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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 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

The NETL MFiX Suite of multiphase flow models: A brief review and recent applications of MFiX-TFM to fossil energy technologies

Here, the MFiX suite of multiphase computational fluid dynamics (CFD) codes is being developed at U.S. Department of Energy's National Energy Technology Laboratory (NETL). It includes several different approaches to multiphase simulation: MFiX-TFM, a two-fluid (Eulerian–Eulerian) model; MFiX-DEM, an Eulerian fluid model with a Lagrangian Discrete Element Model for the solids phase; and MFiX-PIC, Eulerian fluid model with Lagrangian particle ‘parcels’ representing particle groups. These models are undergoing continuous development and application, with verification, validation, and uncertainty quantification (VV&UQ) as integrated activities. After a brief summary of recent progress in the verification, validation and uncertainty quantification (VV&UQ), this article highlights two recent accomplishments in the application of MFiX-TFM to fossil energy technology development. First, recent application of MFiX to the pilot-scale KBR TRIG™ Transport Gasifier located at DOE's National Carbon Capture Center (NCCC) is described. Gasifier performance over a range of operating conditions was modeled and compared to NCCC operational data to validate the ability of the model to predict parametric behavior. Second, comparison of code predictions at a detailed fundamental scale is presented studying solid sorbents for the post-combustion capture of CO 2 from flue gas. Specifically designed NETL experiments are being used to validate hydrodynamics and chemical kinetics for the sorbent-based carbon capture process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

Thermodynamic estimation of minor element distribution between immiscible liquids in Fe-Cu-based metal phase generated in melting treatment of municipal solid wastes

Graphical abstract: Display Omitted Highlights: Black-Right-Pointing-Pointer Two liquids separation of metal occurs in the melting of municipal solid waste. Black-Right-Pointing-Pointer The distribution of PGMs etc. between two liquid metal phases is studied. Black-Right-Pointing-Pointer Quite simple thermodynamic model is applied to predict the distribution ratio. Black-Right-Pointing-Pointer Au and Ag originated from WEEE are found to be concentrated into Cu-rich phase. - Abstract: Waste electrical and electronic equipment (WEEE) has become an important target in managing material cycles from the viewpoint of not only waste management and control of environmental pollution but also resource conservation. This study investigated the distribution tendency of trace elements in municipal solid waste (MSW) or incinerator ash, including valuable non-ferrous metals (Ni, Co, Cr, Mn, Mo, Ti, V, W, Zr), precious group metals (PGMs) originated from WEEE (Ag, Au, Pd, Pt), and others (Al, B, Pb, Si), between Fe-rich and Cu-rich metal phases by means of simple thermodynamic calculations. Most of the typical alloying elements for steel (Co, Cr, Mo, Nb, Ni, Si, Ti, V, and W) and Rh were preferentially distributed into the Fe-rich phase. PGMs, such as Au, Ag, and Pd, were enriched in the Cu-rich phase, whereas Pt was almost equally distributed into both phases. Since the primary metallurgical processing of Cu is followed by an electrolysis for refining, and since PGMs in crude copper have been industrially recovered from the resulting anode slime, our results indicated that Ag, Au, and Pd could be effectively recovered from MSW if the Cu-rich phase could be selectively collected.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Numerical and experimental studies on effects of moisture content on combustion characteristics of simulated municipal solid wastes in a fixed bed

Highlights: • The effects of moisture content on the burning process of MSW are investigated. • A two-dimensional mathematical model was built to simulate the combustion process. • Temperature distributions, process rates, gas species were measured and simulated. • The The conversion ratio of C/CO and N/NO in MSW are inverse to moisture content. - Abstract: In order to reveal the features of the combustion process in the porous bed of a waste incinerator, a two-dimensional unsteady state model and experimental study were employed to investigate the combustion process in a fixed bed of municipal solid waste (MSW) on the combustion process in a fixed bed reactor. Conservation equations of the waste bed were implemented to describe the incineration process. The gas phase turbulence was modeled using the k–ε turbulent model and the particle phase was modeled using the kinetic theory of granular flow. The rate of moisture evaporation, devolatilization rate, and char burnout was calculated according to the waste property characters. The simulation results were then compared with experimental data for different moisture content of MSW, which shows that the incineration process of waste in the fixed bed is reasonably simulated. The simulation results of solid temperature, gas species and process rate in the bed are accordant with experimental data. Due to the high moisture content of fuel, moisture evaporation consumes a vast amount of heat, and the evaporation takes up most of the combustion time (about 2/3 of the whole combustion process). The whole bed combustion process reduces greatly as MSW moisture content increases. The experimental and simulation results provide direction for design and optimization of the fixed bed of MSW.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Structure, Hydration, and Interactions of Native and Hydrophobically Modified Phytoglycogen Nanoparticles

Phytoglycogen is a highly branched polymer of glucose produced as soft, compact nanoparticles by sweet corn. Properties such as softness, porosity, and mechanical integrity, combined with nontoxicity and biodegradability, make phytoglycogen nanoparticles ideal for applications involving the human body, ranging from skin moisturizing and rejuvenation agents in personal care formulations to functional therapeutics in biomedicine. To further broaden the range of applications, phytoglycogen nanoparticles can be chemically modified with hydrophobic species such as octenyl succinic anhydride (OSA). In this study, we present a self-consistent model of the particle structure, water content, and degree of chemical modification of the particles, as well as the emergence of well-defined interparticle spacings in concentrated dispersions, based on small-angle neutron scattering (SANS) measurements of aqueous dispersions of native phytoglycogen nanoparticles and particles that were hydrophobically modified using octenyl succinic anhydride (OSA) in both its protiated (pOSA) and deuterated (dOSA) forms. Measurements on native particles with reduced polydispersity have allowed us to refine the particle morphology, which is well described by a hairy particle (core-chain) geometry with short chains decorating the surface of the particles. The isotopic variants of OSA-modified particles enhanced the scattering contrast for neutrons, revealing lightly modified hairy chains for small degrees of substitution (DS) of OSA, and a raspberry particle geometry for the largest DS value, where the OSA-modified hairy chains collapse to form small seeds on the surface of the particles. This refined model of native and OSA-modified phytoglycogen nanoparticles establishes a quantitative basis for the development of new applications of this promising sustainable nanotechnology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2011

SWIFT OBSERVATIONS OF THE 2006 OUTBURST OF THE RECURRENT NOVA RS OPHIUCHI. III. X-RAY SPECTRAL MODELING

Following the Swift X-ray observations of the 2006 outburst of the recurrent nova RS Ophiuchi, we developed hydrodynamical models of mass ejection from which the forward shock velocities were used to estimate the ejecta mass and velocity. In order to further constrain our model parameters, we present synthetic X-ray spectra from our hydrodynamical calculations, which we compare to the Swift data. An extensive set of simulations was carried out to find a model that best fits the spectra up to 100 days after outburst. We find a good fit at high energies but require additional absorption to match the low energy emission. We estimate the ejecta mass to be in the range (2-5) x 10{sup -7} M{sub sun} and the ejection velocity to be greater than 6000 km s{sup -1} (and probably closer to 10, 000 km s{sup -1}). We also find that estimates of shock velocity derived from gas temperatures via standard model fits to the X-ray spectra are much lower than those of the true shock velocities.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Bayesian estimation of the $S$ factor and thermonuclear reaction rate for 16 O(p, γ) 17 F

The 16 O(p, γ) 17 F reaction is the slowest hydrogen-burning process in the CNO mass region. Its thermonuclear rate sensitively impacts predictions of oxygen isotopic ratios in a number of astrophysical sites, including AGB stars. The reaction has been measured several times at low bombarding energies using a variety of techniques. The most recent evaluated experimental rates have a reported uncertainty of about 7.5% below 1 GK. However, the previous rate estimate represents a best guess only and was not based on rigorous statistical methods. We apply a Bayesian model to fit all reliable 16 O(p, γ) 17 F cross section data, and take into account independent contributions of statistical and systematic uncertainties. The nuclear reaction model employed is a single-particle potential model involving a Woods-Saxon potential for generating the radial bound state wave function. The model has three physical parameters, the radius and diffuseness of the Woods-Saxon potential, and the asymptotic normalization coefficients (ANCs) of the final bound state in 17 F. Here, we find that performing the Bayesian S -factor fit using ANCs as scaling parameters has a distinct advantage over adopting spectroscopic factors instead. Based on these results, we present the first statistically rigorous estimation of experimental 16 O(p, γ) 17 F reaction rates, with uncertainties (±4.2%) of about half the previously reported values.

6 ≤ A ≤ 19↗
DOE OSTI2024

Quantum Thermodynamics of Nonequilibrium Processes in Lattice Gauge Theories

A key objective in nuclear and high-energy physics is to describe nonequilibrium dynamics of matter, e.g., in the early Universe and in particle colliders, starting from the standard model of particle physics. Classical computing methods, via the framework of lattice gauge theory, have experienced limited success in this mission. Quantum simulation of lattice gauge theories holds promise for overcoming computational limitations. Because of local constraints (Gauss’s laws), lattice gauge theories have an intricate Hilbert-space structure. This structure complicates the definition of thermodynamic properties of systems coupled to reservoirs during equilibrium and nonequilibrium processes. We show how to define thermodynamic quantities such as work and heat using strong-coupling thermodynamics, a framework that has recently burgeoned within the field of quantum thermodynamics. Our definitions suit instantaneous quenches, simple nonequilibrium processes undertaken in quantum simulators. To illustrate our framework, we compute the work and heat exchanged during a quench in a Z 2 lattice gauge theory coupled to matter in 1+1 dimensions. Here, the thermodynamic quantities, as functions of the quench parameter, evidence a phase transition. For general thermal states, we derive a simple relation between a quantum many-body system’s entanglement Hamiltonian, measurable with quantum-information-processing tools, and the Hamiltonian of mean force, used to define strong-coupling thermodynamic quantities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1982

Solar disturbances and mesospheric odd nitrogen

The odd nitrogen (NOx) abundance of the high latitude mesosphere exhibits a large variability in response to energetic particle precipitation. Model calculations for a very large particle event predict increases in the NOx mixing ratio that can exceed a factor of ten over time periods of the order of one week in the summer hemisphere. A more typical sized event can still lead to an enhancement of a factor of three in summer. Relative changes in the winter hemisphere are less dramatic due to a larger ambient NOx mixing ratio predicted here. However, a factor of two increase in NOx is possible during a very large event. Owing to the large variability, it is difficult to define a physically meaningful mean state profile in the high latitude mesosphere. Rather, the NOx abundance likely displays an erratic behavior which is correlated with the level of solar activity.

Orsini, N.↗
NASA NTRS1984

Electron precipitation zones around major ground-based VLF signal sources

The spatial distribution of electron precipitation induced by VLF signals from ground-based transmitters is determined by using a test particle computer model of the gyroresonant wave-particle interaction (Inan et al., 1982). The results are presented as contours of energy flux on a map of the region around each transmitter. It is shown that the size of the precipitation zones is a strong function of the geographic location of the transmitter, as well as its radiated power and operating frequency. In general, the precipitation zones are much wider in longitude than in latitude and are oriented along lines of constant geomagnetic latitude. Assuming backscatter and/or wave echoing, precipitation zones around the points that are magnetically conjugate to the sources are also estimated. The results presented can be used to interpret satellite- or ground-based measurements of the precipitation induced by ground-based VLF transmitters.

Inan, U. S.↗
NASA NTRS1997

Magnetospheric Plasmas-Flow and Energization of the Ionospheric Source

In a paper of more than a decade ago, estimated the strength of the ionospheric source and its ability to supply the different plasma regions of the Earth's magnetosphere. The launch of the POLAR spacecraft with the Thermal Ion Dynamics Experiment (TIDE) and the active control of spacecraft potential thro6gh the Plasma Source Instrument (PSI) made possible for the first time the direct measurement of low energy ions moving from the ionosphere into the lobes of the magnetotail. A particle trajectory model has been used to trace particles representative 6f TIDE measurements, taken during the operation of PSI, back to the location of the ionospheric source and forward to the entry point of the ions to the plasma sheet.

Chappell, C. R.↗
NASA NTRSDate not supplied

Comparing Particle Flow Regimes in the L2K Arcjet with Martian Entry Conditions

In this study, the US3D-DUST code will be used to simulate particles in the L2K dusty-flow test environments and compare them to conditions in the shock layer of the Schiaparelli capsule during its entry into the Martian atmosphere in 2016. The particle Reynolds, Mach, and Knudsen numbers, key non-dimensional numbers that characterize the dusty-flow environments, will be compared between the L2K and Martian shock layers. This study will provide a preliminary assessment of how well-suited L2K dusty-flow conditions are for particle drag model validation and the development of particle impact surface damage correlations. The results of this study may help to guide the design of future dusty flow environments in the L2K facility

Dusty flow↗
DOE OSTI2018

The Sterile Neutrino Discovery

New research results have potentially identified a fourth type of neutrino, a “sterile neutrino” particle. This particle provides challenges for the Standard Model of particle physics, if found to be a valid result in future experiments. The work, conducted by a multi-institutional team at Fermi National Accelerator Laboratory (Fermilab) near Chicago, confirms results found in the 1990s in the Los Alamos Liquid Scintillator Neutrino Detector (LSND).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2013

Modeling and Analysis of FCM UN TRISO Fuel Using the PARFUME Code

The PARFUME (PARticle FUel ModEl) modeling code was used to assess the overall fuel performance of uranium nitride (UN) tri-structural isotropic (TRISO) ceramic fuel in the frame of the design and development of Fully Ceramic Matrix (FCM) fuel. A specific modeling of a TRISO particle with UN kernel was developed with PARFUME, and its behavior was assessed in irradiation conditions typical of a Light Water Reactor (LWR). The calculations were used to access the dimensional changes of the fuel particle layers and kernel, including the formation of an internal gap. The survivability of the UN TRISO particle was estimated depending on the strain behavior of the constituent materials at high fast fluence and burn-up. For nominal cases, internal gas pressure and representative thermal profiles across the kernel and layers were determined along with stress levels in the pyrolytic carbon (PyC) and silicon carbide (SiC) layers. These parameters were then used to evaluate fuel particle failure probabilities. Results of the study show that the survivability of UN TRISO fuel under LWR irradiation conditions might only be guaranteed if the kernel and PyC swelling rates are limited at high fast fluence and burn-up. These material properties are unknown at the irradiation levels expected to be reached by UN TRISO fuel in LWRs. Therefore, more effort is needed to determine them and positively conclude on the applicability of FCM fuel to LWRs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

An approach to assess the Particulate Matter exposure for the population living around a cement plant: modelling indoor air and particle deposition in the respiratory tract

In this paper we studied the exposure to three size fractions of outdoor particulate matter (PM{sub 10}, PM{sub 2.5}, and PM{sub 1}) collected in an area influenced by a cement plant. For that purpose, three groups of population were evaluated (children, adults and retired) in two seasons (summer and winter). Outdoor measured PM concentrations, as well as physiological parameters and activity patterns of the three groups of population were used as input data in two different models. The first one was an indoor air quality model, used to elucidate indoor PM concentrations in different microenvironments. The second one was a dosimetry model, used to evaluate the internal exposure and the distribution of the different PM fractions in the respiratory tract. Results from the indoor air quality model showed that special attention must be paid to the finest particles, since they penetrate indoors in a greater degree. Highest pulmonary doses for the three PM sizes were reported for retired people, being this a result of the high amount of time in outdoor environments exercising lightly. For children, the exposure was mainly influenced by the time they also spend outdoors, but in this case due to heavy intensity activities. It was noticed that deposition of fine particles was more significant in the pulmonary regions of children and retired people in comparison with adults, which has implications in the expected adverse health effects for those vulnerable groups of population. - Highlights: • PM deposition in the respiratory tract was evaluated for three population groups. • Activity patterns and different microenvironments were used in our calculation. • Outdoor activities are the main contributors to PM deposited mass. • Children experienced the highest deposition dose in the pulmonary region. • Retired registered the highest deposited mass in the respiratory tract as a whole.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2002

3D Finite Element Analysis of Particle-Reinforced Aluminum

Deformation in particle-reinforced aluminum has been simulated using three distinct types of finite element model: a three-dimensional repeating unit cell, a three-dimensional multi-particle model, and two-dimensional multi-particle models. The repeating unit cell model represents a fictitious periodic cubic array of particles. The 3D multi-particle (3D-MP) model represents randomly placed and oriented particles. The 2D generalized plane strain multi-particle models were obtained from planar sections through the 3D-MP model. These models were used to study the tensile macroscopic stress-strain response and the associated stress and strain distributions in an elastoplastic matrix. The results indicate that the 2D model having a particle area fraction equal to the particle representative volume fraction of the 3D models predicted the same macroscopic stress-strain response as the 3D models. However, there are fluctuations in the particle area fraction in a representative volume element. As expected, predictions from 2D models having different particle area fractions do not agree with predictions from 3D models. More importantly, it was found that the microscopic stress and strain distributions from the 2D models do not agree with those from the 3D-MP model. Specifically, the plastic strain distribution predicted by the 2D model is banded along lines inclined at 45 deg from the loading axis while the 3D model prediction is not. Additionally, the triaxial stress and maximum principal stress distributions predicted by 2D and 3D models do not agree. Thus, it appears necessary to use a multi-particle 3D model to accurately predict material responses that depend on local effects, such as strain-to-failure, fracture toughness, and fatigue life.

Shen, H.↗
DOE OSTI2021

Efficient Failure Probability Calculations and Modeling Interface Debonding in TRISO Particles with BISON

This document constitutes completion of the NEAMS milestone, which is titled Demonstrate efficiency improvements in TRISO failure probability calculations and the effect of debonding on fission product transport in TRISO fuel particles in Bison . In this report we present the development of the following: (1) the anisotropic elasticity model of pyrolytic carbon and extended material models using the local coordinate system for aspherical particle geometry; (2) a capability of modeling interface debonding in TRISO particles; and (3) an efficient high-fidelity approach to calculate the failure probability of TRISO particles. Benchmark problems and AGR-2 tests are used to verify the models and demonstrate these new capabilities.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Neural Networks for Modeling and Control of Particle Accelerators

Particle accelerators are host to myriad nonlinear and complex physical phenomena. They often involve a multitude of interacting systems, are subject to tight performance demands, and should be able to run for extended periods of time with minimal interruptions. Often times, traditional control techniques cannot fully meet these requirements. One promising avenue is to introduce machine learning and sophisticated control techniques inspired by artificial intelligence, particularly in light of recent theoretical and practical advances in these fields. Within machine learning and artificial intelligence, neural networks are particularly well-suited to modeling, control, and diagnostic analysis of complex, nonlinear, and time-varying systems, as well as systems with large parameter spaces. Consequently, the use of neural network-based modeling and control techniques could be of significant benefit to particle accelerators. For the same reasons, particle accelerators are also ideal test-beds for these techniques. Many early attempts to apply neural networks to particle accelerators yielded mixed results due to the relative immaturity of the technology for such tasks. The purpose of this paper is to re-introduce neural networks to the particle accelerator community and report on some work in neural network control that is being conducted as part of a dedicated collaboration between Fermilab and Colorado State University (CSU). We describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.

43 PARTICLE ACCELERATORS↗