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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

From natural language to control signals: a conceptual framework for semantic channel finding in complex experimental infrastructure

Modern experimental platforms such as particle accelerators, fusion devices, telescopes, and industrial process control systems expose tens to hundreds of thousands of control and diagnostic channels, accumulated over decades of hardware evolution. Operators and AI systems alike depend on informal expert knowledge, inconsistent naming conventions, and scattered documentation to locate the signals required for monitoring, troubleshooting, and automated control, creating a persistent bottleneck for reliability, scalability, and emerging language-model-driven interfaces. We formalize semantic channel finding, the task of mapping natural-language intent to concrete control-system signals, as a general problem in complex experimental infrastructure, and introduce a four-paradigm conceptual framework to guide architecture selection based on facility-specific data regimes. The paradigms span (i) direct in-context lookup over small, curated channel dictionaries, (ii) constrained hierarchical navigation through structured trees, (iii) interactive agent exploration using iterative reasoning and tool-based database queries, and (iv) ontology-grounded semantic search that decouples channel meaning from facility-specific naming conventions. We demonstrate the practical feasibility of each paradigm through proof-of-concept implementations at four operational facilities spanning two orders of magnitude in scale: from compact free-electron lasers to large synchrotron light sources, operating under diverse control-system architectures ranging from clean hierarchical naming schemes to legacy environments with decades of heterogeneous conventions. Where evaluated against expert-curated operational queries, these instantiations achieve 90%–97% accuracy, validating the framework’s applicability across real-world deployment scenarios. To accelerate adoption across the broader scientific and industrial control-system community, we release open-source, plug-and-play implementations of all three interactive paradigms-direct lookup, hierarchical navigation, and middle-layer exploration-within the Osprey framework, together with tools for channel database generation, interactive testing, and minimal-configuration deployment. This work establishes semantic channel finding as a foundational capability for human-centric and agentic AI interfaces at large-scale facilities, providing both a systematic framework for architecture design and practical resources to enable adoption without building custom infrastructure from scratch.

channel finding↗
DOE OSTI2025

Wind Supply Chain Security: Hardware Enumeration and Analysis

This project, undertaken by Idaho National Laboratory (INL) for the Department of Energy (DOE) Wind Energy Technologies Office (WETO), focused on the enumeration and analysis of six key devices important to wind technologies. The devices analyzed included Beckhoff Bus Terminal Controllers (BK1120 and BC9000), a Beckhoff Economy Built-in Panel PC (CP6231), an N-Tron Managed Industrial Ethernet Switch (711FX3), a Bachmann M1 Gateway, and a Bachmann Smart Power Plant Controller. Device selection was driven by availability and budget constraints, with several components sourced from existing wind farms and others procured through a co-agreement with another WETO-funded project. The project's primary objective was to create a hardware bill of materials (HBOM) for each device, identifying and documenting all components to assess potential security and supply chain risks. A detailed analysis revealed over 750 unique components across the six devices, with 80% successfully identified and accompanied by datasheets. Notably, Texas Instruments emerged as the leading supplier, providing over 16% of the components, followed by ON Semiconductor at 11.3%, Analog Devices at 5.3%, and Renesas Electronics Corp at 4.1%. Other notable vendors included Toshiba Corporation, iC-Haus Corporation, Atmel, Vishay, and STMicroelectronics. The enumeration process involved thorough documentation of each component, including its designation, quantity, identifiers, pin package, description, vendor, model, and country of origin. This process provided valuable insights into the complexity and diversity of the electronic systems within these wind devices. It also highlighted the distinct separation of components between vendors, suggesting a trend of vendor-specific component usage. Key findings from the project emphasized the importance of broadening the scope of vendor analysis in future research to gain a comprehensive understanding of component distribution and commonality. The identification of vendor-specific component usage patterns offers new avenues for research and underscores the significance of continued investigation in this field. Overall, this project provides critical insights into the component composition of wind devices, aiding in the development of improved supply chain management and component sourcing strategies. The results contribute valuable knowledge to the wind technology sector, laying the groundwork for enhanced security and resilience in wind energy systems.

17 - WIND ENERGY↗
DOE OSTI2024

Toward Multiscale, Multimaterial 3D Printing

Biological materials and organisms possess the fundamental ability to self-organize, through which different components are assembled from the molecular level up to hierarchical structures with superior mechanical properties and multifunctionalities. These complex composites inspire material scientists to design new engineered materials by integrating multiple ingredients and structures over a wide range. Additive manufacturing, also known as 3D printing, has advantages with respect to fabricating multiscale and multi-material structures. The need for multifunctional materials is driving 3D printing techniques toward arbitrary 3D architectures with the next level of complexity. In this paper, the aim is to highlight key features of those 3D printing techniques that can produce either multiscale or multimaterial structures, including innovations in printing methods, materials processing approaches, and hardware improvements. Several issues and challenges related to current methods are discussed. Ultimately, the authors also provide their perspective on how to realize the combination of multiscale and multimaterial capabilities in 3D printing processes and future directions based on emerging research.

36 MATERIALS SCIENCE↗
DOE OSTI2026

From Cell to System: Accelerated hpc Simulations of BESS Aging under Frequency Regulation and Arbitrage use cases

Lithium-ion battery energy storage systems (BESS) packs have emerged as a leading solution for grid-scale energy storage, enhancing resiliency and balancing load fluctuations. Yet, experimental characterization of large-format LIB packs-particularly to assess performance and degradation over hundreds of cycles - demands substantial hardware investment and multi-year testing campaigns. In this work, we couple a hierarchical, physics-based modeling framework agnostic to electrode chemistries with high-performance computing to accelerate systems level evaluation by upto two orders of magnitude. Building on the open-source liionpack platform, we implement cell, module, and pack-scale electrochemical models enriched with mechanistic aging mechanisms and deploy them on an HPC cluster to simulate 150−200kWh systems over 500 - 1,000 cycles with in days. We subject these virtual B ESS to both constant-current cycling and realistic grid service profiles spanning frequency regulation, ramp-rate support, and energy arbitrage-and quantify the resulting degradation patterns. Our results reveal that localized cell aging can induce substantial nonuniformity at module and pack levels, with service-specific cycling protocols driving distinct aging modes. This rapid, multiscale modeling approach provides a powerful design-space exploration tool for optimizing electrical architecture, control strategies, and operational schedules to prolong pack lifetime and lower total cost of ownership.

Ayalasomayajula, Surya [ORNL] (ORCID:0009000860788↗
DOE OSTI2021

Autonomous experimentation systems for materials development: A community perspective

Solutions to many of the world's problems depend upon materials research and development. However, advanced materials can take decades to discover and decades more to fully deploy. Humans and robots have begun to partner to advance science and technology orders of magnitude faster than humans do today through the development and exploitation of closed-loop, autonomous experimentation systems. This review discusses the specific challenges and opportunities related to materials discovery and development that will emerge from this new paradigm. Our perspective incorporates input from stakeholders in academia, industry, government laboratories, and funding agencies. We outline the current status, barriers, and needed investments, culminating with a vision for the path forward. We intend the article to spark interest in this emerging research area and to motivate potential practitioners by illustrating early successes. We also aspire to encourage a creative reimagining of the next generation of materials science infrastructure. To this end, we frame future investments in materials science and technology, hardware and software infrastructure, artificial intelligence and autonomy methods, and critical workforce development for autonomous research.

36 MATERIALS SCIENCE↗
DOE OSTI2021

SYMBIOSYS: A Methodology for Performance Analysis of Composable HPC Data Services

Microservices are a powerful new way of building, customizing, and deploying distributed services owing to their flexibility and maintainability. Several large-scale distributed platforms have emerged to serve the growing needs of data-centric workloads and services in commercial computing. Concurrently, high-performance computing (HPC) systems and software are rapidly evolving to meet the demands of diversified applications and heterogeneity. The interplay of hardware factors, software configuration parameters, and the flexibility offered with a microservice architecture makes it nontrivial to estimate the optimal service instantiation for a given application workload. Further, this problem is exacerbated when considering that these services operate in a dynamic and heterogeneous HPC environment. An optimally integrated service can be vastly more performant than a haphazardly integrated one. Existing performance tools for HPC either fail to understand the request-response model of communication inherent to microservices or they operate within a narrow scope, limiting the insight that can be gleaned from employing them in isolation. We propose a methodology for integrated performance analysis of HPC microservices frameworks and applications called SYMBIOSYS. We describe its design and implementation within the context of the Mochi framework. This integration is achieved by combining distributed callpath profiling and tracing with a performance data exchange strategy that collects fine-grained, low-level metrics from the RPC communication library and network layers. The result is a portable, low-overhead performance analysis setup that provides a holistic profile of the dependencies among microservices and how they interact with the Mochi RPC software stack. Using HEPnOS, a production-quality Mochi data service, we demonstrate the low-overhead operation of SYMBIOSYS at scale and use it to identify the root causes of poorly performing service configurations.

microservices↗
DOE OSTI2020

Islanding Detection in Rural Distribution Systems

This paper summarizes the literature on detection of islanding resulting from distributed generating capabilities in a power distribution system, with emphasis on the rural distribution systems. It is important to understand the legacy technology and equipment in the rural distribution electrical environment due to the growth of power electronics and the potential for adding the new generations of intelligent sensors. The survey identified four areas needing further research: 1. Robustness in the presence of distribution grid disturbances; 2. the future role of artificial intelligence in the islanding application; 3. more realistic standard tests for the emerging electrical environment; 4. smarter sensors. In addition, this paper presents a synchro-phasor-based islanding detection approach based on a wireless sensor network developed by the University of Texas at Austin. Initial test results in a control hardware-in-the-loop (CHIL) simulation environment suggest the effectiveness of the developed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

GPU-friendly surface model for Monte-Carlo detector simulations

The demands for Monte-Carlo simulation are drastically increasing with the Large Hadron Collider’s high-luminosity upgrade, and are expected to exceed the currently available compute resources. At the same time, modern high-performance computing has adopted powerful hardware accelerators, particularly GPUs. The AdePT and Celeritas projects aim to address the demanding computational needs by leveraging these heterogeneous computing architectures. While both have successfully ported realistic detector simulations to GPUs using the VecGeom library, the complexity of geometry modeling emerged as a bottleneck. Thread divergence and high register usage were degrading the GPU performance. Therefore, a new, GPU-friendly surface-based model has been introduced in the VecGeom library that decomposes the divergent code of the 3D primitive solids into simpler and more balanced surface algorithms. In this work, we present the latest developments, focusing on the additions required to efficiently model complex setups like the CMS Phase-2 geometry. This includes memory reduction techniques, and adding accelerating structures for faster traversal.

Diederichs, Severin [CERN]↗
DOE OSTI2020

AWB-GCN: A Graph Convolutional Network Accelerator with Runtime Workload Rebalancing

The recent development of deep learning has been mostly focusing on Euclidean data, such as images, videos, audios, etc. However, most real-world information and relation are often expressed as graphs. To efficiently learn from graph data, graph convolutional networks (GCNs) emerge as a promising approach, showing advantages in several practical applications such as social network analysis, knowledge discovery, 3D modeling, motion capturing, etc. Real-world graphs are usually extremely large and imbalanced, posting significant performance demand and design challenges on the hardware dedicated for GCN inference. In this paper, we propose an architecture design called UW-GCN to accelerate graph convolutional network inference. To tackle the major performance bottleneck from workload imbalance, we propose dynamic neighborhood stealing and remote chunk shuffling techniques, relying on hardware flexibility to achieve hardware auto-tuning under negligible area or delay overhead. Specifically, UW-GCN is able to smartly profile the sparse graph pattern while continuously adjusting the workload distribution via routing reconfiguration among parallel processing elements (PEs). The ideal configuration is then reused in the remaining iterations. To the best of our knowledge, this is the first accelerator design particularly for GCN and the first work relying on hardware auto-tuning, which is normally based on software, to achieve near-optimal workload balance in processing sparse structures.

Geng, Tong↗
DOE OSTI2022

Temperature Controlled Glass Additive Manufacturing

Glass additive manufacturing (AM) is an emerging technology with a wide range of applications in chemistry, biology, optical science, and engineering. A custom laser-based glass 3D printer was developed by a group of engineers at Los Alamos National Laboratory (LANL) and is being optimized to produce hardware for chemical processing equipment, microfluidic systems, as well as optical elements. AM glass using a filament deposition modeling (FDM) approach allows for generation of parts with high optical quality. The quality of the glass can be affected by the generation of defects such as bubbles and vaporization which affect the optical quality of the glass. The defects can also affect the mechanical performance of the glass and lead to sample cracking.

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

Scoping Study for Fast Flux Testing in the Advanced Test Reactor

The value of fast spectrum reactors remains prominent in the nuclear technology portfolio. The performance of these reactors can be maximized with advancements in nuclear fuel technologies, but development of these technologies is currently held back by lack of fast spectrum test reactors available to the United States. Spectral modification of experiment positions in the thermal spectrum Advanced Test Reactor (ATR) has long been used to support fast reactor fuel development, but these methods have not been progressed to their full potential. This study investigated the use of concentric rings of aluminum-clad fuel plates in ATR flux traps and thermal neutron absorbing filters to increase fast neutron flux on test specimens. This concept was termed the Boosted Energy Advanced Spectrum Test (BEAST). This approach will enable irradiation of advanced fuel designs in prototypic-length fuel pins and representative flux environment to support post irradiation exams, enable transient testing, and produce the type of data that will permit lead test assembly irradiations in true Sodium Fast Reactors (SFRs) when they become available. Neutronic predictions were performed to investigate BEAST design options and thermal hydraulic models were produced to ensure feasibility of BEAST. Two versions were considered based on the geometric limitations of ATR’s small and large flux traps. The small version was found to be preferable due to slightly higher fast flux and fast-to-thermal neutron ratio. Perhaps more influentially, the small flux trap option was also preferred to avoid conflict with ongoing very high temperature reactor fuel irradiation programs in ATR’s large northeast flux trap. The small flux trap option provided less than half the test volume of the large version, but still had adequate volume for seven SFR pins in cross section which could be stacked two-high in ATR’s 1.2m long core to accommodate up to 14 EBR-II size pins. The preference for the small flux trap configuration should be revisited if additional collaborative test programs emerge with the need to irradiate a significant volume of additional specimens. Calculations were performed regarding a lithium deuteride ring to convert thermal neutrons into 14 MeV fusion neutrons. At the time this report was written these calculations were partially complete and it remains to be seen whether the concept would be worth including in BEAST. Given the preference for the small flux trap option, which does not afford enough room for the 14 MeV ring, it was concluded to defer future work on the lithium deuteride ring. This decision could be revisited if fusion material research programs emerge for collaborative testing in BEAST. A cadmium-lined specimen holder design was found to be adequate in filtering thermal neutrons and preferred over other neutron absorbers based on past experience with cadmium baskets. It was acknowledged that cadmium-bearing hardware would become depleted and need to be replaced occasionally, which appeared feasible from a mechanical design perspective. Neutronic studies investigated different enrichment levels in the booster fuel using uranium-molybdenum alloy dispersion fuel which has performed well in past ATR irradiations. Both options were able to drive fuel pins to SFR-like fission heating rates. The high enriched booster fuel option outperformed the low enriched option by ~20% on key metrics including fast flux and fast-to-thermal ratio, but the low enriched option was favored in order to broaden options for potential fuel suppliers. The preferred BEAST design options including cadmium filter with low enriched booster fuel in the small flux trap configuration was predicted to achieve 6.2E14 n/cm2sec fast flux (>0.1 MeV) with a fast-to-thermal ratio of 44.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

High-fidelity dimer excitations using quantum hardware

The quantum simulation of entangled spin systems can play a central role in quantum magnetic materials discovery. Additionally, the simulation of spectroscopic signatures, such as the dynamical structure factor accessed in inelastic neutron scattering (INS), necessitates a long timescale for circuit evolution. This is because the energy resolution is directly related to the time over which the circuit could be meaningfully evolved. However, canonical Trotterization requires deep circuits precluding such long-time evolution—even for a small number of qubits. Here, in this study, we demonstrate “direct” resource efficient fast-forwarding (REFF) measurements with short-depth circuits that can be used to capture longer time dynamics of spin Hamiltonians. We showcase the results of the dynamics of a quantum spin dimer, the basic quantum unit of emergent many-body spin systems, whose density of states we simulate accurately. The long temporal evolution and measurement of the two-spin correlation functions enable the calculation of the dynamical structure factor S⁡(Q = 0, ω) measured in the neutron scattering cross-section. We exhibit the clarity of the triplet gap and the triplet splitting of the quantum dimer with class-leading fidelity that enables comparison to experimental neutron data. Our results on current circuit hardware outline an important workflow to predict and benchmark against the outputs of INS experiments of quantum magnets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Highly-scalable GPU-accelerated compressible reacting flow solver for modeling high-speed flows

Emerging supercomputing systems utilize a combination of central processing units (CPUs) and graphics processing units (GPUs) in an effort to reach exascale capabilities while minimizing the energy footprint of operating such systems. Such heterogeneous machines introduce new challenges for fluids solvers because the hardware architecture and operation of a GPU are fundamentally different from conventional CPUs. In this work, a general approach for efficient implementation of finite-volume based reacting flow solvers on such heterogeneous systems is presented. Three main challenges, namely, data access pattern, thread divergence, and thread safety, are addressed. Since compressible reacting flows require special methods to deal with chemical reactions, hyperbolic and nonlinear convection terms, and the presence of turbulence, specific algorithms that ensure GPU-based efficiency are developed. The approach is demonstrated on the widely available OpenFOAM open source software by modifying core algorithms for GPU accessibility. The scalability of the resulting solver, is demonstrated using practical test cases, including flow through a scramjet engine and the dynamics of a rotating detonation engine. Here, the solver provides near-ideal scaleup on a large number of GPUs (>3000), and extremely efficient use of the GPUs, with throughput nearly a constant even when processing a large number of control volumes.

42 ENGINEERING↗
DOE OSTI2026

Study the Protection Improvements for a Weak Grid Area With High IBRs

NLR is collaborating with Florida Power & Light (FPL) and GE to investigate power system stability and protection reliability challenges in a weak-grid region with high penetration of inverter-based resources (IBRs). This presentation will primarily focus on the protection aspects of the study. We will share key insights from this real-world project, including best practices for developing high-fidelity fault study models, establishing a controller-hardware-in-the-loop (CHIL) platform for testing physical relays, identifying system-level protection challenges, and designing enhanced protection schemes to address those issues. Through this discussion, the audience will gain practical understanding of protection studies in IBR-dominated systems, the emerging challenges associated with reduced fault current and altered transient behavior, and effective mitigation strategies. In particular, we will highlight the critical importance of IBR compliance with IEEE 2800-2022 to ensure dependable and secure protection relay operation in modern transmission systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

ADVERT: An Asynchronous Runtime for Fine-Grained Network Systems

The Data Vortex Network, a novel fine-grained high-radix interconnect, provides the performance and injection rates required by the fine-grained, unpredictable communication patterns of irregular applications. This paper presents ADVERT, an asynchronous runtime system that provides performance and productivity for the fine-grained Data Vortex Network. ADVERT integrates a lightweight memory manager (DVMem) for the user accessible SRAM integrated in the network interface, and a communication library (DVComm) that implements active messaging primitives (remote execution, and, based on this, get and put routines). ADVERT hides the complexity of controlling all the network hardware features through the low-level Data Vortex programming interface, while providing comparable performance. We discuss ADVERT's design and present an analysis of three exemplar irregular kernels (Triangle Count, Page Rank, and GUPS). ADVERT can provide the communication substrate required to build emerging higher level asynchronous many tasking runtimes and partitioned global address space libraries on top of the Data Vortex Network.

Friese, Ryan D.↗
DOE OSTI2026

Advanced Research on Integrated Energy Systems Cyber Range

As digital technologies expand to meet the needs of a more autonomous, interconnected, and advanced power system, new cybersecurity complexities and vulnerabilities arise. The ARIES Cyber Range enables the energy sector to evaluate these evolutions and validate cybersecurity solutions without impacting live systems. Combining power grid-scale hardware with emulation and simulation approaches, the ARIES Cyber Range can faithfully replicate modern energy systems - from grid physics to communication networks, and everything in between - with real-world fidelity. At NLR, researchers and partners are answering complex power system cybersecurity questions, examining emerging threats to the electric sector, and de risking new security technologies, all at a mission-relevant speed that keeps pace with rapidly evolving systems and hazards.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Measurement-induced entanglement and teleportation on a noisy quantum processor

Measurement has a special role in quantum theory: by collapsing the wavefunction, it can enable phenomena such as teleportation and thereby alter the ‘arrow of time’ that constrains unitary evolution. When integrated in many-body dynamics, measurements can lead to emergent patterns of quantum information in space–time that go beyond the established paradigms for characterizing phases, either in or out of equilibrium. For present-day noisy intermediate-scale quantum (NISQ) processors, the experimental realization of such physics can be problematic because of hardware limitations and the stochastic nature of quantum measurement. Here we address these experimental challenges and study measurement-induced quantum information phases on up to 70 superconducting qubits. By leveraging the interchangeability of space and time, we use a duality mapping to avoid mid-circuit measurement and access different manifestations of the underlying phases, from entanglement scaling to measurement-induced teleportation. We obtain finite-sized signatures of a phase transition with a decoding protocol that correlates the experimental measurement with classical simulation data. The phases display remarkably different sensitivity to noise, and we use this disparity to turn an inherent hardware limitation into a useful diagnostic. Our work demonstrates an approach to realizing measurement-induced physics at scales that are at the limits of current NISQ processors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

SRF Thin Films: Not just for Cavities

Recent years have seen renewed interest and activities in developing SRF cavity materials based on thin film technologies. In this framework, considerable progress has been achieved in the development of high quality films and layered structures along with associated deposition techniques such as ECR, HiPIMS, and ALD. Beyond cavity applications, the developments in SRF thin film technologies find a variety of applications in the fields of superconducting metamaterials, electronics, sensors and quantum devices. High quality Nb films with high RRR open the way for enhanced coherence times for quantum qbits. Other SRF thin films such as NbTiN are developed for superconducting backend processes for future generations of computing hardware and radiation-hard sensors for nuclear and high-energy physics. The unifying theme across these technologies is that the same physics and material properties such as extreme low loss, stability, and manufacturability are required. This talk will present an overview of the emerging applications of SRF films and structures beyond accelerator cavities.

Valente-Feliciano, A.-M.↗