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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Study of optical Laue diffraction

We present the study of the optical diffraction pattern of one and two-dimensional gratings with defects, designed using desktop pc and printed on OHP sheet using laser printer. Gratings so prepared, using novel low cost technique provides good visual aid in teaching. Diffraction pattern of the monochromatic light (632.8nm) from the grating so designed is similar to that of x-ray diffraction pattern of crystal lattice with point defects in one and two-dimensions. Here both optical and x-ray diffractions are Fraunhofer. The information about the crystalline lattice structure and the defect size can be known.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Laboratory earthquake forecasting: A machine learning competition

Earthquake prediction, the long-sought holy grail of earthquake science, continues to confound Earth scientists. Could we make advances by crowdsourcing, drawing from the vast knowledge and creativity of the machine learning (ML) community? We used Google’s ML competition platform, Kaggle, to engage the worldwide ML community with a competition to develop and improve data analysis approaches on a forecasting problem that uses laboratory earthquake data. The competitors were tasked with predicting the time remaining before the next earthquake of successive laboratory quake events, based on only a small portion of the laboratory seismic data. The more than 4,500 participating teams created and shared more than 400 computer programs in openly accessible notebooks. Complementing the now well-known features of seismic data that map to fault criticality in the laboratory, the winning teams employed unexpected strategies based on rescaling failure times as a fraction of the seismic cycle and comparing input distribution of training and testing data. In addition to yielding scientific insights into fault processes in the laboratory and their relation with the evolution of the statistical properties of the associated seismic data, the competition serves as a pedagogical tool for teaching ML in geophysics. The approach may provide a model for other competitions in geosciences or other domains of study to help engage the ML community on problems of significance.

58 GEOSCIENCES↗
DOE OSTI2023

Learning to learn by using nonequilibrium training protocols for adaptable materials

Evolution in time-varying environments naturally leads to adaptable biological systems that can easily switch functionalities. Advances in the synthesis of environmentally responsive materials therefore open up the possibility of creating a wide range of synthetic materials which can also be trained for adaptability. We consider high-dimensional inverse problems for materials where any particular functionality can be realized by numerous equivalent choices of design parameters. By periodically switching targets in a given design algorithm, we can teach a material to perform incompatible functionalities with minimal changes in design parameters. We exhibit this learning strategy for adaptability in two simulated settings: elastic networks that are designed to switch deformation modes with minimal bond changes and heteropolymers whose folding pathway selections are controlled by a minimal set of monomer affinities. The resulting designs can reveal physical principles, such as nucleation-controlled folding, that enable such adaptability.

Science & Technology - Other Topics↗
DOE OSTI2013

THE PULSAR SEARCH COLLABORATORY: DISCOVERY AND TIMING OF FIVE NEW PULSARS

We present the discovery and timing solutions of five new pulsars by students involved in the Pulsar Search Collaboratory, a NSF-funded joint program between the National Radio Astronomy Observatory and West Virginia University designed to excite and engage high-school students in Science, Technology, Engineering, and Mathematics (STEM) and related fields. We encourage students to pursue STEM fields by apprenticing them within a professional scientific community doing cutting edge research, specifically by teaching them to search for pulsars. The students are analyzing 300 hr of drift-scan survey data taken with the Green Bank Telescope at 350 MHz. These data cover 2876 deg{sup 2} of the sky. Over the course of five years, more than 700 students have inspected diagnostic plots through a web-based graphical interface designed for this project. The five pulsars discovered in the data have spin periods ranging from 3.1 ms to 4.8 s. Among the new discoveries are PSR J1926-1314, a long period, nulling pulsar; PSR J1821+0155, an isolated, partially recycled 33 ms pulsar; and PSR J1400-1438, a millisecond pulsar in a 9.5 day orbit whose companion is likely a white dwarf star.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

DOUBLE COMPACT OBJECTS. III. GRAVITATIONAL-WAVE DETECTION RATES

The unprecedented range of second-generation gravitational-wave (GW) observatories calls for refining the predictions of potential sources and detection rates. The coalescence of double compact objects (DCOs)—i.e., neutron star–neutron star (NS–NS), black hole–neutron star (BH–NS), and black hole–black hole (BH–BH) binary systems—is the most promising source of GWs for these detectors. We compute detection rates of coalescing DCOs in second-generation GW detectors using the latest models for their cosmological evolution, and implementing inspiral-merger-ringdown gravitational waveform models in our signal-to-noise ratio calculations. We find that (1) the inclusion of the merger/ringdown portion of the signal does not significantly affect rates for NS–NS and BH–NS systems, but it boosts rates by a factor of ∼1.5 for BH–BH systems; (2) in almost all of our models BH–BH systems yield by far the largest rates, followed by NS–NS and BH–NS systems, respectively; and (3) a majority of the detectable BH–BH systems were formed in the early universe in low-metallicity environments. We make predictions for the distributions of detected binaries and discuss what the first GW detections will teach us about the astrophysics underlying binary formation and evolution.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Applications of emulation and Bayesian methods in heavy-ion physics

Abstract Heavy-ion collisions provide a window into the properties of many-body systems of deconfined quarks and gluons. Understanding the collective properties of quarks and gluons is possible by comparing models of heavy-ion collisions to measurements of the distribution of particles produced at the end of the collisions. These model-to-data comparisons are extremely challenging, however, because of the complexity of the models, the large amount of experimental data, and their uncertainties. Bayesian inference provides a rigorous statistical framework to constrain the properties of nuclear matter by systematically comparing models and measurements. This review covers model emulation and Bayesian methods as applied to model-to-data comparisons in heavy-ion collisions. Replacing the model outputs (observables) with Gaussian process emulators is key to the Bayesian approach currently used in the field, and both current uses of emulators and related recent developments are reviewed. The general principles of Bayesian inference are then discussed along with other Bayesian methods, followed by a systematic comparison of seven recent Bayesian analyses that studied quark-gluon plasma properties, such as the shear and bulk viscosities. The latter comparison is used to illustrate sources of differences in analyses, and what it can teach us for future studies.

Paquet, Jean-François (ORCID:0000000187368171)↗
DOE OSTI2016

Goldilocks models of higher-dimensional inflation (including modulus stabilization)

We explore the mechanics of inflation within simplified extra-dimensional models involving an inflaton interacting with the Einstein-Maxwell system in two extra dimensions. The models are Goldilocks-like inasmuch as they are just complicated enough to include a mechanism to stabilize the extra-dimensional size (or modulus), yet simple enough to solve explicitly the full extra-dimensional field equations using only simple tools. The solutions are not restricted to the effective 4D regime with H || m {sub KK} (the latter referring to the characteristic mass splitting of the Kaluza-Klein excitations) because the full extra-dimensional Einstein equations are solved. This allows an exploration of inflationary physics in a controlled calculational regime away from the usual four-dimensional lamp-post. The inclusion of modulus stabilization is important because experience with string models teaches that this is usually what makes models fail: stabilization energies easily dominate the shallow potentials required by slow roll and so open up directions to evolve that are steeper than those of the putative inflationary direction. We explore (numerically and analytically) three representative kinds of inflationary scenarios within this simple setup. In one the radion is trapped in an inflaton-dependent local minimum whose non-zero energy drives inflation. Inflation ends as this energy relaxes to zero when the inflaton finds its own minimum. The other two involve power-law scaling solutions during inflation. One of these is a dynamical attractor whose features are relatively insensitive to initial conditions but whose slow-roll parameters cannot be arbitrarily small; the other is not an attractor but can roll much more slowly, until eventually transitioning to the attractor. The scaling solutions can satisfy H > m {sub KK}, but when they do standard 4D fluctuation calculations need not apply. When in a 4D regime the solutions predict η ≅ 0 and so r ≅ 0.11 when n {sub s} ≅ 0.96 and so are ruled out if tensor modes remain unseen. Assessment of general parameters is difficult until a full 6D fluctuation calculation is done.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Sterile neutrinos and flavor ratios in IceCube

The flavor composition of astrophysical neutrinos observed in neutrino telescopes is a powerful discriminator between different astrophysical neutrino production mechanisms and can also teach us about the particle physics properties of neutrinos. In this paper, we investigate how the possible existence of light sterile neutrinos can affect these flavor ratios. We consider two scenarios: (i) neutrino production in conventional astrophysical sources, followed by partial oscillation into sterile states; (ii) neutrinos from dark matter decay with a primary flavor composition enhanced in tau neutrinos or sterile neutrinos. Throughout the paper, we constrain the sterile neutrino mixing parameters from a full global fit to short and long baseline data. We present our results in the form of flavor triangles and, for scenario (ii), as exclusion limits on the dark matter mass and lifetime, derived from a fit to IceCube high energy starting events and through-going muons. We argue that identifying a possible flux of neutrinos from dark matter decay may require analyzing the flavor composition as a function of neutrino energy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Analytical general solutions for static wormholes in f ( R , T ) gravity

Originally proposed as a tool for teaching the general theory of relativity, wormholes are today approached in many different ways and are seeing as an efficient alternative for interstellar and time travel. Attempts to achieve observational signatures of wormholes have been growing as the subject has become more and more popular. In this article we investigate some f ( R , T ) theoretical predictions for static wormholes, i.e., wormholes whose throat radius can be considered a constant. Since the T -dependence in f ( R , T ) gravity is due to the consideration of quantum effects, a further investigation of wormholes in such a theory is well motivated. We obtain the energy conditions of static wormholes in f ( R , T ) gravity and apply an analytical approach to find their physical and geometrical solutions. We highlight that our results are in agreement with previous solutions and assumptions presented in the literature.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Breaking the silos: The art documentation suite

The art event-processing framework is used by almost all new experiments at Fermilab, and by several outside of Fermilab. All use art as an external product in the same sense that the compiler, ROOT, Geant4, CLHEP and boost are external products. The art team has embarked on a campaign to document art and develop training materials for new users. Many new users of art have little or no knowledge of C++, software engineering, build systems or the many external packages used by art or their experiments, such as ROOT, CLHEP, HEPPDT, and boost. To effectively teach art requires that the training materials include appropriate introductions to these topics as they are encountered. Experience has shown that simply referring readers to the existing native documentation does not work, too often a simple idea that they need to understand is described in a context that presumes prerequisites that are unimportant for a beginning user of art. There is the additional complication that the training materials must be presented in a way that does not presume knowledge of any of the experiments using art. Finally, new users of art arrive at random times throughout the year and the training materials must allow them to start to learn art at any time. This presentation will explain the strategies adopted by the art team to develop a documentation suite that complies with these boundary conditions. It will also show the present status of the documentation suite, including feedback the art team has received from pilot users.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

The CMS data analysis school experience

The CMS Data Analysis School is an official event organized by the CMS Collaboration to teach students and post-docs how to perform a physics analysis. The school is coordinated by the CMS schools committee and was first implemented at the LHC Physics Center at Fermilab in 2010. As part of the training, there are a number of “short” exercises on physics object reconstruction and identification, Monte Carlo simulation, and statistical analysis, which are followed by “long” exercises based on physics analyses. Some of the long exercises go beyond the current state of the art of the corresponding CMS analyses. This paper describes the goals of the school, the preparations for a school, the structure of the training, and student satisfaction with the experience as measured by surveys.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Careers at National Laboratories

It’s common for math majors and professors to be aware of possible careers outside of teaching, especially jobs like data science, finance, actuarial science, and some government agencies. But from my experience talking with undergraduates, graduate students, and professors in mathematics, careers at national laboratories are not as well-known. It’s my goal in this article to give you some background and history of the national lab system, a glimpse into the work mathematicians do, and finally some insight into getting a job at a national lab.

career development, recruitment↗
DOE OSTI2014

RCSB PDB Mobile : iOS and Android mobile apps to provide data access and visualization to the RCSB Protein Data Bank

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) resource provides tools for query, analysis and visualization of the 3D structures in the PDB archive. As the mobile Web is starting to surpass desktop and laptop usage, scientists and educators are beginning to integrate mobile devices into their research and teaching. In response, we have developed the RCSB PDB Mobile app for the iOS and Android mobile platforms to enable fast and convenient access to RCSB PDB data and services. Lastly, using the app, users from the general public to expert researchers can quickly search and visualize biomolecules, and add personal annotations via the RCSB PDB's integrated MyPDB service.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Gas metallicity distributions in SDSS-IV MaNGA galaxies: what drives gradients and local trends?

ABSTRACT The gas metallicity distributions across individual galaxies and across galaxy samples can teach us much about how galaxies evolve. Massive galaxies typically possess negative metallicity gradients, and mass and metallicity are tightly correlated on local scales over a wide range of galaxy masses; however, the precise origins of such trends remain elusive. Here, we employ data from SDSS-IV MaNGA to explore how gas metallicity depends on the local stellar mass density and on galactocentric radius within individual galaxies. We also consider how the strengths of these dependencies vary across the galaxy mass-size plane. We find that radius is more predictive of local metallicity than stellar mass density in extended lower-mass galaxies, while we find density and radius to be almost equally predictive in higher-mass and more compact galaxies. Consistent with previous work, we find a mild connection between metallicity gradients and large-scale environment; however, this is insufficient to explain variations in gas metallicity behaviour across the mass-size plane. We argue our results to be consistent with a scenario in which extended galaxies have experienced smooth gas accretion histories, producing negative metallicity gradients over time. We further argue that more compact and more massive systems have experienced increased merging activity that disrupts this process, leading to flatter metallicity gradients and more dominant density-metallicity correlations within individual galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Plant Metabolic Network 16: expansion of underrepresented plant groups and experimentally supported enzyme data

Abstract The Plant Metabolic Network (PMN) is a free online database of plant metabolism available at https://plantcyc.org. The latest release, PMN 16, provides metabolic databases representing >1200 metabolic pathways, 1.3 million enzymes, >8000 metabolites, >10 000 reactions and >15 000 citations for 155 plant and green algal genomes, as well as a pan-plant reference database called PlantCyc. This release contains 29 additional genomes compared with PMN 15, including species listed by the African Orphan Crop Consortium and nonflowering plant species. Furthermore, 52 new enzymes with experimentally supported function information have been included in this release. The single-species databases contain a combination of experimental information from the literature and computationally predicted information obtained through PMN’s database generation pipeline for a single species, while PlantCyc contains only experimental information but for any species within Viridiplantae. PMN is a comprehensive resource for querying, visualizing, analyzing and interpreting omics data with metabolic knowledge. It also serves as a useful and interactive tool for teaching plant metabolism.

Hawkins, Charles (ORCID:0000000312849047)↗
DOE OSTI2013

IMG 4 version of the integrated microbial genomes comparative analysis system

The Integrated Microbial Genomes (IMG) data warehouse integrates genomes from all three domains of life, as well as plasmids, viruses and genome fragments. IMG provides tools for analyzing and reviewing the structural and functional annotations of genomes in a comparative context. IMG’s data content and analytical capabilities have increased continuously since its first version released in 2005. Since the last report published in the 2012 NAR Database Issue, IMG’s annotation and data integration pipelines have evolved while new tools have been added for recording and analyzing single cell genomes, RNA Seq and biosynthetic cluster data. Finally, different IMG datamarts provide support for the analysis of publicly available genomes (IMG/W: http://img.jgi.doe.gov/w), expert review of genome annotations (IMG/ER: http://img.jgi.doe.gov/er) and teaching and training in the area of microbial genome analysis (IMG/EDU: http://img.jgi.doe.gov/edu).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Metabolic Changes Underlying Interactions Between Obesity and Non‐Alcoholic Fatty Liver Disease in South Asian Adults

Non‐alcoholic fatty liver disease (NAFLD) is often referred to as the hepatic manifestation of the metabolic syndrome, which is characterized by at least three of the following: hypertension, hyperglycemia, abdominal obesity, elevated plasma triglycerides and reduced plasma high‐density lipoproteins. While hepatic steatosis has been well studied in animal models, the relationship between body weight, hepatic steatosis and insulin resistance is not well characterized in humans. Moreover, not all human subjects with obesity develop metabolic complications. In addition, it is unclear why South Asian adults develop insulin resistance and diabetes even at lower levels of adiposity and body mass index compared to their Western counterparts. To address this question, we used a convenient sample of Sri Lankan adult females (n = 30) who underwent routine abdominal surgery at the Teaching Hospital of Peradeniya. Anthropometric data, adipose tissue specimens and fasted serum samples were collected for analyses of glucose, lipid and inflammatory markers. Histological sections of adipose tissue were obtained from omental fat (OF) and anterior abdominal wall fat (AF), and adipocyte cross‐sectional area was measured using the ImageJ software. Further, the presence of hepatic steatosis was assessed using ultrasound scanning by a radiologist. Participants with higher grade of fatty liver had a significantly higher body mass index (BMI), fasting blood glucose and aspartate aminotransferase levels. Additionally, participants with higher grade of fatty liver also had significantly higher serum levels of non‐HDL cholesterol and the pro‐inflammatory adipokine, resistin. Interestingly, there were no significant differences in serum adiponectin levels between the groups. Individuals with fatty liver also had a higher mean adipocyte area in both OF and AF, indicating a higher degree of adipocyte hypertrophy associated with fatty liver. Currently, the measurements of additional biomarkers of inflammation and insulin resistance are underway. These findings indicate distinct metabolic differences between South Asian adults with varying degrees of fatty liver, and may help in establishing effective treatment strategies for obesity‐associated NAFLD. Support or Funding Information Funded by an International Research/Development Seed grant from the Office of International Affairs and the Office of the Vice President for Research at Texas Tech university (TTU), and an International Research Seed Grant from The College of Human Sciences at TTU, and by the International Research Center, University of Peradeniya.

Albracht‐Schulte, Kembra↗
DOE OSTI2017

Discovering phases, phase transitions, and crossovers through unsupervised machine learning: A critical examination

Here, we apply unsupervised machine learning techniques, mainly principal component analysis (PCA), to compare and contrast the phase behavior and phase transitions in several classical spin models - the square and triangular-lattice Ising models, the Blume-Capel model, a highly degenerate biquadratic-exchange spin-one Ising (BSI) model, and the 2D XY model, and examine critically what machine learning is teaching us. We find that quantified principal components from PCA not only allow exploration of different phases and symmetry-breaking, but can distinguish phase transition types and locate critical points. We show that the corresponding weight vectors have a clear physical interpretation, which is particularly interesting in the frustrated models such as the triangular antiferromagnet, where they can point to incipient orders. Unlike the other well-studied models, the properties of the BSI model are less well known. Using both PCA and conventional Monte Carlo analysis, we demonstrate that the BSI model shows an absence of phase transition and macroscopic ground-state degeneracy. The failure to capture the 'charge' correlations (vorticity) in the BSI model (XY model) from raw spin configurations points to some of the limitations of PCA. Finally, we employ a nonlinear unsupervised machine learning procedure, the 'antoencoder method', and demonstrate that it too can be trained to capture phase transitions and critical points.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗