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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 901 records · Page 50
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Numerical Investigation of a Shielded Chevron Nozzle

Reynolds-Averaged Navier-Stokes simulations have been performed on a three-stream inverted velocity profile nozzle with and without various configurations of chevrons attached. The nozzle was mounted on a planform to imitate an engine mounted above a wing, shielding ground observers from engine noise. Several chevron designs intended to aggressively mix the jet and move noise sources upstream for shielding were examined to investigate there effects on noise and thrust. Numerical results for the baseline nozzle and one chevron configuration were compared with far-field noise and particle image velocimetry data obtained in NASA Glenn Research Center's Aero-Acoustic Propulsion Laboratory. A configuration in which chevrons alternate penetration into the primary stream and tertiary fan stream was explored using the Modern Design of Experiments approach. Short, high-penetration chevrons demonstrated a significant noise reduction for a relatively small thrust penalty.

shielding↗
NASA NTRS2019

Numerical Investigation of a Shielded Chevron Nozzle

Reynolds-Averaged Navier-Stokes simulations have been performed on a three-stream invertedvelocity profile nozzle with and without various configurations of chevrons attached.The nozzle was mounted on a planform to imitate an engine mounted above a wing, shieldingground observers from engine noise. Several chevron designs intended to aggressively mix thejet and move noise sources upstream for shielding were examined to investigate their effects onnoise and thrust. Numerical results for the baseline nozzle and one chevron configuration werecompared with far-field noise and particle image velocimetry data obtained in NASA GlennResearch Center’s Aero-Acoustic Propulsion Laboratory. A configuration in which chevronsalternate penetration into the primary stream and tertiary fan stream was explored using theModern Design of Experiments approach. Short, high-penetration chevrons demonstrated asignificant noise reduction for a relatively small thrust penalty.

chevrons↗
NASA NTRS2017

MAVEN observations of tail current sheet flapping at Mars

The Martian magnetotail is a complex regime through which atmospheric particles are lost to space. Our current understanding of Mars' tail continues to develop with the comprehensive particle and field data collected by Mars Atmosphere and Volatile EvolutioN (MAVEN). In this work, we identify periods when MAVEN encounters multiple current sheet crossings through a single tail traversal in order to understand tail dynamics. We apply an analysis technique that has been developed and validated by using multipoint measurements in order to separate the spatial and temporal properties associated with current sheet flapping. Events are classified into periods of steady flapping, due to a global motion of the current sheet, and kink‐like flapping, resulting from localized wave propagation along the tail current sheet. Out of 106 periods during which multiple current sheet crossings were observed, 20 were due to steady flapping and 10 from kink‐like flapping. A majority of the kink‐like events resulted from waves propagating in the opposite direction of the solar wind convection electric field, regardless of their location in the tail, unlike at Earth and Venus. This finding suggests that possible magnetosphere energy sources, whereby plasma is accelerated and removed from the Martian environment, are not located in the central magnetotail; rather, these waves may be driven by a source located at the tail flank based on the direction of the solar wind electric field. Therefore, by identifying potential sources of impulsive energy release in the tail, we may better understand mechanisms that drive atmospheric loss at Mars.

Gina A. DiBraccio↗
NASA NTRS2020

Preparing for Mars 2020 and Future Space Missions: Technology Advancements Driving Contamination Control Requirements and Cleanroom Protocols

Future space exploration missions will force contamination control requirements to become more strict to support increasingly sensitive instrumentation and search for life missions. Driving issues for these extremely clean requirements include increased instrument sensitivity, return sample science, and protecting ambitious mission science objectives. Preparing to meet these requirements mandates that contamination control provide new guidelines and more involved support for the cleanrooms during flight hardware assembly, including establishing better methods for setting cleanroom personnel limits to reduce particle fall out in cleanrooms. Limited literature exists for universal methods of determining cleanroom personnel limits, and what does exist includes mostly theory and assumptions on determining the limit. In this work, published method will be assessed against particle fall out data collected from the ISO 5 cleanrooms of the Mars 2020 Perseverance Rover assembly. Additional evaluations will assess contamination control required cleanroom protocols and the overall success of meeting strict cleanliness requirements of the Adaptive Caching Assembly (ACA) and sample tubes to safeguard future scientific endeavors.

Chen, Nicole↗
NASA NTRSDate not supplied

Ab Initio Electronic Structure Calculations of CNN for CN Excitation Studies

The CN molecule is an important contributor to radiative heat flux in shock layers around vehicles entering Titan’s atmosphere. Current data for heavy particle (de)excitation rate coefficients of CN leads to uncertainties in the population of CN in its first and second excited states. This in turn leads to uncertainties in the radiative heat flux predicted by Computational Fluid Dynamics (CFD) simulations of Titan atmospheric entry. This work performs ab initio electronic structure calculations of the CNN complex to create Potential Energy Surfaces (PESs) that correlate to the ground and first and second excited states of CN. Specifically, the state combinations of CN(X,A,B) + N(4S𝑜) correlate to six states of CNN (three Quintet A” and three Triplet A”). Initial calculations of these states suggest that heavy particle (de)excitation of CN by N atoms is likely to proceed through collinear geometries on triplet surfaces. Complete PESs will show all of the reaction pathways in detail, and will be used in nonadiabatic dynamics calculations to evaluate improved rate coefficients and reduce uncertainty in the radiative heat flux during Titan entry.

Eric C Geistfeld↗
NASA NTRSDate not supplied

Ab Initio Electronic Structure Calculations of CNN for CN Excitation Studies

The CN molecule is an important contributor to radiative heat flux in shock layers around vehicles entering Titan’s atmosphere. Current data for heavy particle (de)excitation rate coefficients of CN leads to uncertainties in the population of CN in its first and second excited states. This in turn leads to uncertainties in the radiative heat flux predicted by Computational Fluid Dynamics (CFD) simulations of Titan atmospheric entry. This work performs ab initio electronic structure calculations of the CNN complex to create Potential Energy Surfaces (PESs) that correlate to the ground and first and second excited states of CN. Specifically, the state combinations of CN(X,A,B) + N(4S𝑜) correlate to six states of CNN (three Quintet A” and three Triplet A”). Initial calculations of these states suggest that heavy particle (de)excitation of CN by N atoms is likely to proceed through collinear geometries on triplet surfaces. Complete PESs will show all of the reaction pathways in detail, and will be used in nonadiabatic dynamics calculations to evaluate improved rate coefficients and reduce uncertainty in the radiative heat flux during Titan entry.

Eric Geistfeld↗
NASA NTRS2023

Satellite characterization of global stratospheric sulfate aerosols released by Tonga volcano

Large volcanic eruptions create an enhanced layer of sulfate aerosols in the stratosphere. These sulfuric acid droplets persist for many months, altering the climate and stratospheric chemistry. Sulfate aerosols scatter sunlight back to space, cooling the surface of the Earth and absorb outgoing thermal radiation, heating the stratosphere. The calculation of the climate impact of sulfate aerosols depends on their physical properties such as droplet size and chemical composition. These properties are not well known, and this uncertainty contributes to the errors in climate model predictions. Here we derive the first empirical formula that predicts the composition of stratospheric sulfate aerosols from volcanic eruptions from the air temperature and water vapor pressure. Measurements of atmospheric infrared transmittance of the Hunga Tonga-Hunga Ha'apai sulfate aerosol plume by the Atmospheric Chemistry Experiment (ACE) satellite were analyzed to determine composition (weight percent of sulfuric acid) and median particle radius. These data are supplemented by measurements of the Raikoke and Nabro eruptions. Our analysis allows the properties of volcanic aerosols in the stratosphere to be predicted reliably in atmospheric models.

P Bernath↗
DOE OSTI2024

Interpreting Transformers for Jet Tagging

Machine learning (ML) algorithms, particularly attention-based transformer models, have become indispensable for analyzing the vast data generated by particle physics experiments like ATLAS and CMS at the CERN LHC. Particle Transformer (ParT), a state-of-the-art model, leverages particle-level attention to improve jet-tagging tasks, which are critical for identifying particles resulting from proton collisions. This study focuses on interpreting ParT by analyzing attention heat maps and particle-pair correlations on the $\eta$-$\phi$ plane, revealing a binary attention pattern where each particle attends to at most one other particle. At the same time, we observe that ParT shows varying focus on important particles and subjets depending on decay, indicating that the model learns traditional jet substructure observables. These insights enhance our understanding of the model's internal workings and learning process, offering potential avenues for improving the efficiency of transformer architectures in future high-energy physics applications.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2010

Micrometeoroid Impacts and Optical Scatter in Space Environment

This paper discusses the results of an attempt to use laboratory test data and empirically derived models to quantify the degree of surface damage and associated light scattering that might be expected from hypervelocity particle impacts in space environment. Published descriptions of the interplanetary dust environment were used as the sources of particle mass, size, and velocity estimates. Micrometeoroid sizes are predicted to be predominantly in the mass range 10(exp -5) g or less, with most having diameters near 1 micrometer, but some larger than I20 micrometers, with velocities near 20 kilometers per second. In a laboratory test, latex ( p = 1.1. grams per cubic centimeter) and iron (7.9 grams per cubic centimeter) particles with diameters ranging from 0.75 micrometers to 1.60 micrometers and with velocities ranging from 2.0 kilometers per second to 18.5 kilometers per second, were shot at a Be substrate mirror that had a dielectric coated gold reflecting surface. Scanning electron and atomic force microscopy were used to measure crater dimensions that were then associated with particle impact energies. These data were then fitted to empirical models derived from solar cell and other spacecraft surface components returned from orbit, as well as studies of impact craters studied on glassy materials returned from the lunar surface, to establish a link between particle energy and impact crater dimension. From these data, an estimate of total expected damaged area was computed and this result produced an estimate of expected surface scatter from the modeled environment.

Heaney, James B.↗
NASA NTRS1978

The problem of low energy particle measurements in the magnetosphere

The accurate measurement of low energy (less than 100 eV) particle properties in the magnetosphere has been difficult, partly because of the low density of such particles, but more particularly because of spacecraft interference effects. Some early examples of how these phenomena have affected particle measurements on an OGO spacecraft are presented. Data obtained with the UCSD particle detectors on ATS-6 are then presented showing how some of these difficulties have been partially overcome. Future measurements of low energy particles in the magnetosphere can be improved by: (1) improving the low energy resolution of detectors; (2) building electrostatically clean spacecraft; (3) controlling spacecraft potential; and (4) using auxiliary measurements, particularly wave data.

Whipple, E. C., Jr.↗
DOE OSTI2025

Measurement of 𝑑 2⁢ 𝜎/𝑑⁢|$\vec{q}$|⁢𝑑⁢𝐸 avail in charged current 𝜈 𝜇 -nucleus interactions at ⟨𝐸 𝜈 ⟩=1.86 GeV using the NOvA Near Detector

Double- and single-differential cross sections for inclusive charged-current 𝜈 𝜇 -nucleus scattering are reported for the kinematic domain 0 to 2 GeV/𝑐 in three-momentum transfer and 0 to 2 GeV in available energy, at a mean 𝜈 𝜇 energy of 1.86 GeV. The measurements are based on an estimated 995,760 𝜈 𝜇 charged-current (CC) interactions in the scintillator medium of the NOvA Near Detector. The subdomain populated by 2-particle-2-hole (2p2h) reactions is identified by the cross section excess relative to predictions for 𝜈 𝜇 -nucleus scattering that are constrained by a data control sample. Models for 2-particle-2-hole processes are rated by 𝜒 2 comparisons of the predicted-versus-measured 𝜈 𝜇 CC inclusive cross section over the full phase space and in the restricted subdomain. Shortfalls are observed in neutrino generator predictions obtained using the theory-based València and SuSAv2 2p2h models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2013

Scattering Properties of Lunar Dust Analogs

A number of space missions are planned to explore the lunar exosphere which may contain a small population of dust particles. The objective of this paper is to present preliminary results from scattering experiments on a suspension of lunar simulants to support one such mission. The intensity of the light scattered from a lunar simulant is measured with a commercial version of the spectrometer used in the forthcoming LADEE mission. Physical properties of the lunar simulant are described along with two similarly-sized reference microspheres. We confirm that micron-sized particles tend to form agglomerates rather than remaining isolated entities and that certain general characteristic of the target particles can be predicted from intensity measurements alone. These results can be used directly to assess general features of the lunar exosphere from LADEE instrument data. Further analysis of particle properties from such remote sensing data will require measurements of polarization signatures.

Lunar dust↗
DOE OSTI2020

Data Assimilative Optimization of WSA Source Surface and Interface Radii using Particle Filtering

TheWang-Sheeley-Arge (WSA) model estimates solar wind speed and interplanetary magnetic field polarity in the inner heliosphere using global photospheric magnetic field maps. WSA employs the Potential Field Source Surface (PFSS) and Schatten Current Sheet (SCS) models to determine the Sun's global coronal magnetic field. The PFSS and SCS models are connected through two radial parameters, the source surface and interface radii, which specify the overlap region between the inner SCS and outer PFSS models. Though both radii values are adjustable, they have typically been fixed to 2.5 solar radii. Our work highlights how solar wind predictions improve when the radii are allowed to vary over time. Data assimilation using particle filtering (sequential Monte Carlo) is used to infer optimal values over a fixed time window. Solar wind model predictions and satellite observations are compared with a newly developed quality-of-agreement prediction metric. The agreement metric between the model and observations is assumed to correspond to the probability of the two key WSA model parameters, the source surface and interface radii, where the highest metric value implies the optimal radii.We find that the optimal particle filter values of solar radii can perform twice as well as standard values for an exploratory period during Carrington Rotation 1901, with these values also reducing nonphysical kinking effects seen in solar magnetic field lines. Data assimilation choices of input realization and time frame have implications for variation in the solar wind over time. We present this work's theoretical context and practical applications for prediction accuracy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Charged particle tracking in real-time using a full-mesh data delivery architecture and associative memory techniques

We present a flexible and scalable approach to address the challenges of charged particle track reconstruction in real-time event filters (Level-1 triggers) in collider physics experiments. The method described here is based on a full-mesh architecture for data distribution and relies on the Associative Memory approach to implement a pattern recognition algorithm that quickly identifies and organizes hits associated to trajectories of particles originating from particle collisions. We describe a successful implementation of a demonstration system composed of several innovative hardware and algorithmic elements. The implementation of a full-size system relies on the assumption that an Associative Memory device with the sufficient pattern density becomes available in the future, either through a dedicated ASIC or a modern FPGA. We demonstrate excellent performance in terms of track reconstruction efficiency, purity, momentum resolution, and processing time measured with data from a simulated LHC-like tracking detector.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Addressing the data and real-time challenges in large scale particle physics experiments through AI and in situ computing technologies

Modern high energy physics experiments are faced not only with the challenge of having to deal with extremely high data rates but with the need to process data quickly to meet real time constraints. At Fermilab, we explore the use of novel computing technologies and techniques to address these challenges. I will discuss my R&D efforts in applying such computing solutions to enhance the multi-messenger astronomy capabilities and improve the overall physics performance of large-scale LArTPC based neutrino experiments. These efforts offer excellent opportunities for fruitful collaboration.

43 PARTICLE ACCELERATORS↗
NASA NTRS1986

Retrieval of aerosol size distribution moments from multiwavelength particulate extinction data

An iterative method for deriving the particle size distribution from multiwavelength satellite remote sensing data is presented and its use illustrated with an application to SAGE II data. The compression size distribution method (CSD) features interpolation and look-up features for relating the coefficients of a least-squares fit as a function of wavelength to parameters of the compression function that have been obtained by Mie calculations. Results are reported of comparisons between particulate radii predicted for the El Chichon volcano aerosol based on SAGE II data and 14 radii measured with NASA flights through the aerosol with aircraft carrying wire impactors.

Livingston, J. M.↗
DOE OSTI2024

ACE-ENA: Fast Liquid Water Content

These data were collected during the Aerosol and Cloud Experiments in the Eastern North Atlantic field campaign as part of ARM Aerial Facility deployment (ACE-ENA, https://www.arm.gov/research/campaigns/aaf2017ace-ena). The ARM Aerial Facility Gulfstream-1 was deployed at Lajes Air Base (IATA: TER, ICAO: LPLA), on Terceira Island in the Azores, Portugal, for the two Intensive Observation Periods from June 20 through July 22, 2017 (IOP#1) and from January 11 through February 22, 2018 (IOP#2). The G-1 aircraft performed 20+19 research flights over the ARM Eastern North Atlantic (ENA) site and Atlantic Ocean to measure atmospheric turbulence, cloud water content and drop size distributions, aerosol precursor gases, aerosol chemical composition and size distributions. The current data set presents re-processed Particle Volume Monitor PVM-100A (aka Gerber probe) data: Liquid Water Content (LWC), Particle Surface Area (PSA), and the effective droplet radius (re) averaged to 50 Hz, 10 Hz, and 1 Hz.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

CACTI: Fast Liquid Water Content

These data were collected during the Cloud, Aerosol, and Complex Terrain Interactions (CACTI; https://www.arm.gov/research/campaigns/amf2018cacti ) field campaign in the Sierras de Córdoba mountain range of north-central Argentina as part of the ARM Aerial Facility (AAF) deployment. The ARM Aerial Facility Gulfstream-1 was operated from Las Higueras Airport (IATA: RCU, ICAO: SAOC), Río Cuarto, Córdoba, Argentina, for the Intensive Observation Period (IOP) from Nov. 1 through Dec. 15, 2018. The G-1 aircraft performed 22 research flights over the first ARM Mobile Facility (AMF1) location in the Sierras de Córdoba mountain range to measure atmospheric state and turbulence, cloud water content and droplet size distributions, aerosol precursor gases, and aerosol chemical composition and size distributions. The current data set presents re-processed Particle Volume Monitor PVM-100A (aka Gerber probe) data: Liquid Water Content (LWC), Particle Surface Area (PSA), and the effective droplet radius (re) averaged to 50Hz, 10Hz, and 1Hz.

54 ENVIRONMENTAL SCIENCES↗