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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 37 records · Page 2

Towards Smart Grids Enhanced Situation Awareness: A Bi-Level Quasi-Static State Estimation Model

Smart Grid situational awareness is provided by Energy Management Systems. A core process of these systems is State Estimation. The great majority of state estimators model the Smart Grid through a set of nonlinear algebraic equations, named the measurement model. Problem formulation considers the Gauss solution. Several model improvements have been presented regarding the Gauss solution, aiming between others to provide measurement noise robustness to the state estimation process. While considerable effort has been focused on such developments, state estimation is still constrained by the implicit modelling error, and thus inevitably vulnerable to cyber-threats. In this work, a state estimation bi-level formal model is presented towards Smart Grids enhanced situational awareness considering the concepts of synthetic measurements and innovation. Comparative test results with the state-of-the-art on the IEEE 14-bus system are presented highlighting improved situational awareness to bad data. Easy-to-implement model, without hard-to-derive parameters, built-on the classic weighted least squares solution, highlight potential aspects for real-life implementation.

cyber security↗

The Thermococcales as a model system: historical perspectives and emerging tools

Thermococcales are among the most widely studied hyperthermophilic Archaea and have become key models for understanding life at extreme temperatures. Early work in the 1980s culminated in the isolation of novel Thermococcales species from hydrothermal vents that grew rapidly, tolerated extreme heat, and metabolized diverse substrates, making them uniquely amenable for laboratory studies. Their thermostable enzymes and emerging genetic tools facilitated detailed investigations of core processes such as DNA replication, repair, and transcription under conditions that challenge most life forms. These practical advantages, together with the accumulation of tools and protocols, cemented the role of Thermococcales as a model system. Here, we recount how chance discoveries, environmental adaptations, and experimental practicality intersected to establish Thermococcales as a central model for studying archaeal biology and extremophile physiology.

59 BASIC BIOLOGICAL SCIENCES↗

Parameter Optimization Toolbox for NS-3 network optimization, NS-3 Parameter Optimization Framework [SWR-18-60]

This simulation-based parameter optimization framework is proposed to tune parameters of different types of communication networks using ns-3 to achieve the optimal network performance. It consists of three main components: an ns-3 packet reporting module; a sampler running simulations with all possible parameter sets for the input parameter variables by using a parallel executor at each generation; and a hybrid optimization algorithm for tuning configurable parameters of hybrid designs and application parameter variables. The proposed hybrid metaheuristic optimization algorithm combines an evolutionary algorithm with a gradient descent function to quickly achieve an approximate globally optimum solution. This software is designed to be used in a multi-core processing Linux environment and run over a long duration of time. The execution time varies depending mainly upon the nature of the ns-3 configuration being simulated. This software includes a custom ns-3 QoS measurement application which must be included with the ns-3 source code during installation of the software.

Hasandka, Adarsh↗

Systems and methods for rapid processing and storage of data

Systems and methods of building massively parallel computing systems using low power computing complexes in accordance with embodiments of the invention are disclosed. A massively parallel computing system in accordance with one embodiment of the invention includes at least one Solid State Blade configured to communicate via a high performance network fabric. In addition, each Solid State Blade includes a processor configured to communicate with a plurality of low power computing complexes interconnected by a router, and each low power computing complex includes at least one general processing core, an accelerator, an I/O interface, and cache memory and is configured to communicate with non-volatile solid state memory.

Stalzer, Mark A.↗

Method and apparatus for providing thermal wear leveling

Exemplary embodiments provide thermal wear spreading among a plurality of thermal die regions in an integrated circuit or among dies by using die region wear-out data that represents a cumulative amount of time each of a number of thermal die regions in one or more dies has spent at a particular temperature level. In one example, die region wear-out data is stored in persistent memory and is accrued over a life of each respective thermal region so that a long term monitoring of temperature levels in the various die regions is used to spread thermal wear among the thermal die regions. In one example, spreading thermal wear is done by controlling task execution such as thread execution among one or more processing cores, dies and/or data access operations for a memory.

Roberts, David A.↗

Method and apparatus for providing thermal wear leveling

Exemplary embodiments provide thermal wear spreading among a plurality of thermal die regions in an integrated circuit or among dies by using die region wear-out data that represents a cumulative amount of time each of a number of thermal die regions in one or more dies has spent at a particular temperature level. In one example, die region wear-out data is stored in persistent memory and is accrued over a life of each respective thermal region so that a long term monitoring of temperature levels in the various die regions is used to spread thermal wear among the thermal die regions. In one example, spreading thermal wear is done by controlling task execution such as thread execution among one or more processing cores, dies and/or data access operations for a memory.

Roberts, David A.↗

The γ -process nucleosynthesis in core-collapse supernovae

The γ-process nucleosynthesis in core-collapse supernovae is generally accepted as a feasible process for the synthesis of neutron-deficient isotopes beyond iron. However, crucial discrepancies between theory and observations still exist: the average yields of γ-process nucleosynthesis from massive stars are still insufficient to reproduce the solar distribution in galactic chemical evolution calculations, and the yields of the Mo and Ru isotopes are a factor of ten lower than the yields of the other γ-process nuclei. We investigate the γ-process in five sets of core-collapse supernova models published in the literature with initial masses of 15, 20, and 25 M ⊙ at solar metallicity. We compared the γ-process overproduction factors from the different models. To highlight the possible effect of nuclear physics input, we also considered 23 ratios of two isotopes close to each other in mass relative to their solar values. Further, we investigated the contribution of C–O shell mergers in the supernova progenitors as an additional site of the γ-process. Our analysis shows that a large scatter among the different models exists for both the γ-process integrated yields and the isotopic ratios. We find only ten ratios that agree with their solar values, all the others differ by at least a factor of three from the solar values in all the considered sets of models. The γ-process within C–O shell mergers mostly influences the isotopic ratios that involve intermediate and heavy proton-rich isotopes with A > 100. We conclude that there are large discrepancies both among the different data sets and between the model predictions and the solar abundance distribution. More calculations are needed; particularly updating the nuclear network, because the majority of the models considered in this work do not use the latest reaction rates for the γ-process nucleosynthesis. Moreover, the role of C–O shell mergers requires further investigation.

79 ASTRONOMY AND ASTROPHYSICS↗

Comprehensive Analysis of the Neutrino Process in Core-collapsing Supernovae

We investigate the neutrino flavor change effects due to neutrino self-interaction and shock wave propagation, as well as the matter effects on the neutrino process in core-collapsing supernovae (CCSNe). For the hydrodynamics, we use two models: a simple thermal bomb model and a specified hydrodynamics model for SN1987A. For the presupernova model, we take an updated model, adjusted to explain SN1987A, which employs recent developments in the (n, γ) reaction rates for nuclei near the stability line (A ~ 100). As for the neutrino luminosity, we adopt two different models: equivalent neutrino luminosity and nonequivalent luminosity models. The latter is taken from a synthetic analysis of CCSN simulation data, which quantitatively presented the results obtained by various neutrino transport models. Relevant neutrino-induced reaction rates are calculated using a shell model for light nuclei and a quasiparticle random phase approximation model for heavy nuclei. For each model, we present abundances of the light nuclei ( 7 Li, 7 Be, 11 B, and 11 C) and the heavy nuclei ( 92 Nb, 98 Tc, 138 La, and 180 Ta) produced by the neutrino process. The light nuclei abundances turn out to be sensitive to the Mikheyev–Smirnov–Wolfenstein (MSW) region around O-Ne-Mg layer while the heavy nuclei are mainly produced prior to the MSW region. Through detailed analyses, we find that neutrino self-interaction becomes a key ingredient, in addition to the MSW effect, for understanding the neutrino process and the relevant nuclear abundances. The normal mass hierarchy is shown to be more compatible with the meteorite data. The main nuclear reactions for each nucleus are also investigated in detail.

79 ASTRONOMY AND ASTROPHYSICS↗

Amorphous and Nanocomposite Magnets for High Efficiency, High Speed Motor Designs

This project developed metal amorphous nanocomposite (MANC) soft magnetic materials (SMMs) for a rare earth (RE)-free 2.5 kW motor with 4% increased efficiency. The Project modeled RE-free motor topologies. The project outcomes addressed: (a) metal to alloy processing & magnet core production; (b) soft magnetic laminate & core post-processing; and (c) producing a 2.5 kW motor extending to TRL-5.

30 DIRECT ENERGY CONVERSION↗

Strontium-84 Enrichments in Presolar Grains Provide First Evidence of p -process Nucleosynthesis in Core-collapse Supernovae

This study reports detection of rare p-process isotopes within presolar grains. Presolar grains are relic dust grains from dying stars. These microscopic dust particles are found in primitive solar system materials. Their distinct isotopic compositions record the nucleosynthetic processes in their parent stars and the Galactic chemical environment in which these stars formed. We studied presolar graphite grains of high-density type from the Murchison meteorite and found five grains with subgrains that show enrichments in 84 Sr compared to the solar abundance. 84 Sr is the neutron-deficient isotope of strontium that can be produced in the deep oxygen-rich interior of high-mass stars that end their lives as core-collapse supernovae. The observed 84 Sr excesses cannot be produced in low-mass asymptotic giant branch stars, the source of most high-density presolar graphites found in meteorites. High-density graphites with embedded 84 Sr excesses are, instead, compatible with a core-collapse supernovae origin. The graphite subgrains condensed from carbon-rich materials in the outer layers of core-collapse supernovae, where 84 Sr was destroyed by neutron captures during hydrostatic evolution of the stars and their final explosion. Based on current theoretical stellar models, a few percent of contribution from the inner regions of core-collapse supernovae, which are enriched in p-process nuclides, to the outer carbon-rich regions is the most likely explanation for the observed enrichment of 84 Sr in the subgrains of the high-density graphites. In this study, we present the first observational evidence that core-collapse supernovae produce and eject isotopes made by the p-process.

Astronomy and AstroPhysics↗

Classification of Cloud Particle Imagery from Aircraft Platforms Using Convolutional Neural Networks

Abstract A vast amount of ice crystal imagery exists from a variety of field campaign initiatives that can be utilized for cloud microphysical research. Here, nine convolutional neural networks are used to classify particles into nine regimes on over 10 million images from the Cloud Particle Imager probe, including liquid and frozen states and particles with evidence of riming. A transfer learning approach proves that the Visual Geometry Group (VGG-16) network best classifies imagery with respect to multiple performance metrics. Classification accuracies on a validation dataset reach 97% and surpass traditional automated classification. Furthermore, after initial model training and preprocessing, 10 000 images can be classified in approximately 35 s using 20 central processing unit cores and two graphics processing units, which reaches real-time classification capabilities. Statistical analysis of the classified images indicates that a large portion (57%) of the dataset is unusable, meaning the images are too blurry or represent indistinguishable small fragments. In addition, 19% of the dataset is classified as liquid drops. After removal of fragments, blurry images, and cloud drops, 38% of the remaining ice particles are largely intersecting the image border (≥10% cutoff) and therefore are considered unusable because of the inability to properly classify and dimensionalize. After this filtering, an unprecedented database of 1 560 364 images across all campaigns is available for parameter extraction and bulk statistics on specific particle types in a wide variety of storm systems, which can act to improve the current state of microphysical parameterizations.

54 ENVIRONMENTAL SCIENCES↗

Modeling and Measuring the Stress Distribution in Soft Magnetic Cores due to Epoxy Impregnation and Curing

Understanding the effects of viscoelastic relaxation of stresses is critical in electric motor and inductor applications, where the magnetic material is fully or partially comprised of an amorphous phase and impregnated in an epoxy. Magnetic Amorphous Nanocomposites (MANCs) are a class of recently developed high-frequency magnetic materials that exhibit low magnetic hysteresis, high saturation flux density and very low AC magnetic losses. MANCs are formed as long, thin ribbons, a shape factor that minimizes eddy current-induced self-heating. This feature, in addition to their 1 GPa strength, and makes them attractive candidates for high-speed, high-power density, electric motors. MANCs are used in the form of tape-wound cores (TWCs). During the manufacturing process, the cores are impregnated with liquid epoxy between each layer of ribbon. Validated knowledge of the stresses imposed by the manufacturing process and during operation is necessary to understand motor performance limitations with respect to strength. Magnetostriction, the strain imposed by reversal of the magnetic field, also affects performance. When the epoxy cures, it contracts volumetrically by 8%, imposing radial and circumferential stresses that vary along the radial direction. To date, these stresses have received little attention in the literature. Here, we model the stress distribution throughout a TWC due to epoxy curing. Strain gauge measurements reported here indicate substantially lower tangential strain than model values, which is beneficial and which we attribute to viscoelastic relaxation of the epoxy layers. We will incorporate a constitutive model of this viscoelastic relaxation, and conduct more detailed strain measurements to understand how this takes

24 POWER TRANSMISSION AND DISTRIBUTION↗

Predicting the effects of climate change on the cross-scale epidemiological dynamics of a fungal plant pathogen

The potential for climate change to exacerbate the burden of human infectious diseases is increasingly recognized, but its effects on infectious diseases of plants have received less attention. Understanding the impacts of climate on the epidemiological dynamics of plant pathogens is imperative, as these organisms play central roles in natural ecosystems and also pose a serious threat to agricultural production and food security. We use the fungal ‘flax rust’ pathogen (Melampsora lini) and its subalpine wildflower host Lewis flax (Linum lewisii) to investigate how climate change might affect the dynamics of fungal plant pathogen epidemics using a combination of empirical and modeling approaches. Our results suggest that climate change will initially slow transmission at both the within- and between-host scales. However, moderate resurgences in disease spread are predicted as warming progresses, especially if the rate of greenhouse gas emissions continues to increase at its current pace. These findings represent an important step towards building a holistic understanding of climate effects on plant infectious disease that encompasses demographic, epidemiological, and evolutionary processes. A core result is that neglecting processes at any one scale of plant pathogen transmission may bias projections of climate effects, as climate drivers have variable and cascading impacts on processes underlying transmission that occur at different scales.

59 BASIC BIOLOGICAL SCIENCES↗

Mixed core processor unit

A method and apparatus for processing data. The data is sent to a processor unit comprising a group of neural cores, a group of digital processing cores, and a routing network connecting the group of digital processing cores. The data is processed in the processor unit to generate a result.

97 MATHEMATICS AND COMPUTING↗

Quality Procedures for TCR Metal Core Structure Advanced Manufacturing Processes

The Transformational Challenge Reactor (TCR) Manufacturing WBS# 3.02.04.02 organization is responsible for the advanced manufacturing process, research, development, and implementation that supports the TCR program under the TCR Additive Manufacturing (AM) Thrust. Advanced manufacturing at Oak Ridge National Laboratory (ORNL) includes the development and capabilities to use modern advanced manufacturing techniques, such as AM (e.g., 3D printing) and other novel methods, to rapidly design, develop, produce, finish, and characterize parts, samples, and components to support the nuclear and other high-quality standards industries. Deliverable # M2TC-20OR04020110 involved the development of TCR quality procedures for the TCR metal core structure by using the advanced manufacturing processes being developed at ORNL’s Manufacturing Demonstration Facility (MDF) and other ORNL locations. This report discusses the details of these procedures.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Bayesian model selection for GRB 211211A through multiwavelength analyses

ABSTRACT Although GRB 211211A is one of the closest gamma-ray bursts (GRBs), its classification is challenging because of its partially inconclusive electromagnetic signatures. In this paper, we investigate four astrophysical scenarios as possible progenitors for GRB 211211A: a binary neutron star merger, a black hole–neutron star merger, a core-collapse supernova, and an r-process enriched core collapse of a rapidly rotating massive star (a collapsar). We perform a large set of Bayesian multiwavelength analyses based on different models describing these scenarios and priors to investigate which astrophysical scenarios and processes might be related to GRB 211211A. Our analysis supports previous studies in which the presence of an additional component, likely related to r-process nucleosynthesis, is required to explain the observed light curves of GRB 211211A, as it cannot be explained solely as a GRB afterglow. Fixing the distance to about $350~\rm Mpc$, namely the distance of the possible host galaxy SDSS J140910.47+275320.8, we find a statistical preference for a binary neutron star merger scenario.

(transients:) gamma-ray bursts↗

Mesocrystallizing Nanograins for Enhanced Li + Storage

Morphology and crystallinity of electrode materials have a major effect on their charge carrier storage properties when applied in rechargeable batteries. While nanosizing electrode particles (with larger surface area) and maintaining electrode integrity are both good for performance enhancement, they seem to contradict each other and can be hardly well-balanced. Herein, we designed electrode particles consisting of numerous nanograins with uniform crystalline orientation to guarantee both high surface area and high structural integrity, allowing the significant improvement of Li + storage kinetics and performance. Applying this “mesocrystallizing” strategy to a NiCo 2 O 4 -based anode, resulting in various degrees of pseudocapacitance response, the long-term cyclability and rate performance of this material have been largely enhanced. Impressively, the mesocrystalline NiCo 2 O 4 electrode exhibits a high reversible capacity of 1403 mAh g -1 after 200 cycles at 1.6 A g -1 (a rate of 1.8 C). The growth mechanism of mesocrystalline materials with different morphologies is identified to be a topotactic strctural transition process featuring a gradual edge-to-core corrasion process. This work presents an important synthetic clue to balance the morpholgy and crystallinity of battery electrode materials for their perforamnce optimization and is expected to inspire future structural design for battery materials beyond the one prototyped here.

25 ENERGY STORAGE↗