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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Stereo-Optic High Definition Imaging: A New Technology to Understand Bird and Bat Avoidance of Wind Turbines

There is a critical need to develop monitoring tools to track aerofauna (birds and bats) in three dimensions around wind turbines. New monitoring systems will reduce permitting uncertainty by increasing the understanding of how birds and bats are interacting with wind turbines, which will improve the accuracy of impact predictions. Biodiversity Research Institute (BRI), The University of Maine Orono School of Computing and Information Science (UMaine SCIS), HiDef Aerial Surveying Limited (HiDef), and SunEdison, Inc. (formerly First Wind) responded to this need by using stereo-optic cameras with near-infrared (nIR) technology to investigate new methods for documenting aerofauna behavior around wind turbines. The stereo-optic camera system used two synchronized high-definition video cameras with fisheye lenses and processing software that detected moving objects, which could be identified in post-processing. The stereo- optic imaging system offered the ability to extract 3-D position information from pairs of images captured from different viewpoints. Fisheye lenses allowed for a greater field of view, but required more complex image rectification to contend with fisheye distortion. The ability to obtain 3-D positions provided crucial data on the trajectory (speed and direction) of a target, which, when the technology is fully developed, will provide data on how animals are responding to and interacting with wind turbines. This project was focused on testing the performance of the camera system, improving video review processing time, advancing the 3-D tracking technology, and moving the system from Technology Readiness Level 4 to 5. To achieve these objectives, we determined the size and distance at which aerofauna (particularly eagles) could be detected and identified, created efficient data management systems, improved the video post-processing viewer, and attempted refinement of 3-D modeling with respect to fisheye lenses. The 29-megapixel camera system successfully captured 16,173 five-minute video segments in the field. During nighttime field trials using nIR, we found that bat-sized objects could not be detected more than 60 m from the camera system. This led to a decision to focus research efforts exclusively on daytime monitoring and to redirect resources towards improving the video post- processing viewer. We redesigned the bird event post-processing viewer, which substantially decreased the review time necessary to detect and identify flying objects. During daytime field trials, we determine that eagles could be detected up to 500 m away using the fisheye wide-angle lenses, and eagle-sized targets could be identified to species within 350 m of the camera system. We used distance sampling survey methods to describe the probability of detecting and identifying eagles and other aerofauna as a function of distance from the system. The previously developed 3-D algorithm for object isolation and tracking was tested, but the image rectification (flattening) required to obtain accurate distance measurements with fish-eye lenses was determined to be insufficient for distant eagles. We used MATLAB and OpenCV to improve fisheye lens rectification towards the center of the image, but accurate measurements towards the image corners could not be achieved. We believe that changing the fisheye lens to rectilinear lens would greatly improve position estimation, but doing so would result in a decrease in viewing angle and depth of field. Finally, we generated simplified shape profiles of birds to look for similarities between unknown animals and known species. With further development, this method could provide a mechanism for filtering large numbers of shapes to reduce data storage and processing. These advancements further refined the camera system and brought this new technology closer to market. Once commercialized, the stereo-optic camera system technology could be used to: a) research how different species interact with wind turbines in order to refine collision risk models and inform mitigation solutions; and b) monitor aerofauna interactions with terrestrial and offshore wind farms replacing costly human observers and allowing for long-term monitoring in the offshore environment. The camera system will provide developers and regulators with data on the risk that wind turbines present to aerofauna, which will reduce uncertainty in the environmental permitting process.

Adams, Evan↗
DOE OSTI2023

Multi-scale models of whole cells: progress and challenges

Whole-cell modeling is “the ultimate goal” of computational systems biology and “a grand challenge for 21st century”. These complex, highly detailed models account for the activity of every molecule in a cell and serve as comprehensive knowledgebases for the modeled system. Their scope and utility far surpass those of other systems models. In fact, whole-cell models (WCMs) are an amalgam of several types of “system” models. The models are simulated using a hybrid modeling method where the appropriate mathematical methods for each biological process are used to simulate their behavior. Given the complexity of the models, the process of developing and curating these models is labor-intensive and to date only a handful of these models have been developed. While whole-cell models provide valuable and novel biological insights, and to date have identified some novel biological phenomena, their most important contribution has been to highlight the discrepancy between available data and observations that are used for the parametrization and validation of complex biological models. Another realization has been that current whole-cell modeling simulators are slow and to run models that mimic more complex (e.g., multi-cellular) biosystems, those need to be executed in an accelerated fashion on high-performance computing platforms. In this manuscript, we review the progress of whole-cell modeling to date and discuss some of the ways that they can be improved.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Experiences Detecting Defective Hardware in Exascale Supercomputers

In May 2022, the newest supercomputer to top the TOP 500 list was Frontier at Oak Ridge National Laboratory, demonstrating the capability of computing more than 1.1 quintillion (1018) floating-point calculations every second. Driving this ground-breaking rate of computing is Frontier’s more than 37,000 graphics processing units (GPUs) and 9,408 central processing units (CPUs). In total, Frontier contains more than 60 million parts. At this scale, the smallest margin of error may generate hundreds of hardware errors across the system. These errors are capable of directly hindering world-class science performed on Frontier if not found. In this work, we describe and evaluate two strategies for finding hardware-level faults in Frontier’s 9,408 compute nodes. There are two strategies developed: the first uses the Slurm scheduler to scavenge available compute time to run the node screen, the second builds upon the lessons learned in the first strategy and enforces a weekly screen of each node. Using June 2023 as a case study, we find that the first scheduling strategy consumed more than ten times the resources as the second scheduling strategy, but successfully detected five hardware defects in Frontier. We summarize the lessons learned while developing and running a node screen on the world’s first exascale supercomputer.

Hagerty, Nick↗
DOE OSTI2021

On applications of quantum computing to plasma simulations

Quantum computing is gaining increased attention as a potential way to speed up simulations of physical systems, and it is also of interest to apply it to simulations of classical plasmas. However, quantum information science is traditionally aimed at modeling linear Hamiltonian systems of a particular form that is found in quantum mechanics, so extending the existing results to plasma applications remains a challenge. Here, we report a preliminary exploration of the long-term opportunities and likely obstacles in this area. First, we show that many plasma-wave problems are naturally representable in a quantumlike form and thus are naturally fit for quantum computers. Second, we consider more general plasma problems that include non-Hermitian dynamics (instabilities, irreversible dissipation) and nonlinearities. We show that by extending the configuration space, such systems can also be represented in a quantumlike form and thus can be simulated with quantum computers too, albeit that requires more computational resources compared to the first case. Third, we outline potential applications of hybrid quantum–classical computers, which include analysis of global eigenmodes and also an alternative approach to nonlinear simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

University of Rhode Island Regional Earth Systems Center

The primary objective of this program was to establish the URI Regional Earth System Center (“Center”) that would enhance overall societal wellbeing (health, financial, environmental) by utilizing the best scientific information and technology to achieve optimal policy decisions with maximum stakeholder commitment for energy development, coastal environmental management, water resources protection and human health protection, while accelerating regional economic growth. The Center was to serve to integrate existing URI institutional strengths in energy, coastal environmental management, water resources, and human wellbeing. This integrated research, educational and public/private sector outreach Center was to focus on local, state and regional resources. The centerpiece activity of the Center was in the development and implementation of integrated assessment models (IAMs) that both ‘downscaled’ global observations and interpolated/extrapolated regional observations for analyzing the complexity of interactions among humans and the natural climate system to further our understanding and, ultimately, to predict the future state of our regional earth system. The Center was to begin by first ‘downscaling’ existing global earth systems management tools for studying the causes of local, state and regional climate change and potential social and environmental consequences, with a focus on the regional resources identified above. The Center would ultimately need to address the full feedbacks inherent in the nonlinear earth systems by quantifying the “upscaled” impacts of those regional changes on the global earth system. Through an interacting suite of computer simulations that are informed by observations from the nation’s evolving climate observatories, the Center activities integrates climate science, technology, economics, and social policy into forecasts that will inform solutions to pressing issues in regional climate change science, ‘green economy’ investment and climate policy. These project objectives were designed as part of a 5-year program, which would have constituted the initial phase for the establishment of the Center. Almost immediately (i.e. before receiving even the first year of funding) we were informed that we would not be receiving any funding beyond the initial phase; one year. This seriously impacted our ability to deliver on our objectives and, with that, a re-scoping of the Center priorities was designed to fit the 1-year constraints on funding. It was decided that, given the Center’s emphasis on building IAMs, the best way to proceed was to first focus on one particularly important component of the IAM – a natural sciences model that would be useful for research and forecasting of the circualation/ecology/biogeochemistry of RI’s coastal waters. We have succeeded on that necessarily more limited objective, as we will describe below.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Nonlinear model of infection wavy oscillation of COVID-19 in Japan based on diffusion kinetics

The infectious propagation of SARS-CoV-2 is continuing worldwide, and specifically, Japan is facing severe circumstances. Medical resource maintenance and action limitations remain the central measures. An analysis of long-term follow-up reports in Japan shows that the infection number follows a unique wavy oscillation, increasing and decreasing over time. However, only a few studies explain the infection wavy oscillation. This study introduces a novel nonlinear mathematical model of the new infection wavy oscillation by applying the macromolecule diffusion theory. In this model, the diffusion coefficient that depends on population density gives nonlinearity in infection propagation. As a result, our model accurately simulated infection wavy oscillations, and the infection wavy oscillation frequency and amplitude were closely linked with the recovery rate of infected individuals. In conclusion, our model provides a novel nonlinear contact infection analysis framework.

60 APPLIED LIFE SCIENCES↗