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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1978

A distribution model for the aerial application of granular agricultural particles

A model is developed to predict the shape of the distribution of granular agricultural particles applied by aircraft. The particle is assumed to have a random size and shape and the model includes the effect of air resistance, distributor geometry and aircraft wake. General requirements for the maintenance of similarity of the distribution for scale model tests are derived and are addressed to the problem of a nongeneral drag law. It is shown that if the mean and variance of the particle diameter and density are scaled according to the scaling laws governing the system, the shape of the distribution will be preserved. Distributions are calculated numerically and show the effect of a random initial lateral position, particle size and drag coefficient. A listing of the computer code is included.

Fernandes, S. T.↗
NASA NTRS1989

Application of a vectorized particle simulation in high-speed near-continuum flow

An efficient particle simulation technique, developed for use on vector architecture based supercomputers for studying hypersonic rarefied gas flows is employed to simulate the complex wake generated by Mach six flow over a 10 deg half-angle wedge for freestream Reynolds numbers of 1780 and 3560. Data obtained are compared against higher Reynolds number experimental results. Simulations utilized as many as 10 to the 5th computational cells and 10 to the 7th simulated particles having power-law interaction potentials. A code performance of 1.8-2.4 microsec of Cray-2 CPU time to process a single particle per timestep is achieved. Diffuse adiabatic and isothermal wedge surface models are used in this investigation. Although the wedge geometry is two-dimensional, the simulation incorporates a width-wise direction, resulting in a three-dimensional computation.

Woronowicz, Michael S.↗
NASA NTRS1990

Fundamentals of chemistry modeling applicable to a vectorized particle simulation

This paper describes the fundamentals of extending the vectorized particle simulation method derived by Baganoff and McDonald (1990), McDonald and Baganoff (1988), and McDonald (1989) for modeling chemically reacting flows. Details of reaction mechanics per reaction are presented, with particular attention given to the quantum nature of the vibrational mode. The models of reactive flows developed here were verified through a simulation of a superheated diatomic gas relaxing thermochemically to equilibrium in a reservoir.

Haas, Brian L.↗
NASA NTRS2009

Transparent Conveyor of Dielectric Liquids or Particles

The concept of a transparent conveyor of small loose dielectric parti cles or small amounts of dielectric liquids has emerged as an outgro wth of an effort to develop efficient, reliable means of automated re moval of dust from solar cells and from windows of optical instrumen ts. This concept is based on the previously reported concept of an e lectrodynamic screen, according to which a grid-like electric field is established on and near a surface and is moved along the surface p erpendicularly to the grid lines. The resulting electrodynamic force s on loose dielectric particles or dielectric liquid drops in the vic inity would move the particles or drops along the surface. In the or iginal dust-removal application, dust particles would thus be swept out of the affected window area. Other potential applications may occ ur in nanotechnology -- for example, involving mixing of two or more fluids and/or nanoscale particles under optical illumination and/or optical observation.

Calle, Carlos I.↗
NASA NTRS1991

Ablation of silicate particles in high-speed continuum and transition flow with application to the collection of interplanetary dust particles

The ablative deceleration of spheres in the continuum and slip regimes is studied using spherical 7.1-micron-diam soda-lime glass particles launched from vacuum at about 4500 m/sec speed through a 13-micron-thick plastic film into a capture chamber containing Xe at 0.1 or 0.2 atm pressure and 295 K temperature. The results of SEM examinations of the collected ablated particles showed that the ratio of the ablated-particle radius (Rf) to the initial radius (R0) increased with gas pressure (from Rf/R0 about 0.67 at 0.1 atm, to about 0.88 at 0.2 atm). A model was developed to describe the ablation and deceleration of spheres in high-speed continuum and slip flow. The pressure dependence predicted by the model agreed with experimental results.

Rulison, Aaron J.↗
DOE OSTI2025

Outlook towards deployable continual learning for particle accelerators

Particle accelerators are high power complex machines. To ensure uninterrupted operation of these machines, thousands of pieces of equipment need to be synchronized, which requires addressing many challenges including design, optimization and control, anomaly detection and machine protection. With recent advancements, machine learning (ML) holds promise to assist in more advance prognostics, optimization, and control. While ML based solutions have been developed for several applications in particle accelerators, only few have reached deployment and even fewer to long term usage, due to particle accelerator data distribution drifts caused by changes in both measurable and non-measurable parameters. In this paper, we identify some of the key areas within particle accelerators where continual learning can allow maintenance of ML model performance with distribution drifts. Particularly, we first discuss existing applications of ML in particle accelerators, and their limitations due to distribution drift. Next, we review existing continual learning techniques and investigate their potential applications to address data distribution drifts in accelerators. By identifying the opportunities and challenges in applying continual learning, this paper seeks to open up the new field and inspire more research efforts towards deployable continual learning for particle accelerators.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Computational fluid dynamic analysis of a novel particle-to-air fluidized-bed heat exchanger for particle-based thermal energy storage applications

Long-duration energy storage technologies are being targeted to enable cost-effective, decarbonized energy systems. Particle-based thermal energy storage systems are one promising technology by storing excess electricity or heat as sensible thermal energy in inexpensive, solid, inert particles. These systems are only possible if an effective and economical particle-to-working fluid heat exchanger exists. This study predicts the performance of a proposed, direct-contact, particle-to-air, pressurized fluidized-bed heat exchanger using computational fluid dynamics. The common Eulerian-Eulerian framework for modeling fluidized beds is first benchmarked to experimental results at a previously untested operating condition and application. Then, the benchmarked model evaluates the performance of a proposed design for a commercial-scale version of the novel particle-to-air heat exchanger. The results show pressure drop and gas-phase approach temperatures are advantageous compared to other proposed designs for particle-to-air heat exchangers in the literature; approach temperatures were less than 5 °C and gas-phase pressure drop across the fluidized bed was 32 kPa. The model also highlights the importance of gas distributor design and representation in the Eulerian-Eulerian framework to control fluidization behavior. In conclusion, the model built and benchmarked in this study can be leveraged to advance the design and analysis of these heat exchangers critical to the deployment of a promising long-duration energy storage technology.

25 ENERGY STORAGE↗
NASA NTRS2001

Microcalorimetry: The First Two Decades

Our group at GSFC began experimental and theoretical work on microcalorimetry almost twenty years ago, in August of 1982. Over the next 10 months, we completed the initial demonstration of a Si impurity thermometer-based calorimeter as an X-ray spectrometer. This successful demonstration resulted in the development by many investigators of scientific applications for microcalorimeters, ranging from optical spectroscopy to dark matter detection to particle physics applications. Many new technical approaches for cryogenic detectors were proposed by investigators and have been developed. In this presentation, I will describe the early development of microcalorimeters at GSFC and University of Wisconsin and the subsequent rapid growth of this work around the world The key milestones in the early development were the initial spectroscopy demonstrations and the selection of XRS, our microlcalorimeter-based instrument for the Advanced X-ray Astrophysics Facility (AXAF) and ultimately for ASTRO-E. An additional key event was the development of the direct detection of dark matter experiment and the formation of the Center for Particle Astrophysics. Both of these programs provided long term support for this technology in its precarious early days. A major additional technical step in the development of detectors was the demonstration of devices based on superconducting transition edge sensors (TES). These detectors promised (and have delivered) improved energy resolution and higher event rate capabilities. They couple naturally to SQUIDS, which operate well at the low temperatures where the detectors must operate. The past two decades have taken microcalorimeters from their infancy to applications in real experiments. I will provide an overview of the early development of the devices and review the breadth of the present technology and applications.

Moseley, Harvey↗
DOE OSTI2021

Accelerating End-to-End Deep Learning for Particle Reconstruction using CMS open data

Machine learning algorithms are gaining ground in high energy physics for applications in particle and event identification, physics analysis, detector reconstruction, simulation and trigger. Currently, most data-analysis tasks at LHC experiments benefit from the use of machine learning. Incorporating these computational tools in the experimental framework presents new challenges. This paper reports on the implementation of the end-to-end deep learning with the CMS software framework and the scaling of the end-to-end deep learning with multiple GPUs. The end-to-end deep learning technique combines deep learning algorithms and low-level detector representation for particle and event identification. We demonstrate the end-to-end implementation on a top quark benchmark and perform studies with various hardware architectures including single and multiple GPUs and Google TPU.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Single-particle scattering spectroscopy: fundamentals and applications

Metallic nanoparticles supporting a localized surface plasmon resonance have emerged as promising platforms for nanoscopic labels, sensors, and (photo-) catalysts. To use nanoparticles in these capacities, and to gain mechanistic insight into the reactivity of inherently heterogeneous nanoparticles, single-particle characterization approaches are needed. Single-particle scattering spectroscopy has become an important, highly sensitive tool for localizing single plasmonic nanoparticles and studying their optical properties, local environment, and reactivity. In this review, we discuss approaches taken for collecting the scattered light from single particles, their advantages and disadvantages, and present some recent applications. We introduce techniques for the excitation and detection of single-particle scattering such as high-angle dark-field excitation, total internal reflection dark-field excitation, scanning near-field microscopy, and interferometric scattering. We also describe methods to achieve polarization-resolved excitation and detection. We then discuss different approaches for scanning, ratiometric, snapshot, and interferometric hyperspectral imaging techniques used to extract spectral information. Finally, we provide a brief overview of specialized setups for in situ measurements of nanoparticles in liquid systems and setups coupled to scanning tip microscopes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Recent MCNP6 ® Code Developments and Improvements for Nuclear Engineering Applications [Slides]

The Los Alamos MCNP Monte Carlo radiation transport code has been the international gold standard for particle transport applications for over three decades. Many developments to the code have taken place with several significant new feature additions, major improvements, and enhancements to existing features. With significant institutional and programmatic investment in the code since the time of the last public release in 2018, important code development and infrastructure modernization has taken place and remains a high priority for all ongoing efforts across the code development team.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2008

Virtual Energetic Particle Observatory (VEPO)

The Virtual Energetic Particle Observatory (VEPO) focuses on improved discovery, access, and usability of heliospheric energetic particle and ancillary data products from selected spacecraft and sub-orbital instruments of the heliophysics data environment. The energy range of interest extends over the full range of particle acceleration from keV energies of suprathermal seed particles to GeV energies of galactic cosmic ray particles. Present spatial coverage is for operational and legacy spacecraft operating from the inner to the outer heliosphere, e.g. from measurements by the two Helios spacecraft to 0.3 AU to the inner heliosheath region now being traversed by the two Voyager spacecraft. This coverage will eventually be extended inward to ten solar radii by the planned NASA solar probe mission and at the same time beyond the heliopause into the outer heliosheath by continued Voyager operations. The geospace fleet of spacecraft providing near-Earth interplanetary measurements, selected magnetospheric spacecraft providing direct measurements of penetrating interplanetary energetic particles, and interplanetary cruise measurements from planetary spacecraft missions further extend VEPO resources to the domain of geospace and planetary interactions. Ground-based (e.g., neutron monitor) and high-altitude suborbital measurements can expand coverage to the highest energies of galactic cosmic rays affected by heliospheric interaction and of solar energetic particles. Science applications include investigation of solar flare and coronal mass ejection events. acceleration and transport of interplanetary particles within the inner heliosphere, cosmic ray interactions with planetary surfaces and atmospheres, sources of suprathermal and anomalous cosmic ray ions in the outer heliosphere, and solar cycle modulation of galactic cosmic rays. Robotic and human exploration, and eventual habitation, of planetary and space environments beyond the Earth require knowledge of radiation hazards informed by VEPO data resources. The VEPO project has completed the first year of work to define science requirements, to document and register selected data products in SPASE format while evolving SPASE for increased applicability to VEPO data, and to support enhanced discovery and access for these products through the evolving data query and middleware system of the Virtual Heliospheric Observatory (VHO). The VEPO team operates as a heliophysics focus group for energetic particle data resources in partnership with VHO and also leverages existing data services of NASA's Space Physics Data Facility. We invite comments from the U.S. and international data provider and user communities on review of the current VEPO/VHO user interface, on directions for future evolution of VEPO and supporting data systems including VHO and SPDF, and on relations to other elements of the heliophysics virtual observatory environment.

Cooper, John F.↗
DOE OSTI2022

Computational study of inertial migration of prolate particles in a straight rectangular channel

Inertial migration of spherical particles has been investigated extensively using experiments, theory, and computational modeling. Yet, a systematic investigation of the effect of particle shape on inertial migration is still lacking. Herein, we numerically mapped the migration dynamics of a prolate particle in a straight rectangular microchannel using smoothed particle hydrodynamics at moderate Reynolds number flows. After validation, we applied our model to 2:1 and 3:1 shape aspect ratio particles at multiple confinement ratios. Their effects on the final focusing position, rotational behavior, and transitional dynamics were studied. In addition to the commonly reported tumbling motion, for the first time, we identified a new logrolling behavior of a prolate ellipsoidal particle in the confined channel. This new behavior occurs when the confinement ratio is above an approximate threshold value of K = 0.72. Our microfluidic experiments using cell aggregates with similar shape aspect ratio and confinement ratio confirmed this new predicted logrolling motion. In this study, we also found that the same particle can undergo different rotational modes, including kayaking behavior, depending on its initial cross-sectional position and orientation. Furthermore, we examined the migration speed, angular velocity, and rotation period as well as their dependence on both particle shape aspect ratio and confinement ratio. Our findings are especially relevant to the applications where particle shape and alignment are used for sorting and analysis, such as the use of barcoded particles for biochemical assays through optical reading, or the shape-based enrichment of microalgae, bacteria, and chromosomes.

42 ENGINEERING↗
DOE OSTI2024

End-to-end codesign of Hessian-aware quantized neural networks for FPGAs

Here, we develop an end-to-end workflow for the training and implementation of co-designed neural networks (NNs) for efficient field-programmable gate array (FPGA) hardware. Our approach leverages Hessian-aware quantization of NNs, the Quantized Open Neural Network Exchange intermediate representation, and the hls4ml tool flow for transpiling NNs into FPGA firmware. This makes efficient NN implementations in hardware accessible to nonexperts in a single open sourced workflow that can be deployed for real-time machine-learning applications in a wide range of scientific and industrial settings. We demonstrate the workflow in a particle physics application involving trigger decisions that must operate at the 40-MHz collision rate of the CERN Large Hadron Collider (LHC). Given the high collision rate, all data processing must be implemented on FPGA hardware within the strict area and latency requirements. Based on these constraints, we implement an optimized mixed-precision NN classifier for high-momentum particle jets in simulated LHC proton-proton collisions.

47 OTHER INSTRUMENTATION↗