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At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Hydropower Capacity Factor Trends & Analytics for the United States

This data repository contains all code, input data, and data generated for Turner et al. (2024)—“Hydropower capacity factors trending down in the United States”. File descriptions: – hydro-cf-trends-inputs.zip: Full set of input data used in this study, organized for direct entry into “/data” directory of hydro-cf-trends data processing pipeline. – hydro-cf-trends.zip: Full data processing pipeline, coded using the R {targets} framework. This is a snapshot release (v1.0) of the code repository stored at https://code.ornl.gov/turnersw/hydro-cf-trends/. – hydro-cf-trends-results.zip: Provides all dam level results required to reproduce results and graphics in Turner et al. (2024). Dams are identified by the “complxID” (root of the hydropower plant ID in the Existing Hydropower Assets Database, inherited from HILARRI). Results include: • dam_CF_trends.csv: Table of long-term trends in annualized capacity factors for 610 dams and modeled annualized capacity factors for 362 modeled dams (naturalized and assimilated flows). • dam_annualized_CF_gen.csv: Annualized time series of the following variables for each of 610 hydropower dams with nameplate > 5MW – Reported nameplate capacity (MW) – Implied maximum annual generation (MWh) – Reported net generation (MWh) – Computed annual capacity factor – Modeled annual capacity factor (362 modeled plants only)

13 HYDRO ENERGY↗
DOE OSTI2021

Fast Extraction and Characterization of Fundamental Frequency Events from a Large PMU Dataset using Big Data Analytics

A novel method for fast extraction of fundamental frequency events (FFE) based on measurements of frequency and rate of change of frequency by Phasor Measurement Units (PMU) is introduced. The method is designed to work with exceptionally large historical PMU datasets. Statistical analysis was used to extract the features and train Random Forest and Catboost classifiers. The method is capable of fast extraction of FFE from a historical dataset containing measurements from hundreds of PMUs captured over multiple years. The reported accuracy of the best algorithm for classification expressed as Area Under the receiver operating Characteristic curve reaches 0.98, which was obtained in out-of-sample evaluations on 109 system-wide events over 2 years observed at 43 PMUs. Then Minimum Volume Enclosing Ellipsoid Algorithm was used to further analyze the events. 93.72% events were correctly characterized, where average duration of the event as seen by the PMU was 9.93 sec.

Baembitov, Rashid↗
DOE OSTI2023

PNNL Superfund Research Program Analytics (srpAnalytics Data Release v.1.0)

The OSU/PNNL superfund Research Program represents a longstanding collaboration to quantify Polycyclic Aromatic Hydrocarbons at various superfund sites in the Pacific Northwest and assess their potential impact on human health. To link the chemical measurements to biological activity, we describe the use of the zebrafish as a high-throughput developmental model of human exposure that provides quantitative measurements of the biological ramifications of exposure to toxicants. The PNNL Superfund have implemented a dose-response modelling pipeline to calculate benchmark dose parameters that enable the comparison of potency across chemicals and phenotypes. Our portal provides public access to this dataset and an interactive web site designed to enable exploration and re-use of this data by the scientific community at http://srp.pnnl.gov.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

PNNL Superfund Research Program Analytics (srpAnalytics Data Release v.1.0)

The OSU/PNNL superfund Research Program represents a longstanding collaboration to quantify Polycyclic Aromatic Hydrocarbons at various superfund sites in the Pacific Northwest and assess their potential impact on human health. To link the chemical measurements to biological activity, we describe the use of the zebrafish as a high-throughput developmental model of human exposure that provides quantitative measurements of the biological ramifications of exposure to toxicants. The PNNL Superfund have implemented a dose-response modelling pipeline to calculate benchmark dose parameters that enable the comparison of potency across chemicals and phenotypes. Our portal provides public access to this dataset and an interactive web site designed to enable exploration and re-use of this data by the scientific community at http://srp.pnnl.gov.

OSU-PNNL Superfund Research Program Center SRP↗
DOE OSTI2021

Analytical Framework for Homeowner-Focused Computational Cost-Benefit Mitigation Decision Making

As a result of increasing windstorm losses in the United States over the past 50 years, a variety of residential wind hazard mitigation strategies have been recommended. Wind hazard mitigation undoubtedly reduces windstorm losses; however, little customized information is available to support the economic decision-making process for individual stakeholders, especially at the consumer level. Therefore, there is a need for decision support tools to calculate, evaluate, and present the economic benefits of mitigation over variable decision-making time horizons for unique building characteristics in specific geographical locations. This paper presents a cost-benefit computational decision-making recommendation framework that evaluates and presents the cost effectiveness of mitigation, customized based on location, years of interest, and building characteristics. The decision-making framework consists of two cores. The user-independent core and user-dependent core which consists of eight steps, divided into four subprocesses: (1) data acquisition, (2) data evaluation, (3) cost-benefit calculation, and (4) results comparison and decision making. To demonstrate the framework, a wood-framed single-family home in light suburban terrain in Golden Meadow, Louisiana, is used as a case study, considering retrofit mitigation with a $15,000 budget and a decision-making time horizon of 30 years. The case study provides six mitigation options, with cost ranging between approximately $2,000 and $15,000 and net benefit/cost ratios ranging from 2.4 to 13. Once fully implemented in a decision making information tool, the developed mitigation recommendation framework will provide valuable information that can be used by home designers, builders, owners, and other stakeholders to better understand the economic facets of wind hazard mitigation, providing critical information as part of the overall decision-making process.

Orooji, Fatemeh↗
DOE OSTI2023

Galactic Bar Resonances with Diffusion: An Analytic Model with Implications for Bar–Dark Matter Halo Dynamical Friction

Abstract The secular evolution of disk galaxies is largely driven by resonances between the orbits of “particles” (stars or dark matter) and the rotation of non-axisymmetric features (spiral arms or a bar). Such resonances may also explain kinematic and photometric features observed in the Milky Way and external galaxies. In simplified cases, these resonant interactions are well understood: for instance, the dynamics of a test particle trapped near a resonance of a steadily rotating bar is easily analyzed using the angle-action tools pioneered by Binney, Monari, and others. However, such treatments do not address the stochasticity and messiness inherent to real galaxies—effects that have, with few exceptions, been previously explored only with complex N -body simulations. In this paper, we propose a simple kinetic equation describing the distribution function of particles near an orbital resonance with a rigidly rotating bar, allowing for diffusion of the particles’ slow actions. We solve this equation for various values of the dimensionless diffusion strength Δ, and then apply our theory to the calculation of bar–halo dynamical friction. For Δ = 0, we recover the classic result of Tremaine and Weinberg that friction ultimately vanishes, owing to the phase mixing of resonant orbits. However, for Δ > 0, we find that diffusion suppresses phase mixing, leading to a finite torque. Our results suggest that stochasticity—be it physical or numerical—tends to increase bar–halo friction, and that bars in cosmological simulations might experience significant artificial slowdown, even if the numerical two-body relaxation time is much longer than a Hubble time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

A Semi-analytical Model for Stellar Evolution in AGN Disks

Disks of gas accreting onto supermassive black holes may host numerous stellar-mass objects, formed within the disk or captured from a nuclear star cluster. We present a simplified model of stellar evolution in these dense environments, which exhibits exceptional agreement with full stellar evolution calculations at a minuscule fraction of the cost. Although the model presented here is limited to stars burning hydrogen in their cores, it is sufficient to determine the evolutionary fate of disk-embedded stars: whether they proceed to later stages of nuclear burning and leave behind a compact remnant, reach a quasi-steady state where mass loss and accretion balance one another, or whether accretion proceeds faster than stellar structure can adjust, causing a runaway. We highlight how various disk parameters and phenomena such as gap opening affect stellar evolution outcomes. We also highlight how our model can accommodate time-varying conditions, such as those experienced by a star on an eccentric orbit, and can couple to N -body integrations. This model will enable more detailed studies of stellar populations and their interaction with accretion disks than have previously been possible.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Axion Perturbations: A General Analytical Treatment

Cosmological data provides us two key constraints on dark matter (DM): it must have a particular abundance, and it must have an adiabatic spectrum of density perturbations in the early universe. Many different cosmological scenarios have been proposed that establish the abundance of axion DM in qualitatively different ways. In this paper we emphasize that, despite this variety of backgrounds, the perturbations in axion DM can be understood from universal principles. How does a feebly interacting axion field acquire perturbations proportional to those of photons? How do the isocurvature power spectrum and non-Gaussianity depend on the background evolution of the universe? We answer these questions for a completely general choice of cosmological background and temperature-dependent axion potential. We show that the most general solution to the axion field equation on super-horizon scales is entirely determined by the family of background solutions for different initial field values . This holds for both the component in the field perturbation solution contributing to the DM isocurvature perturbation (enhanced at late times by the sensitivity of the DM abundance to the initial condition, , which can be large for initial conditions near the hilltop), and the other component that contributes to the DM curvature perturbation. In particular, we explain that an unperturbed axion field in the early universe evolving into one with nontrivial adiabatic perturbations is guaranteed by Weinberg's theorem on adiabatic modes. These results have been derived before with various assumptions, such as a radiation dominated background or a quadratic potential. Our aim is to give a clear, simple derivation that is manifestly independent of those assumptions, and thus can be applied to any cosmological axion scenario.

Cosmology and Nongalactic Astrophysics (astro-ph.C↗
DOE OSTI2025

Analytical Approximations for Beamstrahlung at Very High Energy Electron-Positron Colliders

Among the many effects that occur in beam-beam electron-positron collisions at TeV energies, emission of hard synchrotron radiation, or beamstrahlung, has special importance. Beamstrahlung determines the energy spectrum of the most energetic electrons, positrons, and photons and supplies the initial condition for the calculation of all other QED processes. In this paper, we show that the description of beamstrahlung simplifies in the limit of large quantum parameter $Υ$, which is realized in 10 TeV collider designs. The beamstrahlung spectra for electrons and photons are given in terms of universal functions. We supply approximations to these functions that will be useful for more general studies of the beam-beam interaction at very high energies.

Accelerator Physics (physics.acc-ph)↗
DOE OSTI2021

A VECTOR ANALYTICAL FRAMEWORK FOR POPULATION MODELING

We propose a vector alternative to the typical raster based population modeling framework. When compared with rasters, vectors are more precise, have the ability to hold more information, and are more conducive to areal constructs such as building and parcel outlines. While rasters have traditionally provided computational efficiency, much of this efficiency is reduced at finer resolutions and computational resources are more plentiful today. Herein we describe the approach and implementation methodology. We also describe the output data stack for the United States and provide examples and applications.

Moehl, Jessica↗
DOE OSTI2026

Introduction to and comparison of deep learning and optimization approaches to analytical wake modeling of a tilted wind turbine

This paper introduces innovative optimization and deep learning techniques to enhance the prediction of complex wake dynamics in the downstream wind velocity of tilted wind turbines. Traditional methods for calibrating the Bastankhah wake model often lead to increased errors in wind velocity distribution due to overfitting of the local wake characteristics. To address this issue, we propose an additional global optimization step to reduce errors in wind velocity predictions with respect to various wake parameters. Despite this improvement, the Bastankhah model's axisymmetric Gaussian wake shape limits its accuracy for complex wake structures. Therefore, we also propose a deep learning approach, which demonstrates promising results by accurately modeling complex wake shapes across a broader range of tilt angles with minimal computational cost. The deep learning approach achieves near-identical predictions to high-fidelity large-eddy simulations, representing a promising advancement in wake modeling.

17 WIND ENERGY↗