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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Expected Power-Utility Maximization Under Incomplete Information and with Cox-Process Observations

We consider the problem of maximization of expected terminal power utility (risk sensitive criterion). The underlying market model is a regime-switching diffusion model where the regime is determined by an unobservable factor process forming a finite state Markov process. The main novelty is due to the fact that prices are observed and the portfolio is rebalanced only at random times corresponding to a Cox process where the intensity is driven by the unobserved Markovian factor process as well. This leads to a more realistic modeling for many practical situations, like in markets with liquidity restrictions; on the other hand it considerably complicates the problem to the point that traditional methodologies cannot be directly applied. The approach presented here is specific to the power-utility. For log-utilities a different approach is presented in Fujimoto et al. (Preprint, 2012).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Modeling O and N Alloying in Nb for SRF Applications

N and O-alloyed superconducting radio frequency cavities exhibit extraordinary quality factors. Developing diffusion models that describe interstitial N and O in Nb is important for optimizing alloyed cavity quality factors and accelerating gradients. N and O-alloyed Nb samples are examined with SEM AND SIMS and their diffusion profiles modeled.

Lechner, Eric↗
DOE OSTI2013

Comparison of neutron diffusion and Monte Carlo models for a fission wave

Many groups have used neutron diffusion simulations to study fission wave phenomena in natural or depleted uranium. However, few studies of fission wave phenomena have been published that use Monte Carlo simulations to confirm the results of diffusion models for this type of system. In the present work we show the results of a criticality and burnup simulation of a traveling wave reactor using MCNPX 2.7.0. The characteristics of the fission wave in this simulation are compared with those from a simple one-dimensional, one-group neutron diffusion model. The diffusion simulations produce a wave speed of 5.9 cm/yr versus 5.3 cm/yr for the Monte Carlo simulations. The axial flux profile in the Monte Carlo simulation is similar in shape to the diffusion results, but with different peak values, and the two profiles have an R2 value of 0.93. The {sup 238}U, {sup 239}Np and {sup 239}Pu burnup profiles from the diffusion simulation show good agreement with the Monte Carlo simulations, R values of 0.98, 0.93 and 0.97 respectively are observed. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

ENERGETIC PARTICLE CROSS-FIELD PROPAGATION EARLY IN A SOLAR EVENT

Solar energetic particles (SEPs) have been observed to easily spread across heliographic longitudes, and the mechanisms responsible for this behavior remain unclear. We use full-orbit simulations of a 10 MeV proton beam in a turbulent magnetic field to study to what extent the spread across the mean field can be described as diffusion early in a particle event. We compare the full-orbit code results to solutions of a Fokker-Planck equation including spatial and pitch angle diffusion, and of one including also propagation of the particles along random-walking magnetic field lines. We find that propagation of the particles along meandering field lines is the key process determining their cross-field spread at 1 AU at the beginning of the simulated event. The mean square displacement of the particles an hour after injection is an order of magnitude larger than that given by the diffusion model, indicating that models employing spatial cross-field diffusion cannot be used to describe early evolution of an SEP event. On the other hand, the diffusion of the particles from their initial field lines is negligible during the first 5 hr, which is consistent with the observations of SEP intensity dropouts. We conclude that modeling SEP events must take into account the particle propagation along meandering field lines for the first 20 hr of the event.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Modeling Ni redistribution in the hydrogen electrode of solid oxide cells through Ni(OH) 2 diffusion and Ni-YSZ wettability change

Ni redistribution in the hydrogen electrodes of solid oxide cells is an important degradation mechanism. Its driving force is still under debate. This work focuses on the interplay between Ni(OH) 2 diffusion and Ni-YSZ wettability change. With a Ni(OH) 2 diffusion model developed in our previous work, we further employ three models for the Ni-YSZ contact angle to quantify the Ni-YSZ wettability change. The microstructure evolutions in a reconstructed Ni-YSZ electrode are simulated under selected experimental operating conditions. It is shown that the phenomenological model can capture the driving force of Ni spreading/detachment on YSZ surface and the Ni migration reported in experiments can be qualitatively reproduced through the competition between Ni(OH) 2 diffusion and Ni-YSZ wettability change. It is also found that the initial microstructure of the active layer and the microstructure characteristics in the support layer can strongly affect the distribution of steam partial pressure and overpotential, hence the Ni redistribution, in the active layer, which may explain the inconsistencies in experiments. Further, our results show that there are two missing pieces in current theory of Ni redistribution: a mechanism of fast Ni diffusion under humid atmosphere and the physical reason behind the Ni spreading/detachment.

25 ENERGY STORAGE↗
DOE OSTI2014

A stochastic extension of the explicit algebraic subgrid-scale models

The explicit algebraic subgrid-scale (SGS) stress model (EASM) of Marstorp et al. [“Explicit algebraic subgrid stress models with application to rotating channel flow,” J. Fluid Mech. 639, 403–432 (2009)] and explicit algebraic SGS scalar flux model (EASFM) of Rasam et al. [“An explicit algebraic model for the subgrid-scale passive scalar flux,” J. Fluid Mech. 721, 541–577 (2013)] are extended with stochastic terms based on the Langevin equation formalism for the subgrid-scales by Marstorp et al. [“A stochastic subgrid model with application to turbulent flow and scalar mixing,” Phys. Fluids 19, 035107 (2007)]. The EASM and EASFM are nonlinear mixed and tensor eddy-diffusivity models, which improve large eddy simulation (LES) predictions of the mean flow, Reynolds stresses, and scalar fluxes of wall-bounded flows compared to isotropic eddy-viscosity and eddy-diffusivity SGS models, especially at coarse resolutions. The purpose of the stochastic extension of the explicit algebraic SGS models is to further improve the characteristics of the kinetic energy and scalar variance SGS dissipation, which are key quantities that govern the small-scale mixing and dispersion dynamics. LES of turbulent channel flow with passive scalar transport shows that the stochastic terms enhance SGS dissipation statistics such as length scale, variance, and probability density functions and introduce a significant amount of backscatter of energy from the subgrid to the resolved scales without causing numerical stability problems. The improvements in the SGS dissipation predictions in turn enhances the predicted resolved statistics such as the mean scalar, scalar fluxes, Reynolds stresses, and correlation lengths. Moreover, the nonalignment between the SGS stress and resolved strain-rate tensors predicted by the EASM with stochastic extension is in much closer agreement with direct numerical simulation data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Modeling the Contribution of Precipitation Loss to a Radiation Belt Electron Dropout Observed by Van Allen Probes

A drift-diffusion model is used to simulate the low-altitude electron distribution, accounting for azimuthal drift, pitch angle diffusion, and atmospheric backscattering effects during a rapid electron dropout event on 21st August 2013, at L = 4.5. Additional external loss effects are introduced during times when the low-altitude electron distribution cannot be reproduced by diffusion alone. Here, the model utilizes low-altitude electron count rate data from five POES/MetOp satellites to quantify pitch angle diffusion rates. Low-altitude data provides critical constraint on the model because it includes the drift loss cone region where the electron distribution in longitude is highly dependent on the balance between azimuthal drift and pitch angle diffusion. Furthermore, a newly derived angular response function for the detectors onboard POES/MetOp is employed to accurately incorporate the bounce loss cone measurements, which have been previously contaminated by electrons from outside the nominal field-of-view. While constrained by low-altitude data, the model also shows reasonable agreement with high-altitude data. Pitch angle diffusion rates during the event are quantified and are faster at lower energies. Precipitation is determined to account for all of the total loss observed for 450 keV electrons, 88% for 600 keV and 38% for 900 keV. Predictions made in the MeV range are deemed unreliable as the integral energy channels E3 and P6 fail to provide the necessary constraint at relativistic energies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Diffusion-controlled reactions modeling in Geant4-DNA

Context Under irradiation, a biological system undergoes a cascade of chemical reactions that can lead to an alteration of its normal operation. There are different types of radiation and many competing reactions. As a result the kinetics of chemical species is extremely complex. The simulation becomes then a powerful tool which, by describing the basic principles of chemical reactions, can reveal the dynamics of the macroscopic system. To understand the dynamics of biological systems under radiation, since the 80s there have been on-going efforts carried out by several research groups to establish a mechanistic model that consists in describing all the physical, chemical and biological phenomena following the irradiation of single cells. This approach is generally divided into a succession of stages that follow each other in time: (1) the physical stage, where the ionizing particles interact directly with the biological material; (2) the physico-chemical stage, where the targeted molecules release their energy by dissociating, creating new chemical species; (3) the chemical stage, where the new chemical species interact with each other or with the biomolecules; (4) the biological stage, where the repairing mechanisms of the cell come into play. This article focuses on the modeling of the chemical stage. Method This article presents a general method of speeding-up chemical reaction simulations in fluids based on the Smoluchowski equation and Monte-Carlo methods, where all molecules are explicitly simulated and the solvent is treated as a continuum. The model describes diffusion-controlled reactions. This method has been implemented in Geant4-DNA. The keys to the new algorithm include: (1) the combination of a method to compute time steps dynamically with a Brownian bridge process to account for chemical reactions, which avoids costly fixed time step simulations; (2) a k–d tree data structure for quickly locating, for a given molecule, its closest reactants. The performance advantage is presented in terms of complexity, and the accuracy of the new algorithm is demonstrated by simulating radiation chemistry in the context of the Geant4-DNA project. Application The time-dependent radiolytic yields of the main chemical species formed after irradiation are computed for incident protons at different energies (from 50 MeV to 500 keV). Both the time-evolution and energy dependency of the yields are discussed. The evolution, at one microsecond, of the yields of hydroxyls and solvated electrons with respect to the linear energy transfer is compared to theoretical and experimental data. According to our results, at high linear energy transfer, modeling radiation chemistry in the trading compartment representation might be adopted.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Fundamental Study on Sorption Behavior of Europium to Mica Flakes - 19116

It is well known that biotite exists with flake form in actual underground environment, dominating sorption of cationic radionuclides in a geological disposal system consisting of crystalline rock. The behavior of sorption of radionuclides will differ depending on the difference in shape, while most of the previous studies have used powder biotite. This study focused on the influence of flake structure of phyllosilicate minerals such as biotite on the diffusion and sorption processes of radionuclides, examining the sorption behaviors of Eu on biotite, phlogopite and muscovite in flake form. These flakes (5 mm x 6 mm) were prepared for the sorption experiments and the initial concentrations of the Eu ions were set to 1 mM. The sorption experiments were conducted by mixing 0.4 g of biotite flakes and 4 mL at pH 5 for 7 days. As a result, the sorption amount of Eu increased little by little with internal diffusion in all minerals, respectively. The diffusion process of Eu into the layer structure could be also observed by secondary ion-microprobe mass spectrometry (SIMS) analysis. The apparent diffusion coefficient of Eu into each flake was estimated by fitting a 2-D diffusion model to the sorption data. The estimated diffusion values were clearly smaller than that of matrix diffusion in granite. Hence it was suggested that the so-called Kd-model, which is a local equilibrium model, is not always applicable to the estimation of the retardation effect (i.e., migration rate) of radionuclides in rock matrix. In other words, the migration rate might depend also on the diffusion process of radionuclide in the inside of phyllosilicate minerals in addition of the macro diffusion process in rock matrix. Besides, sorption amount and diffusion coefficient of biotite, phlogopite and muscovite were largely different. Not only the tetrahedral structure adjacent to the potassium but also the octahedral structure might affect the restraint of the interlayer ion (K ions) and the sorption behavior. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

A two-phase model that unifies and extends the classical models of membrane transport

Two models describe solvent transport through swollen, nonporous membranes. The pore-flow model, based on fluid mechanics, works for porous membranes, whereas the solution-diffusion model invokes molecular diffusion to treat nonporous membranes. Both approaches make valid arguments for swollen polymer membranes, but they disagree in their predictions of intramembrane pressure and concentration profiles. Using a fluid-solid model that treats the solvent and membrane matrix as separate phases, we show both classical models to be valid, to represent complementary approaches to the same phenomenon, and to make identical predictions. The fluid-solid model clarifies recent reverse osmosis measurements; provides a predictive and mechanistic basis for empirical high-pressure limiting flux phenomena, in quantitative agreement with classic measurements; and gives a framework to treat nonporous but mechanically heterogeneous membrane materials.

Science & Technology - Other Topics↗
DOE OSTI2018

Nonlinear optimization for a tumor invasion PDE model

In this work, we introduce a methodology to approximate unknown parameters that appear on a non-linear reaction–diffusion model of tumor invasion. These equations consider that tumor-induced alteration of micro-environmental pH furnishes a mechanism for cancer invasion. A coupled system reaction–diffusion explaining this model is given by three partial differential equations for the non-dimensional spatial distribution and temporal evolution of the density of normal tissue, the neoplastic tissue growth and the excess concentration of H{sup +} ions. The tumor model parameters have a corresponding biological meaning: the reabsorption rate, the destructive influence of H{sup +} ions in the healthy tissue, the growth rate of tumor tissue and the diffusion coefficient. We propose to solve the direct problem using the Finite Element Method (FEM) and minimize an appropriate functional including both the real data (obtained via in-vitro experiments and fluorescence ratio imaging microscopy) and the numerical solution. The gradient of the functional is computed by the adjoint method.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Multicomponent transport of alcohols in an anion exchange membrane measured by in-situ ATR FTIR spectroscopy

Multicomponent transport through membranes is encountered in many applications, including photoelectrochemical CO2 reduction devices that convert CO2 into alcohols. We report the use of in-situ ATR FTIR spectroscopy to quantify the permeability of Selemion AMV, a commonly used anion exchange membrane, to mixtures of alcohols. An in-situ ATR FTIR spectrophotometer probe inserted into a standard diffusion cell enabled straightforward measurement of membrane permeability in multicomponent transport experiments without the need to periodically remove aliquots from the diffusion cell. The solubilities of alcohols in Selemion AMV were measured using a standard sorption/desorption technique. The solution-diffusion model was used to calculate alcohol diffusivities in Selemion AMV from measured permeabilities and solubilities. In addition, the relative contributions of alcohol solubility and diffusivity to overall permeability are discussed, and changes in permeability, solubility, and diffusivity with changing composition in binary and ternary alcohol mixtures are described.

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

Combined Normal and Disruption, Electromagnetic Transient, Thermal, and Structural Analysis of COMPASS Upgrade

We report that COMPASS Upgrade is a replacement for the COMPASS device at the Institute of Plasma Physics (IPP) of the Czech Academy of Sciences. It is a cryogenic copper machine with a major radius of 0.89 m, with 5 T at the plasma centerline and 2-MA plasma current. It is intended to develop ITER relevant plasma densities and high power fluxes in the divertor region. The entire vacuum vessel is planned to reach 500 °C. The COMPASS-U TF coil is a bitter plate-like design with radial conductor plates that extend the width of the TF inner leg. Currents redistribute radially based on resistive and inductive effects. This necessitates an electromagnetic (EM) transient analysis of the coil current distribution. For copper coils like COMPASS Upgrade, the solution must be coupled with a thermal solution to properly include the temperature-dependent resistive effects. The EM transient solution includes the TF magnetic loads, and a stress pass on the results produces in-plane loads. The EM solution chosen requires inclusion of all the conducting and nonconducting regions surrounding the TF coil. With the TF current distribution solved, the addition of the poloidal coils and resulting background fields allows the determination of the out-of-plane loads. Integration of the Joule heating produced from the EM solution produces temperature distributions throughout the shot, which can be read in to a structural pass to include thermal stresses in the evaluation. This is true of both TF and PF temperature prediction with appropriate packing fractions. Currents in the PF coils, with computed background fields, produce Lorentz loads. Time transients of the PF currents produce startup eddy currents in the structures included in the model; inclusion of the vessel and other passive structures allows these to be included in a stress pass. The EM transient solution includes all the elements needed for a disruption analysis with prescribed motions and quench of the plasma. From a model originally intended to simulate current diffusion in the TF coil, the analysis can be refined to be used to predict the performance of most of the components of the tokamak or provide boundary conditions for more detailed submodels. In this article, the use of the current diffusion model for bounding assessments of the COMPASS Upgrade TF, PF, vessel, external structure, and disruption analyses will be presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

2016 Standard Scenarios Report: A U.S. Electricity Sector Outlook

The Standard Scenarios and this associated report, which are now in their second year, present an examination of some of the key aspects of the change occurring, or anticipated to occur, in the power sector over the next several decades. The Standard Scenarios consist of 18 power sector scenarios which have been projected using the National Renewable Energy Laboratory's (NREL's) Regional Energy Deployment System (ReEDS) long-term capacity expansion model and the dGen rooftop PV diffusion model. The purpose of the Standard Scenarios and this associated report is to provide context, discussion, and data to inform stakeholder decision-making regarding the future direction of U.S. power sector. As an extension to this report, the Standard Scenario outputs are presented in a downloadable format online using the Standard Scenarios' Results Viewer at http://en.openei.org/apps/reeds/. This report reflects high-level conclusions and analysis, whereas the Standard Scenarios' Results Viewer includes the scenario results that can be used for more in-depth analysis.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Isopycnal mixing by mesoscale eddies significantly impacts oceanic anthropogenic carbon uptake

Abstract Anthropogenic carbon dioxide uptake varies across Earth System Models for reasons that have remained obscure. When varied within a single model, the lateral eddy mixing coefficient A Redi produces a range of uptake similar to the modeled range. The highest uptake, resulting from a simulation with a constant A Redi of 2400 m 2 /s, simulates 15% more historical carbon uptake than a model with A Redi = 400 m 2 /s. A sudden doubling in carbon dioxide produces a 21% range in carbon uptake across the models. Two spatially dependent representations of A Redi produce uptake that lies in the middle of the range of constant values despite predicting very large values in the subtropical gyres. One‐dimensional diffusive models of the type used for integrated assessments can be fit to the simulations, with A Redi accounting for a substantial fraction of the effective vertical diffusion. Such models, however, mask significant regional changes in stratification and biological carbon storage.

Gnanadesikan, Anand↗
DOE OSTI2025

IoT-based retrofit information diffusion in future smart communities

Community-scale building retrofits are not merely scaled-up versions of single-building retrofits. They involve complex challenges, such as reconciling individual interests with collective goals and managing the dynamic interplay between buildings through mechanisms like power grids and social connections. Internet of Things (IoT) connectivity holds the potential to leverage these interplays to balance individual and collective interests effectively in smart communities. One critical aspect of this interplay is information diffusion, which shapes how retrofit decisions spread among neighbors, influencing individual choices and ultimately impacting community-level retrofit outcomes. In other words, IoT-based smart devices automatically push tailored retrofit notifications to homeowners, which completely changes the format of information diffusion in the future. To investigate this influence by such information diffusion, the study used CityBES to simulate energy performance for different retrofits and applied an information diffusion model to analyze how decisions spread in a networked community of 192 buildings. The diffusion process was modeled on a weighted, directed network, capturing the dynamics of information flow and decision-making across 16 scenarios. Individual retrofit benefits were evaluated through payback years, while community-level retrofit outcomes were assessed using greenhouse gas (GHG) emission reductions. The results demonstrate that easier information diffusion among neighbors encourages households to prioritize retrofit measures that align with the majority’s optimal choices, even at the expense of individual financial benefits. In this case, such collective prioritization enhanced community-level retrofit performance, increasing GHG emission reductions by up to 29.4 %. However, this improvement came with trade-offs, as the average payback period for households extended by approximately 1.74 years. These findings highlight the potential of IoT-based information diffusion in future smart communities to coordinate individual interests with collective goals, ultimately accelerating community-level building retrofits.

Shu, Lei↗
DOE OSTI2014

A First-Passage Kinetic Monte Carlo method for reaction–drift–diffusion processes

Stochastic reaction–diffusion models are now a popular tool for studying physical systems in which both the explicit diffusion of molecules and noise in the chemical reaction process play important roles. The Smoluchowski diffusion-limited reaction model (SDLR) is one of several that have been used to study biological systems. Exact realizations of the underlying stochastic processes described by the SDLR model can be generated by the recently proposed First-Passage Kinetic Monte Carlo (FPKMC) method. This exactness relies on sampling analytical solutions to one and two-body diffusion equations in simplified protective domains. In this work we extend the FPKMC to allow for drift arising from fixed, background potentials. As the corresponding Fokker–Planck equations that describe the motion of each molecule can no longer be solved analytically, we develop a hybrid method that discretizes the protective domains. The discretization is chosen so that the drift–diffusion of each molecule within its protective domain is approximated by a continuous-time random walk on a lattice. New lattices are defined dynamically as the protective domains are updated, hence we will refer to our method as Dynamic Lattice FPKMC or DL-FPKMC. We focus primarily on the one-dimensional case in this manuscript, and demonstrate the numerical convergence and accuracy of our method in this case for both smooth and discontinuous potentials. We also present applications of our method, which illustrate the impact of drift on reaction kinetics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Kinetic modeling of evolution of 3 + 1:Resonance enhanced multiphoton ionization plasma in argon at low pressures

We present numerical kinetic modeling of generation and evolution of the plasma produced as a result of resonance enhanced multiphoton ionization (REMPI) in Argon gas. The particle-in-cell/Monte Carlo collision (PIC/MCC) simulations capture non-equilibrium effects in REMPI plasma expansion by considering the major collisional processes at the microscopic level: elastic scattering, electron impact ionization, ion charge exchange, and recombination and quenching for metastable excited atoms. The conditions in one-dimensional (1D) and two-dimensional (2D) formulations correspond to known experiments in Argon at a pressure of 5 Torr. The 1D PIC/MCC calculations are compared with the published results of local drift-diffusion model, obtained for the same conditions. It is shown that the PIC/MCC and diffusion-drift models are in qualitative and in reasonable quantitative agreement during the ambipolar expansion stage, whereas significant non-equilibrium exists during the first few 10 s of nanoseconds. 2D effects are important in the REMPI plasma expansion. The 2D PIC/MCC calculations produce significantly lower peak electron densities as compared to 1D and show a better agreement with experimentally measured microwave radiation scattering.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗