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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 235 records · Page 13

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DOE OSTI2024

Effect of Cathode Cooling in Three-Dimensional Simulations of an Atmospheric Pressure Glow Discharge

The Atmospheric Pressure Glow Discharge (APGD) is a relatively simple and versatile plasma source used in a wide range of applications. Active cooling of the cathode can effectively mitigate instabilities, leading to glow-to-arc transitions. This study investigates the effect of varying the degree of cathode cooling in APGD with a planar cathode in helium. The plasma flow model incorporates mass conservation, chemical species transport, momentum conservation, conservation of thermal energy of heavy species and of electrons, and electrostatics. The model is applied to time-dependent simulations through a three-dimensional computational domain describing the whole discharge, without geometric symmetry or steady-state assumptions. Simulations of an experimentally characterized APGD explore the effects of electric current and cathode cooling—ranging from thermally insulated to extreme convective cooling. Results show the formation of an annular region with high electric field over the cathode surface under conditions of high current and low cooling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Deep-learning-driven simulations of boundary layer clouds over the Southern Great Plains

Abstract. Based on long-term observations at the Southern Great Plains site by the Atmospheric Radiation Measurement (ARM) program for training and validation, a deep-learning model is developed to simulate the daytime evolution of boundary layer clouds (BLCs) from the perspective of land–atmosphere coupling. The model takes ARM measurements (including early-morning soundings and diurnally varying surface meteorological conditions and heat fluxes) as inputs and predicts hourly estimates (including cloud occurrence, the positions of cloud boundaries, and the vertical profile of the cloud fraction) as outputs. The deep-learning model offers good agreement with the observed cloud fields, especially in the accuracy with which cloud occurrence and base height are reproduced. When the inputs are substituted by reanalysis data from ERA5 and MERRA-2, the outputs of the deep-learning model provide a better agreement with observation than the cloud fields extracted from ERA5 and MERRA-2 themselves. Thus, the deep-learning model shows great potential to serve as a diagnostic tool for the performance of physics-based models in simulating stratiform and cumulus clouds. By quantifying biases in clouds and attributing them to the simulated atmospheric state variables versus the model-parameterized cloud processes, this observation-based deep-learning model may offer insights into the directions needed to improve the simulation of BLCs in physics-based models for weather forecasting and climate prediction.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Data and figures for "Integrated modeling of boron powder injection for real-time plasma-facing component conditioning"

This dataset contains raw and processed data, as well as supplementary figures used in the paper titled "Integrated modeling of boron powder injection for real-time plasma-facing component conditioning." The data includes simulation results for boron transport and deposition in DIII-D tokamak scenarios, and processed plots. It provides insights into the effects of boron powder injection on plasma-facing component conditioning and surface composition.

ablative particle injection↗

DOE OSTI2021

Processed Surface Imagery & Raster Imagery taken onboard TigerShark (U3) UAS

Land-surface orthomosaic imagery derived from the images collected using the Micasense Altum Imager on board the UAS TigerShark (U3) on March 11th, 2021 at an altitude of 2000 ft. The Altum takes images of the land surface across five visible bands and one long wave infrared thermal band. The photogrametry software Agisoft PhotoScan v 1.4 is used to align and stitch the images into a larger composet image using the technique of structure from motion image capture to construct a dense cloud and 3-D model of the surface, which is used to produce a digital elevation model of the terraine surveyed and orthomosaic imagery. This dataset contains the raster calculated orthomosaics of various vegetative indicies, which are used to indicate plant health and land surface characteristics, including Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), Normalized Difference Water Index (NDWI), surface temperature, and Enhanced_vegetation_index (EVI). These orthomosaics were collected west of the Starkville, MS, airport, and include natural, agricultural, and industrial land coverage. The images have a resolution of 0.2 m/pix.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021