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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.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Understanding the Golden Eagle and Bald Eagle Sensory Worlds to Enhance Detection and Response to Wind Turbines

Golden Eagles (Aquila chrysaetos) and Bald Eagles (Haliaeetus leucocephalus) are known to be involved in collisions with wind turbines. Our primary goal of this project was to characterize the auditory and visual physiology of Golden and Bald Eagles with the ultimate intention of providing this information to engineers for the development of novel deterrent systems. These systems can be used to reduce the risk of eagle collisions with turbines by alerting eagles to the presence of wind turbines so that they may change course, or deterring them from approaching turbines while operational. We proposed a two-phase research project. First, we needed to know basic eagle sensory physiology to develop effective multimodal (auditory and visual) stimuli tuned to eagle’s specific sensory capabilities. Second, we complemented the first phase of the project by running behavioral tests of prototype stimuli in wildlife rehabilitation centers to determine the responses of eagles. These two stages were necessary to ensure that the stimuli characteristics were not only conspicuous to the Golden and Bald Eagle’s sensory systems, but also generated the intended response when flying near wind turbines (e.g. enhanced detection).

17 WIND ENERGY↗
DOE OSTI2026

EAGLE-I Power Outage Data 2025

The provided EAGLE-I historic dataset includes power outage information at the county level for 2025 at 15-minute intervals collected by the EAGLE-I program at ORNL. The data has been collected from utility's public outage maps using an ETL process. The dataset details FIPS code, county name, state name, total number of customers without power, and a date/timestamp. For detailed metadata, refer to the linked metadata DOI.

EAGLE-I↗
DOE OSTI2015

EAGLE: 'EAGLE'Is an' Algorithmic Graph Library for Exploration

The Resource Description Framework (RDF) and SPARQL Protocol and RDF Query Language (SPARQL) were introduced about a decade ago to enable flexible schema-free data interchange on the Semantic Web. Today data scientists use the framework as a scalable graph representation for integrating, querying, exploring and analyzing data sets hosted at different sources. With increasing adoption, the need for graph mining capabilities for the Semantic Web has emerged. Today there is no tools to conduct "graph mining" on RDF standard data sets. We address that need through implementation of popular iterative Graph Mining algorithms (Triangle count, Connected component analysis, degree distribution, diversity degree, PageRank, etc.). We implement these algorithms as SPARQL queries, wrapped within Python scripts and call our software tool as EAGLE. In RDF style, EAGLE stands for "EAGLE 'Is an' algorithmic graph library for exploration. EAGLE is like 'MATLAB' for 'Linked Data.'

Source record↗
DOE OSTI2022

Interannual consistency of migration phenology is season- and breeding region-specific in North American Golden Eagles

Abstract Interannual consistency (an indicator of the strength of adjustments) in migration phenology of Golden Eagles (Aquila chrysaetos) in North America is most strongly associated with the breeding region, the season, and with late-season temperature on breeding and wintering grounds. Consistency was greatest in boreal spring migration and the breeding regions of eastern Canada. Using multi-year GPS tracks of 83 adults breeding in 3 spatially distant regions (Alaska, northeast Canada, and southeast Canada), we quantified the interannual consistency of migration phenology and wintering latitude within and among individuals tracked across multiple years and the repeatability (r) by breeding regions and seasons. By comparing regions and seasons, we found that consistency was highest (r > 0.85) for boreal spring migration in eastern Canada while Alaska had the lowest value (r < 0.15). Because seasonal consistency of migration phenology was only detected in eastern Canada, we conclude that seasonal features are not a primary constraint. While regional differences in consistency were not related to differences in migratory distances, they could be the result of genetic or habitat differences. We also found that temperatures warmer than the decadal average at the region of departure delayed the start of boreal spring migration by ~10 days and advanced boreal autumn migration by ~20 days. These results suggest that warmer temperatures would reduce residence time on breeding grounds, contrary to expectations and trends found in other studies. Wide variations in migratory strategies across a species distribution can add to the list of challenges for conservation but may give migrants the capacity to acclimate to environmental changes.

Zoology↗
DOE OSTI2021

Quantifying Turbine-Level Risk to Golden Eagles Using a High-Fidelity Updraft Model and a Stochastic Behavioral Model

To minimize the effects of wind farms on Golden Eagle (Aquila chrysaetos) populations while enabling sustainable development of renewable energy resources, it is important to understand how eagles interact with atmospheric flows, terrain features, and anthropogenic structures. Models that predict migratory flight paths provide one tool that helps us grasp how the location of wind farms may influence interactions and impacts on migrating Golden Eagles. The current state-of-the-art in predicting migratory flight paths uses a deterministic fluid-flow analogy to predict eagle trajectory using only an orographic updraft potential computed from topographical features. This model does not take into account variables, such as thermal updrafts and time varying atmospheric conditions that are known to influence migratory behavior. In this work, we improve on the model with the objective of developing tools that advance our understanding of how atmospheric flows and terrain features affect migratory eagle behavior and their interactions with wind farms. Specifically, we 1) incorporate both orographic and thermal updraft information in simulating eagle flight paths; 2) incorporate stochasticity into eagle travel patterns to better capture the influence of exogenous factors on, and the inherent stochasticity of eagle behavior; 3) consider spatio-temporal atmospheric data at wind-farm-scale when computing updraft potential; and 4) account for how atmospheric conditions and the direction of migration change seasonally and how these changes affect eagle migratory flight behavior. We tested the model using a 50km by 50km region with 50 m resolution in the western United States. We simulated 900 independent, probabilistic eagle tracks during southerly and northerly migration, assuming eagles solely rely on orographic updrafts. The preliminary results indicate that the inclusion of finer resolution atmospheric data allows for the inclusion of realistic conditions that an eagle experiences. The stochasticity in eagle tracks provides a platform to include uncertainty in eagle decision making and help produce robust eagle presence maps. We will deploy updraft and downdraft velocities computed using a high-fidelity, wind farm scale, computational fluid dynamics solver under development at National Renewable Energy Laboratory. This work is a first step in the development of a predictive and generalizable eagle behavior model at the wind farm scale that does not rely on empirical data collection. Although the current model is intended for migratory eagles, we will extend and refine this model to inform the development of additional behavioral modes, including resident eagle behavior. This modeling approach improves our ability to understand eagle use of the landscape at a fine scale, and it is our hope that this work will ultimately help advance strategies that minimize the impact of wind development on Golden Eagle populations.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
DOE OSTI2020

Detection and Perception of Sound by Eagles and Surrogate Raptors

One overarching objective of this program of study was the accumulation of objective, scientifically valid information relating to auditory performance of bald and golden eagles that may be used to guide the development of acoustic alerting/deterrence technologies intended to discourage encroachment into wind energy air spaces. To that end, analyses aimed at the characterization of sensitivity to sound in bald and golden eagles, along with findings in the supra-threshold, dynamic frequency spaces related to response latencies and amplitudes, leads us to conclude that bald, and golden eagles navigate the same basic working auditory space, as in other known and thus far characterized members of the diurnal raptor family. Specifically, bald and golden eagles, along with other raptor species within the group, operate in an auditory space characterized by a frequency band at least four octaves wide and centered on 2 kHz, with an upper frequency limit between 6 and 10 kHz at 80 dB SPL and a lower frequency limit that almost certainly extends below 0.2 kHz. Consequently, we recommend that signal designers use these data as a guideline in efforts to design effective and efficient acoustic alerting/deterrent systems. It is important to note that signal energy broadcast outside of this frequency band at moderate levels will not contribute to the efficacy of a deterrent but will add an unnecessary fraction to the overall acoustic pollution budget. The importance of this consideration is heightened by contemporaneous concerns related to the transmission of noise broadcast by wind energy farms. In addition, based on analyses of data acquired from red-tailed hawks using the same experimental paradigm and data acquisition system, we conclude that auditory function in the red-tailed hawk is sufficiently like that observed in bald and golden eagles to permit its use as a surrogate species. Response waveforms, threshold-frequency curves, and input-output characteristics match those of eagles closely. It should be noted however, that differences in sensitivity and slightly extended high-frequency limits of hearing should be taken into account when extrapolating findings from one species to the others. Although the inclusion of behavioral tests of red-tailed hawks to acoustic stimuli was beyond the scope of this investigation, future efforts to assess response parameters like signal-type preference and habituation rate will further elucidate their suitability to serve as eagle surrogates in behavioral studies; nonetheless, the species in question are well matched with respect to basic auditory performance. A second essential objective of this program of study was the acoustic characterization of a subset of calls comprising the vocal repertoires of bald and golden eagles that may be used to supplement auditory performance findings in the effort to guide the development of acoustic alerting signals. With regard to that objective, the vocal repertoires of both bald and golden eagle species are rich and varied. While similar in spectrographic structure, distinctive differences are also clear. Generally, golden eagles produce some calls with shorter durations, and similar “sounding” calls exhibit distinctively different spectrographic patterns than those of bald eagles. Both species produce calls that contain a wide variety of nonlinear elements that operate to enhance the rich and varied nature of commonly observed vocal products. Comparison of the average power spectra of commonly observed bald and golden eagle calls with threshold-frequency curves leads to the conclusion that call energies fall within the frequency bounds of hearing. Further, the acoustic energy of calls considered in this report tend to fall into overlapping, but different frequency ranges of the acoustic sensitivity curve. This condition may encourage signal designers to vary the frequency content of acoustic deterrence signals in the field. Finally, preliminary observations relating to the tendencies and proclivities of bald eagles to attend to the acoustic landscape lead to the conclusion that eagles monitor their immediate sound environment assiduously. Individuals respond to a variety of natural and synthetic sound signals reliably and, perhaps most relevant in the context of the engineering of acoustic alerting/deterrence technologies, habituation to most sounds considered in this effort was minimal. These preliminary results, while calling for extended behavioral testing, are promising and set the stage for the exportation of behavioral studies into real world scenarios.

17 WIND ENERGY↗
DOE OSTI2020

Atmospheric Modeling to Enable Prediction of Golden Eagle Interactions with Wind Power Plants

This panel will explore the use of technologies and methods that enhance our understanding of eagle behavior in and near wind energy facilities. The decreasing costs of tracking technologies and substantial computational capabilities are allowing for finer resolution and confidence of eagle observations and the modeling of such datasets increase our understanding of their movements and use of airspace and underlying landscapes. Behavior ecologists' intrinsic knowledge of eagle behavior can augment and further enhance inferences from technology-derived information alone, e.g., GPS, camera, radar, etc. The panel will discuss the state of science and, given the cost-effective tools available, what research objectives are emerging to better assess and reduce wind-eagle risk. The discussion will focus on the following areas: Integrating Behavioral and Quantitative Ecologist perspectives of bald eagle and golden eagle behavior and wind energy risk; Regional-scale vs. facility-scale investigations of bald eagle and golden eagle use of airspace. For example, avoidance behavior to assess risk at facility-scale, and eagle use of landscapes, e.g., territories, nesting, and life-cycle behavior; Bald eagle and golden eagle use of airspace and nexus with atmospheric flow dynamics of wind energy generation; GPS, biomonitoring, tracking camera, radar, and other tools/techniques for deepening the knowledge of eagle behavior in and around wind farms.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
DOE OSTI2016

Wind Energy Industry Eagle Detection and Deterrents: Research Gaps and Solutions Workshop Summary Report

The Bald and Golden Eagle Protection Act (BGEPA) prohibits the 'take' of these birds. The act defines take as to 'pursue, shoot, shoot at, poison, wound, kill, capture, trap, collect, destroy, molest or disturb.' The 2009 Eagle Permit Rule (74 FR 46836) authorizes the U.S. Fish and Wildlife Service (USFWS) to issue nonpurposeful (i.e., incidental) take permits, and the USFWS 2013 Eagle Conservation Plan Guidance provides a voluntary framework for issuing programmatic take permits to wind facilities that incorporate scientifically supportable advanced conservation practices (ACPs). Under these rules, the Service can issue permits that authorize individual instances of take of bald and golden eagles when the take is associated with, but not the purpose of, an otherwise lawful activity, and cannot practicably be avoided. To date, the USFWS has not approved any ACPs, citing the lack of evidence for 'scientifically supportable measures.' The Eagle Detection and Deterrents Research Gaps and Solutions Workshop was convened at the National Renewable Energy Laboratory in December 2015 with a goal to comprehensively assess the current state of technologies to detect and deter eagles from wind energy sites and the key gaps concerning reducing eagle fatalities and facilitating permitting under the BGEPA. During the workshop, presentations and discussions focused primarily on existing knowledge (and limitations) about the biology of eagles as well as technologies and emerging or novel ideas, including innovative applications of tools developed for use in other sectors, such as the U.S. Department of Defense and aviation. The main activity of the workshop was the breakout sessions, which focused on the current state of detection and deterrent technologies and novel concepts/applications for detecting and minimizing eagle collisions with wind turbines. Following the breakout sessions, participants were asked about their individual impressions of the relative priority of each of the existing and novel ideas.

17 WIND ENERGY↗
DOE OSTI2015

Wintering Golden Eagles on the coastal plain of South Carolina

Golden Eagles (Aquila chrysaetos) are rare winter residents in eastern North America, with most found along the Appalachian Mountains and few reported on the coastal plain of the Carolinas. We used remote cameras baited with wild pig (Sus scrofa) and white-tailed deer (Odocoileus virginianus) carcasses to detect, age, and individually identify Golden Eagles on the U.S. Department of Energy’s Savannah River Site on the coastal plain of South Carolina. We identified eight individual Golden Eagles during the winters of 2013–2014 and 2014–2015, with one detected during both winters. We detected eagles for 19 and 66 calendar days during the winters of 2013–2014 and 2014–2015, respectively, with two adult eagles detected for 30 and 31 calendar days in 2014–2015. Eagles typically scavenged on carcasses for a few days, left, and then returned when cameras were baited with another carcass, suggesting they had remained in the area. These observations suggest that large tracts of forests on the coastal plain may be important wintering areas for some Golden Eagles and, further, that other areas in the coastal plain of the southeastern United States may also harbor wintering eagles. Identification of wintering areas of Golden Eagles in the east will be an important step in the conservation of this protected species, and camera traps baited with carcasses can be an effective tool for such work.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Hanford Site Bald Eagle Monitoring Report for Fiscal Year 2014

The Bald Eagle (Haliaeetus leucocephalus) plays an important predatory role in the ecosystem and also serves as a national symbol for the United States of America. In 2007, the U.S. Fish and Wildlife Service (USFWS) determined that the population of bald eagles in the lower 48 States had sufficiently recovered, so the species could be removed from the federal endangered and threatened species list. The State of Washington also down-listed Bald Eagles from threatened to sensitive. Federal laws including the Bald and Golden Eagle Protection Act of 1940 and the Migratory Bird Treaty Act of 1918 still provide protection for eagles, their nest trees, and communal night roosts. The National Bald Eagle Management Guidelines, produced by the U.S. Fish and Wildlife Service, provides monitoring and management guidance for Bald Eagles (USFWS 2007). The Department of Energy (DOE) Richland Operations Office has the Bald Eagle Management Plan for the Hanford Site, South-Central Washington (DOE 2013), which defines appropriate protection measures for nests and roost sites based on federal and state guidelines. Monitoring is essential to maintain current biological information about bald eagle abundance and distribution on the Hanford Site, to ensure compliance with protection regulations, and to inform future protection and management efforts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Hanford Site Bald Eagle Monitoring Report for Fiscal Year 2013

The Bald Eagle (Haliaeetus leucocephalus) plays an important predatory role in the ecosystem and also serves as a national symbol for the United States of America. In 2007 the U.S. Fish and Wildlife Service (USFWS) determined that the population of bald eagles in the lower 48 States had sufficiently recovered, so the species could be removed from the federal endangered and threatened species list. The State of Washington also down-listed Bald Eagles from threatened to sensitive. Federal laws including the Bald and Golden Eagle Protection Act of 1940 and the Migratory Bird Treaty Act of 1918 still provide protection for eagles, their nest trees, and communal night roosts. The National Bald Eagle Management Guidelines, produced by the U.S. Fish and Wildlife Service, provides monitoring and management guidance for Bald Eagles (USFWS 2007). The Department of Energy Richland Operations Office (DOE) has the Bald Eagle Management Plan for the Hanford Site, South-Central Washington (DOE 2009) that defines appropriate protection measures for nests and roost sites based on federal and state guidelines. Monitoring is essential to maintain current biological information about bald eagle abundance and distribution on the Hanford Site, to ensure compliance with protection regulations, and to inform future protection and management efforts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Bald Eagle Monitoring Report for Fiscal Year 2012

The Bald Eagle (Haliaeetus leucocephalus) plays an important predatory role in the ecosystem and serves as a national symbol for the United States of America. In 2007 the U.S. Fish and Wildlife Service (USFWS) determined that the population of bald eagles in the lower 48 States had sufficiently recovered, so the species could be removed from the federal endangered and threatened species list. The State of Washington also down-listed Bald Eagles from threatened to sensitive. However, Federal laws including the Bald and Golden Eagle Protection Act of 1940 and the Migratory Bird Treaty Act of 1918 still provide protection for eagles, their nest trees, and communal night roosts. The U.S. Fish and Wildlife Service, The National Bald Eagle Management Guidelines (USFWS 2007), provides monitoring and management guidance for Bald Eagles. The U.S. Department of Energy (DOE), Richland Operations Office (RL) has a Hanford Site bald eagle management plan (DOE 2009) that defines appropriate protection measures for nests and roost sites based on federal and state guidelines. Monitoring is essential to maintain current biological information about bald eagle abundance and distribution on the Hanford Site, to ensure compliance with protection regulations, and to inform future protection and management efforts.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1989

The implementation of the graphics of program EAGLE: A numerical grid generation code on NASA Langley SNS computer system

Program EAGLE (Eglin Arbitrary Geometry Implicit Euler) Numerical Grid Generation System is a composite (multi-block) algebraic or elliptic grid generation system designed to discretize the domain in and/or around any arbitrarily shaped three dimensional regions. This system combines a boundary conforming surface generation scheme and includes plotting routines designed to take full advantage of the DISSPLA Graphics Package (Version 9.0). Program EAGLE is written to compile and execute efficiently on any Cray machine with or without solid state disk (SSD) devices. Also, the code uses namelist inputs which are supported by all Cray machines using the FORTRAN compiler CFT77. The namelist inputs makes it easier for the user to understand the inputs and operation of Program EAGLE. EAGLE's numerical grid generator is constructed in the following form: main program, EGG (executive routine); subroutine SURFAC (surface generation routine); subroutine GRID (grid generation routine); and subroutine GRDPLOT (grid plotting routines). The EAGLE code was modified to use on the NASA-LaRC SNS computer (Cray 2S) system. During the modification a conversion program was developed for the output data of EAGLE's subroutine GRID to permit the data to be graphically displayed by IRIS workstations, using Plot3D. The code of program EAGLE was modified to make operational subroutine GRDPLOT (using DI-3000 Graphics Software Packages) on the NASA-LaRC SNS Computer System. How to implement graphically, the output data of subroutine GRID was determined on any NASA-LaRC graphics terminal that has access to the SNS Computer System DI-300 Graphics Software Packages. A Quick Reference User Guide was developed for the use of program EAGLE on the NASA-LaRC SNS Computer System. One or more application program(s) was illustrated using program EAGLE on the NASA LaRC SNS Computer System, with emphasis on graphics illustrations.

Houston, Johnny L.↗
DOE OSTI2022

Bayesian State-Space Modeling Framework for Understanding and Predicting Golden Eagle Movements Using Telemetry Data

Predicting raptor movements through a wind power plant under given atmospheric and topographical conditions is a crucial first step in the overall goal of quantifying the risk of turbine-related collisions and mortalities. Extracting behavioral traits of golden eagles (Aquila chrysaetos) from telemetry data requires the fusion of noisy and sparse movement data (location, heading, velocity) with a stochastic mathematical representation of the eagles' decision-making processes. In this study, we framed this problem in a Bayesian state-space framework where both observations and decision-making are assumed to be stochastic processes connected through hidden states (mode of flight, intent), and the unknown model parameters are assumed to be random variables that are calibrated using the available telemetry data. This framework allowed for rigorous consideration of underlying uncertainties while allowing for both data and prior biological knowledge to contribute to a probabilistic and predictive agent-based movement model. We implemented and applied the Bayesian framework to understand movement behavior of 23 GPS-tagged golden eagles travelling in the western US for years 2019 and 2020. Our preliminary findings show that the Bayesian state-space framework provides a robust inverse modeling apparatus to decode eagle behavioral characteristics from telemetry data. This study was primarily aimed at verifying and validating the framework with selected golden eagle tracks (both long- and short-ranged), with future research aimed at extending the framework to include multi-mode flight, consideration of atmospheric data and uplift mechanisms, eagle-to-eagle interaction, and eagle-to-turbine interaction.

Bayesian modeling↗