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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

FSVPy: A python-based package for fluorescent streak velocimetry (FSV)

Predictive constitutive equations that connect easy-to-measure transport properties (e.g., viscosity and conductivity) with system performance variables (e.g., power consumption and efficiency) are needed to design advanced thermal and electrical systems. In this work, we explore the use of fluorescent particle-streak analysis to directly measure the local velocity field of a pressure-driven flow, introducing a new Python package (FSVPy) to perform the analysis. Fluorescent streak velocimetry combines high-speed imaging with highly fluorescent particles to produce images that contain fluorescent streaks, whose length and intensity can be related to the local flow velocity. By capturing images throughout the sample volume, the three-dimensional velocity field can be quantified and reconstructed. We demonstrate this technique by characterizing the channel flow profiles of several non-Newtonian fluids: micellar Cetylpyridinium Chloride solution, Carbopol 940, and Polyethylene Glycol. We then explore more complex flows, where significant acceleration is created due to microscale features encountered within the flow. We demonstrate the ability of FSVPy to process streaks of various shapes and use the variable intensity along the streak to extract position-specific velocity measurements from individual images. Thus, we demonstrate that FSVPy is a flexible tool that can be used to extract local velocimetry measurements from a wide variety of fluids and flow conditions.

Mechanics↗
NASA NTRS1996

Numerical Investigation of Slag Behavior for RSRM

It is known that the flow field of the redesigned solid rocket motor (RSRM) is very complicated due to the complex characteristics of turbulent multi-phase flow, chemical reaction, particle combustion, evaporation, breakup and agglomeration etc. It requires multi-phase calculations, chemical reaction simulation, and particle combustion, evaporation, and breakup models to obtain a better understanding of thermophysics for the RSRM design using numerical methods. Also, the slag buildup due to the molten particles is another factor affecting the performance of the RSRM. To achieve this goal, the volume of fluid (VOF) method is used to capture the free surface motion so as to simulate the accumulation of the molten particles (slag) of the RSRM. A finite rate chemistry model is used to simulate the chemical reaction effects. For multi-phase calculations, the Hermsen combustion model is used for the aluminum particle combustion analysis and the Taylor Analogy Breakup (TAB) model is used for the particle breakup analysis. An interphase mas-exchange model introduced by Spalding is used for the evaporation calculation. The particle trajectories are calculated using a one-step implicit method for several groups of particle sizes by which the drag forces and heat fluxes are then coupled with the gas phase equations. The preliminary results predicted a reasonable physical simulation of the particle effects using a simple two dimensional solid rocket motor configuration. It shows that the AL/AL2O3 particle sizes are reduced due to the combustion, evaporation, and breakup. The flow field is disturbed by the particles. Mach number distributions in the nozzle are deformed due to the effect of particle concentrations away from the center line.

Liaw, P.↗
DOE OSTI2020

SRF Fixture Design and HOM analysis

A particle accelerator can either be a normal conducting or a superconducting accelerator. While a superconducting accelerator is a more energy efficient option, they traditionally use a liquid helium bath to achieve the temperatures needed for superconductivity. This makes superconducting accelerators operationally complex and expensive. To make superconducting accelerators a more commercially viable option IARC is working on a cryogen free accelerator which can be seen below.

43 PARTICLE ACCELERATORS↗
NASA NTRS1992

SN 1987A - The impact of greater than 50 MeV gamma-ray luminosity limits on theories of particle acceleration

Analysis of the data obtained from two flights of a balloonborne gamma-ray detector to observe SN 1987A was completed. The detector, which included a spark chamber to determine the arrival directions of the photons, was sensitive in the energy range 50-500 MeV. The 95 percent confidence upper limit to the flux on day 55 after the explosion has been established to be 1.1 x 10 exp -5 photons/sq cm/s and on day 407 to be 3.4 x 10 exp -5 photons/sq cm/s. These limits are compared with various theoretical predictions.

Sood, R. K.↗
NASA NTRSDate not supplied

Understanding PIP Measurements of Particle Shape via Image Analysis

A number of instruments exist to measure the size, shape and orientation angle of precipitation particles near the surface; this study will specifically focus on three of them: the precipitation imaging package (PIP), the multi-angle snowflake camera (MASC), and the two-dimensional video distrometer (2DVD). The measurements of particular interest for developing precipitation microphysical retrievals from polarimetric radar and satellite-based microwave data are of the particle size, aspect ratio, and orientation angle. Due to differences in instrument design and processing software, however, the measurements made by PIP, MASC, and 2DVD are not in agreement on these key measurements. The aim of the present study is to understand how the differences between these three instruments impact their measurements of the size, aspect ratio, and orientation angle of winter precipitation particles. To this end, we have reprocessed the video files produced by PIP in a manner that replicates how the MASC and 2DVD instruments operate and process their respective data. Our findings suggest that the MASC processing software results in superior particle characteristic measurements in comparison to the other instruments, although a cursory comparison of measurements from the actual instruments suggests the PIP captures the largest number of particles of the three instruments, making PIP potentially better for computing distributions.

Charles N. Helms↗
NASA NTRS1998

Particle Detectors and Data Analysis for Cusp Transient Features Campaign

Grant NAG5-5084 was awarded to support the participation of South West Research Institute (SwRI) in building the energy per unit charge particle detectors for the Cusp Transient Features Campaign and analysis of flight data from these instruments. The detectors are part of an instrumented payload (Rocket 36.152, Dr. R. Pfaff, P.I.) launched from Svalbard on December 3, 1997, into the dark cusp. The particle instruments, a Cusp Electron Detector (CED) and a Cusp Ion Detector (CID), built on this project, provided differential energy and angular measurements along the rocket trajectory throughout the flight.

Sharber, J. R.↗
DOE OSTI2025

A versatile machine learning workflow for high-throughput analysis of supported metal catalyst particles

Accurate and efficient characterization of nanoparticles (NPs), particularly regarding particle size distribution, is essential for advancing our understanding of their structure-property relationship and facilitating their design for various applications. In this study, we introduce a novel two-stage artificial intelligence (AI)-driven workflow for NP analysis that leverages prompt engineering techniques from state-of-the-art single-stage object detection and large-scale vision transformer (ViT) architectures. This methodology is applied to transmission electron microscopy (TEM) and scanning TEM (STEM) images of heterogeneous catalysts, enabling high-resolution, high-throughput analysis of particle size distributions for supported metal catalyst NPs. The model's performance in detecting and segmenting NPs is validated across diverse heterogeneous catalyst systems, including various metals (Ru, Cu, PtCo, and Pt), supports (silica (SiO 2 ), γ-alumina (γ-Al 2 O 3 ), and carbon black), and particle diameter size distributions with mean and standard deviations ranging from 1.6 ± 0.2 nm to 9.7 ± 4.6 nm. The proposed machine learning (ML) methodology achieved an average F1 overlap score of 0.91 ± 0.01 and demonstrated the ability to disentangle overlapping NPs anchored on catalytic support materials. The segmentation accuracy is further validated using the Hausdorff distance and robust Hausdorff distance metrics, with the 90th percent of the robust Hausdorff distance showing errors within 0.4 ± 0.1 nm to 1.4 ± 0.6 nm. In conclusion, our AI-assisted NP analysis workflow demonstrates robust generalization across diverse datasets and can be readily applied to similar NP segmentation tasks without requiring costly model retraining.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Alpha particle loss measurements and analysis in JET DT plasmas

Abstract Burning reactor plasmas will be self-heated by fusion born alpha particles from deuterium-tritium reactions. Consequently, a thorough understanding of the confinement and transport of DT-born alpha particles is necessary to maintain the plasma self-heating. Measurements of fast ion losses provide a direct means to monitor alpha particle confinement. JET’s 2021–2022 second experimental DT-campaign offers burning plasma scenarios with advanced fast ion loss diagnostics for the first time in nearly 25 years. Coherent and non-coherent alpha losses were observed due to a variety of low frequency MHD activity. This manuscript will present the loss mechanisms, spatial and pitch dependencies, scalings with plasma parameters, correlations with wall impurities, and magnitude of DT-alpha born losses.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1976

Supersonic Flow of Chemically Reacting Gas-Particle Mixtures. Volume 2: RAMP - A Computer Code for Analysis of Chemically Reacting Gas-Particle Flows

A computer program written in conjunction with the numerical solution of the flow of chemically reacting gas-particle mixtures was documented. The solution to the set of governing equations was obtained by utilizing the method of characteristics. The equations cast in characteristic form were shown to be formally the same for ideal, frozen, chemical equilibrium and chemical non-equilibrium reacting gas mixtures. The characteristic directions for the gas-particle system are found to be the conventional gas Mach lines, the gas streamlines and the particle streamlines. The basic mesh construction for the flow solution is along streamlines and normals to the streamlines for axisymmetric or two-dimensional flow. The analysis gives detailed information of the supersonic flow and provides for a continuous solution of the nozzle and exhaust plume flow fields. Boundary conditions for the flow solution are either the nozzle wall or the exhaust plume boundary.

Penny, M. M.↗
NASA NTRS1972

Applications of activation analysis to geochemical, meteoritic and lunar studies.

The application of activation analysis techniques to the analysis of cosmological materials, i.e., terrestrial, tektitic, meteoritic, and lunar matter, is reviewed. Elemental determinations can be made by instrumental fast-neutron and thermal-neutron activation analysis, photonuclear and charged-particle activation analysis, and by radiochemical neutron activation analysis. Partition-coefficient methods, autoradiography studies, gamma-gamma coincidence counting, and age determination by neutron activation are discussed. Attention is given to K-Ar and I-Xe dating of meteorites.

Showalter, D. L.↗
NASA NTRS1994

Aerosol particles in the upper troposphere and lower stratosphere: Elemental composition and morphology of individual particles in northern midlatitudes

Atmospheric particles were collected in the midlatitude upper troposphere (UT) and lower stratosphere (LS) by inetrial impaction for subsequent electron microscopy and individual particle element analysis. More than 97% of particles analyzed on impactor substrates exposed in the LS contained only O and S in detectable quantities; these particles are believed to be acidic sulfate. Nonsulfate materials seen in the remaining particles included soot, other c-rich substances and crustal materials. Although not predominantly sulfate, usually carried a sulfer-rich coating in the LS. Samples collected very near and just below the tropopause were also dominated by sulfates. The fraction of sulfate particles analyzed on impactor substrates exposed in the UT was 91-94% of the total particle concentration. Nonsulfate substances observed in the UT samples included crustal-type material, hydrated marine salts, carbon-rich materials of several types, and metal-containing substances of uncertain origin. Most of these UT particles were not coated with detectable quantitites of sulfate.

Sheridan, Patrick J.↗
DOE OSTI2022

Particle classification by image analysis improves understanding of corn stover degradation mechanisms during deconstruction

Biomass feedstock heterogeneity is a principal roadblock to implementation of the biorefinery concept. Even within an identical cultivar of corn stover, different bales contain not only varying abundance moisture, ash, glucan, and other chemical compounds, but also varying abundance of tissue anatomies (e.g., leaf, husk, cob, or stalk). These different anatomical components not only differ in their response to pretreatment and enzymatic hydrolysis to glucose, but also vary in their mechanical and conveyance properties. Although this heterogeneous nature of corn stover feedstock has been identified as a challenge, a fundamental knowledge gap of how these tissues behave during biorefining processing remains. Here, we demonstrate the use of a commercial fiber image analyzer typically used for wood fiber characterization to monitor the particle size and shapes of non-woody feedstock during milling, pretreatment, and hydrolysis. Additionally, we present novel use of Gaussian process classification to distinguish bundle, parenchyma, and fiber particles to an accuracy of 96.4%. Quantitative probability distribution plots for characteristics such as length and roundness allow elucidation of particle morphology as pretreatment and enzymatic hydrolysis progress. In both stalk pith and stalk rind, particles peel into individual cells whose walls are subsequently fragmented during enzymatic hydrolysis.

09 BIOMASS FUELS↗
NASA NTRS1990

Particle acceleration in step function shear flows - A microscopic analysis

The transport of energetic particles in a moving, scattering fluid, which has a large shear in its velocity over a distance small compared with the scattering mean free path is discussed. The analysis is complementary to an earlier paper by Earl, Jokipii, and Morfill (1988), which considered effects of more-gradual shear in the diffusion approximation. The case in which the scattering fluid undergoes a step function change in velocity, in the direction normal to the flow is considered. An analytical, approximate calculation and a Monte Carlo analysis of particle motion are presented. It is found that particles gain energy at a rate proportional to the square of the magnitude of the velocity change.

Jokipii, J. R.↗
DOE OSTI2025

Thermal Analysis of a Solid Particle Light-Trapping Planar Cavity Receiver Using Computational Fluid Dynamics

Concentrated solar power (CSP) is one of the most effective ways of harnessing solar power to create efficient, durable, and resilient energy systems. This study entails thermal modeling and analysis of a novel central tower receiver configuration. This receiver uses solid particles as the heat transfer fluid (HTF), a promising option for third-generation CSP systems. The configuration considered here is the light-trapping planar cavity receiver (LTPCR) introduced by the National Renewable Energy Laboratory. While heat transfer studies of various LTPCR subsystems have been done, system-level thermal analysis of the LTPCR receiver has not been attempted. This study also presents important sensitivity analyses of the operating parameters of the CSP system, which can help guide the design of future central tower receivers. This study employs Ansys Fluent as a computational fluid dynamics (CFD) tool to model fluid dynamics and heat transfer in the receiver, intending to quantify its thermal performance. The model seamlessly integrates Monte Carlo ray tracing data, which generates absorbed solar flux profiles from the heliostat field design, with the heat transfer characteristics of the fluidized particle bed. This unified model is designed to accurately predict the thermal behavior of the LTPCR. Analysis of preliminary results reveals that the primary loss mechanisms are radiative and natural convective losses, in that order. Based on observations from a baseline case, several strategies are suggested and numerically tested. These solutions include selective cooling of high-temperature regions and manipulation of particle bed parameters. Selective cooling of high-temperature regions reduced the peak temperature by 151 degrees C and decreased thermal losses by 0.9%. Improving the particle-wall heat transfer coefficient (P-W HTC) of the particle bed decreased the thermal losses by 1.7% and decreased the peak temperatures by 57 degrees C. Decreasing the particle inlet temperature (PIT) also reduced thermal losses by 3.5% and decreased peak temperatures by 29 degrees C. Compounding these strategies improved the thermal losses of the receiver from 13.5% in the baseline case to 7.5%. Additionally, the study explores the variation in thermal performance across different locations of the receiver, where a variation of thermal losses from 12.9% to 17.3% is found. This allows a comprehensive evaluation of potential improvements in efficiency and temperature management.

computational fluid dynamics↗
DOE OSTI2023

Spectro-Microscopy Studies of Atmospheric Particles

Our project investigated composition and physical properties of individual atmospheric particles collected in field campaigns organized by the DOE Atmospheric Systems Research and Atmospheric Radiation Measurement (ASR/ARM) programs, such as the Green Ocean Amazon (GoAmazon, 2014/5), the Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE, 2016/7), the Aerosol and Cloud Experiment in the Eastern North Atlantic (ACE-ENA, 2017/8), the Aerosol–Ice Formation Closure Pilot Study (AEROICESTUDY, 2019) and in additional small-scale supporting field experiments focused on the investigation of the light-absorbing (aka brown carbon) atmospheric particles. In these studies, we investigated the contribution of natural and anthropogenic sources to populations of atmospheric particles during representative atmospheric conditions; characterized particle composition and evaluated their hygroscopic properties and propensity to act as cloud condensation nuclei (CCN) and ice nuclei (IN); correlated typical particle-type and mixing state characteristics with real-time measurements in the areas of studies. We used multi-modal spectro-microscopy techniques to examine elemental and molecular composition, mixing state, size, and higher order morphology for individual particles. Specifically, we used computer-controlled scanning electron microscopy and X-ray microanalysis for quantitative analysis of particle elemental composition, and we used transmission electron microscopy to provide additional information on the distribution of different components within individual particles (particle heterogeneity). We used synchrotron-based scanning transmission X-ray microscopy for quantitative description of the mixing state and molecular bonding of carbon in particles. The particle composition, mixing state, and morphology from analyzed periods was then combined with the real-time ARM measurements of aerosol size distribution, CCN concentration, hygroscopicity, and aerosol bulk composition. Combined together, results of our studies allowed us to assess the major particle sources (biogenic vs. anthropogenic, primary vs secondary) and gain insight into the atmospheric processing of aerosol particles resulting from condensation, coagulation, oxidative aging, and cloud processing. In collaboration with other scientists involved in field campaigns, we carried out statistical analysis of particle properties and their source-specific contributions to regional aerosol loading under representative air mass, meteorological, and cloud conditions.

scanning transmission X-ray microscopy↗
NASA NTRS1987

Particle field holography data reduction by Fourier transform analysis

The size distribution of a particle field hologram is obtained with a Fourier transformation of the Fraunhofer diffraction pattern of the reconstructed hologram. Off-axis absorption holograms of particle fields with known characteristics were obtained and analyzed with a commercially available instrument. The mean particle size of the reconstructed hologram was measured with an error of + or - 5 percent, while the distribution broadening was estimated within + or - 15 percent. Small sections of a pulsed laser hologram of a synthetic fuel spray were analyzed with this method thus yielding a spatially resolved size distribution. The method yields fast and accurate automated analysis of particle field holograms.

Hess, Cecil F.↗
DOE OSTI2021

Interpretation of multiple solutions in fully iterative GF2 and GW schemes using local analysis of two-particle density matrices

Due to the presence of non-linear equations, iterative Green’s function methods can result in multiple different solutions even for simple molecular systems. In contrast to the wave-function methods, a detailed and careful analysis of such molecular solutions was not performed before. In this work, we use two-particle density matrices to investigate local spin and charge correlators that quantify the charge resonance and covalent characters of these solutions. When applied within the unrestricted orbital set, spin correlators elucidate the broken symmetry of the solutions, containing necessary information for building effective magnetic Hamiltonians. Based on GW and GF2 calculations of simple molecules and transition metal complexes, we construct Heisenberg Hamiltonians, four-spin-four-center corrections, and biquadratic spin–spin interactions. These Hamiltonian parameterizations are compared to previous wave-function calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗