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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Interaction of Particles and Turbulence in the Solar Nebula

The most widely accepted theories for the formation of the Solar system claim that small solid particles continue to settle into a thin layer at the midplane of the Solar nebula until it becomes gravitationally unstable and collapses directly into km-sized planetesimals. This scenario has been challenged on at least two grounds: (1) due to turbulence, the particles may not settle into a thin layer, and (2) a thin layer may not be unstable. The Solar nebula contains at least three sources of turbulence: radial shear, vertical shear, and thermal convection. The first of these is small and probably negligible, while the last is poorly understood. However, the second contribution is likely to be substantial. The particle-rich layer rotates at nearly the Keplerian speed, but the surrounding gaseous nebula rotates slower because it is partly supported by pressure. The resulting shear generates a turbulent boundary layer which stirs the particles away from the midplane, and forestalls gravitational instability. Our previous work used a 'zero-equation' (Prandtl) model to predict the intensity of shear-generated turbulence, and enabled us to demonstrate numerically that settling of particles to the midplane is self-limiting. However, we neglected the possibility that mass loading by particles might damp the turbulence. To explore this, we have developed a more sophisticated 'one-equation' model which incorporates local generation, transport, and dissipation of turbulence, as well as explicit damping of turbulence by particles. We also include a background level of global turbulence to represent other sources. Our results indicate that damping flattens the distribution of particles somewhat, but that background turbulence thickens the particle layer.

Dacles-Mariani, Jennifer S.↗
DOE OSTI2020

Calorimetry with deep learning: particle simulation and reconstruction for collider physics

Using detailed simulations of calorimeter showers as training data, we investigate the use of deep learning algorithms for the simulation and reconstruction of single isolated particles produced in high-energy physics collisions. We train neural networks on single-particle shower data at the calorimeter-cell level, and show significant improvements for simulation and reconstruction when using these networks compared to methods which rely on currently-used state-of-the-art algorithms. We define two models: an end-to-end reconstruction network which performs simultaneous particle identification and energy regression of particles when given calorimeter shower data, and a generative network which can provide reasonable modeling of calorimeter showers for different particle types at specified angles and energies. We investigate the optimization of our models with hyperparameter scans. Furthermore, we demonstrate the applicability of the reconstruction model to shower inputs from other detector geometries, specifically ATLAS-like and CMS-like geometries. These networks can serve as fast and computationally light methods for particle shower simulation and reconstruction for current and future experiments at particle colliders.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2023

Oxidation of Silicon Particles Suspended in Mullite Matrix With Dual-Mode Vacancy Diffusion of Oxygen

Mullite bond coats filled with silicon particles have recently been proposed for the next generation of environmental barrier coatings (EBCs). The sacrificial oxidation of the silicon particles eliminates some of the environmental durability issues associated with traditional EBC designs. To investigate this novel design approach, a mathematical formulation and resulting numerical method have been developed for simulating the oxidation of silicon particles embedded in a mullite matrix. The focus is on the oxidation of the silicon in a dry oxygen environment where the oxidant is presumably oxygen. Oxygen transport from the exterior environment through the mullite is assumed to occur via two lattice defect diffusion mechanisms. As a result, the rate of oxygen transport is dictated by the self-diffusivity of the lattice defects. The numerical method is implemented using the COMSOL Multiphysics® program (COMSOL, Inc.). The method is applied to simulate the oxidation of silicon particles in a mullite pellet in recent oxidation experiments. Numerical results compare favorably with the oxidation behavior observed in the oxidation experiments. The numerical method is also used to investigate the effects of various features of the mullite-silicon particle system on the oxidation behavior.

silicon oxidation↗
DOE OSTI2021

Deuterated polyethylene nanowire arrays for high-energy density physics

Abstract The interaction of intense, ultrashort laser pulses with ordered nanostructure arrays offers a path to the efficient creation of ultra-high-energy density (UHED) matter and the generation of high-energy particles with compact lasers. Irradiation of deuterated nanowires arrays results in a near-solid density environment with extremely high temperatures and large electromagnetic fields in which deuterons are accelerated to multi-megaelectronvolt energies, resulting in deuterium–deuterium (D–D) fusion. Here we focus on the method of fabrication and the characteristics of ordered arrays of deuterated polyethylene nanowires. The irradiation of these array targets with femtosecond pulses of relativistic intensity and joule-level energy creates a micro-scale fusion environment that produced $2\times {10}^6$ neutrons per joule, an increase of about 500 times with respect to flat solid CD 2 targets irradiated with the same laser pulses. Irradiation with 8 J laser pulses was measured to generate up to 1.2 × 10 7 D–D fusion neutrons per shot.

Optics↗
NASA NTRS1983

Dependence of 50-keV upstream ion events at IMP 7 and 8 upon magnetic field bow shock geometry

Results are presented for a statistical study of four years (1972-1976) of IMP 7 and 8 observations at approximately 40 R(E) of 50-200 keV upstream ion events measured with the Energetic Particle Experiment. A monotonic increase in the probability of observing upstream particle events is found with a decrease in the angle (theta-Bn) between the interplanetary magnetic field (IMF) and the local shock normal at the point where the IMF intersects the bow shock, independent of the length of time of bow shock connections exceeding approximately 10 min. Approximately equal probabilities are found for observing an event above a given flux from any portion of the bow shock with the same value of theta-Bn, a growth time of the 50-200 keV events of approximately 10 min, a maximum attainable flux of approximately 25,000/sq cm s sr, and a positive correlation between the probability of exceeding a given flux and the 3 hr Kp index. It is concluded that the local structure of the bow shock in the immediate vicinity of the field line connection is the dominant influence in the generation process of energetic upstream particle events and that wave-particle interactions produce a self-throttling mechanism that limits the maximum flux of ions escaping the upstream foreshock.

Mitchell, D. G.↗
DOE OSTI2025

Isotopic analysis of Nd nanoparticles using single particle MC-ICP-MS: A comparative study with single particle-ICP-TOF-MS

Single particle - inductively coupled plasma - mass spectrometry (SP-ICP-MS) is a powerful technique for characterization of the elemental and isotopic composition of individual particles. In this work, the capabilities of the newest generation of MC-ICP-MS with acquisition rates down to 50 ms were evaluated for single particle analysis, with a focus on isotopic precision achievable on a single-particle level. Nd (NdVO 4 ) nanoparticles (~120 nm in diameter) were used as case study and were first characterized in terms of mass (respective size) and particle number concentration by SP-ICP-TOF-MS and then by SP-MC-ICP-MS for isotopic precision. For the isotopic ratio measurements, the MC-ICP-MS performance was compared to the ICP-TOF-MS and it was found that the isotope ratio precision was increased (R 2 between 0.98 and 0.99) compared to ICP-TOF-MS (R 2 between 0.88 and 0.97). The accuracy attained on a single particle level, was compared to bulk digestion followed by MC-ICP-MS analysis, and the SP-MC-ICP-MS technique was able to determine the particle population average to be <4 %, percent relative differences for the 142 Nd/ 144 Nd, 143 Nd/ 144 Nd, 145 Nd/ 144 Nd, 146 Nd/ 144 Nd, and 148 Nd/ 144 Nd ratios The detection limit for the SP-MC-ICP-MS approach was also assessed. Here, when utilizing an all Faraday-cup based detection scheme the determined LOD for the measurements was 0.2fg for Nd, per particle. Based on these results, the newest generation of MC-ICP-MS has demonstrated its utility for performing SP measurement, particularly when high precision isotopic determination is warranted.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Super-resolving microscopy images of Li-ion electrodes for fine-feature quantification using generative adversarial networks

Abstract For a deeper understanding of the functional behavior of energy materials, it is necessary to investigate their microstructure, e.g., via imaging techniques like scanning electron microscopy (SEM). However, active materials are often heterogeneous, necessitating quantification of features over large volumes to achieve representativity which often requires reduced resolution for large fields of view. Cracks within Li-ion electrode particles are an example of fine features, representative quantification of which requires large volumes of tens of particles. To overcome the trade-off between the imaged volume of the material and the resolution achieved, we deploy generative adversarial networks (GAN), namely SRGANs, to super-resolve SEM images of cracked cathode materials. A quantitative analysis indicates that SRGANs outperform various other networks for crack detection within aged cathode particles. This makes GANs viable for performing super-resolution on microscopy images for mitigating the trade-off between resolution and field of view, thus enabling representative quantification of fine features.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

Efficient Hot Electron Transfer from Small Au Nanoparticles

Many important chemical transformations enabled by plasmonic hot carrier photocatalysis have been reported, although their efficiencies are often too low for practical applications. Here, we examine how the efficiency of plasmon-induced hot electron transfer depends on the Au particle size in Au-tipped CdS nanorods. We show that with decreasing Au size, the plasmon width increases due to enhanced surface damping contributions. The excitation of Au nanoparticles leads to an instrument response time-limited ultrafast hot electron transfer process to CdS ($\ll$140 fs). The quantum efficiency of this process increases from ~1% to ~18% as the particle size decreases from 5.5 ± 1.1 to 1.6 ± 0.5 nm due to both enhanced hot electron generation and transfer efficiencies in small Au particles. Our finding suggests that decreasing plasmonic particle size is an effective approach for improving plasmon-induced hot carrier transfer efficiency and provides important insight for the rational improvement of plasmonic hot carrier-based devices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

A better way to define dark matter haloes

ABSTRACT Dark matter haloes have long been recognized as one of the fundamental building blocks of large-scale structure formation models. Despite their importance – or perhaps because of it! – halo definitions continue to evolve towards more physically motivated criteria. Here, we propose a new definition that is physically motivated, effectively unique, and parameter-free: ‘A dark matter halo is comprised of the collection of particles orbiting in their own self-generated potential’. This definition is enabled by the fact that, even with as few as ≈300 particles per halo, nearly every particle in the vicinity of a halo can be uniquely classified as either orbiting or infalling based on its dynamical history. For brevity, we refer to haloes selected in this way as physical haloes. We demonstrate that (1) the mass function of physical haloes is Press–Schechter, provided the critical threshold for collapse is allowed to vary slowly with peak height; and (2) the peak-background split prediction of the clustering amplitude of physical haloes is statistically consistent with the simulation data, with accuracy no worse than ≈5 per cent.

Astronomy & Astrophysics↗
NASA NTRS1999

Heterogeneous Combustion of Porous Graphite Particles in Normal and Microgravity

Combustion of solid fuel particles has many important applications, including power generation and space propulsion systems. The current models available for describing the combustion process of these particles, especially porous solid particles, include various simplifying approximations. One of the most limiting approximations is the lumping of the physical properties of the porous fuel with the heterogeneous chemical reaction rate constants. The primary objective of the present work is to develop a rigorous model that could decouple such physical and chemical effects from the global heterogeneous reaction rates. For the purpose of validating this model, experiments with porous graphite particles of varying sizes and porosity are being performed at NASA Lewis Research Center. The details of the experimental and theoretical model development effort are described.

Chelliah, Harsha↗
NASA NTRS2001

Heterogenous Combustion of Porous Graphite Particles in Normal and Microgravity

Combustion of solid fuel particles has many important applications, including power generation and space propulsion systems. The current models available for describing the combustion process of these particles, especially porous solid particles, include various simplifying approximations. One of the most limiting approximations is the lumping of the physical properties of the porous fuel with the heterogeneous chemical reaction rate constants. The primary objective of the present work is to develop a rigorous model that could decouple such physical and chemical effects from the global heterogeneous reaction rates. For the purpose of validating this model, experiments with porous graphite particles of varying sizes and porosity are being performed. The details of this experimental and theoretical model development effort are described.

Chelliah, Harsha K.↗
NASA NTRS2003

Combustion Of Porous Graphite Particles In Oxygen Enriched Air

Combustion of solid fuel particles has many important applications, including power generation and space propulsion systems. The current models available for describing the combustion process of these particles, especially porous solid particles, include various simplifying approximations. One of the most limiting approximations is the lumping of the physical properties of the porous fuel with the heterogeneous chemical reaction rate constants [1]. The primary objective of the present work is to develop a rigorous modeling approach that could decouple such physical and chemical effects from the global heterogeneous reaction rates. For the purpose of validating this model, experiments with porous graphite particles of varying sizes and porosity are being performed under normal and micro gravity.

Delisle, Andrew J.↗
DOE OSTI2025

Investigation of Solid Particle Reactors for Nonoxidative Dehydrogenation of Ethane: Toward Solar Thermal Ethylene Production

Concentrating solar power plants can generate renewable heat at temperatures well above those of most industrial processes. Ceramic particles irradiated with concentrated sunlight can store high-quality sensible heat and transfer this to power generation systems. These concepts and materials hold great potential to also enable thermal processes in the chemical industry, but effective strategies for transferring heat from thermal energy storage media into chemical reactors are still under development. This present work evaluated the thermal and chemical compatibility of various solid particle media (including quartz, bauxite, and alumina particles) integrated directly into tube reactors and the subsequent effects on reactor performance for the nonoxidative dehydrogenation of ethane reaction. Empty tube reactors without loaded particles (representing conventional ethane cracking coils) showed significant heat transfer limitations as the tube diameter was scaled. The incorporation of media into the reactor significantly aided heat transfer to the gaseous ethane reactant and increased its conversion by as much as 10% at similar space velocities. Despite direct contact with hydrocarbon gases, alumina and quartz media showed negligible coke formation. Even during reaction in 100% ethane feed gas at 825 °C, the average selectivity of the coke product was only 0.57% when using the quartz media. These materials further demonstrated excellent thermal stability during subsequent reoxidation in air at 800 °C, which simulated the reheating of particles in a circulating particle solar receiver. Conversely, high rates of coke formation, with a product selectivity of 27.5%, were observed on sintered bauxite particles during the reaction, likely promoted by transition metal constituents. These particles fractured upon reoxidation due to exotherms generated from coke combustion. In conclusion, while the use of cofed steam could mitigate attrition of redox-active particles, the ability of inert metal oxide particles to efficiently transfer heat to concentrated ethane reactant gas while suppressing side reactions or degradation suggests that these media could effectively couple solar thermal plants to reactors for next-generation production of ethylene and other critical chemicals.

Hydrocarbons↗
DOE OSTI2023

A standard convention for particle-level Monte Carlo event-variation weights

Streams of event weights in particle-level Monte Carlo event generators are a convenient and immensely CPU-efficient approach to express systematic uncertainties in phenomenology calculations, providing systematic variations on the nominal prediction within a single event sample. But the lack of a common standard for labelling these variation streams across different tools has proven to be a major limitation for event-processing tools and analysers alike. Here we propose a well-defined, extensible community standard for the naming, ordering, and interpretation of weight streams that will serve as the basis for semantically correct parsing and combination of such variations in both theoretical and experimental studies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1977

Wingtip smoke generator

Device produces nontoxic smoke of low particle density, assisting in investigation and study of aircraft wingtip vortexes in flight. It can be dimensioned according to available current and oil capacity.

Rogers, J. R.↗
NASA NTRS1988

Predicting the arrival times of solar particles

A procedure has been developed to generate a computerized time-intensity profile of the solar proton intensity expected at the earth after the occurrence of a significant solar flare on the sun. This procedure is a combination of many pieces of independent research and theoretical results. Many of the concepts used were first reported by Smart and Shea (1979) and are summarized by Smart and Shea (1985). Extracts from the general procedure that relate to predicting the expected onset time and time of maximum at the earth after the occurrence of a solar flare are presented.

Smart, D. F.↗
DOE OSTI2022

An Efficient Bayesian Approach to Learning Droplet Collision Kernels: Proof of Concept Using “Cloudy,” a New n -Moment Bulk Microphysics Scheme

The small-scale microphysical processes governing the formation of precipitation particles cannot be resolved explicitly by cloud resolving and climate models. Instead, they are represented by microphysics schemes that are based on a combination of theoretical knowledge, statistical assumptions, and fitting to data (“tuning”). Historically, tuning was done in an ad hoc fashion, leading to parameter choices that are not explainable or repeatable. Recent work has treated it as an inverse problem that can be solved by Bayesian inference. The posterior distribution of the parameters given the data—the solution of Bayesian inference—is found through computationally expensive sampling methods, which require over $\mathcal{O}$(10 5 ) evaluations of the forward model; this is prohibitive for many models. We present a proof of concept of Bayesian learning applied to a new bulk microphysics scheme named “Cloudy,” using the recently developed Calibrate-Emulate-Sample (CES) algorithm. Cloudy models collision-coalescence and collisional breakup of cloud droplets with an adjustable number of prognostic moments and with easily modifiable assumptions for the cloud droplet mass distribution and the collision kernel. The CES algorithm uses machine learning tools to accelerate Bayesian inference by reducing the number of forward evaluations needed to $\mathcal{O}$(10 2 ). It also exhibits a smoothing effect when forward evaluations are polluted by noise. In a suite of perfect-model experiments, we show that CES enables computationally efficient Bayesian inference of parameters in Cloudy from noisy observations of moments of the droplet mass distribution. In an additional imperfect-model experiment, a collision kernel parameter is successfully learned from output generated by a Lagrangian particle-based microphysics model.

54 ENVIRONMENTAL SCIENCES↗