to understand how nurses conceptualize medical–surgical patient rooms as productive settings in relation to lighting, as well as the ways in which nurses believe these spaces could be enhanced for patient satisfaction. Content analysis was used to interpret themes emerging from nurses’ subjective responses to open-ended items. Three of the facilities had older, traditional lighting systems; one had a contemporary framework. A theme of environmental control over both overhead and task lighting emerged from data from all items. Although controllability was among the “best” lighting attributes, more refinement is necessary for optimal staff productivity and patient satisfaction. Daylighting was also considered to be among the best attributes. Control over light level via additional dimming capability for patients, as well as additional light sources, was prominent across the four hospitals. Unique to the more modern facility, trespassing of light was problematic for nurses considering the experiences of patients—even where modern models exist, more attention can be paid to the ways in which window shades, and light sources outside of rooms, penetrate spaces and affect users. Finally, the finding that nurses and patients desire greater control over the lighting in patient rooms is consistent with Ulrich’s theory of supportive design for healthcare and coincides with advances in lighting technology. Despite differences in the level of sophistication in lighting among the four facilities, control continues to be a primary concern for nurses.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Convergent Protocols for Computing Protein–Ligand Interaction Energies Using Fragment-Based Quantum Chemistry

Fragment-based quantum chemistry methods offer a way to sidestep the steep nonlinear scaling of electronic structure calculations so that large molecular systems can be investigated using high-level methods. Here, we use fragmentation to compute protein–ligand interaction energies in systems with several thousand atoms, using a new software platform for managing fragment-based calculations that implements a screened many-body expansion. Convergence tests using a minimal-basis semiempirical method (HF-3c) indicate that two-body calculations, with single-residue fragments and simple hydrogen caps, are sufficient to reproduce interaction energies obtained using conventional supramolecular electronic structure calculations, to within 1 kcal/mol at about 1% of the computational cost. We also demonstrate that the HF-3c results are illustrative of trends obtained with density functional theory in basis sets up to augmented quadruple-ζ quality. Strategic deployment of fragmentation facilitates the use of converged biomolecular model systems alongside high-quality electronic structure methods and basis sets, bringing ab initio quantum chemistry to systems of hitherto unimaginable size. This will be useful for generation of high-quality training data for machine learning applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Ensembles of novelty detection classifiers for structural health monitoring using guided waves

Guided wave structural health monitoring uses sparse sensor networks embedded in sophisticated structures for defect detection and characterization. The biggest challenge of those sensor networks is developing robust techniques for reliable damage detection under changing environmental and operating conditions. To address this challenge, we develop a novelty classifier for damage detection based on one class support vector machines. We identify appropriate features for damage detection and introduce a feature aggregation method which quadratically increases the number of available training observations.We adopt a two-level voting scheme by using an ensemble of classifiers and predictions. Each classifier is trained on a different segment of the guided wave signal, and each classifier makes an ensemble of predictions based on a single observation. Using this approach, the classifier can be trained using a small number of baseline signals. We study the performance using monte-carlo simulations of an analytical model and data from impact damage experiments on a glass fiber composite plate.We also demonstrate the classifier performance using two types of baseline signals: fixed and rolling baseline training set. The former requires prior knowledge of baseline signals from all environmental and operating conditions, while the latter does not and leverages the fact that environmental and operating conditions vary slowly over time and can be modeled as a Gaussian process.

Dib, Gerges (ORCID:0000000255004047)↗
DOE OSTI2013

Rocky flats closure project - lessons learned in worker stakeholder engagement

The Rocky Flats Environmental Technology Site (EPA Superfund site near Denver, Colorado) produced plutonium components for nuclear weapons for the U.S. defense program. The facility shut down in 1989 and clean up began in 1992. To ensure safe remediation of inactive nuclear sites, site owners have begun to consult stakeholders more widely in recent years. The closure of Rocky Flats aimed to set the standard for stakeholder involvement in doing the work safely, complying with regulations/standards, in a cost-effective manner. We have studied, using ethnographic methods, the extent to which workers at Rocky Flats were involved in communication and decision making strategies. Our results point out that workers can have perceptions of the site remediation process that differ from management and even other workers and that a significant number of workers questioned the commitment by management to engage the worker as stakeholder. The most effective remediation efforts should involve careful consideration of the insights and observations of all workers, particularly those who face immediate and high-level health and safety risks. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2013

Technology Development Life Cycle Processes

This report and set of appendices are a collection of memoranda originally drafted in 2009 for the purpose of providing motivation and the necessary background material to support the definition and integration of engineering and management processes related to technology development. At the time there was interest and support to move from Capability Maturity Model Integration (CMMI) Level One (ad hoc processes) to Level Three. As presented herein, the material begins with a survey of open literature perspectives on technology development life cycles, including published data on “what went wrong.” The main thrust of the material presents a rational exposé of a structured technology development life cycle that uses the scientific method as a framework, with further rigor added from adapting relevant portions of the systems engineering process. The material concludes with a discussion on the use of multiple measures to assess technology maturity, including consideration of the viewpoint of potential users.

Beck, David Franklin↗
DOE OSTI2025

A Gigaparsec-scale Hydrodynamic Volume Reconstructed with Deep Learning

The next generation of spectroscopic surveys will map the large-scale structure of the Universe at high redshifts (2 ≤ z ≤ 5) using millions of quasar spectra, enabling major advances in constraining both the standard cosmological model and its extensions. Robust cosmological analyses of these data sets require numerical simulations that both cover gigaparsec volumes and resolve features on ∼10 kpc scales and smaller. However, running such large-volume, high-resolution hydrodynamic simulations is computationally prohibitive. We present a generative deep learning model that enhances a low-resolution, gigaparsec-scale (960 h −1 Mpc) hydrodynamic simulation using a smaller (80 h −1 Mpc) high-resolution input hydrodynamic simulation as training data. The resulting enhanced simulation reproduces the line-of-sight power spectrum to within ∼10% and the three-dimensional power spectrum at the ∼20% level at intermediate to small scales (k ≲ 2 h Mpc −1 ). Our method shows strong promise for producing realistic simulations for cosmological analyses with current surveys such as the Dark Energy Spectroscopic Instrument and upcoming next-generation experiments, but further improvements are needed to accurately recover the large-scale modes. We publicly release the enhanced hydrodynamic simulation, along with a halo catalog from a companion N-body dark matter simulation to support the calibration of data analysis pipelines for these large-scale surveys.

Convolutional neural networks↗
DOE OSTI2016

WISE PHOTOMETRY FOR 400 MILLION SDSS SOURCES

We present photometry of images from the Wide-Field Infrared Survey Explorer (WISE) of over 400 million sources detected by the Sloan Digital Sky Survey (SDSS). We use a “forced photometry” technique, using measured SDSS source positions, star–galaxy classification, and galaxy profiles to define the sources whose fluxes are to be measured in the WISE images. We perform photometry with The Tractor image modeling code, working on our “unWISE” coaddds and taking account of the WISE point-spread function and a noise model. The result is a measurement of the flux of each SDSS source in each WISE band. Many sources have little flux in the WISE bands, so often the measurements we report are consistent with zero given our uncertainties. However, for many sources we get 3σ or 4σ measurements; these sources would not be reported by the “official” WISE pipeline and will not appear in the WISE catalog, yet they can be highly informative for some scientific questions. In addition, these small-signal measurements can be used in stacking analyses at the catalog level. The forced photometry approach has the advantage that we measure a consistent set of sources between SDSS and WISE, taking advantage of the resolution and depth of the SDSS images to interpret the WISE images; objects that are resolved in SDSS but blended together in WISE still have accurate measurements in our photometry. Our results, and the code used to produce them, are publicly available at http://unwise.me.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Nonparametric test of consistency between cosmological models and multiband CMB measurements

We present a novel approach to test the consistency of the cosmological models with multiband CMB data using a nonparametric approach. In our analysis we calibrate the REACT (Risk Estimation and Adaptation after Coordinate Transformation) confidence levels associated with distances in function space (confidence distances) based on the Monte Carlo simulations in order to test the consistency of an assumed cosmological model with observation. To show the applicability of our algorithm, we confront Planck 2013 temperature data with concordance model of cosmology considering two different Planck spectra combination. In order to have an accurate quantitative statistical measure to compare between the data and the theoretical expectations, we calibrate REACT confidence distances and perform a bias control using many realizations of the data. Our results in this work using Planck 2013 temperature data put the best fit ΛCDM model at 95% (∼ 2σ) confidence distance from the center of the nonparametric confidence set while repeating the analysis excluding the Planck 217 × 217 GHz spectrum data, the best fit ΛCDM model shifts to 70% (∼ 1σ) confidence distance. The most prominent features in the data deviating from the best fit ΛCDM model seems to be at low multipoles 18 < ℓ < 26 at greater than 2σ, ℓ ∼ 750 at ∼1 to 2σ and ℓ ∼ 1800 at greater than 2σ level. Excluding the 217×217 GHz spectrum the feature at ℓ ∼ 1800 becomes substantially less significance at ∼1 to 2σ confidence level. Results of our analysis based on the new approach we propose in this work are in agreement with other analysis done using alternative methods.

79 ASTRONOMY AND ASTROPHYSICS↗