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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

ZPPR-15 Small Reactivity Worth Experiments

In addition to measuring the worth of sodium voiding and the worth of simulated control rods, the ZPPR staff measured the Doppler worth of four standard samples, the worth of axial expansion and the worth of radial bowing in ZPPR-15. Doppler sample worths were measured in ZPPR-15A, ZPPR-15B and ZPPR-15D. The Doppler samples were natural UO 2 , depleted uranium metal, depleted U-10Zr alloy and 33% enriched UO 2 . These samples were placed in a sample capsule in the inner core of ZPPR-15 and heated to various temperatures between 300 K and 1100 K. The resulting changes in reactivity relative to the reference configuration were measured to determine the Doppler worths of the samples. Special segmented drawers were constructed to measure the worth of axial expansion in ZPPR15. The segments were connected to each other, and the back segment was connected to a spring-loaded cable. Pulling the cable introduced small gaps between drawer segments to simulate axial expansion, and releasing the cable eliminated those gaps. The worth of this simulated axial expansion was measured in ZPPR-15A, ZPPR-15B and ZPPR-15D. The worth of radial bowing was measured in ZPPR-15, but the experimenters regarded the result as unsatisfactory. Radial bowing was measured by two methods in ZPPR-17A, so the ZPPR-17A bowing measurements were analyzed in place of the unpublished ZPPR-15 radial bowing measurement. The first ZPPR-17A measurement consisted of rearranging the plates in 96 core drawers at the core-radial blanket boundary to simulate outward motion of the fuel during bowing. The second ZPPR-17A measurement used a new bowing oscillator to move the core plates a small distance vertically in a special drawer. The published uncertainties for the Doppler worth, axial expansion worth and radial bowing worth measurements are the statistical uncertainties in the measurements. In reality, the published uncertainty for each of these measurements is just one component of the total uncertainty. There are additional uncertainties specific to each measurement and a common uncertainty related to conversion from the natural measurement units, cents, to pcm for calculations. A full uncertainty analysis was performed for each measurement. The significant uncertainties were quantified, and a total uncertainty was determined for each measurement. The ZPPR-15 and ZPPR-17A experimental records were used to create detailed as-built Monte Carlo models of the Doppler worth, axial expansion and radial bowing measurement configurations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

OGLE-2017-BLG-0406: Spitzer Microlens Parallax Reveals Saturn-mass Planet Orbiting M-dwarf Host in the Inner Galactic Disk

We report the discovery and analysis of the planetary microlensing event OGLE-2017-BLG-0406, which was observed both from the ground and by the Spitzer satellite in a solar orbit. At high magnification, the anomaly in the light curve was densely observed by ground-based-survey and follow-up groups, and it was found to be explained by a planetary lens with a planet/host mass ratio of q=7.0×10{sup −4} from the light-curve modeling. The ground-only and Spitzer-“only” data each provide very strong one-dimensional (1D) constraints on the 2D microlens parallax vector π{sub E}. When combined, these yield a precise measurement of π{sub E} and of the masses of the host M{sub host}=0.56±0.07 M{sub ⊙} and planet M {sub planet} = 0.41 ± 0.05 M {sub Jup}. The system lies at a distance D {sub L} = 5.2 ± 0.5 kpc from the Sun toward the Galactic bulge, and the host is more likely to be a disk population star according to the kinematics of the lens. The projected separation of the planet from the host is a{sub ⊥}=3.5±0.3 au (i.e., just over twice the snow line). The Galactic-disk kinematics are established in part from a precise measurement of the source proper motion based on OGLE-IV data. By contrast, the Gaia proper-motion measurement of the source suffers from a catastrophic 10σ error.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Applications of Multibody for Everybody (M4E) in Marine Energy

Multibody for Everybody (M4E) is an open-source symbolic dynamics modeling framework designed to automate the derivation of equations of motion and simulation of constrained multibody systems using the joint coordinate formulation.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Modeling the Effect of the Interplanetary Magnetic Field on Cosmic Ray Muon Shadows

Cosmic ray (CR) muon shadows were located using muon data from the MINOS Far Detector in Northern Minnesota. The shadows were located independently across 3 time periods; near solar minimum, solar maximum, and over the entire 13 year span of the data. A muon distribution for each shadow was then sampled to simulate CR motions near the Sun using the Parker Spiral model of the Sun’s IMF and a dipole model of the Earth’s GMF. The resulting particle distributions were then compared to their position with respect to the Sun. An analytical relationship between the primary CR cutoff energy E0 and the associated shadow deflections was observed. The minimum cutoff energy of the primary CR energy spectrum consistent with the Parker Spiral model was determined to be $E_0 = 22.8 \pm 1.2$~TeV. This value is 2-3 times higher than the experimentally determined value. Complexities that can be added to the Parker Spiral Model and affect the overall shift of the the Sun’s cosmic ray shadow are discuss ed to explain discrepancies. Results show that the Parker Spiral model is most consistent with the the solar minimum shadow and least consistent with the solar maximum shadow, as expected.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Modeling the Effect of the Heliospheric Magnetic Field on Cosmic Ray Muon Shadows

Shadows cast in the cosmic ray (CR) muon sky by the Sun were located using muon data from the MINOS far detector in Northern Minnesota. The shadows were observed independently across three time periods; near solar minimum, near solar maximum, and over the entire 13 year span of the data. A distribution of muon positions for each shadow was then sampled to simulate CR motions near the Sun using the Parker spiral model of the Heliospheric Magnetic Field (HMF) and a dipole model of the Geomagnetic Field (GMF). The resulting particle distributions were then compared to their position with respect to the Sun. Results show that the Parker spiral model is most consistent with the solar minimum shadow and least consistent with the solar maximum shadow, as expected. The simple Parker spiral is more consistent with the data for a harder CR spectrum than is actually present, indicating the need for a more detailed HMF model. Plausible modifications to the Parker spiral model which would affect the overall shift of the Sun's CR shadow are discussed.

Adamson, P. [Fermilab]↗
DOE OSTI2023

Comparing theoretical predictions of radiation-free velocities of edge dislocations to molecular dynamics simulations

Transonic defect motion is of interest for high strain-rate plastic deformation as well as for crack propagation. Ever since Eshelby's 1949 prediction [J. D. Eshelby, Proc. Phys. Soc. A 62, 307 (1949)] in the isotropic limit of a “radiation-free” transonic velocity $v$ RF = $\sqrt{2}$c T , where shock waves are absent, there has been speculation about the significance of radiation-free velocities (if they truly exist) for defect mobility. Here, in this work, we argue that they do not play any significant role in dislocation dynamics in metals, based on comparing theoretical predictions of radiation-free velocities for transonic edge dislocations with molecular dynamics simulations for two face-centered cubic metals: Ag, where theory predicts radiation-free states, and Cu, where it does not.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Capabilities of multivariate Bayesian inference toward seismic hazard assessment

Multivariate Bayesian analysis can bring significant benefits to seismic hazard analysis: Its multivariate feature enables computing scalar and vector hazard without making any approximations; Correlations between intensity measures are implicitly modeled, permitting direct simulation of ground motion selection tools such as the conditional mean spectrum and the generalized conditioning intensity measure; and Its updating feature enables a seamless integration of new ground motion data into the hazard results. Here, we first develop a multivariate Bayesian ground motion model through the NGA-West2 database. The model functional form considers fault-type, magnitude, and distance dependencies, and also the linear and the rock intensity dependent site response. We use a hybrid Markov Chain Monte Carlo sampling to perform Bayesian inference consisting of Gibbs step and a multilevel Metropolis-Hastings step. We then perform several checks on the model and note that its performance is satisfactory. Finally, we illustrate the merits of this multivariate Bayesian analysis, which include: ground motion model updating with ground motion data recorded in the last four years not part of the NGA-West2 database; computation of scalar and vector seismic hazard using the un-updated and updated ground motion models for Los Angeles, CA; and simulation of the conditional mean spectrum under scalar and vector IM conditioning while accounting for different sources of aleatoric and epistemic uncertainties.

58 GEOSCIENCES↗
DOE OSTI2022

OC6 Phase Ia: CFD Simulations of the Free-Decay Motion of the DeepCwind Semisubmersible

Currently, the design of floating offshore wind systems is primarily based on mid-fidelity models with empirical drag forces. The tuning of the model coefficients requires data from either experiments or high-fidelity simulations. As part of the OC6 (Offshore Code Comparison Collaboration, Continued, with Correlation, and unCertainty (OC6) is a project under the International Energy Agency Wind Task 30 framework) project, the present investigation explores the latter option. A verification and validation study of computational fluid dynamics (CFD) models of the DeepCwind semisubmersible undergoing free-decay motion is performed. Several institutions provided CFD results for validation against the OC6 experimental campaign. The objective is to evaluate whether the CFD setups of the participants can provide valid estimates of the hydrodynamic damping coefficients needed by mid-fidelity models. The linear and quadratic damping coefficients and the equivalent damping ratio are chosen as metrics for validation. Large numerical uncertainties are estimated for the linear and quadratic damping coefficients; however, the equivalent damping ratios are more consistently predicted with lower uncertainty. Some difference is observed between the experimental and CFD surge-decay motion, which is caused by mechanical damping not considered in the simulations that likely originated from the mooring setup, including a Coulomb-friction-type force. Overall, the simulations and the experiment show reasonable agreement, thus demonstrating the feasibility of using CFD simulations to tune mid-fidelity models.

17 WIND ENERGY↗
DOE OSTI2026

Arctic Deployment of a Fully Integrated Self-Powered Drifting Buoy Harvesting Wave Energy via a Triboelectric Nanogenerator

The Arctic Ocean remains one of the most poorly sampled regions on Earth, where improved in situ environmental monitoring is vital for advancing oceanographic and atmospheric studies. However, data collection efforts are constrained by the short operational lifespans and high costs of conventional systems. Drifting buoys powered by pendulum-driven wave energy harvesters offer a cost-effective alternative, yet earlier designs have neither been optimized for real-world wave conditions nor validated in the Arctic. In this study, we develop a self-powered drifting buoy that integrates a pendulum-driven triboelectric nanogenerator (TENG) system with a mechanical motion rectifier, a high-gear-ratio transmission, and power management circuits. Through coupled buoy–pendulum dynamic simulations and laboratory testing using a motion simulator, we identify an optimal pendulum mass of 1.6 kg (12.7% of total buoy weight) that maximizes energy output while maintaining buoy stability. Laboratory experiments achieved average power outputs of 12.7 mW under Arctic-like wave and temperature conditions. The system was successfully deployed in the Bering Sea, where it generated 11 J of energy in 3.1 m waves, marking the first Arctic deployment of a TENG-based drifting buoy for sea surface temperature monitoring. This work establishes a cost-effective framework for designing self-powered Arctic monitoring platforms and advances the feasibility of long-term environmental observations in real Arctic waters.

marine enerby↗
DOE OSTI2026

fp-tools

The output of a molecular dynamics simulation is a data file containing properties of the motion of the simulated particles as a function of time (e.g., positions, velocities). From this output, scientists can extract various properties which give insight into the physics of the system; for example, the radial distribution function can be computed from the particle positions, which gives insight into how close the system is to melting or freezing. Many publicly available codes to perform molecular dynamics simulations exist and have been well adopted by the scientific community (e.g., LAMMPS, VASP). However, it remains standard practice for scientists to write their own post-processing scripts to extract various properties of interest from the molecular dynamics simulation data. Since in many cases scientists are interested in the same set of “textbook” properties, there is a large duplication of effort in writing these post-processing scripts. Our proposed code, FP-Tools, is a C++ toolkit designed to help scientists extract and analyze quantities of interest from the output of a molecular dynamics simulation, eliminating the need for them to write these codes themselves and thus reducing this duplication of effort. The quantities which are computed by our code are well documented in the literature (either in publications or textbooks), and the algorithms we implement to compute these properties are also well known in the field. We are not introducing new science or methods here; rather, our primary goal is to provide a useful tool to the community in the form of a well-documented, easy to use package.

Hartman, Leah↗
DOE OSTI2025

Beyond curvature-driven grain growth: Insights from fully anisotropic Monte Carlo Potts simulations

Grain boundary (GB) motion away from the center of curvature, termed anti-curvature behavior, has recently been observed in 3D experiments but is not predicted by classical grain growth theory. In this study, we investigate this behavior using a novel, fully anisotropic Monte Carlo Potts (MCP) model that incorporates both misorientation and inclination dependencies of GB energy. We perform 3D grain growth simulations with isotropic and anisotropic GB energies to explore the relationship between GB velocity and curvature. Contrary to the classical relation that velocity is a product of reduced mobility and mean curvature, we observe no consistent correlation between velocity and mean curvature for individual GBs, even under isotropic conditions, though there is correlation between the average velocity and curvature for some cases. The 3D simulations exhibit frequent anti-curvature motion regardless of GB energy anisotropy including with isotropic GBs, though larger curvatures occur with anisotropic GB energy functions that promote low-energy GBs. In 2D simulations, anti-curvature behavior only occurs with the anisotropic functions that favor low-energy GBs. This difference between 2D and 3D results suggests that anti-curvature behavior results in part from the increased freedom of motion intrinsic in 3D GB networks. Furthermore, our results support recent experimental observations that demonstrate that simple curvature-driven models are insufficient for describing GB migration in polycrystals.

Anti-curvature↗
DOE OSTI2022

Finite-Difference Simulation for Infrasound Generated by Finite-Extent Ground Motions

Underground explosions can produce infrasound in the atmosphere, and the wavefield characteristics are often governed by the ground surface motions. Finite-difference methods are popular for infrasound simulation as their generality and robustness allow for complex atmospheric structures and surface topography. A simple point-source approximation is often used because infrasound wavelengths tend to be large relative to the source dimensions. However, this assumption may not be able to capture the complexity of explosion-induced ground motions if the surface area is not compact, and appropriate source models must be incorporated into the finite-difference simulations for accurate infrasound prediction. In this study, we develop a point source representation of the complex ground motions for infrasound sources. Instead of a single point source, we use a series of point sources distributed over the source area. These distributed point sources can be equivalent to air volume changes produced by the ground motions in the atmosphere. Further, we apply the distributed point-source method to a series of buried chemical explosions conducted during the Source Physics Experiment Phase I. Epicentral ground-motion measurements during the experiments provide a way to calculate accurate distributed point sources. We validate and evaluate the accuracy of distributed point source approach for infrasound simulations by direct comparison with acoustic observations in the field experiment.

58 GEOSCIENCES↗
DOE OSTI2020

Three-dimensional phase field sintering simulations accounting for the rigid-body motion of individual grains

Sintering is a widely used powder processing technique in industrial applications. During sintering, atoms migrate to decrease the energy of the system via two main mechanisms: coarsening and densification, both of which lead to significant morphological variation of the sintered microstructure. When simulating sintering dynamics, the phase-field method has been broadly utilized because of its convenience in tracking morphology evolution. When a large number of grains is involved, it is common to use the same order parameter to describe multiple grains that are not in direct contact with one another (in order to reduce the computational memory demands). However, with this treatment it is difficult to handle the rigid-body motion of individual grains during densification. In this work, an implementation scheme is introduced to overcome the challenge of calculating individual particle motion based on existing equations. It uses a grouping algorithm and sets a cutoff radius on each grain for calculating the particle velocity during densification. This method allows for the incorporation of the densification mechanism, which has been commonly ignored in previous work, into phase-field sintering models in three-dimensional simulations with a large number of particles/grains. Moreover, through combination with the smoothed boundary method, material properties of sintered microstructures, such as the effective diffusivity and Young’s modulus, can be calculated during the sintering processes.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Intrinsic size dependent plasticity in BCC micro-pillars under uniaxial tension and pure torsion

The mechanical behavior of submicron body-centered cubic (BCC) micro-pillars is investigated by three-dimensional dislocation dynamics (DD) simulations to better understand the governing mechanisms for size dependent plasticity under uniaxial tension and pure torsion. A formula is developed to compute the incremental plastic twist due to dislocation motion in DD simulations. The DD simulations show that different dislocation microstructures are created depending on the loading conditions, which leads to different size dependent mechanical behavior. While in tension plasticity is mainly governed by the kinetics of dislocation motion controlled partly by the surface dislocation sources, plastic flow in torsion is controlled by dislocation pile-ups associated with strain gradients. The simulation results also reveal a Bauschinger effect and plastic recovery under cyclic twist, which have been observed in recent experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A Nonergodic Ground-Motion Model for the San Francisco Bay Area for Small-Magnitude Earthquakes

ABSTRACT Recently, generative models have become a computationally efficient alternative to physics-based numerical simulations of ground motions. Neural networks can learn from existing ground-motion data to generate unobserved ground-motion data at new source and site locations. A key challenge with generative models is ensuring that predicted ground motions remain within a physically realistic range. For this purpose, we developed an empirical, nonergodic ground-motion model (GMM) for small-magnitude earthquakes in the San Francisco Bay area based on about 5000 recordings per component for Mw ≤ 4 earthquakes. The nonergodic GMM predicts spatially varying median source, site, and path effects for both the Fourier amplitude spectrum (FAS) and the Fourier phase derivative (a proxy for duration), as well as the corresponding epistemic uncertainty for each term. For FAS, our model shows above-average source and site effects in the western part of the region and below-average effects in the eastern part, with regional effects exhibiting larger spatial correlation lengths with increasing frequency. For duration, the source term is negligible for small-magnitude earthquakes, and the site term leads to site-specific variations up to 5 s. Path effects for FAS and duration depend on the source–site pair and are extrapolated spatially using recent methods for path-effect modeling. The aleatory variability of the within-site within-path residuals is similar to the variability found in previous studies for other regions. The nonergodic model provides two key contributions: first, median adjustment terms that are transferable to larger magnitude earthquakes, further reducing aleatory variability in probabilistic seismic hazard analysis; second, region-specific criteria for validating machine learning-based ground-motion generators to evaluate whether synthetic ground motions exhibit physically realistic source, site, and path effects.

Lacour, Maxime↗
DOE OSTI2022

Spatial arrangement of dynamic surface species from solid-state NMR and machine learning-accelerated MD simulations

Here, the surface arrangement of motional organic functionalities is explored by experimental dipolar coupling measurements and the prediction of motionally-averaged coupling constant from molecular dynamics simulations. The use of machine learning potentials was key to reaching the timescale required. The distance between dynamic surface species are important in cooperative heterogeneous catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗