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At least 1,045 records · Page 58

The Development of a Finite Volume Method for Modeling Sound in Coastal Ocean Environment

: As the rapid growth of marine renewable energy and off-shore wind energy, there have been concerns that the noises generated from construction and operation of the devices may interfere marine animals’ communication. In this research, a underwater sound model is developed to simulate sound prorogation generated by marine-hydrokinetic energy (MHK) devices or offshore wind (OSW) energy platforms. Finite volume and finite difference methods are developed to solve the 3D Helmholtz equation of sound propagation in the coastal environment. For finite volume method, the grid system consists of triangular grids in horizontal plane and sigma-layers in vertical dimension. A 3D sparse matrix solver with complex coefficients is formed for solving the resulting acoustic pressure field. The Complex Shifted Laplacian Preconditioner (CSLP) method is applied to efficiently solve the matrix system iteratively with MPI parallelization using a high performance cluster. The sound model is then coupled with the Finite Volume Community Ocean Model (FVCOM) for simulating sound propagation generated by human activities in a range-dependent setting, such as offshore wind energy platform constructions and tidal stream turbines. As a proof of concept, initial validation of the finite difference solver is presented for two coastal wedge problems. Validation of finite volume method will be reported separately.

Coastal↗

Revisiting the formation of cyclic clusters in liquid ethanol

The liquid phase of ethanol in pure and in non-polar solvents was studied at room temperature using Fourier transform infrared (FT-IR) and {sup 1}H nuclear magnetic resonance (NMR) spectroscopies together with theoretical approach. The FT-IR spectra for pure ethanol and solution in cyclohexane at different dilution stages are consistent with {sup 1}H NMR results. The results from both methods were best explained by the results of the density functional theory based on a multimeric model. It is suggested that cyclic trimers and tetramers are dominated in the solution of cyclohexane/hexane with the concentration greater than 0.5M at room temperature. In liquid ethanol, while the primary components at room temperature are cyclic trimers and tetramers, there is a certain amount (∼14%) of open hydroxide group representing the existence of chain like structures in the equilibria. The cyclic cluster model in the liquid and concentrated solution phase (>0.5M) can be used to explain the anomalously lower freezing point of ethanol (159 K) than that of water (273 K) at ambient conditions. In addition, {sup 1}H NMR at various dilution stages reveals the dynamics for the formation of cyclic clusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Error modeling for surrogates of dynamical systems using machine learning: Machine-learning-based error model for surrogates of dynamical systems

A machine learning–based framework for modeling the error introduced by surrogate models of parameterized dynamical systems is proposed. The framework entails the use of high-dimensional regression techniques (eg, random forests, and LASSO) to map a large set of inexpensively computed “error indicators” (ie, features) produced by the surrogate model at a given time instance to a prediction of the surrogate-model error in a quantity of interest (QoI). This eliminates the need for the user to hand-select a small number of informative features. The methodology requires a training set of parameter instances at which the time-dependent surrogate-model error is computed by simulating both the high-fidelity and surrogate models. Using these training data, the method first determines regression-model locality (via classification or clustering) and subsequently constructs a “local” regression model to predict the time-instantaneous error within each identified region of feature space. We consider 2 uses for the resulting error model: (1) as a correction to the surrogate-model QoI prediction at each time instance and (2) as a way to statistically model arbitrary functions of the time-dependent surrogate-model error (eg, time-integrated errors). We then apply the proposed framework to model errors in reduced-order models of nonlinear oil-water subsurface flow simulations, with time-varying well-control (bottom-hole pressure) parameters. The reduced-order models used in this work entail application of trajectory piecewise linearization in conjunction with proper orthogonal decomposition. Moreover, when the first use of the method is considered, numerical experiments demonstrate consistent improvement in accuracy in the time-instantaneous QoI prediction relative to the original surrogate model, across a large number of test cases. When the second use is considered, results show that the proposed method provides accurate statistical predictions of the time- and well-averaged errors.

97 MATHEMATICS AND COMPUTING↗

Active galactic nuclei. III - Accretion flow in an externally supplied cluster of black holes

This third paper in the series modeling QSOs and AGNs as clusters of accreting black holes studies the accretion flow within an externally supplied cluster. Significant radiation will be emitted by the cluster core, but the black holes in the outer halo, where the flow is considered spherically symmetric, will not contribute much to the overall luminosity of the source because of their large velocities relative to the infalling gas and therefore their small accretion radii. As a result, the scenario discussed in Paper I will refer to the cluster cores, rather than to entire clusters. This will steepen the high-frequency region of the spectrum unless inverse Compton scattering is effective. In many cases accretion flow in the central part of the cluster will be optically thick to electron scattering, resulting in a spectrum featuring optically thick radiative component in addition to power-law regimes. The fitting of these spectra to QSO and AGN observations is discussed, and application to 3C 273 is worked out as an example.

Pacholczyk, A. G.↗

Chemical models for simulating single-walled nanotube production in arc vaporization and laser ablation processes

Chemical kinetic models for the nucleation and growth of clusters and single-walled carbon nanotube (SWNT) growth are developed for numerical simulations of the production of SWNTs. Two models that involve evaporation and condensation of carbon and metal catalysts, a full model involving all carbon clusters up to C80, and a reduced model are discussed. The full model is based on a fullerene model, but nickel and carbon/nickel cluster reactions are added to form SWNTs from soot and fullerenes. The full model has a large number of species--so large that to incorporate them into a flow field computation for simulating laser ablation and arc processes requires that they be simplified. The model is reduced by defining large clusters that represent many various sized clusters. Comparisons are given between these models for cases that may be applicable to arc and laser ablation production. Solutions to the system of chemical rate equations of these models for a ramped temperature profile show that production of various species, including SWNTs, agree to within about 50% for a fast ramp, and within 10% for a slower temperature decay time.

Nanotubes, Carbon/chemistry↗

Clustering Approach To Identifying Low Lunar Frozen Orbits In A High-Fidelity Model

Low lunar frozen orbits are of continued interest in the astrodynamics community for trajectory design and space domain awareness. This paper presents a data-driven approach to analyzing a wide variety of numerically-generated lunar trajectories in a 100 × 100 lunar gravity model with the point mass gravity of the Earth and Sun. First, clustering is used to extract a summary of these trajectories: within each cluster, trajectories possess a geometrically similar evolution of perilune but varying drift and lifetimes. Within some clusters, trajectories with a bounded perilune evolution are also identified to produce candidates for lunar frozen orbits of distinct geometries.

lunar frozen orbit gravity model data clustering↗

Strong lensing analysis of the galaxy cluster MACS J1319.9+7003 and the discovery of a shell galaxy

We present a strong-lensing (SL) analysis of the galaxy cluster MACS J1319.9+7003 (z = 0.33, also known as Abell 1722), as part of our ongoing effort to analyze massive clusters with archival Hubble Space Telescope (HST) imaging. We spectroscopically measured with Keck/Multi-Object Spectrometer For Infra-Red Exploration (MOSFIRE) two galaxies multiply imaged by the cluster. Our analysis reveals a modest lens, with an effective Einstein radius of θ{sub e}(z=2)=12±1{sup ′′}, enclosing 2.1±0.3×10{sup 13} M{sub ⊙}. We briefly discuss the SL properties of the cluster, using two different modeling techniques (see the text for details), and make the mass models publicly available (ftp://wise-ftp.tau.ac.il/pub/adiz/MACS1319/). Independently, we identified a noteworthy, young shell galaxy (SG) system forming around two likely interacting cluster members, 20″ north of the brightest cluster galaxy. SGs are rare in galaxy clusters, and indeed, a simple estimate reveals that they are only expected in roughly one in several dozen, to several hundred, massive galaxy clusters (the estimate can easily change by an order of magnitude within a reasonable range of characteristic values relevant for the calculation). Taking advantage of our lens model best-fit, mass-to-light scaling relation for cluster members, we infer that the total mass of the SG system is ∼1.3×10{sup 11} M{sub ⊙}, with a host-to-companion mass ratio of about 10:1. Despite being rare in high density environments, the SG constitutes an example to how stars of cluster galaxies are efficiently redistributed to the intra-cluster medium. Dedicated numerical simulations for the observed shell configuration, perhaps aided by the mass model, might cast interesting light on the interaction history and properties of the two galaxies. An archival HST search in galaxy cluster images can reveal more such systems.

79 ASTRONOMY AND ASTROPHYSICS↗

Data-driven fuel consumption estimation: A multivariate adaptive regression spline approach

Providing guidance and information to drivers to help them make fuel-efficient route choices remains an important and effective strategy in the near term to reduce fuel consumption from the transportation sector. One key component in implementing this strategy is a fuel-consumption estimation model. In this paper, we developed a mesoscopic fuel consumption estimation model that can be implemented into an eco-routing system. Our proposed model presents a framework that utilizes large-scale, real-world driving data, clusters road links by free-flow speed and fits one statistical model for each of cluster. This model includes predicting variables that were rarely or never considered before, such as free-flow speed and number of lanes. We applied the model to a real-world driving data set based on a global positioning system travel survey in the Philadelphia-Camden-Trenton metropolitan area. Results from the statistical analyses indicate that the independent variables we chose influence the fuel consumption rates of vehicles. But the magnitude and direction of the influences are dependent on the type of road links, specifically free-flow speeds of links. Here, a statistical diagnostic is conducted to ensure the validity of the models and results. Although the real-world driving data we used to develop statistical relationships are specific to one region, the framework we developed can be easily adjusted and used to explore the fuel consumption relationship in other regions.

30 DIRECT ENERGY CONVERSION↗

Microstructure modeling of nuclear structural materials: Recent progress and future directions

Modeling and simulation of microstructures are essential to understand the complex responses and behaviors of nuclear materials in extreme environments. The needs to assess the extended life operation as well as the growing interest in accelerating nuclear materials development and qualification have stimulated the use of high-fidelity multiscale models aided by empirical and ab initio data. This paper reviews the role of various models across different length and time scales in investigating irradiation effects on microstructure evolution and degradation, in particular the embrittlement caused by radiation induced or enhanced formation of nanoscale chemical heterogeneities. The strength and limitations of these models, including classical rate theories, cluster dynamics, phase-field methods, and atomistic models informed by ab initio energies, are discussed with seminal examples. Challenges regarding the lack of thermo-kinetic data and theoretical treatments considering chemical complexities and magnetic excitations, as well as the stabilizing effect by excess point defects in nuclear structural materials are presented, along with potential solutions based on ab initio informed surrogate energy models and statistical sampling by Monte Carlo simulations. Further, the review then highlights the opportunities to leverage the advantages of different methods by establishing hybrid models by shared variables or coupled codes and applications. Finally, the review concludes with forward-looking remarks on how the use of physics-based models can aid the improvement of machine-learning models of property degradation and vice versa.

36 MATERIALS SCIENCE↗

PROBING THE ROLE OF DYNAMICAL FRICTION IN SHAPING THE BSS RADIAL DISTRIBUTION. I. SEMI-ANALYTICAL MODELS AND PRELIMINARY N-BODY SIMULATIONS

We present semi-analytical models and simplified N-body simulations with 10{sup 4} particles aimed at probing the role of dynamical friction (DF) in determining the radial distribution of blue straggler stars (BSSs) in globular clusters. The semi-analytical models show that DF (which is the only evolutionary mechanism at work) is responsible for the formation of a bimodal distribution with a dip progressively moving toward the external regions of the cluster. However, these models fail to reproduce the formation of the long-lived central peak observed in all dynamically evolved clusters. The results of N-body simulations confirm the formation of a sharp central peak, which remains as a stable feature over time regardless of the initial concentration of the system. In spite of noisy behavior, a bimodal distribution forms in many cases, with the size of the dip increasing as a function of time. In the most advanced stages, the distribution becomes monotonic. These results are in agreement with the observations. Also, the shape of the peak and the location of the minimum (which, in most of cases, is within 10 core radii) turn out to be consistent with observational results. For a more detailed and close comparison with observations, including a proper calibration of the timescales of the dynamical processes driving the evolution of the BSS spatial distribution, more realistic simulations will be necessary.

79 ASTRONOMY AND ASTROPHYSICS↗

SrFe{sub 0.9}Ti{sub 0.1}O{sub 3−δ}: A cluster spin glass

Graphical abstract: - Highlights: • Prepared SrFe{sub 0.9}Ti{sub 0.1}O{sub 3−δ} is in nanocrystalline form. • Arrott plot shows absence of spontaneous magnetization which rules out the possibility of long range ferromagnetic order. • AC susceptibility data is evidence of cluster spin glass. • There is no magnetic Bragg's reflection. • By substituting Ti{sup 4+}, helical antiferromagetic SrFeO{sub 3} is transformed to a cluster spin glass. - Abstract: The magnetic ground state of nanocrystalline SrFe{sub 0.9}Ti{sub 0.1}O{sub 3−δ} system has been investigated from 2 K to 300 K using AC Susceptibilty (ACS), magnetization and neutron diffraction measurements. The cusp in the temperature dependent magnetization and dispersion below T{sub max} (the temperature at which the maximum susceptibility is observed) in real part of ac susceptibility with frequency is observed. Arrott plot shows the lack of M{sub S} (spontaneous magnetization) down to 2 K, and the non-occurrence of magnetic Bragg reflections below the T{sub max} in neutron diffraction measurements, indicates the absence of long range ferro and antiferromagnetic order. The frequency dependence of T{sub max} obeys Vögel–Fulcher model establishing the cluster spin glass behavior in this system.

36 MATERIALS SCIENCE↗

UNF-ST&DARDS Enhancements for RCCA Data in As-loaded Dual Purpose Cask Models

This report summarizes the work performed to enable detailed modeling of rod cluster control assembly (RCCAs) in dual purpose canisters (DPCs) in as-loaded configurations using the Used Nuclear Fuel – Storage, Transportation & Disposal Analysis Resource and Data System (UNF-ST&DARDS). The goal of this project was to evaluate the reactivity impact that RCCAs have on k eff of DPCs with pressurized water reactor (PWR) fuel to potentially use the additional margin in future post-closure criticality safety analysis. This preliminary evaluation determined the number of DPCs that currently require compensatory actions prior to emplacement in a repository because of their high reactivity under post-closure criticality scenarios, which could be made acceptable by including the as-loaded RCCAs as specified in the Unified Database (UDB). This report briefly describes the modeling methods currently used within UNF-ST&DARDS and the modifications made to automate inclusion of the as-loaded RCCAs in the DPCs for post-closure criticality calculations for the loss of neutron absorber (NA) scenarios, or NA models. For the Zion site, the loss of basket scenarios, or degraded basket (DB) models, are also included. Discussion is also provided regarding the UDB data compared to available site-specific loading map data for the sites, which are specifically evaluated herein. This report compares the modifications to a similar evaluation for the Zion by site conducted by Walker as an initial validation. After the partial validation, all existing PWR sites with applicable NA models within the UDB were evaluated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Swarm intelligence–based distributed stochastic model predictive control for transactive operation of networked building clusters

To maximize potential energy and cost savings, networked clusters of local buildings are formed for energy transactions. Both centralized and distributed decision approaches were explored in past decades as a way to enable efficient transactive operations. However, online distributed stochastic transactive operation has been overlooked in the literature. To bridge gaps in the research, a bi-level distributed stochastic model predictive control framework was proposed to study the transactive operations of building clusters where a system-level agent is employed to coordinate multiple building agents at the subsystem level. The energy transaction is optimized by a marginal price-based particle swarm optimizer at the system level. Given the energy transaction decisions, each building can independently solve a scenario-based two-stage stochastic model to optimally dispatch the electricity and ancillary services for optimal energy performance. The effectiveness of the proposed framework and coordination algorithm are demonstrated in deterministic, stochastic, and online operations and compared to centralized decisions using several sets of experiments. Additionally, the proposed approach can realize autonomous transactive operation and be extended to community-level building clusters in a plug-and-play way.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Quantum mechanical force field for water with explicit electronic polarization

A quantum mechanical force field (QMFF) for water is described. Unlike traditional approaches that use quantum mechanical results and experimental data to parameterize empirical potential energy functions, the present QMFF uses a quantum mechanical framework to represent intramolecular and intermolecular interactions in an entire condensed-phase system. In particular, the internal energy terms used in molecular mechanics are replaced by a quantum mechanical formalism that naturally includes electronic polarization due to intermolecular interactions and its effects on the force constants of the intramolecular force field. As a quantum mechanical force field, both intermolecular interactions and the Hamiltonian describing the individual molecular fragments can be parameterized to strive for accuracy and computational efficiency. In this work, we introduce a polarizable molecular orbital model Hamiltonian for water and for oxygen- and hydrogen-containing compounds, whereas the electrostatic potential responsible for intermolecular interactions in the liquid and in solution is modeled by a three-point charge representation that realistically reproduces the total molecular dipole moment and the local hybridization contributions. The present QMFF for water, which is called the XP3P (explicit polarization with three-point-charge potential) model, is suitable for modeling both gas-phase clusters and liquid water. The paper demonstrates the performance of the XP3P model for water and proton clusters and the properties of the pure liquid from about 900 × 10{sup 6} self-consistent-field calculations on a periodic system consisting of 267 water molecules. The unusual dipole derivative behavior of water, which is incorrectly modeled in molecular mechanics, is naturally reproduced as a result of an electronic structural treatment of chemical bonding by XP3P. We anticipate that the XP3P model will be useful for studying proton transport in solution and solid phases as well as across biological ion channels through membranes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Enhancement of the droplet nucleation in a dense supersaturated Lennard-Jones vapor

The vapor–liquid nucleation in a dense Lennard-Jones system is studied analytically and numerically. A solution of the nucleation kinetic equations, which includes the elementary processes of condensation/evaporation involving the lightest clusters, is obtained, and the nucleation rate is calculated. Based on the equation of state for the cluster vapor, the pre-exponential factor is obtained. The latter diverges as a spinodal is reached, which results in the nucleation enhancement. The work of critical cluster formation is calculated using the previously developed two-parameter model (TPM) of small clusters. A simple expression for the nucleation rate is deduced and it is shown that the work of cluster formation is reduced for a dense vapor. This results in the nucleation enhancement as well. To verify the TPM, a simulation is performed that mimics a steady-state nucleation experiments in the thermal diffusion cloud chamber. The nucleating vapor with and without a carrier gas is simulated using two different thermostats for the monomers and clusters. The TPM proves to match the simulation results of this work and of other studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The unusual smoothness of the extragalactic unresolved radio background

If the radio background is coming from cosmological sources, there should be some amount of clustering due to the large scale structure in the universe. Simple models for the expected clustering combined with the recent measurement by ARCADE-2 of the mean extragalactic temperature lead to predicted clustering levels that are substantially above upper limits from searches for anisotropy on arcminute scales using the Australia Telescope Compact Array and the Very Large Array. The rms temperature variations in the cosmic radio background appear to be more than a factor of 10 smaller (in temperature) than the fluctuations in the cosmic infrared background. It is therefore extremely unlikely that this background comes from galaxies, galaxy clusters, or any sources that trace dark matter halos at z ≲ 5, unless typical sources are smooth on arcminute scales, requiring typical sizes of several Mpc.

79 ASTRONOMY AND ASTROPHYSICS↗

Systematically improvable multiscale solver for correlated electron systems

The development of numerical methods capable of simulating realistic materials with strongly correlated electrons, with controllable errors, is a central challenge in quantum many-body physics. Here we describe a framework for a general multiscale method based on embedding a self-energy of a strongly correlated subsystem into a self-energy generated by a method able to treat large weakly correlated systems approximately. As an example, we present the embedding of an exact diagonalization self-energy into a self-energy generated from self-consistent second-order perturbation theory. Using a quantum impurity model, generated from a cluster dynamical mean field approximation to the two-dimensional Hubbard model, as a benchmark, we illustrate that our method allows us to obtain accurate results at a fraction of the cost of typical Monte Carlo calculations. We test the method in multiple regimes of interaction strengths and dopings of the model. Here, the general embedding framework we present avoids difficulties such as double counting corrections, frequency-dependent interactions, or vertex functions. As it is solely formulated at the level of the single-particle Green's function, it provides a promising route for the simulation of realistic materials that are currently difficult to study with other methods.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Probing the large-scale velocity field with clusters of galaxies

What is the role of clusters of galaxies in probing the large-scale velocity field of the universe? We investigate the distribution of peculiar velocities of clusters of galaxies in the popular low-density (omega = 0.3) flat cold dark matter (CDM) cosmological model, which best fits many large-scale structure observations. An omega = 1 CDM model is also studied for comparison. We find that clusters of galaxies are efficient tracers of the large-scale velocity field. The clusters exhibit a Maxwellian distribution of peculiar velocities, as expected from Gaussian initial density fluctuations. The cluster three-dimensional velocity distribution for the omega = 0.3 model peaks at nu approximately greater than 400 km/s and extends to high velocities of nu approximately 1200 km/s. The rms peculiar velocity of the clusters is 440 km/s. Approximately 10% of all model clusters move with high peculiar velocities nu greater or equal to 700 km/s. The observed velocity distribution of clusters of galaxies is compared with the predictions from cosmological models. The observed data exhibit a larger velocity tail than seen in the model simulations; however, due to the large observational uncertainties, the data are consistent at approximately equal to 3 sigma level with the odel predictions, and with a Gaussian initial density field. The large peculiar velocities reported for some clusters of galaxies (nu approximately greater than 3000 km/s) are likely to be overestimated, if the current model is viable.

Bahcall, Neta A.↗