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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Evaluation of probability density function descriptions for three-component Rayleigh–Taylor mixing

Results from simulations of a three-component Rayleigh–Taylor (RT) mixing problem are presented. These simulations are conducted in heavy–light–heavy and heavy–intermediate–light configurations, and each of these configurations are further considered in high- and low-Reynolds-number regimes. This results in RT-unstable flow with one or both interfaces initially unstable, permitting the influence of problem configuration on the statistical description of three-component RT-driven mixing to be considered. Mass fraction covariances are observed to undergo a sign change through the mixing layer in all four configurations considered. This appears to be unique to the multi-component case and represents another way in which multi-component RT mixing differs from the two-component case. Qualitative and quantitative comparisons of joint and marginal probability density function (PDF) descriptions of species concentration are made. Three-, five-, and six-parameter model PDFs are compared against simulation data to assess how accurately they describe the mixing, and it is found that three-component mixing requires at least a five-parameter model PDF to accurately describe the mixing. Notably, the marginal distributions of three-component mixing do not appear to conform to a beta distribution, representing a departure from the classical two-component RT case. In conclusion, statistical neutrality also appears to influence the optimal choice of model PDF, which is found to be a function of problem configuration.

Large-eddy simulation↗
DOE OSTI2020

Self-radiography of imploded shells on OMEGA based on additive-free multi-monochromatic continuum spectral analysis

Radiographs of pure-DT cryogenic imploding shells provide critical validation of progress toward ignition-scalable performance of inertial confinement fusion implosions. Cryogenic implosions on the OMEGA Laser System can be self-radiographed by their own core spectral emission near ≈2 keV. Utilizing the distinct spectral dependences of continuum emissivity and opacity, the projected optical-thickness distribution of imploded shells, i.e., the shell radiograph, can be distinguished from the structure of the core emission distribution in images.Importantly, this can be done without relying on spectral additives (shell dopants), as in previous applications of implosion self-radiography. Furthermore, demonstrations with simulated data show that this technique is remarkably well-suited to cryogenic implosions and can also be applied to self-radiography of imploded room-temperature CH shells at higher spectral energy (hv ≈ 3–5 keV) based on the very similar continuum spectrum of carbon. Experimental demonstration of additive-free self-radiography with warm CH shell implosions on OMEGA will provide an important proof of principle for future applications to cryogenic DT implosions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Extension of the BMCSL equation of state for hard spheres to the metastable disordered region: Application to the SAFT approach

A simple modification of the Boublík-Mansoori-Carnahan-Starling-Leland equation of state is proposed for an application to the metastable disordered region. The new model has a positive pole at the jamming limit and can accurately describe the molecular simulation data of pure hard in the stable fluid region and along the metastable branch. The new model has also been applied to binary mixtures hard spheres, and an excellent description of the fluid and metastable branches can be obtained by adjusting the jamming packing fraction. The new model for hard sphere mixtures can be used as the repulsive term of equations of state for real fluids. In this case, the modified equations of state give very similar predictions of thermodynamic properties as the original models, and one can remove the multiple liquid density roots observed for some versions of the Statistical Associating Fluid Theory (SAFT) at low temperature without any modification of the dispersion term.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Reversal of particle flux in collisional-finite beta tokamak discharges

The mixed gradient method [Zhong et al. Phys. Rev. Lett. 111, 265001 (2013)] is adopted and effects of collisions and finite beta are included in the Weiland 9-equation fluid model. The particle flux and particle pinch, obtained using the Weiland anomalous transport fluid model, are compared with Tore Supra experimental results. Particle transport is also studied using predictive simulation data for an experimental advanced superconducting tokamak discharge in which neutral beam heating is utilized. The effects of collisions on particle transport are studied by turning collisions on and off in the Weiland model. It is found that the particle pinch region is related to the mode structure. The particle pinch region coincides with the region where the strong ballooning modes are present due to large gradients. The general properties of the fluid model are examined by finding regions where collisions can enhance the particle pinch.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Ions confined in spherical dielectric cavities modeled by a splitting field-theory

The properties of ions confined within spherical dielectric cavities are examined by a splitting field-theory and Monte Carlo simulations. Three types of cavities are considered: one possessing a uniform surface charge density, one with a uniform volume charge density, and one containing mobile ions. In all cases, mobile counterions are present within the dielectric sphere. The splitting theory is based on dividing the electrostatic interaction into long- and short-wavelength contributions and applying different approximations on the two contributions. The splitting theory works well for the case where the dielectric constant of the confining sphere is equal to or less than that of the medium external to the sphere. Nevertheless, by extending the theory with a virial expansion, the predictions are improved. However, when the dielectric constant of the confining sphere is greater than that of the medium outside the sphere, the splitting theory performs poorly, only qualitatively agreeing with the simulation data. In this case, the strong-coupling expansion does not seem to work well, and a modified mean-field theory where the counterions interact directly with only their own image charge gives improved predictions. The splitting theory works best for the system with a uniform surface charge density and worst for the system with a uniform volume charge density. Increasing the number of ions within the sphere, at a fixed radius, tends to increase the ion density near the surface of the sphere and leads to a depletion region in the sphere interior; however, varying the ion number does not lead to any qualitative changes in the performance of the splitting theory.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

The Information Length Concept Applied to Plasma Turbulence

A methodology to study statistical properties of anomalous transport in fusion plasma is investigated. Three time traces generated by the full-f gyrokinetic code GKNET are analyzed for this purpose. The time traces consist of heat flux as a function of the radial position, which is studied in a novel manner using statistical methods. The simulation data exhibit transport processes with both medium and long correlation length along the radius. A typical example of a phenomenon with long correlation length is avalanches. In order to investigate the evolution of the turbulent state, two basic configurations are studied, one flux-driven and one gradient-driven with decaying turbulence. The information length concept in tandem with Boltzmann–Gibbs and Tsallis entropy is used in the investigation. It is found that the dynamical states in both flux-driven and gradient-driven cases are surprisingly similar, but the Tsallis entropy reveals differences between them. This indicates that the types of probability distribution function are nevertheless quite different since the higher moments are significantly different.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Estimation of LOCA break size using cascaded support vector regression - 334

A failure of emergency core cooling system (ECCS) during a certain small break loss of coolant accident (SBLOCA) can cause a severe core uncovery and fuel failure. The safety injection systems (SISs) might not function properly in case of a SBLOCA, due to the slight change of pressure in the pipes. Early trend of the major parameters has to be observed and the accurate information has to be given to the nuclear power plant (NPP) operators by precisely identifying the break size to effectively manage accidents. In this study, the objective is to provide to operators the information on the break size in a short time by considering the accident situations such as hot-leg LOCA, cold-leg LOCA, steam generator tube rupture (SGTR). A cascaded support vector regression (CSVR) is used in order to estimate the break size. The simulation data set was obtained from the optimized power plant reactor 1000 (OPR1000) using modular accident analysis program (MAAP) code. And genetic algorithm (GA) was used to select the input variables of the CSVR model and optimize its parameters. As a result of this study, the CSVR model estimate very well the break size of LOCAs. If the operators can predict the break size in the LOCA, they can response quickly and properly to LOCA circumstances to prevent the core uncovery and fuel failure. Also, it will be possible to more efficiently manage beyond design basis accidents. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Combined Machine Learning and Molecular Dynamics Reveal Two States of Hydration of a Single Functional Group of Cationic Polymeric Brushes

The state of hydration of a macromolecular system regulates a plethora of different properties of such a system. In this article, we develop a novel machine learning (ML) approach, based on the unsupervised clustering algorithm, for probing the hydration behavior of the {N(CH 3 ) 3 } + functional group of the PMETAC [Poly(2-(methacryloyloxy)ethyl trimethylammonium chloride] polyelectrolyte (PE) brush system. The PE brushes and the brush-supported water molecules and counterions (chloride ions) are first described using all-atom molecular dynamics (MD) simulations. The simulation data is subsequently used in our ML framework to identify that (1) the {N(CH 3 ) 3 } + functional groups of the PMETAC brushes have two distinct hydration states with one state (state 1) being characterized by less structured water molecules and the other state (state 2) being characterized by more structured water molecules and (2) an enhancement in the brush grafting density leads to the progressive dissapparenace of state 2. An increase in the grafting density increases the number of chloride counterions in a given volume around the {N(CH 3 ) 3 } + functional group and increases the number of shared water molecules between the {N(CH 3 ) 3 } + and Cl - . The chloride counterions are associated with a hydration layer with much less structured water molecules. Therefore, with an increase in the grafting density, an increase in the percentage of shared water molecules leads to the prevalence of the hydration state [of the {N(CH 3 ) 3 } + moiety] with less structured water molecules. Finally, we explain how the present findings are commensurate with two key previous related results, namely a significantly large chloride ion mobility inside the PMETAC brush layer and the {N(CH 3 ) 3 } + -Cl - average distance remaining independent of the PMETAC brush grafting density. Furthermore, we anticipate that the combined ML-MD-simulation approach proposed in this study can be adapted to probe other soft matter systems to reveal new insights of the underlying mechanisms of emergent phenomenon.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Numerical simulation of hot accretion flows. III. Revisiting wind properties using the trajectory approach

Previous MHD simulations have shown that wind must exist in black hole hot accretion flows. In this paper, we continue our study by investigating the detailed properties of wind and the mechanism of wind production. For this aim, we make use of a 3D general relativistic MHD simulation of hot accretion flows around a Schwarzschild black hole. To distinguish real wind from turbulent outflows, we track the trajectories of the virtual Lagrangian particles from simulation data. We find two types of real outflows, i.e., a jet and a wind. The mass flux of wind is very significant, and its radial profile can be described by M-dot {sub wind}≈ M-dot {sub BH}(r/20 r{sub s}), with M-dot {sub BH} being the mass accretion rate at the black hole horizon and r{sub s} being the Schwarzschild radius. The poloidal wind speed almost remains constant once they are produced, but the flux-weighted wind speed roughly follows v{sub p,wind}(r)≈0.25v{sub k}(r), with v{sub k}(r) being the Keplerian speed at radius r. The mass flux of the jet is much lower, but the speed is much higher, v{sub p,jet} ∼ (0.3–0.4)c. Consequently, both the energy and momentum fluxes of the wind are much larger than those of the jet. The wind is produced and accelerated primarily by the combination of centrifugal force and magnetic pressure gradient, while the jet is mainly accelerated by the magnetic pressure gradient. Finally, we find that the wind production efficiency ϵ{sub wind}≡ E-dot {sub wind}/ M-dot {sub BH}c{sup 2}∼1/1000 is in good agreement with the value required from large-scale galaxy simulations with active galactic nucleus feedback.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Three-Dimensional Aerodynamics and Vortex-Shedding Characteristics of Wind Turbine Airfoils over 360-Degree Angles of Attack

In this work, we present the first three-dimensional (3D) computational investigation of wind turbine airfoils over 360° angles of attack to predict unsteady aerodynamic loads and vortex-shedding characteristics. To this end, static–airfoil simulations are performed for the FFA-W3 airfoil family at a Reynolds number of 107 with the Improved Delayed Detached Eddy Simulation turbulence model. Aerodynamic forces reveal that the onset of boundary-layer instabilities and flow separation does not necessarily coincide with the onset of stall. In addition, a comparison with two-dimensional simulation data and flat plate theory extension of airfoil polars, suggest that, in the deep stall regime, 3D effects remain critical for predicting both the unsteady loads and the vortex-shedding dynamics. For all airfoils, the vortex-shedding frequencies are found to be inversely proportional to the wake width. In the case of slender airfoils, the frequencies are nearly independent of the airfoil thickness, and their corresponding Strouhal number St is approximately 0.15. Based on the calculated St, the potential for shedding frequencies to coincide with the natural frequencies of the International Energy Agency 15 MW reference wind turbine blades is investigated. The analysis shows that vortex-induced vibrations occur primarily at angles of attack of around ±90° for all airfoils.

17 WIND ENERGY↗
DOE OSTI2016

Myricetin is a novel inhibitor of human inosine 5′-monophosphate dehydrogenase with anti-leukemia activity

Human inosine 5′-monophosphate dehydrogenase (hIMPDH) is a rate-limiting enzyme in the de novo biosynthetic pathway of purine nucleotides, playing crucial roles in cellular proliferation, differentiation, and transformation. Dysregulation of hIMPDH expression and activity have been found in a variety of human cancers including leukemia. In this study, we found that myricetin, a naturally occurring phytochemical existed in berries, wine and tea, was a novel inhibitor of human type 1 and type 2 IMPDH (hIMPDH1/2) with IC{sub 50} values of 6.98 ± 0.22 μM and 4.10 ± 0.14 μM, respectively. Enzyme kinetic analysis using Lineweaver-Burk plot revealed that myricetin is a mix-type inhibitor for hIMPDH1/2. Differential scanning fluorimetry and molecular docking simulation data demonstrate that myricetin is capable of binding with hIMPDH1/2. Myricetin treatment exerts potent anti-proliferative and pro-apoptotic effects on K562 human leukemia cells in a dose-dependent manner. Importantly, cytotoxicity of myricetin on K562 cells were markedly attenuated by exogenous addition of guanosine, a salvage pathway of maintaining intracellular pool of guanine nucleotides. Taking together, these results indicate that natural product myricetin exhibits potent anti-leukemia activity by interfering with purine nucleotides biosynthetic pathway through the suppression of hIMPDH1/2 catalytic activity. - Highlights: • Myricetin, a common dietary flavonoid, is a novel inhibitor of hIMPDH1/2. • Myricetin directly binds with hIMPDH1/2 and induces cell cycle arrest and apoptosis of leukemia cells. • The cytotoxicity of myricetin on K562 cells is markedly attenuated by exogenous addition of guanosine.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Accretion of solid materials onto circumplanetary disks from protoplanetary disks

We investigate the accretion of solid materials onto circumplanetary disks from heliocentric orbits rotating in protoplanetary disks, which is a key process for the formation of regular satellite systems. In the late stage of the gas-capturing phase of giant planet formation, the accreting gas from protoplanetary disks forms circumplanetary disks. Since the accretion flow toward the circumplanetary disks affects the particle motion through gas drag force, we use hydrodynamic simulation data for the gas drag term to calculate the motion of solid materials. We consider a wide range of size for the solid particles (10{sup –2}-10{sup 6} m), and find that the accretion efficiency of the solid particles peaks around 10 m sized particles because energy dissipation of drag with circum-planetary disk gas in this size regime is most effective. The efficiency for particles larger than 10 m becomes lower because gas drag becomes less effective. For particles smaller than 10 m, the efficiency is lower because the particles are strongly coupled with the background gas flow, which prevents particles from accretion. We also find that the distance from the planet where the particles are captured by the circumplanetary disks is in a narrow range and well described as a function of the particle size.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Effect of soot concentration on radiative transport in a 2 m JP-8 pool fire

Hubbard et al. (2024) investigated conjugate heat transfer in a 7.9 m JP-8 pool fire, utilizing both heavily sooting and non-sooting fuel models. Their findings indicated that all models produced pool radiative heat fluxes within the measurement uncertainty for large-scale outdoor experiments. This study aims to further investigate the influence of soot concentration on radiative transport. To this end, Large Eddy Simulations (LES) of a 2 m diameter JP-8 pool fire were conducted, employing four turbulent combustion chemistry models: the Eddy Dissipation Concept (EDC) and three variants of flamelet model. Additionally, three variations of the one-equation subgrid scale turbulence kinetic energy model, and multiple mesh resolutions were utilized. The primary validation metrics were pool radiative heat flux and plume radiative fraction, with simulation data compared to experimental results published by Blanchat et al. (2010). The EDC model produced high soot concentrations near the pool surface, resulting in a significant shielding effect. In contrast, the flamelet combustion model has different kinetic limiters for soot production, leading to soot formation higher in the flame, where it can be more readily oxidized. Flamelet models incorporating both acetylene and benzene contributions to soot growth demonstrated better agreement with experimental data. To assess the sensitivity of pool radiative heat flux to soot mass concentration, we used a one-dimensional approximation over a wide range of soot concentrations and compared it to three-dimensional solutions obtained using Discrete Ordinates. Furthermore, this analysis illustrates the impacts of soot shielding and Turbulence Radiation Interactions (TRI), with TRI emission enhancement factors predicted to be in the range of 3–5 near the edges of the plume.

Computational fluid dynamics↗
DOE OSTI2016

Thermal motion in proteins: Large effects on the time-averaged interaction energies

As a consequence of thermal motion, inter-atomic distances in proteins fluctuate strongly around their average values, and hence, also interaction energies (i.e. the pair-potentials evaluated at the fluctuating distances) are not constant in time but exhibit pronounced fluctuations. These fluctuations cause that time-averaged interaction energies do generally not coincide with the energy values obtained by evaluating the pair-potentials at the average distances. More precisely, time-averaged interaction energies behave typically smoother in terms of the average distance than the corresponding pair-potentials. This averaging effect is referred to as the thermal smoothing effect. Here, we estimate the strength of the thermal smoothing effect on the Lennard-Jones pair-potential for globular proteins at ambient conditions using x-ray diffraction and simulation data of a representative set of proteins. For specific atom species, we find a significant smoothing effect where the time-averaged interaction energy of a single atom pair can differ by various tens of cal/mol from the Lennard-Jones potential at the average distance. Importantly, we observe a dependency of the effect on the local environment of the involved atoms. The effect is typically weaker for bulky backbone atoms in beta sheets than for side-chain atoms belonging to other secondary structure on the surface of the protein. The results of this work have important practical implications for protein software relying on free energy expressions. We show that the accuracy of free energy expressions can largely be increased by introducing environment specific Lennard-Jones parameters accounting for the fact that the typical thermal motion of protein atoms depends strongly on their local environment.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

An automated analysis workflow for optimization of force-field parameters using neutron scattering data

Graphical abstract: - Highlights: • An automated workflow to optimize force-field parameters. • Used the workflow to optimize force-field parameter for a system containing nanodiamond and tRNA. • The mechanism relies on molecular dynamics simulation and neutron scattering experimental data. • The workflow can be generalized to any other experimental and simulation techniques. - Abstract: Large-scale simulations and data analysis are often required to explain neutron scattering experiments to establish a connection between the fundamental physics at the nanoscale and data probed by neutrons. However, to perform simulations at experimental conditions it is critical to use correct force-field (FF) parameters which are unfortunately not available for most complex experimental systems. In this work, we have developed a workflow optimization technique to provide optimized FF parameters by comparing molecular dynamics (MD) to neutron scattering data. We describe the workflow in detail by using an example system consisting of tRNA and hydrophilic nanodiamonds in a deuterated water (D{sub 2}O) environment. Quasi-elastic neutron scattering (QENS) data show a faster motion of the tRNA in the presence of nanodiamond than without the ND. To compare the QENS and MD results quantitatively, a proper choice of FF parameters is necessary. We use an efficient workflow to optimize the FF parameters between the hydrophilic nanodiamond and water by comparing to the QENS data. Our results show that we can obtain accurate FF parameters by using this technique. The workflow can be generalized to other types of neutron data for FF optimization, such as vibrational spectroscopy and spin echo.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

LIGHT BRIDGE IN A DEVELOPING ACTIVE REGION. II. NUMERICAL SIMULATION OF FLUX EMERGENCE AND LIGHT BRIDGE FORMATION

Light bridges, the bright structure dividing umbrae in sunspot regions, show various activity events. In Paper I, we reported on an analysis of multi-wavelength observations of a light bridge in a developing active region (AR) and concluded that the activity events are caused by magnetic reconnection driven by magnetconvective evolution. The aim of this second paper is to investigate the detailed magnetic and velocity structures and the formation mechanism of light bridges. For this purpose, we analyze numerical simulation data from a radiative magnetohydrodynamics model of an emerging AR. We find that a weakly magnetized plasma upflow in the near-surface layers of the convection zone is entrained between the emerging magnetic bundles that appear as pores at the solar surface. This convective upflow continuously transports horizontal fields to the surface layer and creates a light bridge structure. Due to the magnetic shear between the horizontal fields of the bridge and the vertical fields of the ambient pores, an elongated cusp-shaped current layer is formed above the bridge, which may be favorable for magnetic reconnection. The striking correspondence between the observational results of Paper I and the numerical results of this paper provides a consistent physical picture of light bridges. The dynamic activity phenomena occur as a natural result of the bridge formation and its convective nature, which has much in common with those of umbral dots and penumbral filaments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Progress Update on Segmentation of Neutron Tomographic Images, 2018

The present report documents the techniques developed to segment fast-neutron tomographic images of objects consisting of assemblies of machined parts with distinct boundaries. This report satisfies the fiscal year 2018 technical deliverable for project OR16-3DTomography-PD3Jb, “3D Tomography and Image Processing Using Fast Neutrons,” to report on the extension of geometric shape-finding algorithms to three dimensions. The project has two overall goals. The first of these goals is to extend associated-particle fast-neutron transmission and, particularly, induced-reaction tomographic imaging algorithms to three dimensions. This aspect of the project is beyond the scope of this report. The second goal is to automatically segment the resultant tomographic images into constituent parts and then extract information about the parts, such as the class of shape and potentially the shape parameters. This report describes progress for the image segmentation part of the project. Imaging techniques have been developed as high-confidence methods for confirming the presence and configuration of special nuclear materials (SNM). This high confidence is achieved at the cost of revealing considerable information that may be undesirable to share with the operator of the equipment. One potential way to make use of the high-confidence of imaging methods without revealing imaging data is to employ automated analysis that can extract meaningful attributes of the SNM without showing imaging data to the operator. An essential step of this automated analysis is the segmentation of the image into its constituent parts. For example, a three-dimensional (3D) fast-neutron tomographic image of an assembly containing uranium could be reconstructed and then segmented into discrete parts. The properties of a constituent part identified as uranium would be of interest and could be extracted. For instance, the volume and density of the part would together determine its mass. Moreover, its shape might be expected to fall into a particular geometric class, such as a cube, cylinder, or sphere, and the parameters of the shape (such as side length, height, or diameter) would be expected to fall in a given range. In such an analysis, automated identification of the boundaries and properties of the uranium part is an essential step. A key goal of the present work is to infer the boundaries of objects in fast-neutron tomographic images via the general method of image segmentation. Development of this capability can be broken into more manageable steps, including 1. operator-guided segmentation of two-dimensional (2D) fast-neutron tomographic images, 2. operator-guided segmentation of 3D fast-neutron tomographic images, 3. development of automated segmentation algorithms, and 4. extraction of shape parameters from constituent volumes in 3D. In the first year, the project team reported progress on the first step. Last year, progress on the second step, the extension into 3D, was reported with application to simulated data. The present report describes additional progress on the second step, and progress toward the third step, automated segmentation algorithms. In particular, a multiphase level set approach for image segmentation in three dimensions has been applied to measured 3D data for the first time. Activities related to the fourth step will also be reported, but it will focus on estimation of 3D volumes rather than shape parameters. In this report, the steps before image segmentation will be described, and the multiphase level sets approach to image segmentation will be briefly reviewed. This will be followed by a discussion of the issues encountered when applying the level set technique to measured 3D transmission images, and then a description of the inclusion of induced-reaction data will be provided. Finally, segmentation results for various measured target assemblies will be presented and the image segmentation portion of this project will be summarized and future directions will be discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗