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At least 397 records · Page 22

All sources NASA NTRS DOE OSTI

DOE OSTI2019

Equilibrium, kinetic, and thermodynamic studies on the sorption of some heavy metal ions by the phosphorus-containing polymer sorbent

The sorption of Cu+{sup 2}, Ni+{sup 2}, Co+{sup 2}, and Zn+{sup 2} ions onto the phosphorus-containing sorbent were studied as a function of the contact time, temperature, and concentration of the initial metal ions. The equilibrium studies are presented by the Langmuir, Freundlich, and Temkin isotherm models. The sorption data are well described by the Langmuir isotherm model, and they also can be simulated by the Freundlich isotherm model. The pseudo-first-order, pseudo-second-order, and intraparticle diffusion models were applied to test the experimental data of the kinetic studies. The pseudo-second-order kinetic model provided the best correlation of the experimental data compared to the other kinetic models. The sorption capacity of the metal ions increased with temperature increasing. The positive value of enthalpy (ΔH°) and the negative value of Gibbs free energy (ΔG°) indicated that the sorption process was endothermic and spontaneous.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Data on the comprehensive first-principles diffusion study of the aluminum-magnesium system

First-principles calculation of diffusion coefficients between Mg and Al is investigated comprehensively using density functional theory (DFT). The effect of different uncertainty sources arising from first principles calculations has been investigated systematically. These sources include the diffusion model, energetic, entropic and attempt frequency calculations. Variation in self and impurity diffusion coefficients of Mg and Al in stable phases are quantified using different DFT settings and compared with the experiments. Using the optimal DFT settings, diffusion coefficients in metastable phases of Al and Mg are predicted. The dataset refers to “An integrated experimental and computational study of diffusion and atomic mobility of the aluminum-magnesium system” [1].

36 MATERIALS SCIENCE↗

DOE OSTI2019

Predictive model of scintillator plastic fogging in portals

We have developed a science-based predictive model for fogging of the scintillator plastics deployed in radiation portal monitors. The only input required is the weather conditions [i.e., daily high and low, for temperature and relative humidity (R.H.)]. The code utilizes this information, together with a thermodynamic model of the water content in equilibrium with the plastic surface, a diffusion model of the water transport into the interior of scintillator plastic panel, and a comparison of the resulting paired “water-content/night-temperature” points as a function of position in the panel against an empirical “fog-line” that establishes a water/temperature criterion for the onset of fogging. In conclusion, we have analyzed the behavior of several representative portal monitor sites, and the output of the model analysis is reasonably consistent with observation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1962

Performance Evaluation of Fixed- and Variable-Area Rocket Exhaust Diffusers Using Single and Clustered Nozzles with and Without Gimbaling

An investigation of exhaust diffusers used for altitude simulation in testing rocket engines was conducted with model diffusers and gaseous nitrogen as the working fluid. This investigation was conducted to evaluate the effects on performance of gimbaling clustered nozzles in a single fixed-area exhaust diffuser. A two-nozzle cluster was gimbaled in all attitudes in four different exhaust-diffuser configurations: (1) a straight circular tube, (2) a straight figure-eight tube, (3) a circular tube with a second throat, and (4) a figure-eight tube with a second throat. Gimbaling clustered nozzles had little effect on the operating pressure ratio for either straight-tube or second-throat diffusers, but caused a large increase in the starting-pressure-ratio requirements in some straight-tube exhaust diffusers. The performance of two or four clustered nozzles with no gimbaling was compared with single-nozzle performance on the basis of the ratio of diffuser area to nozzle-throat area. The performance was found to be dependent on the diffuser- to nozzle-throat-area ratio and independent of both the number of primary nozzles and the nozzle-area ratio. A separate investigation was also conducted to evaluate the performance improvement obtainable with a variable-area exhaust diffuser. This type of diffuser achieved a 26-percent reduction in starting pressure ratio, a 40-percent reduction in operating pressure ratio, and a 50-percent reduction in the overall diffuser length over the values attainable with a fixed-area second-throat diffuser.

ROCKET↗

NASA NTRS1976

A simulation of water pollution model parameter estimation

A parameter estimation procedure for a water pollution transport model is elaborated. A two-dimensional instantaneous-release shear-diffusion model serves as representative of a simple transport process. Pollution concentration levels are arrived at via modeling of a remote-sensing system. The remote-sensed data are simulated by adding Gaussian noise to the concentration level values generated via the transport model. Model parameters are estimated from the simulated data using a least-squares batch processor. Resolution, sensor array size, and number and location of sensor readings can be found from the accuracies of the parameter estimates.

Kibler, J. F.↗

NASA NTRS1988

Cosmic-ray lifetime in the Galaxy - Experimental results and models

The separation of the cosmic-ray Be isotopes achieved by two satellite experiments is discussed. From the measured isotopic ratio between the radioactive Be-10 (half-life = 1,500,000 years) and the stable Be-9, it is deduced that the cosmic rays propagate through matter with an average density of 0.24 = or - 0.07 atoms/ cu cm. The implications of this result for the cosmic-ray age is reviewed in the context of two models of confinement and propagation: the homogeneous model, normally identified with confinement ot the galactic gaseous disk, and a diffusion model in which the cosmic rays extend into a galactic halo. A newly deduced cosmic-ray pathlength distribution, a self-consistent model of solar modulation, and a set of fragmentation cross sections are calculated. It is concluded that in a homogeneous model, the cosmic-ray age is 15 (+7, -4) million years, about a factor longer than early estimates based on the abundances of the light nuclei Li, Be, and B and a nominal interstellar density of 1 atom/ cu cm.

Simpson, J. A.↗

NASA NTRS1990

Convection links biomass burning to increased tropical ozone - However, models will tend to overpredict O3

Biomass burning throughout the inhabited portions of the tropics generates precursors which lead to significant local atmospheric ozone pollution. Several simulations show how this smog could be only an easily observed, local manifestation of a much broader increase in tropospheric ozone. The basic processes are illustrated with a one-dimensional time-dependent model that is closer to true meteorological motions than commonly used eddy diffusion models. Its application to a representative region of South America gives reasonable simulations of the local pollutants measured there. Three illustrative simulations indicate the importance of dilution, principally due to vertical transport, in increasing the efficiency of ozone production, possibly enough for high ozone to be apparent on a very large, intercontinental scale.

Chatfield, Robert B.↗

NASA NTRS2000

Efficient Multi-Dimensional Simulation of Quantum Confinement Effects in Advanced MOS Devices

We investigate the density-gradient (DG) transport model for efficient multi-dimensional simulation of quantum confinement effects in advanced MOS devices. The formulation of the DG model is described as a quantum correction to the classical drift-diffusion model. Quantum confinement effects are shown to be significant in sub-100nm MOSFETs. In thin-oxide MOS capacitors, quantum effects may reduce gate capacitance by 25% or more. As a result, the inclusion or quantum effects in simulations dramatically improves the match between C-V simulations and measurements for oxide thickness down to 2 nm. Significant quantum corrections also occur in the I-V characteristics of short-channel (30 to 100 nm) n-MOSFETs, with current drive reduced by up to 70%. This effect is shown to result from reduced inversion charge due to quantum confinement of electrons in the channel. Also, subthreshold slope is degraded by 15 to 20 mV/decade with the inclusion of quantum effects via the density-gradient model, and short channel effects (in particular, drain-induced barrier lowering) are noticeably increased.

Biegel, Bryan A.↗

NASA NTRS2000

Efficient Multi-Dimensional Simulation of Quantum Confinement Effects in Advanced MOS Devices

We investigate the density-gradient (DG) transport model for efficient multi-dimensional simulation of quantum confinement effects in advanced MOS devices. The formulation of the DG model is described as a quantum correction ot the classical drift-diffusion model. Quantum confinement effects are shown to be significant in sub-100nm MOSFETs. In thin-oxide MOS capacitors, quantum effects may reduce gate capacitance by 25% or more. As a result, the inclusion of quantum effects may reduce gate capacitance by 25% or more. As a result, the inclusion of quantum effects in simulations dramatically improves the match between C-V simulations and measurements for oxide thickness down to 2 nm. Significant quantum corrections also occur in the I-V characteristics of short-channel (30 to 100 nm) n-MOSFETs, with current drive reduced by up to 70%. This effect is shown to result from reduced inversion charge due to quantum confinement of electrons in the channel. Also, subthreshold slope is degraded by 15 to 20 mV/decade with the inclusion of quantum effects via the density-gradient model, and short channel effects (in particular, drain-induced barrier lowering) are noticeably increased.

Biegel, Bryan A.↗

NASA NTRS2006

Hybrid MD-Nernst Planck Model of Alpha-hemolysin Conductance Properties

Motivated by experiments in which an applied electric field translocates polynucleotides through an alpha-hemolysin protein channel causing ionic current transient blockade, a hybrid simulation model is proposed to predict the conductance properties of the open channel. Time scales corresponding to ion permeation processes are reached using the Poisson-Nemst-Planck (PNP) electro-diffusion model in which both solvent and local ion concentrations are represented as a continuum. The diffusion coefficients of the ions (K(+) and Cl(-)) input in the PNP model are, however, calculated from all-atom molecular dynamics (MD). In the MD simulations, a reduced representation of the channel is used. The channel is solvated in a 1 M KCI solution, and an external electric field is applied. The pore specific diffusion coefficients for both ionic species are reduced 5-7 times in comparison to bulk values. Significant statistical variations (17-45%) of the pore-ions diffusivities are observed. Within the statistics, the ionic diffusivities remain invariable for a range of external applied voltages between 30 and 240mV. In the 2D-PNP calculations, the pore stem is approximated by a smooth cylinder of radius approx. 9A with two constriction blocks where the radius is reduced to approx. 6A. The electrostatic potential includes the contribution from the atomistic charges. The MD-PNP model shows that the atomic charges are responsible for the rectifying behaviour and for the slight anion selectivity of the a-hemolysin pore. Independent of the hierarchy between the anion and cation diffusivities, the anionic contribution to the total ionic current will dominate. The predictions of the MD-PNP model are in good agreement with experimental data and give confidence in the present approach of bridging time scales by combining a microscopic and macroscopic model.

Cozmuta, Ioana↗

DOE OSTI2025

Consistent solutions of the radiation diffusion equation in spherical and cylindrical geometries

We have extended the radiation diffusion model of Hammer and Rosen [Phys. Plasmas 10, 1829 (2003)] to diverging spherical and cylindrical geometries. The effect of curvilinear geometry on the supersonic, expanding wavefront increases as the internal radius of a spherical or cylindrical shell approaches zero. Small spherical geometries are important for modeling systems at the size scale of inertial confinement fusion capsules, at these scales existing quasi-analytic models for planar geometry significantly disagree with the results of simulation. With this method, the benefits of rapid iteration can be applied to common spherical systems at much smaller length scales. We present comparisons between numerical diffusion solutions and the analytic model to give ranges of applicability for the model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Robustness of the Ensemble Score Filter to the Type of Assimilated Observation Networks

Recent advances in data assimilation (DA) have focused on developing more flexible approaches that can better accommodate nonlinearities in models and observations. However, it remains unclear how the performance of these advanced methods depends on the observation network characteristics. In this study, we present initial experiments with the surface quasi‐geostrophic model, in which we compare a recently developed ensemble filter using score‐based diffusion models with the standard Local Ensemble Transform Kalman Filter (LETKF). Our results show that the analysis solutions respond differently to the number, spatial distribution, and nonlinear fraction of assimilated observations. We also find notable changes in the multiscale characteristics of the analysis errors. Given that standard DA techniques will eventually be replaced by more advanced methods, we hope this study sets the ground for future efforts to reassess the value of Earth observing systems in the context of newly emerging algorithms.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Modelling and analysis of salt-convection effect on oxide reduction process for uranium oxides using smoothed particle hydrodynamics

Oxygen ion transport via molten salt continuum is a key kinetic feature of electrochemical reduction process for uranium oxides in molten salt. During the electrolysis, the evolution of oxygen ion concentration field in molten salt continuum appears from porous metallic layer to open bulk salt. Despite the important role affecting process throughput, its effect coupled with controlled salt movement was not adequately investigated. To capture the reactive oxygen ion transport phenomena, a multidimensional reduction model based on smoothed particle hydrodynamics (SPH) was combined with the advection-diffusion model. A pelletized oxide fuel bed capturing interconnected salt continuum is considered as a reactant material geometry, which allows forced convective delivery of molten salt through the reactant materials with a relatively low pressure head. Here, in this study, reduction time of a pelletized-fuel bed was quantified with respect to key design parameters of the reactant material configuration. The simulation results demonstrated the advantage of salt convection which effectively removes oxygen ion products from the reactant materials and consequently accelerates the reduction process. Moreover, the reduction-time correlation of a single pelletized fuel was developed as a function of relevant dimensionless parameters and was extended to the application for a pelletized-fuel bed. Finally, several insights and implications in the use of a pelletized oxide fuel were presented. The developed SPH-based framework enabled multi-physics analysis of governing dynamics in appreciating and screening candidate reactant material configurations in a cost-effective manner.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Tunable chemical complexity to control atomic diffusion in alloys

Abstract In this paper we report a new fundamental understanding of chemically-biased diffusion in Ni–Fe random alloys that is tuned/controlled by the intrinsic quantifiable chemical complexity. Development of radiation-tolerant alloys has been a long-standing challenge. Here we show how intrinsic chemical complexity can be utilized to guide the atomic diffusion and suppress radiation damage. The influence of chemical complexity is shown by the example of interstitial atom (IA) diffusion that is the most important defect in radiation effects. We use μs-scale molecular dynamics to reveal sluggish diffusion and percolation of IAs in concentrated Ni–Fe alloys. We develop a mean field diffusion model to take into account the effect of migrating defect energy properties on diffusion percolation, which is verified by a new kinetic Monte Carlo approach addressing detailed processes. We demonstrate that the local variations in the ground state energy of IA configurations in alloys, reflecting the chemical difference between alloying components, drives the percolation effects for atomic diffusion. Percolation, chemically-biased and sluggish diffusion are phenomena that are directly related to the chemical complexity intrinsically to multicomponent alloys.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Conditional diffusion machine-learning framework for mapping valence electron distribution from convergent beam electron diffraction

Quantitative convergent beam electron diffraction (CBED) enables determination of aspherical valence electron distributions through refinement of low-order structure factors, which are highly sensitive to chemical bonding and charge density variations. However, conventional quantitative CBED (QCBED) requires solving a highly nonlinear inverse problem with many coupled parameters, and computationally intensive dynamical diffraction calculations, making it time-consuming and difficult to apply to complex systems. More broadly, reconstructing charge density and orbital electron distribution from diffraction data has long been a central challenge in both x-ray and electron crystallography. Here, in this study, we introduce an artificial-intelligence (AI)-based framework that replaces traditional refinement with a data-driven inverse solver. Using a large synthetic CBED dataset generated by Bloch-wave simulations, we train a conditional diffusion model to directly infer crystal structural parameters and multipole density formalism parameters, and hence valence electron distributions, from CBED patterns alone. By learning from forward simulations across realistic parameter space, the model effectively solves the inverse problem. Compared with direct regression approaches, the diffusion-based framework provides posterior parameter distributions for rigorous uncertainty quantification while preserving quantitative fidelity and reducing analysis time by orders of magnitude. By eliminating the need for external single-crystal x-ray diffraction data and complex nonlinear refinement, this approach enables practical, high-throughput, and in situ quantitative CBED, enabling real-time mapping of valence electron distributions and their correlation with functional responses in quantum and energy materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS1985

Plasma-gas interactions studies in a hybrid plume plasma rocket

Plasma-gas interaction was investigated and the basic mechanisms for energy and particle transport. The solution approach assumes cylindrical geometry and includes a multiplicity of atomic reactions, and the presence of a strong magnetic field is described. The principal reactions are electron and ion impact ionization, and charge exchange between hot ions and cold neutrals. Radial particle and energy transport is mainly by diffusion. A modified Bohm diffusion model for plasma in the core of the plume, and classical neutral particle diffusion in the cooler regions of the flow are presented. Neutrals are allowed to free stream in the low density regions, where the collision mean-free-path becomes comparable, or even larger than the characteristic dimensions of the system.

Chang, F. R.↗

NASA NTRS1992

Time-dependent cosmic ray shocks with injection - A progress report

The study presents preliminary results of a two-fluid hydrodynamical simulation of cosmic-ray-modified shock structure by extending the steady-state calculations of Zank et al. (1991) to the time-dependent case. The present simulations model diffusive shock acceleration of the energetic particle component at planar shocks. A new model for the injection of cosmic ray particles is presented. The quadratic artificial viscosity algorithm is found to be numerically unstable and therefore unusable for strong cosmic ray shocks. There is visible ringing and overshoot in the various profiles. A large enhancement in the fluid density appears downstream of the subshock. This 'overcompression' results from the upstream fluid being compressed in the precursor, then traversing a strong shock with compression ratio near the adiabatic limit of four.

Donohue, D. J.↗

DOE OSTI2020

Analyzing the co-evolution of green technology diffusion and consumers’ pro-environmental attitudes: An agent-based model

Massive diffusion of green technologies is significant for building a cleaner world. However, the process of technology diffusion is usually slow and complex. An in-depth understanding of the mechanism regarding green technology diffusion is an essential precondition for effectively stimulating this process. Green technology diffusion heavily involves both social and technological changes. Although existing studies have provided rich knowledge about identifying critical drivers and barriers affecting green technology diffusion, research that considers consumers’ pro-environmental attitudes and green technology diffusion as an evolving system is still sparse. Aiming at exploring the co-evolution of consumers’ pro-environmental attitudes and green technology diffusion, this paper builds an agent-based model that integrates the relative agreement model with technology diffusion theories to conduct a sequence of controlled numerical experiments, which progressively unveil how attitudinal and technological factors impact green technology diffusion. The main findings include that (1) improving consumers’ pro-environmental attitudes is prominently beneficial to green technology diffusion and maturation; (2) technology maturity has very limited impact on consumers’ first-time purchases but significantly affects consumers’ satisfaction, which would further impact consumers’ repeat purchases; (3) consumers that do not support green technologies frequently emerge during the evolution of attitudes (despite the high technology maturity), which corresponds to the emergence of the anti-environmental groups observed in the real world; (4) active interactions between non-adopters enable their attitudes to converge, which results in the polarization of consumers’ attitudes.

ABM↗