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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Advancement of hybrid fluid-kinetic modeling for HEDP and ICF science

We report on the development progress of a hybrid fluid-kinetic code for simulating fluids and plasmas in a wide range of environments, such as laser–matter interactions, inertial confinement fusion, magnetic confinement fusion, and pulsed power. The suite of numerical tools under development utilizes heterogeneous computer architectures and leverages the benefits of particle–based simulation techniques. By working to combine the kinetic particle-in-cell (PIC) model with a particle-based fluid simulation technique, such as smoothed particle hydrodynamics, we are developing a flexible framework capable of accurately modeling complex flows within and between kinetic and fluid regimes. The TriForce code is under development as a C++ framework for parallel, 3D, particle-based, hybrid fluid-kinetic plasma simulations. The fluid half of TriForce will be based upon the meshless smoothed-particle-hydrodynamics (SPH) approach, well-suited for shear, mixing, and turbulence, whereas the kinetic half resembles a traditional particle-in-cell (PIC) code; other particle-based approaches to fluid modeling that do use a mesh are also possible to use and are under investigation. Maxwell’s electromagnetic field equations are solved either via explicit or implicit algorithms or approximated via resistive magnetohydrodynamics (MHD) using an Ohm’s law and resulting induction equation (extended MHD is under development). A primary goal of enabling direct comparisons, from the same code, between results from the variants of MHD and implicit electromagnetic solutions is to improve our fundamental understanding of systems with magnetic fields. The code is under development to recover results from both radiation-MHD and fully kinetic codes in those limits, and is continuing to be developed from other follow-on grants to operate in between where both descriptions may co-exist and interact. For certain applications, it is desired for a simulation to contain fluid ions and electrons as well as kinetic ions and electrons. Typically, it is too computationally intensive to model a full-scale ICF or HEDP experiment fully kinetically since many cycles are expended with very small time steps on modeling the fluid part of a material that is well treated by the fluid approximation. In this case, many traditional PIC particles can be replaced with a single fluid particle representing the thermal part of the distribution function, and there are fewer needed kinetic particles, which describe the non-thermal part and can be sub-cycled relative to the fluid particle advance. Furthermore, a pure fluid code may, depending on the problem, simply lack many physically important details that are beyond the scope of its reduced approximations and assumptions. In this report, we summarize the objectives achieved in the development of the collisional and kinetic half of the code, and the physics problems to which the code has been applied in the areas of advanced and innovative fusion concepts, pulsed power, and magneto-inertial fusion.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Deep learning approaches for neural decoding across architectures and recording modalities

Decoding behavior, perception or cognitive state directly from neural signals is critical for brain–computer interface research and an important tool for systems neuroscience. In the last decade, deep learning has become the state-of-the-art method in many machine learning tasks ranging from speech recognition to image segmentation. The success of deep networks in other domains has led to a new wave of applications in neuroscience. In this article, we review deep learning approaches to neural decoding. Here, we describe the architectures used for extracting useful features from neural recording modalities ranging from spikes to functional magnetic resonance imaging. Furthermore, we explore how deep learning has been leveraged to predict common outputs including movement, speech and vision, with a focus on how pretrained deep networks can be incorporated as priors for complex decoding targets like acoustic speech or images. Deep learning has been shown to be a useful tool for improving the accuracy and flexibility of neural decoding across a wide range of tasks, and we point out areas for future scientific development.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Demonstrate FARM supervisory capabilities for a thermal energy storage problem for the DETAIL facility: IES Simulation Ecosystem Control System Development

The goal of the power dispatch problem for an Integrated Energy System (IES) is to adjust the power output and the heat flow of each component to maximize the profitability of the whole unit. Facilities that can integrate real-time digital signals, mock nuclear power, thermal energy storage and industrial heat use via high-temperature electrolysis were constructed at INL to support the research activities. The Dynamic Energy Technology and Integration Laboratory (DETAIL) houses the Microreactor Agile Non-nuclear Experimental Test Bed (MAGNET) and the Thermal Energy Distribution System (TEDS). In this report, the hierarchical control system architecture proposed in June 2023 milestone for the flexible operation of DETAIL facility is finalized and demonstrated. A brief description of the components and the corresponding Dymola models from the HYRBID repository is first provided. Then, the current control strategy is presented. In particular, the approach for generating the set-point trajectories to be fed to the PI controllers is analyzed, and its limits were identified. To preserve safe operation over both long-time and real-time horizons, the integration of a Supervisory Control layer embedding a modified version of FARM (Feasible Actuator Range Modifier) module is proposed. FARM is a component of the RAVEN-based FORCE framework designed to support HERON module at optimizing the operation of IES units. The proposed control system for DETAIL foresees FARM to be applied twice, i.e., the original version (“FARM-Validator”) aiding the solution of the power dispatch problem, and a modified version (“FARM-Supervisory”) coordinating the PID controllers. Despite the kernel of the two modules is the same, their tasks are quite different. The former intervenes at the beginning of each hour to prevent constraint violations over long time periods, the latter addresses real-time control tasks and monitors the response of constrained variables at a much finer time resolution. A tentative procedure for training the embedded Digital Twins with the experimental data is also proposed. Finally, the capabilities of the designed architecture and the impact of the added Supervisory Control layer are demonstrated by simulating a representative power dispatch scenario.

25 ENERGY STORAGE↗
NASA NTRSDate not supplied

Design of a High Power Density, High Efficiency, Low THD 250kW Converter for Electric Aircraft

A high efficiency, high power density, low distortion 250kW motor controller is being developed at NASA Glenn Research Center. Future electric aircraft require motor controllers which achieve the needed key performance parameters required to show benefit in increasing overall aircraft efficiency. Through a combination of carefully considered electrical topological choices and through the use of recent advancements in power switches and magnetic materials, a converter is designed which meets these requirements. A multilevel and interleaved converter architecture is chosen to meet the voltage, current, and THD requirements. The enclosure and thermal designs meet their weight targets and enable high altitude operation.

Matthew Granger↗
DOE OSTI2025

Stabilization of magnetic bubbles in [Ni/Co]n multilayers on an oxygen-reconstructed Nb(110) surface via an ultra-thin Cu interlayer

Magnetic thin films hosting topological spin textures, such as magnetic skyrmions, hold high potential for breakthroughs in the field of spintronics, due to good scalability and energy efficiency. Novel computational architectures such as memory-in-logic devices rely on material platforms able to host those topological spin textures. Furthermore, recently proposed designs of novel quantum information technologies are based on heterostructures where topological spin textures are in direct proximity to a superconducting layer. Here, we demonstrate the stabilization of out-of-plane magnetic bubbles in highly ordered [Ni/Co]n multilayers on a Nb(110) single crystal. This is achieved without the need for the removal of the well-known Nb(110)-oxide surface reconstruction, due to the introduction of an ultra-thin Cu interlayer in between the Nb substrate and the magnetic multilayer. The Cu interlayer generates a well-ordered hexagonal surface, which is key for the epitaxial growth of the [Ni/Co]n multilayers hosting the desired out-of-plane anisotropy. The magnetic ground state of the prepared material stacks is directly imaged via spin-polarized low-energy electron microscopy, revealing the presence of magnetic bubble domains with lateral sizes as small as 450 nm.

Dibajeh, Ahmad↗
NASA NTRSDate not supplied

Development of the Microcalorimeter Detector for Athena/X-IFU

The X-ray Integral Field Unit (X-IFU) will be a microcalorimeter instrument on ESA’s Athena X-ray observatory, set to launch around 2037. Athena recently underwent a reformulation exercise resulting in a simplified X-IFU architecture, with a new baseline configuration featuring fewer pixels and readout channels. Newly developed transition edge sensor pixels that are slower and have reduced magnetic field sensitivity have helped enable the new instrument design whilst maintaining flagship quality science. In this paper, we report on the status and plan for continued development of the X-IFU microcalorimeter array. We describe details of the current pixel architecture and performance specifications. We will present the design of the first full scale microcalorimeter arrays that have the necessary flight like electrical and mechanical interfaces for X-IFU. These arrays will undergo testing in a focal-plane assembly (FPA) Development Model (DM) in Europe later in 2024 and serve as a precursor to the X-IFU Engineering Model detector.

Stephen J Smith↗
DOE OSTI2022

Software Architecture and Hardware Organization in Mu2e Solenoid Field Mapping System

Herein, the Mu2e field mapping system is designed to produce high accuracy field maps of the detector solenoid used in the experiment. The data acquisition system is mobile and uses a self-propelled mapper with rotating arms equipped with 3D Hall probes. The measurements require not only accurate magnetic field readouts, but also accurate locations of all Hall probes while measuring data. The latter is accomplished by using the laser tracker to measure positions of several retroreflectors on the field mapper during data acquisition. The measurement process requires scanning the whole space inside the large solenoid and takes many hours to complete, which necessitates its full automation. The automation software includes control of the mapper, readout of Hall and NMR probes and control of a laser tracker, including prediction of retroreflector positions and execution of quality control checks. The software architecture and data acquisition hardware of the field mapping system are described, with special attention given to control of the laser tracker and its integration with the rest of the system.

3d hall probes↗
DOE OSTI2026

Reference Hardware and Software Architecture for a Solenoid Pulser for Scientific Instrumentation at the National Ignition Facility

High current, high voltage solenoid pulser power systems for the generation of magnetic fields in a solenoid is not a radical or new concept. Despite being a cornerstone of scientific and weapons research for over 100 years, a commercial off the shelf unit easily configurable for a broad set of applications has yet to appear on the open market. Pulser systems are instead designed for specific target requirements. For gigawatt to terawatt systems, this is unavoidable. For megawatt systems however, many hundreds of thousands of dollars are wasted designing pulser systems from the ground up for clients, when it is possible to simply architect a modular system once that can have its capacitors swapped for many possible target applications. The National Ignition Facility (NIF) at the Lawrence Livermore National Laboratory (LLNL) is one such institution that would benefit from such a system, having bought such pulsers for several imaging systems. Ideally, all such a system would require is only a bachelors-level circuit analysis to find the correct capacitor values, as well as a written procedure to calibrate the software to correctly deliver the voltages required by the application. In this work, systems architecture and software engineering techniques are used to design and analyze such a system. Such a design, it is the hope of this author, will be used in scientific and engineering purposes in the future to build solenoid pulsers at the National Ignition Facility and other institutions to drastically cut development costs of scientific instrumentation.

42 ENGINEERING↗
DOE OSTI2020

Catalytic upcycling of high-density polyethylene via a processive mechanism

The overconsumption of single-use plastics is creating a global waste catastrophe, with widespread environmental, economic and health-related consequences. In this work we show that the benefits of processive enzyme-catalysed conversions of biomacromolecules can be leveraged to affect the selective hydrogenolysis of high-density polyethylene into a narrow distribution of diesel and lubricant-range alkanes using an ordered, mesoporous shell/active site/core catalyst architecture that incorporates catalytic platinum sites at the base of the mesopores. Solid-state nuclear magnetic resonance revealed that long hydrocarbon macromolecules readily move within the pores of this catalyst, with a subsequent escape being inhibited by polymer–surface interactions, a behaviour that resembles the binding and translocation of macromolecules in the catalytic cleft of processive enzymes. Accordingly, the hydrogenolysis of polyethylene with this catalyst proceeds processively to yield a reliable, narrow and tunable stream of alkane products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Driving magnetic domains at the nanoscale by interfacial strain-induced proximity

Here, we investigate the local nanoscale changes of the magnetic anisotropy of a Ni film subject to an inverse magnetostrictive effect by proximity to a V 2 O 3 layer. Using temperature-dependent photoemission electron microscopy (PEEM) combined with X-ray magnetic circular dichroism (XMCD), direct images of the Ni spin alignment across the first-order structural phase transition (SPT) of V 2 O 3 were obtained. We find an abrupt temperature-driven reorientation of the Ni magnetic domains across the SPT, which is associated with a large increase of the coercive field. Moreover, angular dependent ferromagnetic resonance (FMR) shows a remarkable change in the magnetic anisotropy of the Ni film across the SPT of V 2 O 3 . Micromagnetic simulations based on these results are in quantitative agreement with the PEEM data. Direct measurements of the lateral correlation length of the Ni domains from XMCD images show an increase of almost one order of magnitude at the SPT compared to room temperature, as well as a broad spatial distribution of the local transition temperatures, thus corroborating the phase coexistence of Ni anisotropies caused by the V 2 O 3 SPT. We show that the rearrangement of the Ni domains is due to strain induced by the oxide layers’ structural domains across the SPT. Our results illustrate the use of alternative hybrid systems to manipulate magnetic domains at the nanoscale, which allows for engineering of coercive fields for novel data storage architectures.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Variation of effective filament diameter, irreversibility field, anisotropy, and pinning efficiency in Bi-2212 round wires

Abstract In recent years Bi 2 Sr 2 CaCu 2 O x (Bi-2212) received increasing attention due to its round wire multifilamentary architecture, a unique feature in high- T c superconductor. In fact, round wires are preferable for magnet designs, including solenoids for nuclear magnetic resonance (NMR) or research purpose and accelerator magnets. However, due to the narrow over-pressure heat treatment conditions necessary to obtain high J c and to the peculiar microstructure of Bi-2212 wires, a full understanding of the correlations between the different properties has not yet been developed. In this paper we investigate the effect of a vital part of Bi-2212 optimization, the maximum heat-treatment temperature T max in the range of 885 °C–896 °C, on the variations of J c , effective filament diameter d eff , anisotropy γ , INTER- and intra-grain irreversibility fields and pinning energies U 0 , all critical parameters in unravelling the complex mix of vortex pinning and connectivity that ultimately determines the critical current density. We found that d eff of the higher J c wires heat-treated at lower temperature is much smaller than for the lower J c wires. Moreover, a systematic increase of the irreversibility field and a decrease of the intrinsic Bi-2212 anisotropy underpins the higher J c . The analysis of the pinning energies reveals that there is little sample-to-sample variation in the INTER-grain pinning, whereas in all samples the intra-grain pinning has an enhancement below ∼40–45 K becoming more and more evident with increasing J c . These results suggest that the overall J c performance are not only related to the wire microstructure and connectivity, which obviously affect the INTER-grain properties, but they are also intimately related to the intrinsic and intra-grain properties such as γ and U 0 .

Physics↗
DOE OSTI2026

Machine-learning modeling of magnetization dynamics in quasi-equilibrium and driven metallic spin systems

Here, we present a perspective on recent progress in machine-learning (ML) force-field approaches for large-scale Landau–Lifshitz–Gilbert (LLG) simulations of metallic spin systems. Building on a generalization of the Behler–Parrinello (BP) architecture originally developed for quantum molecular dynamics, we develop scalable and transferable ML models that faithfully capture the complex, environment-dependent electron-mediated exchange fields characteristic of itinerant magnets. A central ingredient of this framework is the implementation of symmetry-aware magnetic descriptors based on group-theoretical bispectrum formalisms. Leveraging these ML force fields, LLG simulations faithfully reproduce hallmark non-collinear magnetic orders—such as the 120° and tetrahedral states—on the triangular lattice, and successfully capture the complex spin textures emerging in the mixed-phase states of a square-lattice double-exchange model under thermal quench. We further discuss a generalized potential theory that extends the BP formalism to incorporate both conservative and nonconservative electronic torques, thereby enabling ML models to learn nonequilibrium exchange fields from computationally demanding microscopic approaches such as nonequilibrium Green’s-function techniques. This extension yields quantitatively accurate predictions of voltage-driven domain-wall motion and establishes a foundation for quantum-accurate, multiscale modeling of nonequilibrium spin dynamics and spintronic functionalities.

Descriptors↗
DOE OSTI2020

Fast neural Poincaré maps for toroidal magnetic fields

Poincaré maps for toroidal magnetic fields are routinely employed to study gross confinement properties in devices built to contain hot plasmas. In most practical applications, evaluating a Poincaré map requires numerical integration of a magnetic field line, a process that can be slow and that cannot be easily accelerated using parallel computations. We propose a novel neural network architecture, the HénonNet, and show that it is capable of accurately learning realistic Poincaré maps from observations of a conventional field-line-following algorithm. After training, such learned Poincaré maps evaluate much faster than the field-line integration method. Moreover, the HénonNet architecture exactly reproduces the primary physics constraint imposed on field-line Poincaré maps: flux preservation. Furthermore, this structure-preserving property is the consequence of each layer in a HénonNet being a symplectic map. We demonstrate empirically that a HénonNet can learn to mock the confinement properties of a large magnetic island by using coiled hyperbolic invariant manifolds to produce a sticky chaotic region at the desired island location. This suggests a novel approach to designing magnetic fields with good confinement properties that may be more flexible than ensuring confinement using KAM tori.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Reconfigurable spin current transmission and magnon–magnon coupling in hybrid ferrimagnetic insulators

Coherent spin waves possess immense potential in wave-based information computation, storage, and transmission with high fidelity and ultra-low energy consumption. However, despite their seminal importance for magnonic devices, there is a paucity of both structural prototypes and theoretical frameworks that regulate the spin current transmission and magnon hybridization mediated by coherent spin waves. Here, we demonstrate reconfigurable coherent spin current transmission, as well as magnon–magnon coupling, in a hybrid ferrimagnetic heterostructure comprising epitaxial Gd 3 Fe 5 O 12 and Y 3 Fe 5 O 12 insulators. By adjusting the compensated moment in Gd 3 Fe 5 O 12 , magnon–magnon coupling was achieved and engineered with pronounced anticrossings between two Kittel modes, accompanied by divergent dissipative coupling approaching the magnetic compensation temperature of Gd 3 Fe 5 O 12 (T M,GdIG ), which were modeled by coherent spin pumping. Remarkably, we further identified, both experimentally and theoretically, a drastic variation in the coherent spin wave-mediated spin current across T M,GdIG , which manifested as a strong dependence on the relative alignment of magnetic moments. Our findings provide significant fundamental insight into the reconfiguration of coherent spin waves and offer a new route towards constructing artificial magnonic architectures.

42 ENGINEERING↗
DOE OSTI2022

Advancing Geophysical Techniques to Image a Stratigraphic Hydrothermal Resource

Sedimentary-hosted geothermal energy systems are permeable structural, structural-stratigraphic, and/or stratigraphic horizons with sufficient temperature for direct use and/or electricity generation. Sedimentary-hosted (i.e., stratigraphic) geothermal reservoirs may be present in multiple locations across the central and eastern Great Basin of the USA, thereby constituting a potentially large base of untapped, economically accessible energy resources. Sandia National Laboratories has partnered with a multi disciplinary group of collaborators to evaluate a stratigraphic system in Steptoe Valley, Nevada using both established and novel geophysical imaging techniques. The goal of this study is to inform an optimized strategy for subsequent exploration and development of this resource and analogous ones. Building from prior Nevada Play Fairway Analysis (PFA), this team is primarily 1) collecting additional geophysical data, 2) employing novel joint geophysical inversion/modeling techniques to update existing 3D geologic models, and 3) integrating the geophysical results to produce a working, geologically constrained thermo-hydrological reservoir model. Prior PFA work highlights Steptoe Valley as a favorable resource basin that likely has both sedimentary and hydrothermal characteristics. However, there remains significant uncertainty on the nature and architecture of the resource(s) at depth, which increases the risk in exploratory drilling. Newly acquired gravity, magnetic, magnetotelluric, and controlled-source electromagnetic data products, in conjunction with new and preexisting geoscientific measurements and observations, are being integrated and evaluated for efficacy in understanding stratigraphic geothermal resources and mitigating exploration risk. Furthermore, the influence of hydrothermal activity on sedimentary-hosted reservoirs in favorable structural settings, and whether fault-controlled systems may locally enhance temperature and permeability in some deep stratigraphic reservoirs, will also be evaluated.

Geothermal, Sedimentary Heat, Geophysics, Seismic,↗
NASA NTRS2018

Project Link!: Dynamics and Control of In-Flight Wing Tip Docking

Project Link! is a NASA-led effort to study the feasibility of multi-aircraft aerial docking systems. In these systems, a group of vehicles physically link to each other during flight to form a larger ensemble vehicle with increased aerodynamic performance and mission utility. This paper presents a dynamic model and control architecture for a system of fixed-wing vehicles with this capability. The dynamic model consists of the 6 degree-of-freedom fixed-wing aircraft equations of motion, a spring-damper-magnet system to represent the linkage force between constituent vehicles, and the NASA-Burnham-Hallock wingtip vortex model to represent the close-proximity aerodynamic interactions between constituents before the linking occurs. The control architecture consists of a guidance algorithm to autonomously drive the constituents towards their linking partners and an inner-loop angular rate controller. A simulation was constructed from the model, and the flight dynamic modes of the linked system were compared to the individual vehicles. Simulation results for both before and after linking are presented.

Cooper, John R.↗
DOE OSTI2022

Large Magnetic Gap in a Designer Ferromagnet–Topological Insulator–Ferromagnet Heterostructure

Abstract Combining magnetism and nontrivial band topology gives rise to quantum anomalous Hall (QAH) insulators and exotic quantum phases such as the QAH effect where current flows without dissipation along quantized edge states. Inducing magnetic order in topological insulators via proximity to a magnetic material offers a promising pathway toward achieving the QAH effect at a high temperature for lossless transport applications. One promising architecture involves a sandwich structure comprising two single‐septuple layers (1SL) of MnBi 2 Te 4 (a 2D ferromagnetic insulator) with ultrathin few quintuple layer (QL) Bi 2 Te 3 in the middle, and it is predicted to yield a robust QAH insulator phase with a large bandgap greater than 50 meV. Here, the growth of a 1SL MnBi 2 Te 4 /4QL Bi 2 Te 3 /1SL MnBi 2 Te 4 heterostructure via molecular beam epitaxy is demonstrated and the electronic structure probed using angle‐resolved photoelectron spectroscopy. Strong hexagonally warped massive Dirac fermions and a bandgap of 75 ± 15 meV are observed. The magnetic origin of the gap is confirmed by the observation of the exchange‐Rashba effect, as well as the vanishing bandgap above the Curie temperature, in agreement with density functional theory calculations. These findings provide insights into magnetic proximity effects in topological insulators and reveal a promising platform for realizing the QAH effect at elevated temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The Application of Coordination to Magnetic Measurement Automation: An SSW System Example

Magnetic measurements are an integral part of the development cycle of accelerator magnets, a part which provides necessary feedback to drive design and manufacturing improvements and corrections. Automation of these measurements allows for reduction of human errors and reproducibility of measurements. Realization of automation via coordination that is separated at the architectural level from the functional code provides flexibility in defining measurement procedures and substantial extensibility. The described Single Stretched Wire (SSW) system herein is an implementation of such a solution with the use of a component-based framework designed to build a family of measurement systems.

43 PARTICLE ACCELERATORS↗