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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Classification of Cloud Particle Imagery from Aircraft Platforms Using Convolutional Neural Networks

Abstract A vast amount of ice crystal imagery exists from a variety of field campaign initiatives that can be utilized for cloud microphysical research. Here, nine convolutional neural networks are used to classify particles into nine regimes on over 10 million images from the Cloud Particle Imager probe, including liquid and frozen states and particles with evidence of riming. A transfer learning approach proves that the Visual Geometry Group (VGG-16) network best classifies imagery with respect to multiple performance metrics. Classification accuracies on a validation dataset reach 97% and surpass traditional automated classification. Furthermore, after initial model training and preprocessing, 10 000 images can be classified in approximately 35 s using 20 central processing unit cores and two graphics processing units, which reaches real-time classification capabilities. Statistical analysis of the classified images indicates that a large portion (57%) of the dataset is unusable, meaning the images are too blurry or represent indistinguishable small fragments. In addition, 19% of the dataset is classified as liquid drops. After removal of fragments, blurry images, and cloud drops, 38% of the remaining ice particles are largely intersecting the image border (≥10% cutoff) and therefore are considered unusable because of the inability to properly classify and dimensionalize. After this filtering, an unprecedented database of 1 560 364 images across all campaigns is available for parameter extraction and bulk statistics on specific particle types in a wide variety of storm systems, which can act to improve the current state of microphysical parameterizations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Responding To A Downed Unmanned Aircraft System (UAS) Platform

A drone may be forced down as part of a kinetic Counter-UAS action or as a spoof signal with a command to land immediately. A drone could also be incidentally discovered by an employee or by a random patrol. In each case, the platform should be considered a suspicious package until it can be determined to be nonhazardous by qualified personnel.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2023

Impacts of Regional Air Mobility and Electrified Aircraft on Local Grid Infrastructure and Airport Electricity Demand

The goal of this work is to analyze the electrical infrastructure that may be necessary to serve electrified aviation at a subset of airports where potential electrified flight demand has been provided. Additionally, this work will estimate the amount of onsite distributed energy resources (i.e., solar photovoltaics and battery energy storage systems) that could be used to serve EA in cost effective scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

TRACER-Uncrewed Aircraft System (TRACER-UAS) Field Campaign Report

Convective processes drive the development of clouds across a variety of scales, thereby playing a central role in governing weather and climate globally. These processes help to set the stage for circulations that redistribute heat and moisture throughout the lower atmosphere, and simultaneously develop storms that supply precipitation to regions that depend on such rain events for supporting a variety of societal needs. At the same time, extreme precipitation events can result in localized flooding of low-lying areas, posing hazards to transportation and regional inhabitants, and potentially damaging structures and infrastructure. As a result, there is an inherent need to better understand the drivers and modulators of clouds and precipitation and leverage such understanding to make projections of how these important systems may evolve with a changing climate. With nearly three billion of Earth’s human inhabitants living within 200 km of a shoreline, development of such understanding is particularly important in coastal regimes. Central drivers of convective cloud development and life cycle in coastal environments include synoptic forcing, local meso- and microscale circulation regimes, microphysical evolution, and aerosol properties. Atmospheric boundary layer (ABL) development and its evolution can help drive the formation and organization of convective clouds, which then impart their own controls through dynamic processes related to latent heating and cooling (including cold-pool formation and propagation), three-dimensional radiative effects, and background environmental conditions (Fan et al. 2016). Such clouds have been contributing to record precipitation events in southeast Texas in recent years, relative to the last several decades of data from regional precipitation gauges (Fagnant et al. 2020). The greater Houston urban area has experienced particularly large increases in the frequency of extreme rainfall events, with enhanced intensity of extreme events (stretching of distribution tails) having potentially significant implications for watershed floodplain planning and mapping in greater Houston and Harris County. While the most extreme precipitation events were associated with tropical cyclones (e.g., Tropical Storm Allison and Hurricane Harvey; Blood 2014, Kao et al. 2019), strong thunderstorms can also deliver large amounts of precipitation over the area over relatively short periods.

54 ENVIRONMENTAL SCIENCES↗