Employing Nanoscale Surface Characterizations in a Field Emission Model.
Abstract not provided.
Hopkins, Matthew M.↗
SEARCH · Search NASA
Results for “mooring model”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Modeling of rarefied ionized flows with the QUIPS and velocity-space hybrid methods.
Abstract not provided.
Oblapenko, Georgii↗
Computational Complexity of Neuromorphic Algorithms
Neuromorphic computing has several characteristics that make it an extremely compelling computing paradigm for post Moore computation. Some of these characteristics include intrinsic parallelism, inherent scalability, collocated processing and memory, and event-driven computation. While these characteristics impart energy efficiency to neuromorphic systems, they do come with their own set of challenges. One of the biggest challenges in neuromorphic computing is to establish the theoretical underpinnings of the computational complexity of neuromorphic algorithms. In this paper, we take the first steps towards defining the space and time complexity of neuromorphic algorithms. Specifically, we describe a model of neuromorphic computation and state the assumptions that govern the computational complexity of neuromorphic algorithms. Next, we present a theoretical framework to define the computational complexity of a neuromorphic algorithm. We explicitly define what space and time complexities mean in the context of neuromorphic algorithms based on our model of neuromorphic computation. Finally, we leverage our approach and define the computational complexities of six neuromorphic algorithms: constant function, successor function, predecessor function, projection function, neuromorphic sorting algorithm and neighborhood subgraph extraction algorithm.
Date, Prasanna↗
Minimal one-dimensional model of bad metal behavior from fast particle-hole scattering
A strongly interacting plasma of linearly dispersing electron and hole excitations in two spatial dimensions (2D), also known as a Dirac fluid, can be captured by relativistic hydrodynamics and shares many universal features with other quantum critical systems. Here, we propose a one-dimensional (1D) model to capture key aspects of the 2D Dirac fluid while including lattice effects and being amenable to nonperturbative computation. When interactions are added to the Dirac-like 1D dispersion without opening a gap, we show that this kind of irrelevant interaction is able to preserve Fermi-liquid-like quasiparticle features while relaxing a zero-momentum charge current via collisions between particle-hole excitations, leading to resistivity that is linear in temperature via a mechanism previously discussed for large-diameter metallic carbon nanotubes. We further provide a microscopic lattice model and obtain numerical results via density-matrix renormalization group simulations, which support the above physical picture. The limits on such fast relaxation at strong coupling are of considerable interest because of the ubiquity of bad metals in experiments.
1-dimensional systems↗
LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales
Not Available
74 ATOMIC AND MOLECULAR PHYSICS↗
Thermodynamics and Magnetism of YCo5 Compound Doped with Fe and Ni: An Ab Initio Study
YCo5 permanent magnet exhibits high uniaxial magnetocrystalline anisotropy energy and has a high Curie temperature. These are good properties for a permanent magnet, but YCo5 has a low energy product, which is notably insufficient for a permanent magnet. In order to improve the energy product in YCo5, we suggest replacing cobalt with iron, which has a much bigger magnetic moment. With a combination of density-functional-theory calculations and thermodynamic CALculation of PHAse Diagrams (CALPHAD) modeling, we show that a new magnet, YFe3(Ni1-xCox)2, is thermodynamically stable and exhibits an improved energy product without significant detrimental effects on the magnetocrystalline anisotropy energy or the Curie temperature.
anisotropy↗
Latitudinal gradient in the respiration quotient and the implications for ocean oxygen availability
Significance The loss of ocean oxygen caused by climate warming is a serious environmental issue and could lead to major declines in animal habitats. However, current Earth system models struggle in explaining observed trends in global ocean oxygen. Using a model, we demonstrate that marine oxygen concentrations depend sensitively on a rarely considered quantity known as the respiration quotient to prescribe the oxygen consumed per mole of organic carbon respired. Using a combination of direct chemical measurements across major biomes in the eastern Pacific Ocean plus changes in the global distribution of oxygen and carbon, we show how the respiration quotient increases systematically with temperature. The findings imply that we can experience more intense declines in ocean oxygen with warming.
54 ENVIRONMENTAL SCIENCES↗
Understanding the role of segmentation on process-structure–property predictions made via machine learning
Here, the present study investigated the effect of porosity surface determination methods on performance of machine learning models used to predict the tensile properties of AlSi10Mg processed by laser powder bed fusion from micro-computed tomography data. Machine learning models applied in this work include support vector machines, neural networks, decision trees, and Bayesian classifiers. The effects of isosurface thresholding and local gradient approaches for porosity segmentation, as well as image filtering schemes, on model precision were evaluated for samples produced under differing levels of global energy density.
36 MATERIALS SCIENCE↗
Comprehensive Assessment and Thermodynamic Modeling of the Pu-Ni system
Explore the source record for details and available documents.
Materials science↗
Evaluation of Ocean Biogeochemistry and Carbon Cycling in CMIP Earth System Models With the International Ocean Model Benchmarking (IOMB) Software System
Abstract The International Ocean Model Benchmarking (IOMB) software package is a new community resource that we use here to evaluate surface and upper ocean biogeochemical variables and integrated anthropogenic carbon uptake from earth system models (ESMs) contributing to the 5th and 6th phases of the Coupled Model Intercomparison Project (CMIP5 and CMIP6). IOMB generates graphics and tables for systematically comparing model predictions against multiple datasets. Our analysis reveals some improvement in the multi‐model mean from CMIP5 to CMIP6 for most of the variables we examined. Compared to data‐constrained estimates of ocean anthropogenic carbon uptake for the 1994–2007 period, negative biases exist for many models between 30 and 50°S. Global model estimates of anthropogenic carbon uptake for the same period do not change significantly from CMIP5 to CMIP6, with the combined ensemble mean estimate of 27.8 ± 0.5 Pg C lower than a data‐constrained estimate of 33.0 ± 4.0 Pg C. At the same time, the change in the natural carbon inventory from CMIP is estimated to be a source of 0.7 ± 0.3 Pg C, which is considerably smaller in magnitude than a data‐constrained estimate of 5.0 ± 3.0 Pg C. With chlorofluorocarbon (CFC) predictions available for several models, we demonstrate that negative anthropogenic dissolved inorganic carbon biases coincide with negative biases in CFC concentration, highlighting the importance of weak exchange between the surface and interior ocean in regulating rates of anthropogenic carbon uptake. To examine the robustness of this attribution across the CMIP models, we calculate the global vertical temperature gradient between 200 and 1,000 m as a metric for global stratification and exchange between the surface and deeper waters. We find a linear relationship between the bias of the vertical temperature gradients and the bias in global anthropogenic carbon uptake, consistent with the hypothesis that model biases in anthropogenic carbon uptake are related to biases in surface‐to‐interior exchange by physical processes.
58 GEOSCIENCES↗
Propagation Pattern for Moment Representation of the Lattice Boltzmann Method
A propagation pattern for the moment representation of the regularized lattice Boltzmann method (LBM) in three dimensions is presented. Using effectively lossless compression, the simulation state is stored as a set of moments of the lattice Boltzmann distribution function, instead of the distribution function itself. An efficient cache-aware propagation pattern for this moment representation has the effect of substantially reducing both the storage and memory bandwidth required for LBM simulations. This article extends recent work with the moment representation by expanding the performance analysis on central processing unit (CPU) architectures, considering how boundary conditions are implemented, and demonstrating the effectiveness of the moment representation on a graphics processing unit (GPU) architecture.
42 ENGINEERING↗
Thermodynamics Modeling for Actinide Monocarbides and Mononitrides from First Principles
The high-temperature thermodynamical properties for the actinide monocarbides and mononitrides ThC, ThN, UC, UN, PuC, and PuN are calculated from first-principles electronic-structure theory. The electronic structure is modeled with density-functional theory (DFT) and is fully relativistic, including the spin-orbit interaction. Furthermore, the DFT is extended to account for orbital–orbital interactions, by means of a parameter-free orbital-polarization (OP) technique, that has proven to be essential for the 5f electrons in plutonium. Strong anharmonicity and the temperature dependence of the lattice vibrations are captured with the self-consistent ab initio lattice dynamics (SCAILD) method. The calculated free energies and heat capacities are compared to published results from quasi-harmonic (QH) theory, and experiments, where available. For the uranium and plutonium compounds, we make use of CALPHAD assessments to help evaluate the theory. Generally, our anharmonic relativistic approach compares well with both CALPHAD and experiments. For the thorium compounds, our theory is in good accord with QH modeling of the free energy at lower temperatures but for the heat capacity the comparison is less favorable.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
High-fidelity modeling of breakdown in helium: initiation processes and secondary electron emission
Understanding the role of physical processes contributing to breakdown is critical for many applications in which breakdown is undesirable, such as capacitors, and applications in which controlled breakdown is intended, such as plasma medicine, lightning protection, and materials processing. The electron emission from the cathode is a critical source of electrons which then undergo impact ionization to produce electrical breakdown. In this study, the role of secondary electron yields due to photons (γ ph ) and ions (γ i ) in direct current breakdown is investigated using a particle-in-cell direct simulation Monte Carlo model. The plasma studied is a one-dimensional discharge in 50 Torr of pure helium with a platinum cathode, gap size of 1.15 cm, and voltages of 1.2–1.8 kV. The current traces are compared with experimental measurements. Larger values of γ ph generally result in a faster breakdown, while larger values of γ i result in a larger maximum current. The 58.4 nm photons emitted from He(2 1 P) are the primary source of electrons at the cathode before the cathode fall is developed. Of the values of γ ph and γ i investigated, those which provide the best agreement with the experimental current measurements are γ ph = 0.005 and γ i = 0.01. In this work, these values are significantly lower than those in the literature for pristine platinum or for a graphitic carbon film which we speculate may cover the platinum. This difference is in part due to the limitations of a one-dimensional model but may also indicate surface conditions and exposure to a plasma can have a significant effect on the secondary electron yields. The effects of applied voltage and the current produced by a UV diode which was used to initiate the discharge, are also discussed.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Anomalously strong near-neighbor attraction in doped 1D cuprate chains
In the cuprates, one-dimensional (1D) chain compounds provide a distinctive opportunity to understand the microscopic physics, owing to the availability of reliable theories. However, progress has been limited by the challenge of controllably doping these materials. We report the synthesis and spectroscopic analysis of the 1D cuprate Ba 2-x Sr x CuO 3+δ over a wide range of hole doping. Our angle-resolved photoemission experiments reveal the doping evolution of the holon and spinon branches. We identify a prominent folding branch whose intensity fails to match predictions of the simple Hubbard model. An additional strong near-neighbor attraction, which may arise from coupling to phonons, quantitatively explains experiments for all accessible doping levels. Furthermore, considering structural and quantum chemistry similarities among cuprates, this attraction may play a similarly important role in high-temperature cuprate superconductors.
1D Chain↗
Sensitivity analysis of numerical modeling input parameters on floating offshore wind turbine loads in extreme idling conditions
Abstract. Floating offshore wind turbine (FOWT) systems are subject to complex environmental loads, with significant potential for damage in extreme storm conditions. Design simulations in these conditions are required to assess the survivability of the device with some level of confidence. Aero-hydro-servo-elastic engineering tools can be used with a reasonable balance of accuracy and computational efficiency. The models require many input parameters to describe the air and water conditions, the system properties, and the load calculations. Each of these parameters has some possible range, due to either statistical uncertainty or variations with time. Variation in the input parameters can have important effects on the uncertainty in the resulting loads, but it is not practical to perform detailed assessments of the impact of this uncertainty for every input parameter. This work demonstrates a method to identify the input parameters that have the most impact on the loads to focus further inspection. The process is done specifically for extreme storm load cases defined in the International Electrotechnical Commission design requirements for floating offshore wind turbines. The analysis was performed using the International Energy Agency Wind 15 MW offshore reference wind turbine atop the University of Maine VolturnUS-S reference platform in two US offshore wind regions, the Gulf of Maine and Humboldt Bay. It was found that the direction of incident waves and current, yaw misalignment, and the length of mooring line sections were among the primary sensitivities.
17 WIND ENERGY↗
Modeling temporal and hormonal regulation of plant transcriptional response to wounding
Plants respond to wounding stress by changing gene expression patterns and inducing the production of hormones including jasmonic acid. This wounding transcriptional response activates specialized metabolism pathways such as the glucosinolate pathways in Arabidopsis thaliana. While the regulatory factors and sequences controlling a subset of wound-response genes are known, it remains unclear how wound response is regulated globally. Here, we how these responses are regulated by incorporating putative cis-regulatory elements, known transcription factor binding sites, in vitro DNA affinity purification sequencing, and DNase I hypersensitive sites to predict genes with different wound-response patterns using machine learning. We observed that regulatory sites and regions of open chromatin differed between genes upregulated at early and late wounding time-points as well as between genes induced by jasmonic acid and those not induced. Expanding on what we currently know, we identified cis-elements that improved model predictions of expression clusters over known binding sites. Using a combination of genome editing, in vitro DNA-binding assays, and transient expression assays using native and mutated cis-regulatory elements, we experimentally validated four of the predicted elements, three of which were not previously known to function in wound-response regulation. Our study provides a global model predictive of wound response and identifies new regulatory sequences important for wounding without requiring prior knowledge of the transcriptional regulators.
59 BASIC BIOLOGICAL SCIENCES↗
Advancing the Theory of Nuclear Data Evaluations [Abstract]
We present recent advances in the R-matrix formalism as well as the Bayesian evaluation framework for improved nuclear data evaluations. The advances in the R matrix formalism include: 1) direct processes, 2) doorway, as well as multistep, processes, and 3) various forms of the Reich-Moore approximation for eliminated capture channels. Furthermore, to address unreasonably small posterior uncertainties often encountered in nuclear data evaluations of large data sets using the conventional form of the Bayes’ theorem, we introduce imperfections (of the data or the model) as a formal evaluation tool for taming the evaluated uncertainties in harmony with Bayes’ theorem. These theoretical advances were motivated by the nuclear data evaluations of differential resolved resonance cross section data using the code SAMMY, as well as the integral benchmark experiments using the SCALE code system, being performed at Oak Ridge National Laboratory for the Nuclear Criticality Safety Program. Some pedagogical applications of the new formalism, as well as a snapshot of the SAMMY modernization efforts, will be presented.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗