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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Integrated Framework of Multisource Data Fusion for Outage Location in Looped Distribution Systems

Accurate outage location is essential for expediting post-outage power restoration, minimizing outage duration, and enhancing the resilience of distribution networks. With the advent of advanced metering infrastructure, data-driven outage location methods have significantly advanced beyond traditional approaches that rely on manual inspections. However, existing methods still face critical challenges, like reliance on single-source data, limited ability to handle partially observable systems or difficulties with loop networks. To the best of our knowledge, no single approach has comprehensively addressed all of these challenges at once. To this end, this paper proposes a comprehensive multisource data fusion framework for outage locations via probabilistic graph networks. The framework consists of three key phases. First, a novel method for reconstituting distribution networks with loops is developed, transforming looped networks into multiple radial subnetworks that retain all outage causalities of the original network. Second, Bayesian network (BN) models are established for each subnetwork, integrating multiple data sources and network structures. Finally, a joint Gibbs sampling mechanism, featuring forward and backward information flow, is designed to merge data from separate BN models and maximize the utilization of limited evidence, ensuring accurate outage location identification. In conclusion, the framework was validated on two modified public test systems, and comparative studies confirmed its effectiveness.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

ASAP: Automatic Synthesis of Area-Efficient and Precision-Aware CGRAs

Coarse-grained reconfigurable accelerators (CGRAs) are a promising accelerator design choice that strikes a balance between performance and adaptability to different computing patterns across various applications domains. Designing a CGRA for a specific application domain involves enormous software/hardware engineering effort. Recent research works explore loop transformations, functional unit types, network topology, and memory size to identify optimal CGRA designs given a set of kernels from a specific application do- main. Unfortunately, the impact of functional units with different precision support has rarely been investigated. To address this gap, we propose ASAP – a hardware/software co-design framework that automatically identifies and synthesizes optimal precision-aware CGRA for a set of applications of interest. Our evaluation shows that ASAP generates specialized designs 3.2×, 4.21×, and 5.8× more efficient (in terms of performance per unit of energy or area) than non-specialized homogeneous CGRAs, for the scientific computing, embedded, and edge machine learning domains, respectively, with limited accuracy loss. Moreover, ASAP provides more efficient designs than other state-of-the-art synthesis frameworks for specialized CGRAs.

artificial intelligence↗
DOE OSTI2024

Catalytic Resonance Theory: Forecasting the Flow of Programmable Catalytic Loops

Chemical transformations on catalyst surfaces occur through series and parallel reaction pathways. These complex networks and their behavior can be most simply evaluated through a three-species surface reaction loop (A* to B* to C* to A*) that is internal to the overall chemical reaction. Application of an oscillating dynamic catalyst to this reactive loop has been shown to exhibit one of three types of behavior: (1) a positive net flux of molecules about the loop in the clockwise direction, (2) a negative net flux of molecules about the loop in the counterclockwise direction, or (3) negligible flux of molecules about the loop at the limit cycle of reaction. Three-species surface loops were simulated with microkinetic modeling to assess the reaction loop behavior resulting from a catalytic surface oscillating between two or more catalyst surface energy states. Selected input parameters for the simulations spanned an 11-dimensional parameter space using 127 688 different parameter combinations. Their converged limit cycle solutions were analyzed for their loop turnover frequencies, the majority of which were found to be approximately zero. Classification and regression machine learning models were trained to predict the sign and magnitude of the loop turnover frequency and successfully performed above accessible baselines. Notably, the classification models exhibited a baseline weighted F1 score of 0.49, whereas trained models achieved weighted F1 scores of 0.94 and 0.96 when trained on the parameters used to define the simulations and derived rate constants, respectively. The trained models successfully predicted catalytic loop behavior, and interpretation of these models revealed all input parameters to be important for the prediction and performance of each model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

AstraAI v1

AstraAI is an open-source, structure-aware AI coding agent designed for large scientific and DOE-HPC codebases such as AMReX-based applications. Unlike general-purpose coding assistants, AstraAI combines retrieval-augmented generation (RAG) with compiler-level Abstract Syntax Tree (AST) analysis to perform precise, scope-constrained code modifications. It identifies exact function spans, enforces locality of edits, and maintains cross-file invariants, enabling deterministic and build-safe transformations in complex C++/GPU environments. AstraAI is intended for developers working on large, evolving HPC frameworks where correctness, reproducibility, and structural integrity are critical. Typical use cases include modifying physics kernels, updating GPU device lambdas, and performing multi-file refactors without breaking compilation or runtime semantics. Compared to conventional LLM-based coding agents - even those with repository access - AstraAI provides structural guarantees rather than free-form text patches. It minimizes unintended diffs, prevents scope drift, preserves formatting and build stability, and reduces structural hallucinations. By integrating compiler tooling directly into the generation loop, AstraAI transforms AI-assisted coding from probabilistic text editing into deterministic, structure-preserving program transformation suitable for mission-critical scientific software.

Natarajan, Mahesh [Lawrence Berkeley National Labo↗
DOE OSTI2026

Enabling Grid-Forming Control with Fault Ride-Through in Unbalanced Distribution Networks

Distribution networks are often unbalanced, causing oscillatory responses in inverter control designed for balanced conditions. Here, to address this problem, this paper proposes a novel time-domain transformation appropriate for inverter control and enables the decomposition of three-phase unbalanced signals into constant positive and negative components. Relations useful for calculating unbalanced active and reactive power are derived from first principle, providing insight into vector products of unbalanced three-phase signals. Furthermore, a grid-forming control effective under unbalanced conditions is developed, which delivers superior performance while meeting UNIFI1 specifications for grid-forming control under unbalanced conditions. specifications applicable to category 4 inverter-based resource, like setting and regulating frequency/voltage, providing voltage support, sharing active power, injecting negative sequence current, and riding through faults. A current limiter is proposed for safe fault ride-through and integrates with the grid-forming control featuring frequency/voltage droop controllers and current and voltage control loops. The transformation of interconnected inverters is formulated and stability of the proposed control analyzed to support robust parameter selections. The effectiveness of the proposed transformation and grid-forming control is demonstrated through analytical results and real-time simulation of a IEEE 123 distribution network on the Real-Time Digital Simulator. Comparison with existing methods shows that the proposed strategy satisfies the UNIFI specifications with a much better performance.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Autotuning PolyBench benchmarks with LLVM Clang/Polly loop optimization pragmas using Bayesian optimization

Here, we develop a ytopt autotuning framework that leverages Bayesian optimization to explore the parameter space search and compare four different supervised learning methods within Bayesian optimization and evaluate their effectiveness. We select six of the most complex PolyBench benchmarks and apply the newly developed LLVM Clang/Polly loop optimization pragmas to the benchmarks to optimize them. We then use the autotuning framework to optimize the pragma parameters to improve their performance. The experimental results show that our autotuning approach outperforms the other compiling methods to provide the smallest execution time for the benchmarks syr2k, 3mm, heat-3d, lu, and covariance with two large datasets in 200 code evaluations for effectively searching the parameter spaces with up to 170,368 different configurations. We find that the Floyd-Warshall benchmark did not benefit from autotuning. To cope with this issue, we provide some compiler option solutions to improve the performance. Then we present loop autotuning without a user's knowledge using a simple mctree autotuning framework to further improve the performance of the Floyd-Warshall benchmark. We also extend the ytopt autotuning framework to tune a deep learning application.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Systems and methods for tensor scheduling

A technique for efficient scheduling of operations in a program for parallelized execution thereof using a multi-processor runtime environment having two or more processors includes constraining the type or number of loop optimization transforms that may be explored such that memory and processing capacity available for the scheduling task are not exceeded, while facilitating a tradeoff between memory locality, parallelization, and/or data communication between memory modules of the multi-processor runtime environment.

Meister, Benoit J.↗
DOE OSTI2025

Real-Time Wave Energy Converter Control Using Instantaneous Frequency

Wave Energy Converters (WECs) rely on effective Power Take-Off (PTO) control strategies to maximize energy absorption under dynamic sea conditions. Traditional hydrodynamic modeling techniques may require computationally intensive convolution calculations, making real-time control implementation challenging. This paper presents an alternative approach by leveraging instantaneous frequency estimation to dynamically adjust PTO damping in response to varying wave frequencies. Two real-time frequency estimation methods are explored: the Hilbert Transform (HT) and Phase-Locked Loop (PLL). The Hilbert Transform method provides accurate frequency tracking but introduces a delayed response due to its dependence on causal data. Conversely, the PLL approach demonstrates strong potential in frequency tracking but requires careful gain tuning, particularly in complex sea states. Comparative evaluations across multiple test cases—including sinusoidal variations, amplitude steps, frequency step changes, and real-world JONSWAP spectrum waves—highlight the strengths and limitations of each method. The two different PTO control techniques across the various frequency estimation methods were tested under real-sea states using a state-space model of a point-absorbing Wave Energy Converter. The Capture Width Ratio (CWR) is used as a performance metric, with results showing that the HT achieves a 10.6% improvement, while the PLL estimation yields a 0.9% improvement relative to the fixed parameter control baseline. These results highlight the effectiveness of real-time frequency estimation in improving energy absorption compared to static control parameters.

WEC control↗
DOE OSTI2026

Exotic Uses of Neutrons an X-rays as Probes for Chiral Magnets (Early Career Award) (Final Report)

This is the final report for Exotic Uses of Neutrons an X-rays as Probes for Chiral Magnets, an Early Career award to Prof. Dustin Gilbert, University of Tennessee, running 09/01/2020 - 08/31/2025. This project used neutron scattering as a unique tool to investigate magnetic chiral structures. Neutron scattering is a powerful technique in which the neutron wavepacket scatters from nuclear or magnetic structures, providing insight into the structure of a material and its magnetic features. In this work, we focused on chiral magnetic structures. Most magnetic materials are colinear ferro- or antiferromagnets, where the spin moments align parallel or anti-parallel with their neighbors. In some materials, the magnetic moments instead curl and can form closed loops. These structures, with the additional feature that the core and perimeter are oriented in opposite out-of-plane directions, exhibit a property called topology; these structures are known as skyrmions. Topology is a broadly used term, but here it refers to a magnetic configuration that cannot be created or destroyed through any continuous transformation. For these looped structures, the closed loop cannot be destroyed continuously, giving rise to unique properties such as collective dynamics and particle-like behavior. This also raises fundamental questions about how such structures form and evolve.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Unfaulting mechanisms of interstitial Frank loops in fluorite-structured ThO 2

Unfaulting of Frank loops in irradiated fluorite-structured oxides is of significance for understanding microstructural evolution. However, the mechanisms have not yet been directly observed. To this end, we utilize molecular dynamics to reveal the atomistic details related to the unfaulting process of interstitial Frank loops in ThO 2 , which involve a single pair or multiple pairs of co-propagating Shockley partials to annihilate the stacking faults. Here, we find that the unfaulting is achieved via a synchronous shear of the partial pairs to remove the extrinsic stacking fault in the cation sublattice and the intrinsic stacking fault in the anion sublattice. The high mobility of oxygen at the dislocation core may reduce the activation barriers of dislocation nucleation and migration. These findings provide a fundamental understanding of the transformation of faulted loops in irradiated ThO 2 , and could be transferable to other fluorite-structured oxides.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Testing of a 15 kA Superconducting Transformer

Here, the manufacturing of superconducting magnets for High Energy Physics (HEP) and Fusion Energy Sciences (FES) applications requires high-current conductors to generate stronger magnetic fields without increasing the inductance of the magnet. Increased inductance is undesirable due to the associated AC losses, which reduce the temperature margin; and the quench protection also becomes complicated. Testing high-current conductors with a direct current (DC) room temperature power supply is unfeasible for two primary reasons: 1) the limited capacity to supply large currents, and 2) the significant heat load losses at the current leads. A superconducting transformer offers a solution to both challenges. A 50-kA superconducting transformer is planned for manufacturing and commissioning at Brookhaven National Laboratory as part of its user facility upgrade. This transformer will facilitate the testing of superconducting cables, conductors, joints, and insert coils under high magnetic field conditions (10 T) and with currents up to 50-kA. To evaluate the manufacturing process and validate the theoretical models, the magnet division has developed and tested a 15-kA prototype transformer. A control loop has been implemented to ensure precise current delivery to the sample. This paper presents the coil design, manufacturing, and experimental results from the cold tests.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Effects of input gradient regularization on neural networks time-series forecasting of thermal power systems

This study proposes using neural networks, specifically gated recurrent unit (GRU), long-short-term memory (LSTM), and transformer networks, to improve control strategies in a 450 MW coal-fired power plant. However, neural networks face issues of becoming overly dependent on just a few variables to make predictions, which negatively impacts control decisions that rely on the model to determine the value of all manipulated variables. The paper introduces regularization techniques, including noise injection and input gradient regularization, during the training phase. Here, the work presents novel contributions in adapting neural networks to control industrial systems and applying regularization techniques from computer vision to industrial process control. Results demonstrate the effectiveness of input gradient regularization in reducing model dependence on subsets of variables, emphasizing the balance between fidelity and controllability. Further exploration is recommended, including the development of recurrent transformers, closed-loop control testing, and a sensitivity analysis on computer models to provide further insight.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

GPU Profiling and Optimizing xRAGE (Final Report)

Our project’s objective is to increase the efficiency of GPU-enabled kernels in xRAGE. To do so, we conduct GPU profiling with NSight Systems on xRAGE tests unsplit_sod_1d and unsplit_sedov_2d to identify bottlenecks and understand the behavior of the GPU during code execution. Next, we analyze these generated GPU profiles to locate the lines of code whose optimization have the most potential for improving runtime. We replicate the structure of the code in smaller test problems that are easier to understand, edit, and run quickly. Within these test problems, we implement two different methods of improving performance: transformation of nested loops into a single MDRangePolicy and hierarchical parallelization using teams of threads. Both methods show speedups in the test code, and after transferring them to xRAGE, they both show up to 30x speedups on various computing platforms. Profiling the edited versions of xRAGE reveals that the GPU successfully executed the bottlenecks with greater efficiency

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

On the Structural Transformation of Ni/BaH 2 During a N 2 -H 2 Chemical Looping Process for Ammonia Synthesis: A Joint In Situ Inelastic Neutron Scattering and First-Principles Simulation Study

The demand for decarbonizing the ammonia industry by using renewable energy has invoked increasing research interests into catalyst development for effective N 2 reduction under mild conditions. Hydride-based materials are among some of the emerging catalysts for ammonia synthesis at ambient pressure and low temperatures (< 673 K). A recent chemical looping process based on Ni/BaH 2 showed the most promise as it can realize ammonia production at a temperature as low as 373 K and under ambient pressure. However, the chemical transformation of the hydride catalyst at the molecular level remains unclear in this process. Here, we report detailed in situ neutron spectroscopy and diffraction investigations along with first-principles simulations on the structural transformation of Ni/BaH 2 during the nitridation and hydrogenation steps in the chemical looping process for ammonia synthesis. It was shown that a ball-milling process of the starting Ni/BaH 2 could significantly decrease the size of BaH 2 and increase the density of defects, thus potentially enhancing the reactivity of the hydride. The evolution from BaH 2 to barium imide (BaNH) was evidenced in the inelastic neutron scattering (INS) and neutron diffraction results during the N 2 reaction step. During the hydrogenation study, in addition to the recovery of BaH 2 , a possible intermediate species, N-deficient barium imide, was also detected. In comparing the N 2 and H 2 reaction steps, the neutron results indicate that the hydrogenation step appears more difficult than the nitridation step, confirming the facile N 2 fixation property of Ni/BaH 2 catalyst in ammonia synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Evaluating Methods for Measuring Grid Frequency in Low-Inertia Power Systems: Preprint

Accurate measurement of grid frequency is a critical component of reliable grid control. Traditionally, methods such as phase locked loops (PLLs) and discrete Fourier transforms (DFTs) have been used in inverters and phasor measurement units (PMUs) to measure frequency. However, as the percentage of inverter-based resources (IBRs) such as solar and wind has increased, these conventional frequency measurement methods are proving unable to guarantee reliable control in some cases. One challenge is measuring frequency during transient events, where there is a disruption in the steady state sinusoidal voltage. During these events, the underlying frequency of the grid may barely change, but measurement methods report a large spike in frequency due to the disrupted waveform. New methods must balance between suppressing spikes in frequency during faults, and providing fast, accurate, measurements in all other grid operation conditions, especially during events with high rate-of-change-of frequency (ROCOF), which are more prevalent in high-IBR power systems. This paper first surveys frequency measurement methods that have been proposed to reduce measurement errors during transient events. Then, both conventional and more novel frequency measurement methods are tested against an IEEE standard and industry recommendations, and their performance is evaluated for events simulated in PSCAD. Results quantify the trade-offs in performance during different grid conditions and lead to suggestions for the most appropriate frequency and ROCOF measurement methods for low inertia grids.

frequency↗
DOE OSTI2021

Molecular dynamics simulation of vacancy and void effects on strain-induced martensitic transformations in Fe-50 at.% Ni model concentrated solid solution alloy

Strain-induced martensitic transformations can improve the strength and ductility of some face centered cubic (FCC) metals and alloys. Irradiation-induced defects such as vacancies, dislocation loops, and voids activate martensitic transformations over a wider range of mechanical loading conditions than in pristine material. Furthermore, the mechanisms underlying irradiation-enabled martensite transformations remain unclear. In this work, we use molecular dynamics simulations to study the effect of vacancies and voids on strain-induced martensitic transformations in a model concentrated solid solution alloy Fe-50 at.% Ni. It has been found that single vacancies have no resolvable effect on the transformation because they reduce the stacking fault energy by a relatively insignificant margin and do so only if the vacancy is located on the stacking fault plane. Voids, however, activate the martensite transformation through shear strain accumulation around the void due to dislocation pileup. The larger the void, the more pronounced this effect.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Mechanisms of Hysteresis and Reversibility across the Voltage-Driven Perovskite–Brownmillerite Transformation in Electrolyte-Gated Ultrathin La 0.5 Sr 0.5 CoO 3−δ

Perovskite cobaltites have emerged as archetypes for electrochemical control of materials properties in electrolyte-gate devices. Voltage-driven redox cycling can be performed between fully oxygenated perovskite and oxygen-vacancy-ordered brownmillerite phases, enabling exceptional modulation of the crystal structure, electronic transport, thermal transport, magnetism, and optical properties. The vast majority of studies, however, have focused heavily on the perovskite and brownmillerite end points. In contrast, here we focus on hysteresis and reversibility across the entire perovskite ↔ brownmillerite topotactic transformation, combining gate-voltage hysteresis loops, minor hysteresis loops, quantitative operando synchrotron X-ray diffraction, and temperature-dependent (magneto)transport, on ion-gel-gated ultrathin (10-unit-cell) epitaxial La 0.5 Sr 0.5 CoO 3-δ films. Further, gate-voltage hysteresis loops combined with operando diffraction reveal a wealth of new mechanistic findings, including asymmetric redox kinetics due to differing oxygen diffusivities in the two phases, nonmonotonic transformation rates due to the first-order nature of the transformation, and limits on reversibility due to first-cycle structural degradation. Minor loops additionally enable the first rational design of an optimal gate-voltage cycle. Combining this knowledge, we demonstrate state-of-the-art nonvolatile cycling of electronic and magnetic properties, encompassing >10 5 transport ON/OFF ratios at room temperature, and reversible metal-insulator-metal and ferromagnet-nonferromagnet-ferromagnet cycling, all at 10-unit-cell thickness with high room-temperature stability. This paves the way for future work to establish the ultimate cycling frequency and endurance of such devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Thermodynamic guiding principles of high-capacity phase transformation materials for splitting H 2 O and CO 2 by thermochemical looping

Here, thermochemical looping splitting of water and carbon dioxide (CO 2 ) with greenhouse-gas-free (GHG-free) energy has the potential to help address the Gt-scale GHG emissions challenge. Reaction thermodynamics largely contributes to the main bottlenecks of cost reduction for thermochemical looping water/CO 2 splitting cycle. Here, we analyze thermodynamic driving forces in such cycles with two-phase ternary ferrites as model systems. We find that cation configurational entropy chiefly determines the change of partial molar entropy with oxygen stoichiometry. In addition, our phase diagram analysis accurately predicts the optimal Fe ratio for maximal water/CO 2 splitting capacity in thermal reduction and in chemical reduction based cycles, underlining the significance of phase boundary positions. With chemical reduction, >10% CO 2 conversion and high oxygen exchange capacity can both be achieved. Furthermore, our reduced Gibbs free energy model illustrates critical thermodynamic factors that influence the water/CO 2 splitting capacity. Our research reveals the thermodynamic driving forces underlying the unconventional high-capacity Fe-poor ferrites, further explained via phase diagrams of Fe–Co–O, Fe–Ni–O and Fe–Mg–O. Future materials improvements can be guided by our reduced Gibbs free energy model.

08 HYDROGEN↗