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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Unified Entrainment and Detrainment Closures for Extended Eddy-Diffusivity Mass-Flux Schemes

The extended Eddy Diffusivity Mass Flux (EDMF) scheme is used as a unied parameterization that simulates subgrid-scale dynamics across a range of regimes.This work presents unied entrainment and detrainment closures that allow this scheme to simulate the dry convective boundary layer, shallow convection and deep convection , while adjacent works present other necessary closures for this unied scheme and test its performance for stable, stratocumulus topped and convective boundary layers. Entrainment and detrainment are modeled as a combination of turbulent and dynamical processes. The turbulent component is taken as downgradient diffusion between subdomains. The dynamical component is based on a ratio of buoyancy and vertical velocity that ensures consistent treatment of the ratio of mass-flux at vanishing area fraction. Dynamical detrainment is controlled by the difference in relative humidity between subdomains when liquid water is present. These closures are rst evaluated with entrainment and detrainment diagnosed from Large Eddy Simulations where decaying tracers are used to identify the different subdomains and mass exchanges between them. When implemented in a single column model (SCM), these closures are tested in simulations of several observationally motivated cases of dry convective boundary layer, shallow convection and deep convection. Results show good agreement between the SCM and Large Eddy Simulations in key properties for climate models and profiles of first, second and third moments. The development of diurnal cycles and the onset of and precipitation (with simplified microphysics) are well predicted by the SCM.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

h5bench: A unified benchmark suite for evaluating HDF5 I/O performance on pre‐exascale platforms

Summary Parallel I/O is a critical technique for moving data between compute and storage subsystems of supercomputers. With massive amounts of data produced or consumed by compute nodes, high‐performant parallel I/O is essential. I/O benchmarks play an important role in this process; however, there is a scarcity of I/O benchmarks representative of current workloads on HPC systems. Toward creating representative I/O kernels from real‐world applications, we have created h5bench , a set of I/O kernels that exercise hierarchical data format version 5 (HDF5) I/O on parallel file systems in numerous dimensions. Our focus on HDF5 is due to the parallel I/O library's heavy usage in various scientific applications running on supercomputing systems. The various tests benchmarked in the h5bench suite include I/O operations (read and write), data locality (arrays of basic data types and arrays of structures), array dimensionality (one‐dimensional arrays, two‐dimensional meshes, three‐dimensional cubes), I/O modes (synchronous and asynchronous). In this paper, we present the observed performance of h5bench executed along several of these dimensions on existing supercomputers (Cori and Summit) and pre‐exascale platforms (Perlmutter, Theta, and Polaris). h5bench measurements can be used to identify performance bottlenecks and their root causes and evaluate I/O optimizations. As the I/O patterns of h5bench are diverse and capture the I/O behaviors of various HPC applications, this study will be helpful to the broader supercomputing and I/O community.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

OpenACC Unified Programming Environment for Multi-hybrid Acceleration with GPU and FPGA

Accelerated computing in HPC such as with GPU, plays a central role in HPC nowadays. However, in some complicated applications with partially different performance behavior is hard to solve with a single type of accelerator where GPU is not the perfect solution in these cases. We are developing a framework and transpiler allowing the users to program the codes with a single notation of OpenACC to be compiled for multi-hybrid accelerators, named MHOAT (Multi-Hybrid OpenACC Translator) for HPC applications. MHOAT parses the original code with directives to identify the target accelerating devices, currently supporting NVIDIA GPU and Intel FPGA, dispatching these specific partial codes to background compilers such as NVIDIA HPC SDK for GPU and OpenARC research compiler for FPGA, then assembles binaries for the final object with FPGA bitstream file. In this paper, we present the concept, design, implementation, and performance evaluation of a practical astrophysics simulation code where we successfully enhanced the performance up to 10 times faster than the GPU-only solution.

Boku, Taisuke↗
DOE OSTI2021

Unified framework for B -anomalies, muon g – 2 and neutrino masses

We present a model of radiative neutrino masses which also resolves anomalies reported in B -meson decays, \( {R}_{D^{\left(\ast \right)}} \) and \( {R}_{K^{\left(\ast \right)}} \) , as well as in muon g – 2 measurement, Δ a μ . Neutrino masses arise in the model through loop diagrams involving TeV-scale leptoquark (LQ) scalars R 2 and S 3 . Fits to neutrino oscillation parameters are obtained satisfying all flavor constraints which also explain the anomalies in \( {R}_{D^{\left(\ast \right)}} \) , \( {R}_{K^{\left(\ast \right)}} \) and Δ a μ within 1 σ . An isospin-3/2 Higgs quadruplet plays a crucial role in generating neutrino masses; we point out that the doubly-charged scalar contained therein can be produced in the decays of the S 3 LQ, which enhances its reach to 1.1 (6.2) TeV at \( \sqrt{s} \) = 14 TeV high-luminosity LHC ( \( \sqrt{s} \) = 100 TeV FCC-hh). We also present flavor-dependent upper limits on the Yukawa couplings of the LQs to the first two family fermions, arising from non-resonant dilepton ( pp → ℓ + ℓ – ) processes mediated by t -channel LQ exchange, which for 1 TeV LQ mass, are found to be in the range (0 . 15 – 0 . 36). These limits preclude any explanation of \( {R}_{D^{\left(\ast \right)}} \) through LQ-mediated B -meson decays involving ν e or ν μ in the final state. We also find that the same Yukawa couplings responsible for the chirally-enhanced contribution to Δ a μ give rise to new contributions to the SM Higgs decays to muon and tau pairs, with the modifications to the corresponding branching ratios being at (2–6)% level, which could be tested at future hadron colliders, such as HL-LHC and FCC-hh.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Gluon splitting at small x: a unified derivation for the JIMWLK, DGLAP and CSS equations

We revisit the calculation of the next-to-leading order (NLO) corrections to dijet production in electron-ion collisions at small x. We focus on the back-to-back configuration where the relative transverse momentum P ⊥ of the measured jets is much larger than both their momentum imbalance K ⊥ and the target saturation momentum Q s (x, A). In this regime, we present for the first time a complete calculation of the real NLO corrections, associated with gluon emissions outside the jet cones, at leading power in 1/P ⊥ . Our result exhibits TMD factorisation, with the same hard factor as at tree-level and a NLO correction to the Weiszäcker-Williams (WW) gluon transverse momentum dependent (TMD) distribution which involves four Wilson-line operators. By studying different kinematical regimes for K ⊥ and for the radiated gluon, we recover all the quantum evolutions that were previously identified for this process at NLO: the B-JIMWLK high-energy evolution and the CSS evolution of the gluon WW TMD, and the DGLAP evolution of the gluon PDF. When both K ⊥ and the transverse momentum transferred by the target are large compared to Q s , all the Wilson-line operators boil down to the unintegrated gluon distribution and our NLO result for the gluon TMD can be used to isolate the transverse-momentum dependent gluon splitting function.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Unifying themes and distinct features of carbon and nitrogen assimilation by polysaccharide-degrading bacteria: a summary of four model systems

Our current understanding of enzymatic polysaccharide degradation has come from a huge number of in vitro studies with purified enzymes. While this vast body of work has been invaluable in identifying and characterizing novel mechanisms of action and engineering desirable traits into these enzymes, a comprehensive picture of how these enzymes work as part of a native in vivo system is less clear. Recently, several model bacteria have emerged with genetic systems that allow for a more nuanced study of carbohydrate active enzymes (CAZymes) and how their activity affects bacterial carbon metabolism. With these bacterial model systems it is now possible to not only study a single nutrient system in isolation (i.e. carbohydrate degradation and carbon metabolism), but also how multiple systems are integrated. Given that most environmental polysaccharides are carbon rich but nitrogen poor (e.g. lignocellulose), the interplay between carbon and nitrogen metabolism in polysaccharide-degrading bacteria can now be studied in a physiologically relevant manner. Therefore, in this review we have summarized what has been experimentally determined for CAZyme regulation, production, and export in relation to nitrogen metabolism for two Gram-positive (Caldicellulosiruptor bescii and Clostridium thermocellum) and two Gram-negative (Bacteroides thetaiotaomicron and Cellvibrio japonicus) polysaccharide-degrading bacteria. By comparing and contrasting these four bacteria we have highlighted the shared and unique features of each, with a focus on in vivo studies, in regard to carbon and nitrogen assimilation. Finally, we conclude with what we believe are two important questions that can act as guideposts for future work to better understand the integration of carbon and nitrogen metabolism in polysaccharide-degrading bacteria.

Cellvibrio japonicus↗
DOE OSTI2023

Towards a unified nonlocal, peridynamics framework for the coarse-graining of molecular dynamics data with fractures

Molecular dynamics (MD) has served as a powerful tool for designing materials with reduced reliance on laboratory testing. However, the use of MD directly to treat the deformation and failure of materials at the mesoscale is still largely beyond reach. In this work, we propose a learning framework to extract a peridynamics model as a mesoscale continuum surrogate from MD simulated material fracture data sets. Firstly, we develop a novel coarse-graining method, to automatically handle the material fracture and its corresponding discontinuities in the MD displacement data sets. Inspired by the weighted essentially non-oscillatory (WENO) scheme, the key idea lies at an adaptive procedure to automatically choose the locally smoothest stencil, then reconstruct the coarse-grained material displacement field as the piecewise smooth solutions containing discontinuities. Then, based on the coarse-grained MD data, a two-phase optimization-based learning approach is proposed to infer the optimal peridynamics model with damage criterion. In the first phase, we identify the optimal nonlocal kernel function from the data sets without material damage to capture the material stiffness properties. Then, in the second phase, the material damage criterion is learnt as a smoothed step function from the data with fractures. As a result, a peridynamics surrogate is obtained. As a continuum model, our peridynamics surrogate model can be employed in further prediction tasks with different grid resolutions from training, and hence allows for substantial reductions in computational cost compared with MD. We illustrate the efficacy of the proposed approach with several numerical tests for the dynamic crack propagation problem in a single-layer graphene. Our tests show that the proposed data-driven model is robust and generalizable, in the sense that it is capable of modeling the initialization and growth of fractures under discretization and loading settings that are different from the ones used during training.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Rigorous computation of short-range order unifies its controversial effects in complex concentrated alloys

Direct experimental observations of chemical short-range order (SRO) in complex concentrated alloys (CCAs) have triggered high interest. However, the reported effects of SRO on yield stresses are controversial, and their atomic-scale mechanisms are elusive, which limits our ability to utilize SRO in alloy design. Here we tackle this challenge using an advanced computational approach that rigorously takes into account the critical lattice distortion in CCAs and further verify our theoretical predictions with experiments. We show that the CoCrNi model alloy has a narrow temperature window around 670 °C for SRO formation. This explains why the mechanical effect of SRO is observed in some experiments but not in others. Here, we propose an effective alloy-doping method to control SRO and reveal atomic-bonding types that dominate SRO formation for different alloys. The strategies and insights generally apply to a broad spectrum of alloys, laying the foundation for designing advanced alloys by manipulating their SRO.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Anion-derived contact ion pairing as a unifying principle for electrolyte design

Enabling new electrochemical technologies requires systems that can operate under ever-more demanding conditions, and progress in energy storage applications reveals tantalizing opportunities to reimagine electrolyte design for performance at extreme potentials. Here, a common thread among these innovations is the formation of significant populations of contact ion pairs (CIPs) in the electrolyte, regardless of the specific cation chemistry or solvent system. The examples summarized in this review suggest that a set of general electrolyte design rules likely exists, where the purposeful selection of anion chemistry can yield CIP structures with tunable control over reaction thermodynamics, kinetics, and interphase chemistry. Identifying the relevant descriptors for high-performance, anion-derived CIP structures can be achieved utilizing a combined experimental and computational approach, aided by machine learning and artificial intelligence, to more rapidly survey the vast combinatorial space available and to enable a new generation of electrolytes for decarbonized electrochemical processes at scale.

electrochemistry↗