Search NASA⌕ Search

SEARCH · Search NASA

Results for “strong scaling”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Making the most of your electrons: Challenges and opportunities in characterizing hybrid interfaces with STEM

Inspired by the unique architectures composed of hard and soft materials in natural and biological systems, synthetic hybrid structures and associated hard-soft interfaces have recently evoked significant interest. Soft matter is typically dominated by structural fluctuations even at room temperature, while hard matter is governed by rigid mechanical behavior. This dichotomy offers considerable opportunities to leverage the disparate properties offered by these components across a wide spectrum spanning from basic science to engineering insights with significant technological overtones. Such hybrid structures, which include polymer nanocomposites, DNA functionalized nanoparticle superlattices, and metal organic frameworks to name a few, have delivered promising insights into the technologically relevant applications such as catalysis, environmental remediation, optoelectronics, and medicine. The interfacial structure between the hard and soft phases demonstrates features across a variety of length scales and often strongly influence the functionality of hybrid systems. While scanning/transmission electron microscopy (S/TEM) has proven to be a valuable tool for acquiring intricate molecular and nanoscale details of these interfaces, the unusual nature of hybrid composites presents a suite of challenges that make assessing or establishing structure–property relationships especially difficult. There are additional considerations at all stages of sample analysis from preparing electron-transparent samples to obtaining sufficient contrast to resolve the interface between dissimilar materials given the dose sensitivity of soft materials. Here, we discuss each of these challenges and supplement a review of recent developments in the field with additional experimental investigations and simulations to present solutions for attaining a nano or molecular-level understanding of these interfaces. These solutions present a host of opportunities for investigating the role interfaces play in this unique class of functional materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Transport of Compressed Woody Biomass: Correlating Rheology and Microcompounder Measurements

Transport of milled solid biomass can be problematic in biomass conversion processes due to the material’s high cohesiveness, low bulk density, and poor flowability. Here, the goal is to investigate the flow behavior of compressed biomass under conditions similar to compression-screw feeders. To mimic the flow of woody biomass inside a compression-screw feeder, two lignocellulosic biomass feedstocks were fed to a co-rotating twin-screw microcompounder. Force and screw speed from the microcompounder were correlated to viscosity in a traditional rheometer, where low-density polyethylene served as a control. The deformation of compressed biomass in a lab-scale compounder is strongly dependent on screw speed and moisture content. Shear stress in woody biomass decreased with the shear rate, indicating negative plastic viscosity. Moreover, viscosity decreased one order of magnitude as screw speed increased from 10 to 90 rpm. Increasing moisture from 10 to 50% reduced the viscosity of the compressed biomass by 60%.

09 BIOMASS FUELS↗
DOE OSTI2022

Oxygen and Proton Transport in Flooded Graphene Pores with N-Dopants and Defects

Reactant transport is an important consideration in the design of ideal electrode structures. For the oxygen reduction reaction catalyzed by Pt/C in proton exchange membrane fuel cell cathodes, O 2 and H + delivery to Pt surfaces and H 2 O transport away are required. Some Pt nanoparticles may only be accessible via micropores that are too small for ionomer molecules to enter, possibly requiring flooding for H + transport. Here, to test if these “buried” Pt particles can play a role in activity through this proposed transport mechanism, we have performed atomic-scale simulations based on reactive force field molecular dynamics with an emphasis on confinement below 20 Å. Diffusion coefficients as a function of the molar concentration and local environment have been evaluated in water domains confined in two-dimensional graphene nanochannels of various channel heights representing a morphological model for micropores in proton exchange fuel cell cathodes. Our study shows that local atomic-scale structures can strongly modify H + , O 2 , and H 2 O transport rates in flooded micropores less than 20 Å in size. We find that there is a critical crossover in diffusion behavior around the 20 Å spacing with larger pores having bulk-like diffusion properties and confinement below 20 Å monotonically decreases diffusion rates. As pore size decreases, we observe locally dispersed water regions that ultimately strand reactants from long-distance transport. These findings suggest that flooded micropores may in fact be viable transport pathways for relevant reactants and products if the pore walls on opposite sides remain separated by ≥10 Å separation. Furthermore, the confinement effect is so strong that N-doping and C-vacancy defects in the C pore wall have only a minimal impact on diffusion rates and their effects are counterintuitively more apparent at larger spacings. These findings provide valuable insight regarding cathode performance and the role “stranded” catalyst particles may play in fuel cell cathodes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A Pacific Tropical Decadal Variability Challenge for Climate Models

Understanding and forecasting Tropical Pacific Decadal-scale Variability (TPDV) strongly rely on climate model simulations. Using a Linear Inverse Modeling (LIM) diagnostic approach, we reveal Coupled Model Intercomparison Project Phase 6 models have significant challenges in reproducing the spatial structure and dominant mechanisms of TPDV. Specifically, while the models' ensemble mean pattern of TPDV resembles that of observations, the spread across models is very large and most models show significant differences from observations. In observations, removing the coupling between extratropics and tropics reduces TPDV by ~60%–70%, and removing the tropical thermocline variability makes the central tropical Pacific a key center of action for TPDV and El Niño Southern Oscillation variability. These characteristics are only confirmed in a subset of models. Differences between observations and simulations are outside the range of natural internal TPDV noise and pose important questions regarding our ability to model the impacts of natural internal low-frequency variability superimposed on long-term climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Ultraconfined terahertz phonon polaritons in hafnium dichalcogenides

The confinement of electromagnetic radiation to subwavelength scales relies on strong light–matter interactions. In the infrared and terahertz spectral ranges, phonon polaritons are commonly employed to achieve deeply subdiffractional light confinement, with such optical modes offering much lower losses in comparison to plasmon polaritons. Among these, hyperbolic phonon polaritons in anisotropic materials offer a promising platform for light confinement. Here we report on ultraconfined phonon polaritons in hafnium-based dichalcogenides with confinement factors exceeding λ 0 /250 in the terahertz spectral range. This extreme light compression within deeply subwavelength thin films is enabled by the large magnitude of the light–matter coupling strength in these compounds and the natural hyperbolicity of HfSe 2 . Our findings emphasize the role of light–matter coupling for polariton confinement, which for phonon polaritons in polar dielectrics is dictated by the transverse–longitudinal optical phonon energy splitting. Our results demonstrate transition-metal dichalcogenides as an enabling platform for terahertz nanophotonic applications.

Kowalski, Ryan A. [Vanderbilt Univ., Nashville, TN↗
DOE OSTI2024

Kinetic-ballooning-bifurcation in tokamak pedestals across shaping and aspect-ratio

We use a new gyrokinetic threshold model to predict a bifurcation in tokamak pedestal width-height scalings that depends strongly on plasma shaping and aspect-ratio. The bifurcation arises from the first and second stability properties of kinetic-ballooning-modes that yields wide and narrow pedestal branches, expanding the space of accessible pedestal widths and heights. The wide branch offers potential for edge-localized-mode-free pedestals with high core pressure. For negative triangularity, low-aspect-ratio configurations are predicted to give steeper pedestals than conventional-aspect-ratio. Both wide and narrow branches have been attained in tokamak experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Tropical Cyclone Super Resolution using conditional diffusion denoising probabilistic model from mesoscale simulation to LES

Accurate modeling of tropical cyclone wind fields is essential for the design, risk assessment, and operational planning of offshore energy infrastructure. While mesoscale simulations are widely used thanks to their computational efficiency, they lack the necessary resolution to capture key features such as wind shear and veer profiles as well as the distribution turbulent kinetic energy (TKE). High-fidelity large-eddy simulation (LES) models on the other hand, can resolve turbulent structures and provide a more accurate representation of the complex wind field, albeit at a higher computational cost. To address this modeling gap, we introduce a two-part generative framework to enhance the resolution and physics-capturing ability of mesoscale simulations. First, a reduced-order model based on Karhunen–Loève (KL) decomposition is used to extract dominant spatial modes from one-dimensional mean wind profiles. A multilayer perceptron (MLP) is trained to map mesoscale mode weights to their LES counterparts, enabling accurate reconstruction of vertical velocity profiles. Second, a conditional Diffusion Denoising Probabilistic Model (DDPM) is developed to super-resolve coarse and low-fidelity mesoscale velocity fields, recovering fine-scale turbulence structures and stress distributions. The framework is evaluated across different tropical cyclone intensity categories defined by the Saffir–Simpson scale and demonstrates strong performance in both interpolation and extrapolation tasks. The generated fields accurately reproduce spatial coherence, stress distributions, and spectral energy characteristics observed in LES data. By bridging the fidelity gap between mesoscale and LES outputs, this approach offers a scalable, data-driven solution for enhancing the representation of tropical cyclone wind fields, enabling more robust offshore energy infrastructure systems design in tropical-cyclone-prone areas.

17 WIND ENERGY↗
DOE OSTI2021

Far-UV Fe emission as proxy of Eddington ratios

ABSTRACT The Eddington ratio is a key parameter that governs the diversity of quasar properties. It can be scaled with a strong anticorrelation between optical Fe iiopt and [O iii] emission. In search of such indicators in the far-UV band, the Hubble Space Telescope far-UV spectra of 150 low-redshift quasars are analysed in combination with their optical SDSS counterparts. The strength of Fe ii+Fe iii λ1123 emission is significantly correlated with that of Fe iiopt. A moderate correlation may also exist between Fe ii λ1071 and Fe iiopt. The finding opens the possibility that far-UV Fe ii emission may serve as a new gauge of the Eddington ratios. The high- and low-ionization lines in the far-UV band display different patterns: for the quasars with higher Eddington ratios, the low-ionization UV lines are stronger, and the high-ionization lines are broader and weaker.

Zheng, Wei↗
DOE OSTI2022

Arp 58 and Arp 68: two M 51-type systems

ABSTRACT We study two M 51-type systems Arp 68 and Arp 58, which strongly differ by their stellar masses, gas content, and environment. Long-slit spectral observations obtained at the Russian 6-m telescope were used to trace the distributions of a line-of-sight (LOS) velocity and a gas-phase oxygen abundance along the spectral cuts. Two systems are compared by their observed properties. We found a very strong large-scale non-circular motion of gas in both systems and a kpc-size saw-edged velocity profile along the tidal spiral arm of Arp 68, probably caused by the gas outflow due to the stellar feedback. A deep decrease of LOS velocity is also found in the ‘hinge’ region in Arp 58, where the inner spiral arm transforms into the tidal spiral arm, which was predicted earlier for M 51-type galaxies. Local sites of star formation and the satellites are compared with the evolutionary models at the colour–colour diagrams. Unlike the spiral galaxy Arp 58, the main galaxy in Arp 68 system is experiencing an ongoing burst of star formation. Gas-phase metallicity estimates show that Arp 58 has a higher metal abundance and reveals a shallow negative radial gradient of the gas-phase oxygen abundance. The emission gas in Arp 68 has noticeably lower metallicity than it is expected for a given luminosity of this galaxy, which may be connected with its space position in the local void.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Dimensionality-driven metal to Mott insulator transition in two-dimensional 1T-TaSe2

Abstract Two-dimensional materials represent a major frontier for research into exotic many-body quantum phenomena. In the extreme two-dimensional limit, electron-electron interaction often dominates over other electronic energy scales, leading to strongly correlated effects such as quantum spin liquid and unconventional superconductivity. The dominance is conventionally attributed to the lack of electron screening in the third dimension. Here, we discover an intriguing metal to Mott insulator transition in 1T-TaSe2 that defies conventional wisdom. Specifically, we find that dimensionality crossover, instead of reduced screening, drives the transition in atomically thin 1T-TaSe2. A dispersive band crossing the Fermi level is found to be responsible for the bulk metallicity in the material. Reducing the dimensionality, however, effectively quenches the kinetic energy of these initially itinerant electrons, and drives the material into a Mott insulating state. The dimensionality-driven metal to Mott insulator transition resolves the long-standing dichotomy between metallic bulk and insulating surface of 1T-TaSe2. Our work further reveals a new pathway for modulating two-dimensional materials that enables exploring strongly correlated systems across uncharted parameter space.

1T-TaSe2↗
DOE OSTI2020

Block orbital-selective Mott insulators: A spin excitation analysis

We present a comprehensive study of the spin excitations—as measured by the dynamical spin structure factor S(q,ω)—of the so-called block-magnetic state of low-dimensional orbital-selective Mott insulators. We realize this state via both a multi-orbital Hubbard model and a generalized Kondo-Heisenberg Hamiltonian. Due to various competing energy scales present in the models, the system develops periodic ferromagnetic islands of various shapes and sizes, which are antiferromagnetically coupled. The 2×2 particular case was already found experimentally in the ladder material BaFe2Se3 that becomes superconducting under pressure. Here we discuss the electronic density as well as Hubbard and Hund coupling dependence of S(q,ω) using density matrix renormalization group method. Several interesting features were identified: (1) An acoustic (dispersive spin-wave) mode develops. (2) The spin-wave bandwidth establishes a new energy scale that is strongly dependent on the size of the magnetic island and becomes abnormally small for large clusters. (3) Optical (dispersionless spin excitation) modes are present for all block states studied here. In addition, a variety of phenomenological spin Hamiltonians have been investigated but none matches entirely our results that were obtained primarily at intermediate Hubbard U strengths. Our comprehensive analysis provides theoretical guidance and motivation to crystal growers to search for appropriate candidate materials to realize the block states, and to neutron scattering experimentalists to confirm the exotic dynamical magnetic properties unveiled here, with a rich mixture of acoustic and optical features.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Thermalization of Interacting Quasi-One-Dimensional Systems

Many experimentally relevant systems are quasi-one-dimensional, consisting of nearly decoupled chains. In these systems, there is a natural separation of scales between the strong intrachain interactions and the weak interchain coupling. When the intrachain interactions are integrable, weak interchain couplings play a crucial part in thermalizing the system. Here, we develop a Boltzmann-equation formalism involving a collision integral that is asymptotically exact for any interacting integrable system, and apply it to develop a quantitative theory of relaxation in coupled Bose gases in the experimentally relevant Newton's cradle setup. Here we find that relaxation involves a broad spectrum of timescales. We provide evidence that the Markov process governing relaxation at late times is gapless; thus, the approach to equilibrium is generally nonexponential, even for spatially uniform perturbations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Computing Bottleneck Structures at Scale for High-Precision Network Performance Analysis

The Theory of Bottleneck Structures is a recently-developed framework for studying the performance of data networks. It describes how local perturbations in one part of the network propagate and interact with others. This framework is a powerful analytical tool that allows network operators to make accurate predictions about network behavior and thereby optimize performance. Previous work implemented a software package for bottleneck structure analysis, but applied it only to toy examples. In this work, we introduce the first software package capable of scaling bottleneck structure analysis to production-size networks. Here, we benchmark our system using logs from ESnet, the Department of Energy's high-performance data network that connects research institutions in the U.S. Using the previously published tool as a baseline, we demonstrate that our system achieves vastly improved performance, constructing the bottleneck structure graphs in 0.21 s and calculating link derivatives in 0.09 s on average. We also study the asymptotic complexity of our core algorithms, demonstrating good scaling properties and strong agreement with theoretical bounds. These results indicate that our new software package can maintain its fast performance when applied to even larger networks. They also show that our software is efficient enough to analyze rapidly changing networks in real time. Overall, we demonstrate the feasibility of applying bottleneck structure analysis to solve practical problems in large, real-world data networks.

benchmark↗
DOE OSTI2019

What Drives Upper-Ocean Temperature Variability in Coupled Climate Models and Observations?

Abstract A key question in climate modeling is to what extent sea surface temperature and upper-ocean heat content are driven passively by air–sea heat fluxes, as opposed to forcing by ocean dynamics. This paper investigates the question using a climate model at different resolutions, and observations, for monthly variability. At the grid scale in a high-resolution climate model with resolved mesoscale ocean eddies, ocean dynamics (i.e., ocean heat flux convergence) dominates upper 50 m heat content variability over most of the globe. For deeper depths of integration to 400 m, the heat content variability at the grid scale is almost totally controlled by ocean heat flux convergence. However, a strong dependence on spatial scale is found—for the upper 50 m of ocean, after smoothing the data to around 7°, air–sea heat fluxes, augmented by Ekman heat transports, dominate. For deeper depths of integration to 400 m, the transition scale becomes larger and is above 10° in western boundary currents. Comparison of climate model results with observations show that the small-scale influence of ocean intrinsic variability is well captured by the high-resolution model but is missing from a comparable model with parameterized ocean-eddy effects. In the deep tropics, ocean dynamics dominates in all cases and all scales. In the subtropical gyres at large scales, air–sea heat fluxes play the biggest role. In the midlatitudes, at large scales >10°, atmosphere-driven air–sea heat fluxes and Ekman heat transport variability are the dominant processes except in the western boundary currents for the 400 m heat content.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

GentenMPI: Distributed Memory Sparse Tensor Decomposition

GentenMPl is a toolkit of sparse canonical polyadic (CP) tensor decomposition algorithms that is designed to run effectively on distributed-memory high-performance computers. Its use of distributed-memory parallelism enables it to efficiently decompose tensors that are too large for a single compute node's memory. GentenMPl leverages Sandia's decades-long investment in the Trilinos solver framework for much of its parallel-computation capability. Trilinos contains numerical algorithms and linear algebra classes that have been optimized for parallel simulation of complex physical phenomena. This work applies these tools to the data science problem of sparse tensor decomposition. In this report, we describe the use of Trilinos in GentenMPl, extensions needed for sparse tensor decomposition, and implementations of the CP-ALS (CP via alternating least squares) and GCP-SGD (generalized CP via stochastic gradient descent) sparse tensor decomposition algorithms. We show that GentenMPl can decompose sparse tensors of extreme size, e.g., a 12.6-terabyte tensor on 8192 computer cores. We demonstrate that the Trilinos backbone provides good strong and weak scaling of the tensor decomposition algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

X-ray Computed Tomography on UNESE Core: FY2020 Data Report to Support Fracture and Multiphase Fluid Flow Studies

Natural and induced fractures are potential preferential pathways for migration of radioactive gases to earths surface from underground nuclear explosions (UNEs). This report documents X-ray computed tomography (XRCT) imaging on 26 samples of rock core that was collected to support the Underground Nuclear Explosion Signatures Experiment (UNESE) program. The XRCT datasets are intended to help fill a data gap on the three-dimensional (3D) characteristics of natural and/or induced fractures at the centimeter and smaller scale, which may strongly influence multiphase fluid flow and transport properties of preferential flow paths and interaction with the matrix of the surrounding host rock. Pre- and post-UNE rock samples were carefully chosen to enable comparison of fractures as a function of lithologic and petrophysical properties, as well as distance to the past UNEs. This report serves as documentation for the data, including an introduction with the research motivation, a methods and materials section, descriptions of the XRCT datasets without post-processing, and recommendations for 3D quantification via image analysis and digital rock physics.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Technology Evaluation of the Yotta SolarLEAF: A Panel-Based Thermally Managed Battery Module

In 2019, the United States installed 13.3 gigawatts of solar energy production capacity. This demand for solar will continually increase as the phasing out of fossil fuels continue. As the demand for solar energy grows, so does the demand to store this generated energy. It is projected that by 2035 the global demand for stationary energy storage will reach the terawatt scale. So, scalable solutions with suitable thermal management systems are required to meet future demand. Yotta Solar has developed an ESS system, the Yotta LEAF, that provides solar energy storage without increasing the footprint of solar arrays. This is particularly useful in applications with limited space (e.g., building roof) and where large scale batteries require strong requirements for fire suppression systems. As part of the Wells Fargo Innovation Incubator (IN2), the National Renewable Energy Laboratory (NREL) has conducted a third-party technology validation of Yotta's alpha prototype. The report includes the objectives, technology description, methodology, and results from experiments conducted at the Thermal Transfer Facility (TTF) at NREL.

14 SOLAR ENERGY↗
DOE OSTI2026

Multi-physics Preconditioning for Thermally Activated Batteries

Thermal batteries, also known as molten-salt batteries, are single-use reserve power systems activated by pyrotechnic heat generation, which transitions the solid electrolyte into a molten state. The simulation of these batteries relies on multiphysics modeling to evaluate performance and behavior under various conditions. This paper presents advancements in scalable preconditioning strategies for the Thermally Activated Battery Simulator (TABS) tool, enabling efficient solutions to the coupled electrochemical systems that dominate computational costs in thermal battery simulations. We propose a hierarchical block Gauss-Seidel preconditioner implemented through the Teko package in Trilinos, which effectively addresses the challenges posed by tightly coupled physics, including charge transport, porous flow, and species diffusion. The preconditioner leverages scalable subblock solvers, including smoothed aggregation algebraic multigrid (SA-AMG) methods and domain-decomposition techniques, to achieve robust convergence and parallel scalability. Strong and weak scaling studies demonstrate the solver’s ability to handle problem sizes up to 51.3 million degrees of freedom on 2048 processors, achieving near sub-second setup and solve times for the end-to-end electrochemical solve. These advancements significantly improve the computational efficiency and turnaround time of thermal battery simulations, paving the way for higher-resolution models and enabling the transition from 2D axisymmetric to full 3D simulations.

25 ENERGY STORAGE↗