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At least 1,333 records · Page 74
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DOE OSTI2012

MODELING COLLISIONAL CASCADES IN DEBRIS DISKS: STEEP DUST-SIZE DISTRIBUTIONS

We explore the evolution of the mass distribution of dust in collision-dominated debris disks, using the collisional code introduced in our previous paper. We analyze the equilibrium distribution and its dependence on model parameters by evolving over 100 models to 10 Gyr. With our numerical models, we confirm that systems reach collisional equilibrium with a mass distribution that is steeper than the traditional solution by Dohnanyi. Our model yields a quasi-steady-state slope of n(m) {approx} m{sup -1.88} [n(a) {approx} a{sup -3.65}] as a robust solution for a wide range of possible model parameters. We also show that a simple power-law function can be an appropriate approximation for the mass distribution of particles in certain regimes. The steeper solution has observable effects in the submillimeter and millimeter wavelength regimes of the electromagnetic spectrum. We assemble data for nine debris disks that have been observed at these wavelengths and, using a simplified absorption efficiency model, show that the predicted slope of the particle-mass distribution generates spectral energy distributions that are in agreement with the observed ones.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

BURST FLUENCE DISTRIBUTIONS OF SOFT GAMMA REPEATERS 1806-20 AND 1900+14 IN THE ROSSI X-RAY TIMING EXPLORER PCA ERA

We study the fluence distributions of over 3040 bursts from SGR 1806-20 and over 1963 bursts from SGR 1900+14 using the complete set of observations available from the Rossi X-Ray Timing Explorer/Proportional Counter Array through 2011 March. Cumulative event distributions are presented for both sources and are fitted with single and broken power laws as well as an exponential cutoff. The distributions are best fitted by a broken power law with exponential cutoff; however the statistical significance of the cutoff is not high and the upper portion of the broken power law can be explained as the expected number of false bursts due to random noise fluctuations. Event distributions are also examined in high and low burst rate regimes and power-law indices are found to be consistent, independent of the burst rate. The contribution function of the event fluence is calculated. This distribution shows that the energy released in the soft gamma repeater (SGR) bursts is dominated by the most powerful events for both sources. The power-law nature of these distributions combined with the dominant energy dissipation of the system occurring in the large, less frequent bursts is indicative of a self-organized critical system, as suggested by Gogus et al. in 1999.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

THE INITIAL MASS FUNCTION MODELED BY A LEFT TRUNCATED BETA DISTRIBUTION

The initial mass function for stars is usually fitted by three straight lines, which means it has seven parameters. The presence of brown dwarfs (BDs) increases the number of straight lines to four and the number of parameters to nine. Another common fitting function is the lognormal distribution, which is characterized by two parameters. This paper is devoted to demonstrating the advantage of introducing a left truncated beta probability density function, which is characterized by four parameters. The constant of normalization, the mean, the mode, and the distribution function are calculated for the left truncated beta distribution. The normal beta distribution that results from convolving independent normally distributed and beta distributed components is also derived. The chi-square test and the Kolmogorov-Smirnov test are performed on a first sample of stars and BDs that belongs to the massive young cluster NGC 6611, and on a second sample that represents the masses of the stars of the cluster NGC 2362.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

THE ANGULAR DISTRIBUTION OF Ly{alpha} RESONANT PHOTONS EMERGING FROM AN OPTICALLY THICK MEDIUM

We investigate the angular distribution of Ly{alpha} photons scattering or emerging from an optically thick medium. Since the evolution of specific intensity I in frequency space and angular space are coupled with each other, we first develop the WENO numerical solver to find the time-dependent solutions of the integro-differential equation of I in frequency and angular space simultaneously. We first show that the solutions with the Eddington approximation, which assume that I is linearly dependent on the angular variable {mu}, yield similar frequency profiles of the photon flux as those without the Eddington approximation. However, the solutions of the {mu} distribution evolution are significantly different from those given by the Eddington approximation. First, the angular distribution of I is found to be substantially dependent on the frequency of the photons. For photons with the resonant frequency {nu}{sub 0}, I contains only a linear term of {mu}. For photons with frequencies at the double peaks of the flux, the {mu}-distribution is highly anisotropic; most photons are emitted radially forward. Moreover, either at {nu}{sub 0} or at the double peaks, the {mu} distributions actually are independent of the initial {mu} distribution of photons of the source. This is because the photons with frequencies either at {nu}{sub 0} or the double peaks undergo the process of forgetting their initial conditions due to resonant scattering. We also show that the optically thick medium is a collimator of photons at the double peaks. Photons from the double peaks form a forward beam with a very small opening angle.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Star-cluster mass and age distributions of two fields in M83 based on HST/WFC3 observations

We study star clusters in two fields in the nearby spiral galaxy M83 using broadband and narrowband optical imaging taken with the Wide Field Camera 3 onboard the Hubble Space Telescope. We present results on the basis of several different catalogs of star clusters in inner and outer fields, and we conclude that different methods of selection do not strongly affect the results, particularly for clusters older than ≈10 Myr. The age distributions can be described by a power law, dN/dτ∝τ{sup γ}, with γ ≈ –0.84 ± 0.12 in the inner field, and γ ≈ –0.48 ± 0.12 in the outer field for τ ≳ 10 Myr. We bracket the difference, Δγ, between the two fields to be in the 0.18 to 0.36 range, based on estimates of the relative star-formation histories. The mass functions can also be described by a power law, dN/dM∝M {sup β}, with β ≈ –1.98 ± 0.14 and β ≈ –2.34 ± 0.26 in the inner and outer fields, respectively. We conclude that the shapes of the mass and age distributions of the clusters in the two fields are similar, as predicted by the quasi-universal model. Any differences between the two fields are at the ≈2σ-3σ (≈1σ-2σ) level for the age (mass) distributions. Therefore, any dependence of these distributions on the local environment is probably weak. We compare the shapes of the distributions with those predicted by two popular cluster disruption models. We find that both show evidence that the clusters are disrupted at a rate that is approximately independent of their mass. We compare the shapes of the distributions with those predicted by two popular cluster disruption models, and find that both show evidence that the clusters are disrupted at a rate that is approximately independent of their mass, and that observational results do not support the earlier disruption of lower-mass clusters relative to their higher-mass counterparts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

The distribution of satellites around massive galaxies at 1 < z < 3 in ZFOURGE/CANDELS: Dependence on star formation activity

We study the statistical distribution of satellites around star-forming and quiescent central galaxies at 1 < z < 3 using imaging from the FourStar Galaxy Evolution Survey and the Cosmic Assembly Near-IR Deep Extragalactic Legacy Survey. The deep near-IR data select satellites down to log (M/M {sub ☉}) > 9 at z < 3. The radial satellite distribution around centrals is consistent with a projected Navarro-Frenk-White profile. Massive quiescent centrals, log (M/M {sub ☉}) > 10.78, have ∼2 times the number of satellites compared to star-forming centrals with a significance of 2.7σ even after accounting for differences in the centrals' stellar-mass distributions. We find no statistical difference in the satellite distributions of intermediate-mass quiescent and star-forming centrals, 10.48 < log (M/M {sub ☉}) < 10.78. Compared to the Guo et al. semi-analytic model, the excess number of satellites indicates that quiescent centrals have halo masses 0.3 dex larger than star-forming centrals, even when the stellar-mass distributions are fixed. We use a simple toy model that relates halo mass and quenching, which roughly reproduces the observed quenched fractions and the differences in halo mass between star-forming and quenched galaxies only if galaxies have a quenching probability that increases with halo mass from ∼0 for log (M{sub h} /M {sub ☉}) ∼ 11 to ∼1 for log (M{sub h} /M {sub ☉}) ∼ 13.5. A single halo-mass quenching threshold is unable to reproduce the quiescent fraction and satellite distribution of centrals. Therefore, while halo quenching may be an important mechanism, it is unlikely to be the only factor driving quenching. It remains unclear why a high fraction of centrals remain star-forming even in relatively massive halos.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Thresholded power law size distributions of instabilities in astrophysics

Power-law-like size distributions are ubiquitous in astrophysical instabilities. There are at least four natural effects that cause deviations from ideal power law size distributions, which we model here in a generalized way: (1) a physical threshold of an instability; (2) incomplete sampling of the smallest events below a threshold x{sub 0}; (3) contamination by an event-unrelated background x{sub b}; and (4) truncation effects at the largest events due to a finite system size. These effects can be modeled in the simplest terms with a “thresholded power law” distribution function (also called generalized Pareto [type II] or Lomax distribution), N(x)dx∝(x+x{sub 0}){sup −a}dx, where x{sub 0} > 0 is positive for a threshold effect, while x{sub 0} < 0 is negative for background contamination. We analytically derive the functional shape of this thresholded power law distribution function from an exponential growth evolution model, which produces avalanches only when a disturbance exceeds a critical threshold x{sub 0}. We apply the thresholded power law distribution function to terrestrial, solar (HXRBS, BATSE, RHESSI), and stellar flare (Kepler) data sets. We find that the thresholded power law model provides an adequate fit to most of the observed data. Major advantages of this model are the automated choice of the power law fitting range, diagnostics of background contamination, physical instability thresholds, instrumental detection thresholds, and finite system size limits. When testing self-organized criticality models that predict ideal power laws, we suggest including these natural truncation effects.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Non-parametric projections of the net-income distribution for all U.S. states for the Shared Socioeconomic Pathways

Abstract Income distributions are a growing area of interest in the examination of equity impacts brought on by climate change and its responses. Such impacts are especially important at subnational levels, but projections of income distributions at these levels are scarce. Here, we project U.S. state-level income distributions for the Shared Socioeconomic Pathways (SSPs). We apply a non-parametric approach, specifically a recently developed principal components algorithm to generate net income distributions for deciles across 50 U.S. states and the District of Columbia. We produce these projections to 2100 for three SSP scenarios in combination with varying projections of GDP per capita to represent a wide range of possible futures and uncertainties. In the generation of these scenarios, we also generated tax adjusted historical deciles by U.S. states, which we used for validating model performance. Our method thus produces income distributions by decile for each state, reflecting the variability in state income, population, and tax regimes. Our net income projections by decile can be used in both emissions- and impact-related research to understand distributional effects at various income levels and identify economically vulnerable populations.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2013

THE MASS DISTRIBUTION OF SUBGIANT PLANET HOSTS

High mass stars are hostile to Doppler measurements due to rotation and activity on the main-sequence, so RV searches for planets around massive stars have relied on evolved stars. A large number of planets have been found around evolved stars with M > 1.5 M{sub Sun }. To test the robustness of mass determinations, Lloyd compared mass distributions of planet hosting subgiants with distributions from integrating isochrones and concluded that it is unlikely the subgiant planet hosts are this massive, but rather that the mass inferences are systematically in error. The conclusions of Lloyd have been called in to question by Johnson et al., who show TRILEGAL-based mass distributions that disagree with the mass distributions in Lloyd, which they attribute to Malmquist bias. Johnson et al. argue that the very small spectroscopic observational uncertainties favor high masses, and there are a large number of high mass sub giants in RV surveys. However, in this Letter, it is shown that Malmquist bias does not impact the mass distributions, but the mass distribution is sensitive to Galaxy model. The relationship needed to reconcile the subgiant planet host masses with any model of the Galactic stellar population is implausible, and the conclusion of Lloyd that spectroscopic mass determinations of subgiants are likely to have been overestimated is robust.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2010

Direct measurement of the Kirkwood-Rihaczek distribution for the spatial properties of a coherent light beam

We present a direct measurement of the Kirkwood-Rihaczek (KR) distribution for spatial properties of a coherent light beam in terms of position and momentum (angle) coordinates. We employ a two-local oscillator (LO) balanced heterodyne detection (BHD) to simultaneously extract the distribution of the transverse position and momentum of a light beam. The two-LO BHD can measure the KR distribution for any complex wave field (including quantum mechanical wave function) without applying tomography methods (inverse Radon transformation). The transformation of the KR distribution to the Wigner, Glauber-Sudarshan P, and Husimi or Q distributions in spatial coordinates are illustrated through experimental data. The KR distribution can provide the local information of a wave field, which is suitable for studying particle properties of a quantum system. Meanwhile, the Wigner function is suitable for studying wave properties such as interference, and hence provides nonlocal information of the wave field. The method developed here can be used for exploring the spatial quantum state for information processing and optical phase-space imaging for biomedical applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2010

Endpoint behavior of the pion distribution amplitude in QCD sum rules with nonlocal condensates

Starting from the QCD sum rules with nonlocal condensates for the pion distribution amplitude, we derive another sum rule for its derivative and its ''integral derivatives''--defined in this work. We use this new sum rule to analyze the fine details of the pion distribution amplitude in the endpoint region x{approx}0. The results for endpoint-suppressed and flattop (or flatlike) pion distribution amplitudes are compared with those we obtained with differential sum rules by employing two different models for the distribution of vacuum-quark virtualities. We determine the range of values of the derivatives of the pion distribution amplitude and show that endpoint-suppressed distribution amplitudes lie within this range, while those with endpoint enhancement--flat-type or Chernyak-Zhitnitsky like--yield values outside this range.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Adaptive Linear State Estimation for Unbalanced Distribution System

The inclusion of PMU functionality in distribution relays enables the implementation of a linear state estimator (LSE) in Distribution Systems (DS). However, the unbalanced topology and phase coupling in distribution lines necessitate modifications to the LSE formulation. Additionally, the higher fault frequency in distribution systems requires a state estimation approach that is resilient to contingencies. This work proposes an adaptive linear state estimation algorithm tailored for unbalanced distribution systems with single-phase and two-phase laterals. Furthermore, a modified Optimal PMU Placement (OPP) strategy is introduced to ensure full observability in distribution systems with single-phase and two-phase buses. To maintain adaptability to topology changes, the state estimator incorporates circuit breaker status data provided by PMUs, ensuring robust performance during topology changes triggered by faults. The performance of the algorithm is verified on the IEEE 13-bus, 34-bus, and 123-bus systems.

PMUs↗
DOE OSTI2024

Distributed-Memory Sparse Deep Neural Network Inference Using Global Arrays

Partitioned Global Address Space (PGAS) models exhibit tremendous promise in developing efficient and productive distributed-memory parallel applications. They have been used extensively in scientific computations due to conveniently offering a ``shared-memory''-like model and convenient interfaces that separate communication with synchronization. Traditionally, PGAS communication models have been applied to dense/contiguously distributed data, but most modern applications depict varied levels of sparsity. Existing PGAS models require certain adaptations to support distributed sparse computations, since associated computations often require matrix arithmetic, in addition to data movement. The Global Arrays toolkit from Pacific Northwest National Laboratory (PNNL) is one of the earliest PGAS models to combine one-sided data communication and distributed matrix operations and is still used in the popular NWChem quantum chemistry suite. Recently, we have expanded the Global Arrays toolkit to support common sparse operations, like sparse matrix-dense matrix multiplies (SpMM), sparse matrix-sparse matrix multiplication (SpGEMM) and Sampled Dense-Dense Matrix Multiplication (SDDMM). As it turns out, these operations are the bedrock of sparse Deep Learning (DL); sparse deep neural networks and Graph Neural Networks (GNNs) have gained increasing attention recently in achieving speedups on training and inference with reduced memory footprints. Unlike scientific applications in High Performance Computing (HPC), modern (distributed-memory capable) DL toolkits often rely on non-standardized and closed-source vendor software optimizations, creating challenges in software-hardware co-design at scale. Our goal is to support a variety of distributed-memory sparse matrix operations and helper functions in the newly created Sparse Global Arrays (SGA), such that it is possible to build portable and productive Machine Learning scenarios for algorithm/software and hardware codesign purposes. Contemporary data-parallel schemes for training/inference are undergoing a major overhaul since model replication limits scalability and causes resource inefficiencies. As such, we have adopted tensor parallelism in decomposing the model and inputs, to mitigate memory issues. Current implementation is built on top of MPI and uses CPUs to maximize the portability across the platforms.

Distributed computing, machine learning↗
DOE OSTI2024

Joint Management and Optimization of Residential Natural Gas and Electricity Distribution Networks Coupled via Fuel Cells

The attractive features of natural gas as well as the growing electric power demand worldwide have created increasing interest in natural-gas-based distributed generation applications for electric distribution networks. Here, this paper investigates the interdependency between a residential natural gas network and an electric distribution network that are linked together via fuel cells. The modeling of the natural gas network is introduced first, and then the algorithm for gas flow study is presented. The optimal placement and sizing of fuel cell based distributed generation systems are formulated to minimize the losses in both the natural gas network and the electric distribution grid, subject to the constraints imposed by both networks. In addition, a probabilistic model for both gas and electricity demands is developed based on historical electricity and natural gas demand data. A K-means clustering method is used to determine the hourly load states to solve the joint probabilistic optimization problem. Simulation studies are carried out on an integrated system consisting of the IEEE 69-bus distribution network and a radial 27-node natural gas network to verify the developed optimization model and the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Voltage Support With PV Inverters in Low-Voltage Distribution Networks: An Overview

Large solar photovoltaic (PV) penetration using inverters in low voltage (LV) distribution networks may pose several challenges, such as reverse power flow and voltage rise situations. These challenges will eventually force grid operators to carry out grid reinforcement to ensure continued safe and reliable operations. However, smart inverters with reactive power control capability enable PV systems to support voltage quality in the distribution network better. Here, this paper gives an overview of the current state-of-the-art control strategies for handling voltage problems through PV inverters and other devices. In addition, the (control) technical issues of PV systems integrated into the LV distribution network are considered from a control point of view. By comparing the control issues of PV integration into the grid, the paper aims to help distribution system operators to expand the volume of PV generation in the distribution system in an efficient and safe manner. Additionally, it will help control engineers and researchers select proper control strategies for PV systems as well as other distributed renewable sources.

42 ENGINEERING↗
DOE OSTI2021

Mining Smart Meter Data to Enhance Distribution Grid Observability for Behind-the-Meter Load Control: Significantly improving system situational awareness and providing valuable insights

Distributed Energy Resources (DERs) are playing an increasingly important role in power systems. In 2023, five categories of DERs-distributed solar, electric vehicles (EVs), energy storage, residential smart thermostats, and small-scale combined heat and power-are expected to contribute about 104 GW to the U.S. summer peak (see GTM, 2018). With the increasing integration of DERs in power distribution systems, distributed load control is imperative to smooth the fluctuations that they introduce. However, a main challenge is that distribution systems lack systematic situational awareness because of their limited sensors. Furthermore, most customer-level behind-the-meter (BTM) DERs, such as rooftop photovoltaics (PVs), are being integrated into distribution systems, which complicates the system monitoring and control. Furthermore, enhanced electric grid monitoring is needed to promote renewable integration while ensuring reliability, but current approaches rely on expensive sensors.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Bus.py: A GridLAB-D Communication Interface for Smart Distribution Grid Simulations

As more Smart Grid technologies (e.g., distributed photovoltaic, spatially distributed electric vehicle charging) are integrated into distribution grids, static distribution simulations are no longer sufficient for performing modeling and analysis. GridLAB-D is an agent-based distribution system simulation environment that allows fine-grained end-user models, including geospatial and network topology detail. A problem exists in that, without outside intervention, once the GridLAB-D simulation begins execution, it will run to completion without allowing the real-time interaction of Smart Grid controls, such as home energy management systems and aggregator control. We address this lack of runtime interaction by designing a flexible communication interface, Bus.py (pronounced bus-dot-pie), that uses Python to pass messages between one or more GridLAB-D instances and a Smart Grid simulator. This work describes the design and implementation of Bus.py, discusses its usefulness in terms of some Smart Grid scenarios, and provides an example of an aggregator-based residential demand response system interacting with GridLAB-D through Bus.py. The small scale example demonstrates the validity of the interface and shows that an aggregator using said interface is able to control residential loads in GridLAB-D during runtime to cause a reduction in the peak load on the distribution system in (a) peak reduction and (b) time-of-use pricing cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Validation of Power Distribution Models using Load Flow Analysis in an ADMS Environment

Electric utilities are facing the need for better monitoring, analysis, and control of their distribution systems. An accurate mathematical model is a key to both the development of cutting-edge, scalable model-based algorithms and the assessment of emerging technologies such as distributed energy resources (DER) for grid planning and operation. However, the constantly evolving nature of power distribution systems poses challenges to maintaining accurate models. In this paper, we propose a novel load flow based approach to validate power distribution models. Networked equipment models described according to the Common Information Model (CIM) standard and a measurement model are used to formulate the distribution load flow problem. First, a system admittance matrix (Ybus) is derived from device-level CIM parameters. Next, the operational parameters (dynamic Ybus and nodal injections) are extracted from the measurement model using sensor configuration and equipment state. An iterative power flow method is then used to compute nodal voltages and branch flows that are compared against the measurement data to find any inconsistencies in the networked equipment model. This approach is implemented within GridAPPS-D, an open-source standards-based platform for advanced distribution management system (ADMS) application development, and demonstrated on the IEEE 13-bus, 123-bus, and 8500-node test feeders.

Common information model, model validation, power ↗