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At least 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

A Hybrid CFD/Engineering Model for Predicting Plume Induced Erosion and Cratering

The Descent Interpolated Gas-Granular Erosion Model (DIGGEM) is a hybrid computational fluid dynamics (CFD) / engineering model calibrated with flight data from Apollo. It is used for the prediction of plume induced viscous erosion and cratering during the descent of landing vehicles. The model assumes a functional relationship between local shear stress and eroded mass flux. It is used along with a suite of other tools to predict complex plume induced environments for Human Landing System (HLS) and Commercial Lunar Payload Services (CLPSS) vehicles.

PSI↗
NASA NTRS2016

Probing for Evidence of Plumes on Europa With HST/STIS

Roth et al. (2014a) reported evidence for plumes of water venting from a southern high latitude region on Europa: spectroscopic detection of off-limb line emission from the dissociation products of water. Here, we present Hubble Space Telescope direct images of Europa in the far-ultraviolet (FUV) as it transited the smooth face of Jupiter to measure absorption from gas or aerosols beyond the Europa limb. Out of 10 observations, we found 3 in which plume activity could be implicated. Two observations showed statistically significant features at latitudes similar to Roth et al., and the third at a more equatorial location. We consider potential systematic effects that might influence the statistical analysis and create artifacts, and are unable to find any that can definitively explain the features, although there are reasons to be cautious. If the apparent absorption features are real, the magnitude of implied outgassing is similar to that of the Roth et al. feature; however, the apparent activity appears more frequently in our data.

Planets and satellites↗
NASA NTRS2021

The Dispersion of the Modified Two-Stream and Lower Hybrid Drift Instabilities in the Near-pole Plume of a Magnetically Shielded Hall Thruster

Recent analytical and numerical investigations have shown that instabilities in the lower hybrid frequency range can grow in the plume region downstream of the front magnet pole pieces of a magnetically shielded Hall thruster. Growth of the Modified Two-Stream (MTSI) and Lower Hybrid Drift (LHDI) instabilities was found with wave propagation in the r-z (or in-) plane and azimuthal (or out-of-plane) directions, respectively. In the analysis of the LHDI electron collisions were found to be insufficient to quench the instability in a region contained by the thruster ion beam and hollow cathode plume. The implication of the findings is that ions may be heated anomalously by these instabilities, in both the out-of-plane and in-plane directions, thereby altering the velocity field and enhancing the energy of those ions that strike nearby thruster surfaces. In this article we summarize the solution of the dispersion relation for each of these instabilities and provide additional results that can be compared directly with data from future plasma diagnostics, including with direct measurements of the wave dispersion.

Ortega, A. Lopez↗
NASA NTRS2023

Distributed Spacecraft Mission (DSM) Plume Design Reference Mission (DRM) Inter-Satellite Link Modeling, Analysis and Simulation

NASA Goddard Space Flight Center (GSFC) Radical Innovation Initiative (RI2) plans to focus intently on DSM capability advancements in FY22-24. A DSM mission involves multiple spacecraft, arranged in a constellation, to achieve one or more common goals via the use of inter-satellite links (ISL) between the satellites. Recently, the GSFC Internal Research & Development (IRAD) program established Enceladus as a design reference mission (DRM) for the current DSM effort to foster the conceptual development of communication architecture, requirements, and solutions for future DSM ISL, as well as being able to push other research areas of interest. Enceladus is an icy moon of the planet Saturn. The DRM Enceladus mission concept involves a constellation of 24 small satellites, orbiting Enceladus around 100 km altitude in 3 planes, as observing nodes for science measurement. The mission science data will be sent back to Earth through a relay orbiting Saturn, using the constellation’s inter-satellite links. A QualNet/STK simulation model of the Relay and constellation ISL optical and RF links is developed for the design and optimization of the link and orbital parameters, as well as the inter-networking protocols. Delay Tolerant Networking (DTN) is utilized in the application layer modeling. This paper describes the plume DRM mission concept of an Enceladus constellation to relay science data to Earth and includes the proposed communication architecture and operation concepts. We present details of the QualNet/STK engineering model for this communication scenario to simulate the end-to-end data traffic through multiple layers (physical, data link, networking, transport and application). A link analysis for the constellation’s ISL, constellation to Relay and Direct to Earth (DTE) optical link is provided and discussed. The results of end-to-end traffic simulation for the data throughout/latency evaluation and assessment of the communication architecture are presented. The investigation of the concept of optical multiple access (OMA) for the Plume DRM is discussed. The modeling and simulation methodology developed in this paper is applicable to other DSMs in near Earth and deep space such as Earth-Moon L1/L2 and Lunar regions.

Distributed Spacecraft Mission (DSM) Inter-satelli↗
NASA NTRSDate not supplied

Evaluating Machine Learning Approaches to Plume Tracking

On July 15, 2022, the Hunga Tonga-Hunga Ha’apai (HTHH) submarine volcano erupted, propelling trace gasses and ash through the troposphere and up into the stratosphere. Previous studies manually tracked the aerosol and trace gas plumes over time across different positions in the southern hemisphere. Using imagery from NASA’s Earth Observing System, including MODIS aerosol products and OMI sulfur dioxide products, this research demonstrates how open-source machine learning (ML) models, like Meta’s Segment Anything Model (SAM), can perform automatic plume tracking following the Hunga Tonga eruption. This extensible methodology, and modular data processing and modeling pipeline, establishes a framework for systematically and rapidly studying natural disasters, including additional volcanic eruptions and large-scale wildfires. By combining advanced machine learning techniques, such as SAM’s zero-shot learning, with large volumes of NASA’s Earth Observation and remote sensing data, this work shows how AI and open science can accelerate research and generate actionable results, even for unprecedented events. The tools and technologies presented here can help translate earth science to action from NASA’s current and future Earth observing satellite missions, and assist researchers and stakeholders in understanding, mapping, and responding to natural disasters in a changing world.

machine learning↗
NASA NTRSDate not supplied

Preparations for Laser Rayleigh Scattering Flow Visualization of Inert Ethane Plumes in PSI Environments at the NASA Langley 60-ft Vacuum Sphere

Understanding of the interaction between the plume and the regolith during powered descent are critical for reliable landings and to avoid damaging the vehicle or nearby infrastructure. To further study this complex flowfield, preparations are underway to describe the interrogation of an impinging ethane plume in lunar-relevant conditions within the 60-ft vacuum sphere at LaRC using Rayleigh diagnostics.

Flow Visualization↗
NASA NTRSDate not supplied

Tracking the Hunga Tonga-Hunga Ha’apai Eruption Stratospheric Aerosol and Trace Gas Plumes Using Machine Learning

On January 15, 2022, the Hunga Tonga-Hunga Ha’apai (hereafter, Hunga Tonga) submarine volcano had an explosive eruption that thrusted ash, gases, and water vapor through the troposphere into the stratosphere and mesosphere. Previous studies manually tracked the aerosol and trace gas plumes over time across different positions in the southern hemisphere. Using data retrieved from low earth orbiting satellite instruments (e.g., OMPS, OMI, and CALIPSO), this research demonstrates how open-source machine learning (ML) models, like Meta’s Segment Anything Model (SAM), with prompt engineering can perform automatic plume tracking following the Hunga Tonga eruption. This extensible methodology, and modular data processing and modeling pipeline using NASA Earthdata and Openscapes, establishes a framework for systematically and rapidly studying extreme events, including volcanic eruptions and large-scale wildfires. By combining advanced machine learning techniques, such as SAM’s zero-shot learning, with large volumes of remote sensing data, this work demonstrates how AI and open science can accelerate research and generate actionable results. The tools and technologies presented here can help translate earth science to action from NASA’s current and future Earth observing satellite missions (e.g., the Atmosphere Observing System (AOS)), and assist researchers and stakeholders in understanding, mapping, and responding to natural disasters and extreme events in a changing world.

David M. Giles↗
NASA NTRSDate not supplied

Wall-Jet Evolution During Plume-Surface Interaction Using PLIF Imaging

Planar laser-induced fluorescence (PLIF) flow visualization was used to examine the spatial evolution for the wall-jet formed by an impinging supersonic jet in a large-scale vacuum environment. This canonical configuration is representative of the plume-surface interaction induced by a rocket exhaust plume impinging on the planetary surface at lunar-relevant and Martian-relevant environments. PLIF flow visualization of the very low-density environment (as low as ~0.006% of standard atmospheric density) was performed using seeded nitric oxide in a nitrogen flow at three test conditions. Two conditions are representative of the lunar environment, and one is representative of the Martian environment. The combined images from two simultaneous PLIF views were used to construct a 2D slice of the flowfield spanning approximately 150 mm in height (determined by the laser sheet) and 500 mm in width (determined by the camera views). The three test conditions showed different behavior for the wall-jet, largely due to the different levels of lifting above the surface and the appearance of a physical process similar to a Kelvin–Helmholtz instability for the Martian-relevant case, which appeared to create a dramatic expansion of the wall-jet height with increased radial distance.

PSI↗
NASA NTRSDate not supplied

Wall-Jet Evolution During Plume-Surface Interaction Using PLIF Imaging

Planar laser-induced fluorescence (PLIF) flow visualization was used to examine the spatial evolution for the wall-jet formed by an impinging supersonic jet in a large-scale vacuum environment. This canonical configuration is representative of the plume-surface interaction induced by a rocket exhaust plume impinging on the planetary surface at lunar-relevant and Martian-relevant environments. PLIF flow visualization of the very low-density environment (as low as ~0.006% of standard atmospheric density) was performed using seeded nitric oxide in a nitrogen flow at three test conditions. Two conditions are representative of the lunar environment, and one is representative of the Martian environment. The combined images from two simultaneous PLIF views were used to construct a 2D slice of the flowfield spanning approximately 150 mm in height (determined by the laser sheet) and 500 mm in width (determined by the camera views). The three test conditions showed different behavior for the wall-jet, largely due to the different levels of lifting above the surface and the appearance of a physical process similar to a Kelvin–Helmholtz instability for the Martian-relevant case, which appeared to create a dramatic expansion of the wall-jet height with increased radial distance.

PSI↗
DOE OSTI2023

Milestone 1.2.14: Surface Characterization of Irradiated Surrogate Non-Native Corrosion Plumes on Aluminum 6061-T6 Specimens

The United States Department of Energy is seeking to evaluate the feasibility of extended dry storage of aluminum-clad spent nuclear fuel (ASNF) in helium-backfilled cannisters. A significant research effort has been devoted to determining the amount of radiation-induced molecular hydrogen generation from corrosion layers that would be present on the fuel assembly surfaces. However, to date, no evidence of radiation-induced changes in the microstructure of the corroded aluminum surfaces have been reported. This report provides surface characterization, in terms of corrosion layer composition and morphology, for aluminum alloy 6061-T6 “plume” samples subjected to one of three potential ASNF drying techniques—“vacuum only”, “vacuum + 4 hours at 100 oC”, and “vacuum + 4 hours at 220 oC”—and gamma irradiated (= 53 MGy) in the presence of helium gas with ~0% added relative humidity. At these high absorbed gamma doses, for the first time ever, radiation-induced circular defects were found on the sample surface, regardless of the drying regime employed. Additionally, large cracks that penetrated through the corrosion layer to expose bare aluminum metal were observed in irradiated “plume” specimens subjected to drying conditions of “vacuum + 4 hours at 220 oC”. The nature and implications of these defects on the extended dry storage of ASNF is unclear, requiring further study.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2024

Enhanced Cross-Shelf Exchange by the Eddies Associated With Plume Front

Broadened width of high chlorophyll concentration band with wavy structures, patches, and filaments are often observed along the western coastal next to the Pearl River Estuary over the northern South China Sea shelf during the transition period from winter to summer monsoon. Whereas, there is no such wide band in other seasons. By using a high-resolution numerical model, we reveal that the complex structure and wider band of high coastal chlorophyll concentration results from the smaller scale eddies (about 20–50 km in diameter) associated with buoyant plume-induced salinity front and density fronts, which are roughly along the 30 and 50 m isobaths, respectively. Two trains of eddies are formed along the fronts by the baroclinic instability triggered by frequently alternating winds over the fronts during the period of monsoon transition. The influences of these two trains of eddies are extended in the cross-shelf direction by their interactions, and they can temporally enhance the cross-shelf flow and material exchange. In conclusion, they serve as an efficient pathway to link the inner shelf toward the continental slope.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Fast imaging of laser ablation of cerium: Dependence of plasma plume dynamics and structure on native oxide growth

We have imaged the evolution of plasma following nanosecond pulsed laser ablation of cerium in air with sub-10 ns resolution. We find the ablated plasma plume expansion and shape to be strongly dependent on the time after mechanical polishing of the sample surface. After an initial shock front common to both new and aged samples (velocities up to 16 km s ₋1 ), we observe a second front that is relatively localized to the surface vicinity of newly polished samples, but in the case of older samples it moves outward at velocities of up to 4 km s ₋1 . We attribute this behavior to the formation and growth of a native oxide layer on the order of hours after polishing. These results demonstrate that plasma imaging can be used to diagnose the presence of, and evaluate the extent of, thin surface oxides or other compounds that form soon after exposure to some atmosphere. These findings also highlight the need to explicitly consider the presence of such overlayers when modeling laser/metal interaction, when making measurements of vapor phase chemistry, and when analyzing the composition, phase, and morphology of solid particulates formed after the ablation of reactive metals.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Using the CAP88 Plume Model & Dose Assessment Code for the FTWC Project

The Environmental Protection & Compliance Division (EPC) uses the Clean Air Act Assessment Package – 1988 (CAP88) plume model and dose assessment code to evaluate measured emissions or projected emissions of airborne radionuclides from Los Alamos National Laboratory (LANL) facilities. This software package will use facility data (e.g., stack height and exit velocity), emissions parameters (chemical form and quantity), and environmental data (wind speed and direction) to predict downwind concentrations of radioactive material and subsequent dose to a member of the public at that location. The United States Environmental Protection Agency (EPA) has approved CAP88 for use in demonstrating compliance with the Radionuclide NESHAP2, that portion of the Clean Air Act addressing emissions of airborne radioactive material from Department of Energy facilities. EPC Division has two procedures which discuss the use of CAP88.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2025

CO2 Plume Imaging with Accelerated Deep Learning-based Data Assimilation Considering Multiple Realizations: Application to the Illinois Basin-Decatur Carbon Sequestration Project

We propose a fast and efficient deep learning workflow for near real-time data assimilation, forecasting and visualization of CO2 plume evolution in saline aquifer and demonstrate its application at a field site. Unlike the previous work, this study incorporates the impact of spatial heterogeneity using multiple realizations. In the proposed workflow, a neural network model utilizes available monitoring data such as downhole pressure measurements as input and predicts the propagating pressure ‘front’ using the diffusive time of flight (DTOF) map which is considered as representative reservoir image of the flow field. The DTOF is the arrival time of pressure front propagation, which can be computed by the Fast Marching Method rapidly without flow simulations. Reservoir model calibration can be implemented by selecting the training data samples that describe the predicted DTOF map based on observed data. The power and efficacy of our workflow is demonstrated by application to the Illinois Basin-Decatur Project.

CO2 plume imaging↗