Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “CLUSTER 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.

At least 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Optimization of stepwise clustering algorithm in backward trajectory analysis

In recent years, the backward trajectory model has been widely used in the research of meteorological and atmospheric environmental quality. This paper presents a comprehensive study on a stepwise clustering analysis algorithm in the clustering process of backward trajectory model and an application of the clustering analysis of single-particle backward trajectory in 2016 in Changchun City. This study starts with an analysis of the original stepwise clustering algorithm and its application to a clustering process of 8784 backward trajectories during 48 h in Changchun City as a benchmark test case. Then, two improvements are made in the algorithm: First, in the process of finding the optimal classification, the algorithm complexity is improved from original O(n 3 ) to O(log(n)*n 2 ) through algorithm improvement. The algorithm performance is enhanced by log(n) times. Next, in the process of re-establishing the classification, the algorithm complexity is improved from the original O(m*n 2 ) to O(m*log(n)*n), that is another algorithm performance improvement by a factor of log(n). Therefore, the accumulative execution efficiency improvement through the algorithm optimization is 2*log(n) times, which has been further verified in the practical application in Changchun City.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1990

The application of optical potentials for reactive scattering - A case study

A precise method is presented for measuring decay fractions of metastable cluster ions with corrections concerning instrumental artifacts and ion trajectory of parents and daughters. Experimental data are used to derive the Gspann parameter and heat capacity of clusters as described in Klots' evaporative ensemble model. The model is applied to obtain binding energies of ammonia cluster ions. The deduced binding energy values are in very good agreement with both thermochemical data and Engelking's (1986) modified statistical theory.

Neuhauser, Daniel↗
DOE OSTI2025

Geometric Interpretation of the Cluster Location Problem Part I: Theory

We present a new framing of the seismic location problem using principles drawn from differential geometry. Our interpretation relies upon the common assumption that travel times observed across a network are continuous, differentiable functions of source location. In consequence, travel‐time functions constitute a differentiable map between the source region and a Riemannian manifold. The manifold is said to be the image of the source region embedded in a generally high‐dimension travel‐time vector space. A cluster of events in the source region has an image of discrete points on the manifold, that, except in the simplest cases, cannot be viewed directly. However, it is possible to project the image of a cluster into a tangent space of the manifold for direct visualization. The projection operator can be computed directly from the data without a velocity model, but produces a distorted rendering of the cluster geometry. With a model we can predict the distortions and correct them to estimate cluster geometry. We develop these points with the simplest possible example, one for which direct visualization of the manifold is possible, using the example as an introduction to the relevant concepts from differential geometry in a familiar setting. The tangent space, a local linearization of the manifold, plays a key role. We develop a metric to estimate the limits of linearization, that is, to determine when the curvature of the manifold invalidates the linear assumption. We also examine the interplay of model error, inadequate network geometry, and pick error. We then generalize our results from the simple case to the general case of 3D source regions observed by general networks. Although we do suggest a new “project and correct” method for location, we do not develop it into a practical algorithm. In conclusion, our intention rather is to highlight new analytical methods grounded in differential geometry.

East Pacific Ocean Islands↗
DOE OSTI2023

Spatio-Temporal Surrogates for Interaction of a Jet with High Explosives: Part II - Clustering Extremely High-Dimensional Grid-Based Data

Building an accurate surrogate model for the spatio-temporal outputs of a computer simulation is a challenging task. A simple approach to improve the accuracy of the surrogate is to cluster the outputs based on similarity and build a separate surrogate model for each cluster. This clustering is relatively straightforward when the output at each time step is of moderate size. However, when the spatial domain is represented by a large number of grid points, numbering in the millions, the clustering of the data becomes more challenging. In this report, we consider output data from simulations of a jet interacting with high explosives. These data are available on spatial domains of different sizes, at grid points that vary in their spatial coordinates, and in a format that distributes the output across multiple files at each time step of the simulation. We first describe how we bring these data into a consistent format prior to clustering. Borrowing the idea of random projections from data mining, we reduce the dimension of our data by a factor of thousand, making it possible to use the iterative k-means method for clustering. We show how we can use the randomness of both the random projections, and the choice of initial centroids in k-means clustering, to determine the number of clusters in our data set. Our approach makes clustering of extremely high dimensional data tractable, generating meaningful cluster assignments for our problem, despite the approximation introduced in the random projections.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A Siamese CNN + KNN-Based Classification Framework for Non-intrusive Load Monitoring

Through the development of smart grids, programs such as demand side response, have been presented as auxiliary services to the real-time operation of distributed networks. In order to provide consumers information on their energy consumption, so that a modulation in consumption is possible, non-intrusive load monitoring has been introduced as an solution to this pattern recognition problem. Non-intrusive load monitoring enables the modeling of electrical loads connected to the low-voltage system, considering only a single measurement point. Presented state-of-the-art solutions though, consider availability of data as well as representation of all possible classes of the environment. This is of course a most conservative hypothesis, since in real-life applications availability of such data is much difficult, as well as the dynamic behavior of models is implicitly evolving in time. Here, a framework that uses neural Siamese networks with k-nearest neighbor clustering is presented toward non-intrusive load monitoring. Online learning feature is implemented, which relaxes the hypothesis of data requirements as well addresses the evolving nature of load profile. k-nearest clustering allows nonlinear characteristic space modelling. Test results using synthetics and real-life data show that the solution, besides obtaining a good generalizability in the classification, also obtained results with an accuracy of 95.77%.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2012

Model Catalysts: Simulating the Complexities of Heterogeneous Catalysts

Surface-science investigations have contributed significantly to heterogeneous catalysis in the past several decades. Fundamental studies of reactive systems on metal single crystals have aided researchers in understanding the effect of surface structure on catalyst reactivity and selectivity for a number of important reactions. Recently, model systems, consisting of metal clusters deposited on planar oxide surfaces, have facilitated the study of metal particle-size and support effects. These model systems not only are useful for carrying out kinetic investigations, but are also amenable to surface spectroscopic techniques, thus enabling investigations under realistic pressures and at working temperatures. By combining surface-science characterization methods with kinetic measurements under realistic working conditions, researchers are continuing to advance the molecular-level understanding of heterogeneous catalysis and are narrowing he pressure and material gap between model and real-world catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Analysis of Dynamical Peculiarities in Nanoalloys at Subsystems Level: Dynamical Degrees of Freedom, Temperature Differences, and the Chameleon Effect

Abstract A novel analysis of the dynamical behavior of nanoalloy systems, as represented by model Ni/Al 13‐atom clusters, over a broad range of energies that cover the stage‐wise transition of the systems from their solid‐like to liquid‐like state is presented. Conceptually, the analysis is rooted in partitioning the systems into judiciously chosen subsystems and characterizing the latter in terms of subsystem‐specific dynamical descriptors that include dynamical degrees of freedom , root‐mean‐square bond‐length fluctuation , and element‐specific subsystem temperature . The analysis reveals a host of intriguing new peculiarities in the dynamical behavior of the Ni/Al 13‐mers, among which are what we call the chameleon effect and the difference in the temperatures of the Ni and Al subsystems at high energies, a difference that strongly depends on the cluster composition and also changes with energy. These do not have an analog in pure Ni 13 and Al 13 and are explained in terms of the coupled effects of the difference between the masses of the Ni and Al atoms (the mass effect) and of the difference in the anharmonicity of the overall interaction potential as experienced by the Ni and Al subsystems of the clusters (the potential effect).

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

Calculations of Solid-State 43Ca NMR Parameters: A Comparison of Periodic and Cluster Approaches and an Evaluation of DFT Functionals

We present a computational study of magnetic-shielding and quadrupolar-coupling tensors of 43Ca sites in crystalline solids. A comparison between periodic and cluster-based approaches for modeling solid-state interactions demonstrates that clusterbased approaches are suitable for predicting 43Ca NMR parameters. Several model chemistries, including Hartree–Fock theory and 17 DFT approximations (SVWN, CA-PZ, PBE, PBE0, PW91, B3PW91, rPBE, PBEsol, WC, PKZB, BMK, M06-L, M06, M06-2X, M06-HF, TPSS, and TPSSh), are evaluated for the prediction of 43Ca NMR parameters. Convergence of NMR parameters with respect to basis sets of the form cc-pVXZ (X5D, T, Q) is also evaluated. All DFT methods lead to substantial, and frequently systematic, overestimations of experimental chemical shifts. Hartree–Fock calculations outperform all DFT methods for the prediction of 43Ca chemical-shift tensors. VC 2017 Wiley Periodicals, Inc. DOI: 10.1002/jcc.24763

Holmes, Sean T.↗
DOE OSTI2018

Clustering in the Three and Four Color Cyclic Particle Systems in One Dimension

We study the κ-color cyclic particle system on the one-dimensional integer lattice ℤ, first introduced by Bramson and Griffeath (Ann Prob:26–45, 1989). In that paper they show that almost surely, every site changes its color infinitely often if κ∈{3,4} and only finitely many times if κ≥5. In addition, they conjecture that for κ∈{3,4} the system clusters, that is, for any pair of sites x, y, with probability tending to 1 as t→∞, x and y have the same color at time t. Here we prove that conjecture.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Stochastic nonlinear analysis of unidirectional fiber composites using image-based microstructural uncertainty quantification

Here, we present a data-driven nonlinear uncertainty quantification and propagation framework to study the microstructure-induced stochastic performance of unidirectional (UD) carbon fiber reinforced polymer (CFRP) composites. The proposed approach integrates (1) microscopic image characterization, (2) stochastic microstructure reconstruction, and (3) efficient multiscale finite element simulations enabled by self-consistent clustering (SCA) analysis. To model the complex microstructural variability, the proposed UQ methods take the non-Gaussian uncertainty sources into account through a distribution-free sampling approach leveraging nonparametric and asymptotic statistical tools. A hierarchical conditional sampling strategy enables the simultaneous sampling of multiple sources of uncertainties. Our approach provides insights into the impact of microstructural variabilities, which are shown to have an increasing impact on the nonlinear responses of UD CFRP parts under progressive compression loading and ultimately on the failure rate over time. We discover that before CFRP parts start to fail, a characteristic time period emerges with distinctive uncertainty distributions specific to the microstructure variability and the probability of failure. Identifying the failure time period is crucial to the reliability prediction, which is an essential component of CFRP design.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Exact diagonalization library for quantum electron models

We present an exact diagonalization C++ template library (EDLib) for solving quantum electron models,including the single-band finite Hubbard cluster and the multi-orbital impurity Anderson model. Theobservables that can be computed using EDLib are single particle Green’s functions and spin–spincorrelation functions. This code provides three different types of Hamiltonian matrix storage that canbe chosen based on the model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Dilute Pd-in-Au alloy RCT-SiO 2 catalysts for enhanced oxidative methanol coupling

Dilute alloy catalysts have the potential to enhance selectivity and activity for large-scale reactions. Highly dilute Pd-in-Au nanoparticle alloys partially embedded in porous silica (“raspberry colloid templated” (RCT)-SiO 2 ) prove to be robust and selective catalysts for oxidative coupling of methanol. Palladium concentrations in the bimetallic nanoparticles as low as ~3.4 at.% catalyze the production of methyl formate with a selectivity of ~95% at conversions of ~55%, whereas conversions are low (<10%) for ~1.7 at.% Pd-in-Au nanoparticle and pure Au nanoparticle catalysts. Fractional reaction orders for both CH 3 OH and O 2 measured for ~3.4 at.% Pd-in-Au nanoparticles supported on RCT-SiO 2 indicated a complex mechanism in which the sites for O 2 dissociation are not saturated. Optimal methyl formate production was found for an equimolar mixture. There is no conversion of methanol in the absence of O 2 between 360 and 450 K. Finally, all observations are consistent with a mechanism derived from model studies, requiring that clusters of Pd be available on the catalyst for O 2 dissociation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Impact of grain boundary and surface diffusion on predicted fission gas bubble behavior and release in UO 2 fuel

In this work, we quantify the impact of grain boundary (GB) and surface diffusion on fission gas bubble evolution and fission gas release in UO 2 nuclear fuel using simulations with a hybrid phase field/cluster dynamics model. Here, we begin with a comprehensive literature review of uranium vacancy and xenon atom diffusivity in UO 2 through the bulk, along GBs, and along surfaces. In our model we represent fast GB and surface diffusion using a heterogeneous diffusivity that is a function of the order parameters that represent bubbles and grains. We find that the GB diffusivity directly impacts the rate of gas release via GB transport, and that the GB diffusivity is likely below 104 times the lower value from Olander and van Uffelen. We also find that the surface diffusivity impacts bubble coalescence and mobility, and that the bubble surface diffusivity is likely below 10 -4 times the value from Zhou and Olander.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Probing neutron-skin thickness with free spectator neutrons in ultracentral high-energy isobaric collisions

We show that the yield ratio of free spectator neutrons produced in high-energy 96 Zr+ 96 Zr to 96 Ru+ 96 Ru collisions is a clean probe of the neutron-skin thickness of colliding nuclei and the slope parameter L of the symmetry energy. The idea is demonstrated based on the proton and neutron density distributions via a state-of-the-art Skyrme-Hartree-Fock-Bogolyubov calculation. Among spectator nucleons given by the Glauber model, free spectator neutrons include those from direct production that survive from clusterization as well as those from deexcitation of heavy clusters described by the popular GEMINI model. More free neutrons are produced in collisions of 96 Zr nucleus due to its larger neutron skin, compared to those produced in collisions of 96 Ru nucleus with a smaller neutron skin. The difference of the free spectator neutron yield is further increased with the increasing difference of the neutron-skin thickness between 96 Zr and 96 Ru with a larger L value, and the increase in ultracentral collisions is particularly insensitive to model details and experimental uncertainties. Since the production of free spectator neutrons is not affected by the complicated dynamics in the mid-rapidity region, the ratio of their multiplicities in ultracentral isobaric collisions is a robust observable for constraining the neutron skin and L value.

79 ASTRONOMY AND ASTROPHYSICS↗