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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Nitric Acid Uptake on Subtropical Cirrus Cloud Particles

The redistribution of HNO3 via uptake and sedimentation by cirrus cloud particles is considered an important term in the upper tropospheric budget of reactive nitrogen. Numerous cirrus cloud encounters by the NASA WB-57F high-altitude research aircraft during CRYSTAL-FACE were accompanied by the observation of condensed-phase HNO3 with the NOAA chemical ionization mass spectrometer. The instrument measures HNO3 with two independent channels of detection connected to separate forward- and downward-facing inlets that allow a determination of the amount of HNO3 condensed on ice particles. Subtropical cirrus clouds, as indicated by the presence of ice particles, were observed coincident with condensed-phase HNO3 at temperatures of 197 K - 224 K and pressures of 122 hPa - 224 hPa. Maximum levels of condensed-phase HNO3 approached the gas-phase equivalent of 0.8 ppbv. Ice particle surface coverages as high as 1.4- 10(exp 14) molecules/sq cm were observed. A dissociative Langmuir adsorption model, when using an empirically derived HNO3 adsorption enthalpy of -11.0 kcal/mol, effectively describes the observed molecular coverages to within a factor of 5. The percentage of total HNO3 in the condensed phase ranged from near zero to 100% in the observed cirrus clouds. With volume-weighted mean particle diameters up to 700 pm and particle fall velocities up to 10 m/s, some observed clouds have significant potential to redistribute HNO3 in the upper troposphere.

Source record↗
NASA NTRS1993

Unequilibrated, equilibrated, and reduced aggregates in anhydrous interplanetary dust particles

Track-rich anhydrous IDP's are probably the most primitive IDP's because they have escaped significant post-accretional alteration; they exhibit evidence of (nebular) gas phase reactions; their mineralogy is similar to comet Halley's dust; and some of them exhibit comet-like IR spectral characteristics. However, basic questions about the mineralogy and petrography of anhydrous IDP's remain unanswered, because they contain aggregated components that can be heterogeneous on a scale of nanometers. In some IDP's, aggregates account for greater than 75 percent of the volume of the particle. The aggregates have been systematically examined using an analytical electron microscope (AEM), which provides probe-forming optics and (x-ray and electron) spectrometers necessary to analyze individual nanometer-sized grains. The AEM results reveal at least three mineralogically distinct classes of aggregates in an hydrous IDP's, with mineralogies reflecting significantly different formation/aggregation environments.

Bradley, J. P.↗
NASA NTRS2004

Nitric Acid Uptake on Subtropical Cirrus Cloud Particles

The redistribution of HNO3 via uptake and sedimentation by cirrus cloud particles is considered an important term in the upper tropospheric budget of reactive nitrogen. Numerous cirrus cloud encounters by the NASA WB-57F high-altitude research aircraft during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers-Florida Area Cirrus Experiment (CRYSTAL-FACE) were accompanied by the observation of condensed-phase HNO3 with the NOAA chemical ionization mass spectrometer. The instrument measures HNO3 with two independent channels of detection connected to separate forward and downward facing inlets that allow a determination of the amount of HNO3 condensed on ice particles. Subtropical cirrus clouds, as indicated by the presence of ice particles, were observed coincident with condensed-phase HNO3 at temperatures of 197-224 K and pressures of 122-224 hPa. Maximum levels of condensed-phase HNO3 approached the gas-phase equivalent of 0.8 ppbv. Ice particle surface coverages as high as 1.4 # 10(exp 14) molecules/ square cm were observed. A dissociative Langmuir adsorption model, when using an empirically derived HNO3 adsorption enthalpy of -11.0 kcal/mol, effectively describes the observed molecular coverages to within a factor of 5. The percentage of total HNO3 in the condensed phase ranged from near zero to 100% in the observed cirrus clouds. With volume-weighted mean particle diameters up to 700 ?m and particle fall velocities up to 10 m/s, some observed clouds have significant potential to redistribute HNO3 in the upper troposphere.

Popp, P. J.↗
DOE OSTI2019

Does the Hood Canal Bridge traffic noise affect migrating steelhead smolts?

Recent research conducted by NOAA’s Manchester Research Laboratory has provided strong evidence of a substantial migration interference and increased mortality risk associated with the Hood Canal Bridge , which drives the need to investigate the sound and vibration generated by the vehicles crossing the bridge. A month-long monitoring of in-water sound pressure and the vibration of the bridge pontoons was performed at the Hood Canal Bridge by three sets of autonomous sound and vibration recording systems deployed along the bridge. At each deployment site, sound pressure in water was recorded by a hydrophone submerged three meters under water, and the vibration of the bridge pontoon was recorded by an array of three orthogonally mounted single-axis accelerometers. Both sound pressure and acceleration data were analyzed and compared to the threshold levels suggested by previous studies. Results show that the observed sound pressure levels and particle accelerations are strongly correlated with traffic volume across the bridge, and particle accelerations occasionally exceeded the threshold levels that could elicit the avoidance behavior of juvenile salmon. It is concluded that the Hood Canal Bridge traffic noise can potentially affect migrating salmonids due to the intense particle accelerations caused by the bridge pontoons in water.

Zang, Xiaoqin↗
DOE OSTI2024

The three-pion K -matrix at NLO in ChPT

The three-particle K-matrix, Κ df,3 , is a scheme-dependent quantity that parametrizes short-range three-particle interactions in the relativistic-field-theory three-particle finite-volume formalism. In this work, we compute its value for systems of three pions in all isospin channels through next-to-leading order in Chiral Perturbation Theory, generalizing previous work done at maximum isospin. We obtain analytic expressions through quadratic order (or cubic order, in the case of zero isospin) in the expansion about the three-pion threshold.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

The isospin-3 three-particle K -matrix at NLO in ChPT

The three-particle K-matrix, K df,3 , is a scheme-dependent quantity that parametrizes short-range three-particle interactions in the relativistic-field-theory three-particle finite-volume formalism. In this work, we compute its value for systems of three pions at maximal isospin through next-to-leading order (NLO) in Chiral Perturbation Theory (ChPT). We compare the values to existing lattice QCD results and find that the agreement between lattice QCD data and ChPT in the first two coefficients of the threshold expansion of K df,3 is significantly improved with respect to leading order once NLO effects are incorporated.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Understanding and control of Zener pinning via phase field and ensemble learning

Zener pinning refers to the dispersion of fine particles which influences grain size distribution via movement of grain boundaries in a polycrystalline material. Grain size distribution in polycrystals has a significant impact on their properties including physical, chemical, mechanical, and optical to name a few. We explore the use of Phase-field modeling and machine-learning techniques to understand and improve the control of grain size distribution via Zener pinning in polycrystalline materials. We develop a machine learning model that determines the relative importance of various parameters to exercise microstructure control via Zener pinning. Our workflow combines high-throughput phase-field simulations and machine learning to address the computational bottlenecks associated with large-scale simulations as well as identify features necessary for microstructure control in polycrystals. A random forest (RF) regression model was developed to predict grain sizes based on five Phase-field model parameters, achieving an average prediction error of 0.72 nm for the training data and 1.44 nm for the test data. The importance of the input parameters is analyzed using the SHapley Additive exPlanations (SHAP) approach which reveals that diffusivity, volume fraction, and particle diameter are the most important parameters in determining the final grain size. These findings will allow us to select the best second-phase particles, optimize grain size distributions and thus design microstructures with the desired properties. The developed method is a highly versatile and generalizable approach that can be used to assess the combined effects of individual features in the presence of multiple variables.

36 MATERIALS SCIENCE↗
DOE OSTI2021

First Principles Simulations of Electrified Interfaces in Electrochemistry

This chapter discusses some of the recent advances made in the first principles modeling of electrochemical catalysts. It also discusses the key development, namely the ability to explicitly treat the effects of surface electrification due to electrochemical processes and applied voltages in a computationally efficient manner. The chapter introduces the thermodynamics and statistical mechanics of electrified metal-solution interfaces. It then discusses the structure of the electrode-electrolyte interface and the effects of applied voltages, followed by an overview of the first-principles model and a motivating example. The chapter also provides a brief summary of classical thermodynamics and describes the basics of thermodynamic detour. It considers the thermodynamics of macroscopic systems and introduces several useful fundamental relations. Here, the chapter also considers a system to exist in a certain macrostate, which is a particular thermodynamic state specified by a set of fixed properties such as constant particle number, constant volume, and constant temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Machine learning methods for particle stress development in suspension Poiseuille flows

Numerical simulations are used to study the dynamics of a developing suspension Poiseuille flow with monodispersed and bidispersed neutrally buoyant particles in a planar channel, and machine learning is applied to learn the evolving stresses of the developing suspension. The particle stresses and pressure develop on a slower time scale than the volume fraction, indicating that once the particles reach a steady volume fraction profile, they rearrange to minimize the contact pressure on each particle. Here we consider how the stress development leads to particle migration, time scales for stress development, and present a new physics-informed Galerkin neural network that allows for learning the particle stresses when direct measurements are not possible. The particle fluxes are compared with the Suspension Balance Model with good agreement. We show that when stress measurements are possible, the MOR-physics operator learning method can also capture the particle stresses.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Incorporating PCM-enabled thermal energy storage into 3D printable cementitious composites

This paper delineates the feasibility of incorporating microencapsulated phase change materials (mPCM) into 3D printable cementitious composite materials. A comprehensive experimental program was carried out to evaluate the impacts of mPCM on the printability, microstructures, mechanical and thermal properties of cementitious 3D printing ‘inks’. Results showed that the mPCM affected the printability of the cementitious ink material based on its physical properties (e.g., particle size) and volume loading – at lower volume loadings, mPCM increased the flowability of the cementitious ink material while leading to increased compressive strength and thermal conductivity for the hardened printed material. However, further increase in mPCM dosage led to a decrease in printability and, therefore, decrease in compressive strength and thermal conductivity as compared to the reference mixture. Here the results also showed that the inclusion of mPCM influence the printing parameters. In general, the inclusion of higher volume contents of mPCM necessitates a higher extrusion rate to achieve a desirable extrudability. Lastly, a thermal network model was formulated for 3D printed mPCM charged building components (e.g., wall). The study shows that microencapsulated PCM materials have good potential to be used in 3D printable cementitious mixtures for improving the thermal and energy performance of 3D printed buildings.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Ionization-Induced Subcycle Metallization of Nanoparticles in Few-Cycle Pulses

Strong-field laser-matter interactions in nanoscale targets offer unique avenues for the generation and detailed characterization of matter under extreme conditions. Field-driven, sub-cycle ionization-induced metallization of nanoscale solids in intense laser fields has been predicted (Peltz et al. Time-Resolved X-ray Imaging of Anisotropic Nano-plasma Expansion. Phys. Rev. Lett. 2014, 113, 133401), but its observation was hampered by a lack of a smoking gun. Here, we report the ultrafast metallization of isolated dielectric and semiconducting nanoparticles under intense few-cycle laser pulses. The highest-energy electron emission is found to be a decisive proof that shows a characteristic cutoff modification to a metallic limit for intensities high enough to ignite carrier avalanching in the volume of the particles. Furthermore, semiclassical Mean-field Mie Monte-Carlo transport simulations reveal the underlying dynamics and explain the observed evolution by near-field driven electron backscattering from the metallizing target.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Fluid-like shock compression of dilute polymer nanocomposites

The shock Hugoniot of heterogenous mixtures of discrete particles has been experimentally investigated for porous agglomerates and fluids, while the study of full-density solids has been primarily limited to compressed powders and high-dimensional composites. By dispersing ceria nanoparticles in a polyethylene matrix, we are able to examine the hydrodynamic behavior of a nonporous, heterogenous solid in thermal equilibrium during weak shock compression. Phase-driven discontinuities in the Hugoniot particle velocity–shock velocity (u−D) relationship of pure polyethylene are replicated in the nanocomposites but are shifted to lower velocity and to higher pressure with higher particle concentration. The results are explained using an isothermal, two-velocity fluid model under the hydrodynamic approximation. The model, which assumes a theoretical equation-of-state for ceria and either a low-order or high-order fit to the measured polyethylene Hugoniot, reasonably predicts the Hugoniot for two different polyethylene/ceria nanocomposites. Using the model, the mixture Hugoniot is shown to be insensitive to the Hugoniot of the stiffer constituent when the moduli are sufficiently disparate, while dependence on particle density and volume fraction is preserved through fluid-like motion.

Moore, Nathan W. [Sandia National Laboratories (SN↗
DOE OSTI2024

Performance Improvements of the Griffin Solvers in FY24

The Griffin code is a MOOSE-based reactor physics application jointly developed by Idaho National Laboratory and Argonne National Laboratory under the Department of Energy Office of Nuclear Energy Nuclear Energy Advanced Modeling and Simulation Program. This fiscal year, we have made significant efforts to improve the performance of transport solver options and cross-section generation for the efficient use of Griffin in advanced reactor applications. For the HFEM-PN solver, the residual evaluations of HFEM kernels were optimized by utilizing the pre- computed averaged cross sections for individual elements. Numerical integration involving the evaluation of basis functions at quadrature points was bypassed by facilitating precomputed element mass matrices for response matrices. Red-black iterations were improved by introducing a new generalized minimum residual based solver. The memory usage of response matrix storage was significantly reduced by applying basis function rotations on interfaces and calculating volumetric odd-parity moments on the fly. Additionally, the adjoint flux and transient calculation capabilities of the HFEM-PN solver were successfully implemented and verified using the TWIGL benchmark problem. For the DFEM-SN solver, memory footprint and computation time were significantly reduced by not treating angular flux vectors as the MOOSE nonlinear system vectors. Specifically for IQS, scalar adjoint weighting was introduced to further eliminate angular adjoint flux storage in the MOOSE auxiliary system. It was demonstrated through the three-dimensional Advanced Burner Test Reactor core problem that the memory usage for transient calculations with the IQS method was reduced by over 7.5× compared to before the optimizations. For the self-shielding application programming interface, a new double-heterogeneity treatment method, named the Bell Function-Based Analytic Two-Region Slowing Down Method, was developed to efficiently flux-volume homogenize TRISO particles with the matrix. Additionally, optimizations were made to hyper- fine group (HFG) slowing down calculations by pretabulating collision probability coefficients and grouping isotopes, significantly reducing the computational time for calculating scattering sources per HFG. Lastly, the pin power reconstruction module was extended to account for temporal behavior in a microreactor analysis problem, specifically for a control drum transient. Verification tests for each of these improvements demonstrated significant performance enhancements and memory reduction.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Reconstruction of 6D Phase Space

A ‘Phase Space’ is a mathematical representation of all possible physical states of matter of a physical volume or system. Particle beams at Fermilab exist in a six-dimensional phase space: three position dimensions, and three momentum dimensions. To ‘reconstruct’ that space means to take measurement data from virtual detectors along those beams and map out where particles are and how they’re moving, using computational methods. In this experiment, we simulated a particle beam (Fig 1) and used the position distribution of each particle at each detector to map out the magnitude of the beam’s initial momentum.

Shirlee, Jermaine [DuPage Coll.]↗
NASA NTRS1972

Survey of lunar carbon compounds. II - The carbon chemistry of Apollo 11, 12, 14, and 15 samples.

The methane and carbide concentrations of a number of Apollo 11, 12, 14, and 15 samples of fines and breccias have been examined by the deuterated acid dissolution method. Location studies indicate that these carbon compounds are concentrated in the outer surfaces of the fines particles of 48-152 micron diameter; for larger particles a volume-related component may contribute. In individual samples the methane and carbide concentrations correlate with parameters indicative of lunar surface exposure. The data provide further evidence that solar wind implantation is the major source of the methane in the fines and that the carbide originates from both solar wind implantation and meteorite impacts.

Cadogan, P. H.↗
NASA NTRS1981

Information theory lateral density distribution for Earth inferred from global gravity field

Information Theory Inference, better known as the Maximum Entropy Method, was used to infer the lateral density distribution inside the Earth. The approach assumed that the Earth consists of indistinguishable Maxwell-Boltzmann particles populating infinitesimal volume elements, and followed the standard methods of statistical mechanics (maximizing the entropy function). The GEM 10B spherical harmonic gravity field coefficients, complete to degree and order 36, were used as constraints on the lateral density distribution. The spherically symmetric part of the density distribution was assumed to be known. The lateral density variation was assumed to be small compared to the spherically symmetric part. The resulting information theory density distribution for the cases of no crust removed, 30 km of compensated crust removed, and 30 km of uncompensated crust removed all gave broad density anomalies extending deep into the mantle, but with the density contrasts being the greatest towards the surface (typically + or 0.004 g cm 3 in the first two cases and + or - 0.04 g cm 3 in the third). None of the density distributions resemble classical organized convection cells. The information theory approach may have use in choosing Standard Earth Models, but, the inclusion of seismic data into the approach appears difficult.

Rubincam, D. P.↗
NASA NTRS1983

Remote sensing of cloud radiation and microphysical parameters

Multispectral cloud radiometer (MCR) data, retrieved from a radiometer installed in a nadir viewing position on a high-altitude aircraft flying at 200 m/s and at an altitude of 60,000 ft above the mean sea level, are analyzed. The data discussed were obtained in the 0.754, 0.7609, 0.7634, 1.626, 2.125, and 11.38-micron channels, and are compared to lidar-derived profiles. Among the cloud parameters under consideration are the cloud scaled optical thickness, cloudtop altitude, scaled volume scattering coefficient, particle thermodynamic phase, mean particle size, and cloudtop temperature.

Wu, M.-L. C.↗
NASA NTRS1985

Quality of remote sensing measurements of cloud physical parameters in the cooperative convective precipitation experiment

In order to develop the remote sensing techniques to infer cloud physical parameters, a multispectral cloud radiometer (MCR) was mounted on a NASA high-altitude aircraft in conjunction with the Cooperative Convective Precipitation Experiment in 1981. The MCR has seven spectral channels, of which three are centered near windows associated with water vapor bands in the near infrared, two are centered near the oxygen A band at 0.76 microns, one is centered at the 1.14-micron water vapor band, and one is centered in the thermal infrared. The reflectance and temperature measured on May 31, 1981, are presented together with theoretical calculations. The results indicate that the MCR produces quality measurements. Therefore several cloud parameters can be derived with good accuracy. The parameters are the cloud-scaled optical thickness, cloud top pressure, volume scattering coefficient, particle thermodynamic phase, effective mean particle size, and cloud-top temperature.

Wu, M.-L.↗