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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 OSTI2026

Model-based, in-situ, non-destructive qualification and certification of parts made by autonomous additive manufacturing

To address the significant productivity challenges associated with the qualification and certification (Q&C) tasks of additively manufactured (AM) parts, which have traditionally relied on rigorous post‐build inspection and testing, we propose an integrated framework that combines model‐based qualification and certification (MBQ&C) with autonomous additive manufacturing (AAM). MBQ&C employs high‐fidelity predictive models, developed within the Integrated Computational Materials Engineering (ICME) paradigm, to simulate process–structure–property–performance relationships for assessing a part’s fitness for use. Since predictive models are commonly machine learning (ML)-based or reduced-order surrogates of validated physics models, they run efficiently, enabling timely inference. In parallel, the self-driving AAM utilises ML-based adaptive, closed‐loop control strategies to avoid, mitigate, or repair defects and anomalies during fabrication, thereby increasing the likelihood of producing acceptable parts. A key feature of the combined AAM-MBQ&C framework is that predictive models explicitly incorporate defects or anomalies that persist after the build, using instance-specific data captured via in-situ sensing. This customisation enables a build‐specific assessment of fitness for use, rather than relying on nominal or generic parameters. Such individualised evaluation provides a robust basis for Q&C-related acceptance decisions relating to each build. Additionally, the rapid solution capabilities of ML or reduced-order models enable the determination of a part’s suitability for service shortly after build completion. As the framework matures, it has the potential to substantially reduce reliance on conventional point‐design approaches—such as time‐consuming post‐build computed tomography scanning and costly destructive testing. Thus, the AAM-MBQ&C framework represents a transformative, scalable strategy for quality assurance of AM components, as parts produced within a stable, validated, and certified envelope can be certified with reduced testing. Key benefits include: (1) significant gains in Q&C productivity through efficient, model-centric assessment; (2) performance-based classification of defects into critical and non-critical categories; (3) the ability to predict potential deviations in the performance of parts affected by real-time, adaptive process control interventions relative to those produced under a certified process, and (4) the enabling of virtual Q&C for service environments that are difficult, hazardous, or impractical to access or reproduce experimentally. Collectively, these capabilities strengthen the business case for AM, particularly for high‐consequence and mission‐critical applications. Finally, although this work focuses on powder-based AM, the proposed techniques could be extended to AM processes employing alternative feedstock forms.

Gunasegaram, Dayalan↗
DOE OSTI2025

Self-Consistent Relativistic Electron Scattering using the Sherlock Scattering Model for X-ray Diagnostics

We present on a new, self-consistent, arbitrary-temperature Romberg integration scheme for modeling electron scattering in materials in a LANL Lagrangian Shock Hydro (LSH) code. Electron beam-target interactions are fundamental to a wide range of scientific and technological applications. When high-energy electron beams hit their target, they may scatter, deposit energy, or ionize the source. These processes govern the behavior and outcomes in nanotechnology manufacturing, electron microscopy, and modern X-ray diagnostics. Simulating these interactions is essential for interpreting experimental results, predicting material responses, and designing efficient tools and experiments. At Los Alamos, this is done using a LSH code, which is a multi-dimension, multi-material, massively parallel, multi-physics code used to simulate applications from asteroid impacts to electron beam interactions. By effectively and efficiently modeling the way that electrons scatter from the beam we can bolster these simulations and more accurately predict experimental outcomes. The model currently implemented in the LSH of interest is based on work by Papp and does not self-consistently preserve momentum in the slightly relativistic regime; here we adopt a model proposed by Braams and Karney and implement a Romberg integration scheme to compute the diffusion tensor. In this paper we will provide background on the Braams-Karney diffusion tensor as well as the Romberg integration scheme we employed to numerically solve for it. We will show that our integration scheme is accurate in solving for the set of scalar potentials used to re-express the diffusion tensor in differential form, and in solving for the diffusion coefficients in the larger LSH code. By using this diffusion tensor rather than the existing Papp one, and numerically integrating it with a Romberg method, we produce much more accurate, self-consistent results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Generalized Power Flow Model of an Extra High-Power Multi-Terminal HVdc Transmission Grid with Parallel-Connected and Voltage-Stacked Converters

To increase power transfer capacity of high-voltage direct current (HVdc) transmission, a new extra high-power HVdc architecture with multiple standard modular multilevel converters (MMCs) per substation has recently been introduced. This paper proposes a power flow model for a multi-terminal HVdc (MTdc) grid with this innovative substation architecture. The proposed MTdc model can be integrated seamlessly with existing ac-dc power flow algorithms with minimal modifications. The model is applicable to various MTdc grid types and topologies, different numbers of dc buses, dc lines, and MMCs per substation, along with diverse control parameters. In addition, it accurately captures both balanced and unbalanced operations of the MTdc grid. The proposed model is verified using a 5-terminal bipole MTdc grid that spans 4 areas in the Eastern Interconnection system of the USA. The numerical solutions obtained from unified and sequential ac-dc power flow algorithms under different operating conditions closely match the time-domain simulation results in PSCAD, validating the accuracy and versatility of the proposed MTdc power flow model.

Nguyen, Quan H.↗
DOE OSTI2025

CROCUS Dual Polarization Ceilometer Data at Northeastern Illinois University Rooftop

This dataset is from the Department of Energy Office of Science funded project, CROCUS Urban Integrated Field Laboratory (https://crocus-urban.org/). The dual-polarization ceilometer (Vaisala CL61) is an autonomous lidar system operating at 910 nm wavelength, providing valuable measurements for understanding atmospheric boundary layer evolution, air quality, and cloud-aerosol interactions. The CL61 measures the backscattered signal intensity alternating between parallel- and cross-polarization signals. The unique depolarization measurement capability improves discrimination between different particle types, such as liquid droplets, ice crystals, and aerosols. The depolarization is highly dependent on the scatterer shape and orientation (spherical vs non-spherical particles), with the linear depolarization ratio providing a measure of dominant backscatter signal component from atmospheric particles at various heights, essentially allowing discrimination between liquid and solid particles. With its efficient optical system, CL61’s improved signal-to-noise ratio compared to traditional ceilometers allows studying detailed vertical profiles of aerosols and clouds up to 15 km height.Datasets are stored in a netCDF data format, and we we encourage users to make use of the associated toolkits available from Unidata (https://www.unidata.ucar.edu/software/netcdf/), Project Pythia (https://foundations.projectpythia.org/core/data-formats/netcdf-cf.html), and our “Instrument Cookbooks” (https://crocus-urban.github.io/instrument-cookbooks) for more information on how to process the metadata-rich datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Orbit-averaging and deposition accuracy for runaway electron beams in hybrid kinetic-MHD simulations of the runaway plateau

We develop a new procedure that combines the kinetic orbit runaway electron code (KORC) and the NIMROD extended-magnetohydrodynamic code to simulate runaway electrons (REs) in the post-disruption plateau. KORC integrates guiding-center orbits, with a barycentric-based binary search strategy providing initial guesses for the Newton–Raphson logical-to-physical coordinate inversion, ensuring reliable particle-to-mesh mapping in NIMROD, whose fields remain static for the present study. Samples are drawn in accord with experimental parallel current profiles of RE beams during the plateau phase. Deposition in NIMROD is verified through comparison with a Python-based finite-element code that ensures periodicity in the poloidal direction and continuity at the magnetic axis. Accurate representation of near-axis fields requires finer mesh resolution to prevent under- and overshoots in current density from orbit inaccuracies. Yet, at a fixed particle count, increasing mesh resolution amplifies statistical noise in the deposited fields. An orbit-averaging method accumulates partial current deposits over multiple kinetic steps and reduces the statistical noise with little added computational cost. By coupling kinetic routines from KORC directly into the NIMROD codebase, these developments lay essential groundwork for future self-consistent KORC–NIMROD coupling.

Algorithms and data structure↗
DOE OSTI2026

Sub-Doppler Cooling of a Trapped Ion in a Phase-Stable Polarization Gradient

Trapped ions provide a highly controlled platform for quantum sensors, clocks, simulators, and computers, all of which depend on cooling ions close to their motional ground state. Existing methods like Doppler, resolved sideband, and dark resonance cooling balance trade-offs between the final temperature and cooling rate. A traveling polarization gradient has been shown to cool multiple modes quickly and in parallel, but utilizing a stable polarization gradient can achieve lower ion energies, while also allowing tailorable light-matter interactions in the sub-wavelength regime. In this Letter, we demonstrate cooling of a trapped ion below the Doppler limit using a phase-stable polarization gradient created using trap-integrated photonic devices. At an axial frequency of 2⁢𝜋×1.45 MHz we achieve ⟨𝑛⟩=1.56±0.07 in 150 μ⁢s and cooling rates of ∼0.3 quanta/μ⁢s. Here, we examine ion dynamics under different polarization gradient phases, detunings, and intensities, showing reasonable agreement between experimental results and a multilevel model. Cooling is fast and power efficient, with lower average motional Fock state occupation when compared to simulated operation under the corresponding running wave configuration. Our results demonstrate a well-controlled test bed for studying the dynamics of multilevel atomic systems in a phase-stable polarization gradient.

Atom & ion cooling↗
DOE OSTI2024

ORBIT: Oak Ridge Base Foundation Model for Earth System Predictability

Earth system predictability is challenged by the complexity of environmental dynamics and the multitude of variables involved. Current AI foundation models, although advanced by leveraging large and heterogeneous data, are often constrained by their size and data integration, limiting their effectiveness in addressing the full range of Earth system prediction challenges. To overcome these limitations, we introduce the Oak Ridge Base Foundation Model for Earth System Predictability (ORBIT), an advanced vision transformer model that scales up to 113 billion parameters using a novel hybrid tensor-data orthogonal parallelism technique. As the largest model of its kind, ORBIT surpasses the current climate AI foundation model size by a thousandfold. Performance scaling tests conducted on the Frontier supercomputer have demonstrated that ORBIT achieves 684 petaFLOPS to 1.6 exaFLOPS sustained throughput, with scaling efficiency maintained at 41% to 85% across 49,152 AMD GPUs. These breakthroughs establish new advances in AI-driven climate modeling and demonstrate promise to significantly improve the Earth system predictability.

Wang, Xiao↗
DOE OSTI2024

Skipper-in-CMOS: Nondestructive Readout With Subelectron Noise Performance for Pixel Detectors

The Skipper-in-CMOS image sensor integrates the nondestructive readout capability of skipper charge coupled devices (Skipper-CCDs) with the high conversion gain of a pinned photodiode (PPD) in a CMOS imaging process while taking advantage of in-pixel signal processing. This allows both single photon counting as well as high frame rate readout through highly parallel processing. The first results obtained from a ${15} \times {15}~\mu $ m2 pixel cell of a Skipper-in-CMOS sensor fabricated in Tower Semiconductor’s commercial 180-nm CMOS image sensor process are presented. Measurements confirm the expected reduction of the readout noise with the number of samples down to deep subelectron noise of $0.15\text {e}^ - $ , demonstrating the charge transfer operation from the PPD and the single photon counting operation when the sensor is exposed to light. This article also discusses new testing strategies employed for its operation and characterization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Improvements to In-Canal Assay of High Specific Activity 60Co at the ATR

Improvements to the quality of measurements in the assaying of High Specific Activity (HSA) cobalt 60 produced at the Advanced Test Reactor at the Idaho National Laboratory are presented. Such assays are conducted regularly between cycles at the ATR, and due to the radiological safety concerns, they are performed within the ATR canal. A standard ion chamber detector was placed in a collimated assay tube within the canal. Another tube, parallel to the detector, was used to position various cobalt 60 standards and targets. The collimated port between these tubes allows for the targets to be pulled across via a winch system. Previous measurements were performed at discrete 1.5-inch steps using a hand-cranked winch system. Charge was collected and integrated for 10 seconds at each discrete step during a scan. Two substantial improvements to the assay include an electronically controlled, motor-driven winch system and a software controlled continuous charge collection. Combined, these changes improved the quality of measurements as well as streamline the assay process. Further examination of these charge profiles indicated a reasonable amount of photon scattering, or shine, before a line-of-sight is established. This created inaccuracies in the reported activity of the cobalt targets. A series of MCNP-6.3 calculations were performed in an effort to quantify and correct for this shine effect. The results of the calculations and how they were employed to a create shine correction factor for the in-canal cobalt assay at the ATR are presented. The overall bias showed an overestimation of the HSA cobalt 60 activity by around 7-8%.

07 - ISOTOPES AND RADIATION SOURCES↗
DOE OSTI2025

Rapid Commissioning of Large Machine Tools Using Finite Element-Based Correction of Geometric Errors

Large computer numerical control (CNC) machine tools derive their stiffness from monolithic cast iron bases or weldments that are sometimes integral to machine motion systems like box ways or guideways. However, the sheer size of castings and even floor flatness deviations result in dimensional errors in these systems, which manifest as machine motion errors. Typical geometric alignment processes rely on an iterative approach, where measurements are taken to assess alignment (straightness, squareness, and parallelism), followed by adjustment of the machine supports (fixators or leveling pads), which can take weeks even for an experienced operator. Conversely, a novel method is proposed to shorten the correction time by eliminating the trial-and-error process in favor of a more deterministic approach guided by a finite element (FE) method. A feasibility study is conducted on a CNC polymer hybrid machine, with a steel weldment frame, supported by six leveling pads. An FE model of the frame is utilized to obtain recommended leveling pad adjustments, based on measurement of machine errors taken using a laser tracker. After a single adjustment cycle, measurements reveal that geometric errors of the machine tool are reduced from 2.22 mm of flatness deviation to 0.32 mm, achieving an 85.6% reduction. Furthermore, the entire process including measurement, adjustment, and assessment is completed in just 6 h by two operators who are not professional service engineers. In conclusion, this methodology demonstrates feasibility for scaling up, especially to large, high-precision CNC machine tools with bases mounted by fixators, offering the capability for bidirectional adjustment.

42 ENGINEERING↗
DOE OSTI2024

SPARTAN (Scalable Probabilistic Application Reconfigurable Tensor Autonomous Network)

The technical founder of Ludwig Computing Inc has been competitively selected for support by Cyclotron Road, a U.S. Department of Energy (DOE) Advanced Manufacturing Office (AMO) Lab-Embedded Entrepreneurship Program (LEEP) through an approved merit review process. Ludwig Computing Inc, supported by the U.S. Department of Energy's Advanced Manufacturing Office through the Cyclotron Road program, has investigated the advantages of probabilistic computing for real-world compute-intensive applications. This research adds to the understanding of alternative computing paradigms by exploring a unique hardware-software co-design that integrates quantum computing methods with nature-inspired problem-solving techniques. The project's focus on areas such as combinatorial optimization, graph analytics, and machine learning demonstrates the potential for significant advancements in computational efficiency and performance. By harnessing natural randomness to streamline large circuits into fewer devices, Ludwig's approach enables massive parallelism, potentially offering higher throughput, speed, and energy efficiency compared to conventional hardware solutions. This work benefits the public by paving the way for more efficient computing solutions that could address complex real-world problems while potentially reducing energy consumption in data-intensive industries.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

CORE-CM in The Greater Green River and Wind River Basins: Transforming and Advancing a National Coal Asset (Final Report)

The following document summarizes project results from “CORE-CM in the Greater Green River and Wind River Basins: Transforming and Advancing a National Coal Asset”. This project is part of the U.S. Department of Energy’s (“DOE”) National Energy Technology Laboratory’s (“NETL”) Carbon Ore, Rare Earth Elements, and Critical Minerals (CORE-CM) Initiative. This report concludes that the Greater Green River and Wind River Basins (GGRB-WRB) Area-of-Interest (AOI 9) is the ideal region for continued research and development in progressing the broader CORE-CM goals outlined by the DOE. Based upon the extensive analyses of technical, social, and community criteria, this report illustrates that the GGRB-WRB hosts numerous potential CORE-CM feedstocks (both coal- and non-coal based), diverse opportunities for utilizing existing industrial waste streams, ample infrastructure and industry to support new CORE-CM-focused technologies, and a highly motivated, well educated, and adaptable workforce to further develop the regional and national CORE-CM supply chain. Additionally, some potential solutions for technological gaps suggest that the GGRB-WRB's diverse resources can play a significant role in achieving the national goal of critical materials independence. With full community participation, meaningful involvement of regional Tribal Nations, and building upon the stakeholder engagement demonstrated here, the GGRB-WRB region presents a unique opportunity for advancing the CORE-CM Initiative. This project was designed to bring together coal-based communities and stakeholders from across the GGRB-WRB to advance new industries for CORE-CM resources. The University of Wyoming (UWyo) School of Energy Resources (SER) led a project team of experts from the Colorado Geological Survey (CGS), Colorado School of Mines (CSM), Los Alamos National Lab (LANL), and local community colleges. Input from basinal, regional, and national experts bolstered the coalition in order to advance the mission of DOE’s CORE-CM initiative and develop the domestic CORE-CM supply chain. Phase I of this project was designed to address the goal of developing and catalyzing economic growth, job creation, and technology innovation in the GGRB-WRB of Wyoming and Colorado, by increasing the supply of CORE-CM to manufacturers of non-fuel Carbon Based Products (CBP) and products reliant upon CM. The GGRB-WRB CORE-CM project worked toward providing benefit through several avenues of performance and research. • Develop a coalition team to achieve project objectives • Complete detailed assessments, including State-of-the-Art (SOTA) Data acquisition of potential CORE-CM materials across the AOI, and meaningfully contributes to DOE’s CORE-CM goals nationally. • Strategic planning for regional economic growth, job creation, and associated technology innovation around coal materials, including plans to maximize the development of potential CORE-CM resources and technology by creating regional public-private partnerships. • Define regional economic growth potential around existing strengths, energy infrastructure, business and industry, including planning for the leveraging of highly trained workforces, existing and novel coal technologies, and energy infrastructure in development of CORE-CM supply chains. • Develop a preliminary strategic plan for increasing the supply of CORE-CM materials to manufacturers of non-fuel Carbon Based Products (CBP) and products reliant upon CM, focusing on regional strengths that result in an emerging diversified CORE-CM economy. • Assemble a committed network of stakeholders and communities that learn about, accept, and grow new energy technologies within coal regions. Additionally, the project team significantly contributed to the CORE-CM Initiative’s national goals, through cross-regional scoping, collaborating with CORE-CM projects in other AOIs, and including parallel regional project experts. In addition to active inclusion and meaningful engagement and contribution to DOE-led working groups, the project team focused on engaging with regional communities including Tribal Nations, economic development groups, and regional government organizations. The project’s CORE-CM development and commercialization plan identified diverse CORECM feedstocks, potential routes towards integration with existing industries, methods for supply-chain development that leverage existing infrastructure and businesses considering the regional economy, identified entry barriers for incorporating traditional and new technologies in those supply chains, recognized opportunities for public-private partnerships to develop technology innovation centers, identified diverse workforces, and conducted stakeholder outreach and education to build a community of understanding on CORE-CM potential in the GGRB-WRB region. Detailed task descriptions can be found in each chapter.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Tough Errors are no Match (TEAM): Optimizing the Quantum Compiler for Noise Resilience

This project builds toward a comprehensive error-mitigating toolkit that makes quantum programming more robust and adaptive to the noisy, resource-limited nature of today’s quantum hardware. To that end, it integrates established error-mitigation methods — such as zero-noise extrapolation and dynamical decoupling — directly into compiler infrastructures. These techniques will be packaged as modules that can automatically adjust and combine based on performance analysis, enabling compilers to explore large design spaces and produce optimized, low-noise quantum programs with minimal manual intervention. In parallel, this project also explores new approaches to analog quantum programming or quantum simulation, and has developed the programming language SimuQ which treats quantum Hamiltonian evolution as the central object.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Single-atom materials boosting wearable orthogonal uric acid detection

Abstract Uric acid (UA) is a vital biomarker for the diagnosis and management of various health conditions, including cardiovascular diseases, gout, kidney disorders, metabolic syndrome, and wound healing. Despite significant advances in wearable sensor technology, challenges persist in developing wearable sensors that are capable of maintaining high sensitivity, selectivity, and stability. In this study, we present an epidermal sensing platform enhanced with single-atom materials (SAMs) designed for flexible and orthogonal electrochemical detection of UA. We designed and synthesized an SAM with Fe-N 5 active sites to boost the electrochemical sensing signals, integrating it with laser-engraved graphene (LEG) to fabricate a wearable SAM-based UA patch sensor. This design provides superior UA detection performance compared to sensors based on conventional nanomaterials. In addition, we enhanced the detection accuracy and range by using an orthogonal approach that combines direct oxidation through differential pulse voltammetry (DPV) along with parallel biocatalytic amperometric detection. The resulting SAM-based UA orthogonal sensor patch demonstrated exceptional performance in wearable applications through tests measuring sweat UA levels in subjects before and after consuming a purine-rich diet. Graphical Abstract

Ding, Shichao↗
DOE OSTI2024

Adaptive Protection and Validated Models to Enable Deployment of High Penetrations of Solar PV (PV-MOD)

The availability and validation of various PV models in commercial tools differ, with some models not yet thoroughly validated for advanced inverter functionalities and reliable performance under weak system conditions. Many existing models do not fully incorporate new inverter control functions, which can affect system stability. The increasing deployment of solar PV and other inverter-based resources (IBRs), including distributed energy resources (DERs), is influencing the reliable operation of protection schemes in distribution systems and microgrids. Emerging adaptive protection schemes (APS) offer new opportunities for protecting these systems during varying configurations and DER operating conditions, though their demonstration and validation remain limited. Adaptive protection schemes face similar challenges, as they are typically designed for specific configurations. There is a growing need for tools and methodologies to streamline the deployment of adaptive protection for safe and reliable DER integration. The project main objective was to develop and validate high-fidelity generic models of solar PV facilities for stability, protection, EMT, and QSTS analyses. This objective was achieved, and these models can now be integrated into commercial software tools, enabling utilities, vendors, and developers to study high-penetration PV systems more confidently. The project also demonstrated advanced applications of these models, including the design and deployment of adaptive protection schemes in high-penetration field applications and microgrids, supporting grid safety and reliability. Several milestones were reached by the end of the project. A sophisticated inverter test plan was developed, and inverters representative of the North American marketplace were selected. EPRI and NREL tested various inverters, conforming to IEEE standards. Improvements were made to existing generic models of IBR units, IBR plants, and aggregated feeders for various analyses. The first generic electromagnetic transient (EMT) model for a solar PV plant was developed, conforming to IEEE Std 2800™-2022 and validated against laboratory measurements of a 2.2 MVA large-scale battery energy storage system (BESS) inverter. That model was then used to produce reference responses illustrating examples of validated and verified IBR plant models that pass or fail tests for technical minimum capability and performance as specified in the IEEE standard. The developed, tested, and validated generic models can be used for transmission planning, stability assessments, expansion planning, and evaluating potential future IBR interconnection requirements. They can also support interconnection screens and conformity assessments of IBR plants, including solar PV. The project significantly contributed to the ongoing standardization and model-based representation and verification of IBR responses. The project further addressed challenges of common distribution protection schemes with increasing deployment of DER by developing, validating, and demonstrating adaptive protection schemes (APS) that can improve the reliable and safe integration of DER into distribution systems. New APS were designed using improved DER models for three common distribution systems: a radial feeder, a meshed network, and a microgrid. Modeling and hardware-in-the-loop (HIL) testing of the APS were conducted, successfully showing their effectiveness and selectivity. Proof-of-concept field demonstration was achieved for two APS, i.e., one on a radial feeder and another one in a microgrid. Field demonstration could not be achieved for the APS on a meshed network, primarily due apprehension of one utility partner and also due to limited access to the protective algorithms in the network protectors. Guidelines developed from the lessons learned in the project lay out the general process followed in the design, installation, and commissioning of APS for various distribution systems. Distribution utility partners’ apprehension about field demonstration of the new APS were addressed—with varying success—by taking a stepped risk-management approach of modeling of a wide range of sensitivities first, performing in-depth proof-of-concept testing in the laboratory including HIL next, and finally deliberately implementing and commissioning the actual protection equipment and algorithms into parts of—or in parallel operation to—the three real distribution systems. Future work should include pilot projects that further show the acceptable performance of the developed APS before these schemes be rolled out more widely. Inclusion of both utility and original equipment manufacturers (OEMs) in future projects could increase chances of successful field demonstration. Despite challenges in achieving the field demonstration goal of the project for all three APS, the research significantly contributed to the innovation of adaptive protection solutions for scalable and reliable DER integration into distribution systems. This project significantly enhances the understanding of the impact of using appropriate inverter models on distribution and transmission (T&D) systems. By addressing the limitations of existing generic models, the project introduces high-fidelity models for stability, protection, electromagnetic transient (EMT), and quasi-static time series (QSTS) analyses. These models, integrated into commercial software tools, enable utilities, vendors, and developers to confidently study high-penetration PV systems. The project also demonstrates advanced applications, including adaptive protection schemes (APS) for distribution systems and microgrids, ensuring grid safety and reliability. The technical effectiveness and economic feasibility of the methods are evident through the development and validation of sophisticated inverter test plans and the selection of representative inverters. Testing by EPRI and NREL on retail, commercial, and utility-scale inverters, conforming to IEEE standards, underscores the robustness of the models. Improvements to existing generic models for various analyses further enhance their validity and applicability. The project also identifies gaps in common distribution protection schemes and designed new APS using improved DER models, demonstrating their effectiveness through modeling and hardware-in-the-loop (HIL) testing. The project’s benefits to the public are manifold. By advancing the standardization and model-based representation of IBR response, it supports transmission planning, stability assessments, and future IBR interconnection requirements. The generic models can facilitate better communication between transmission planners and developers, supporting expected IBR plant capability and performance. Additionally, the development of APS for radial feeders, meshed networks, and microgrids supports the integration of distributed energy resources (DERs) into distribution systems, enhancing grid reliability and safety. The project’s emphasis on thorough testing and simplicity in design ensures practical and scalable solutions for DER integration.

14 SOLAR ENERGY↗
DOE OSTI2025

Quantum Simulators and Applications on Quantum Framework

Simulating quantum circuits is essential for validating quantum algorithms. However, no single simulator consistently performs best - efficiency depends on circuit structure, entanglement, and depth. In this work, we integrate Qiskit-Aer (state-vector and matrix product state) and QTensor, a tree-tensor-network based simulator, into the Quantum Framework (QFw), a modular platform that supports multiple quantum backends via a unified interface. We also enable distributed quantum approximate optimization algorithm (DQAOA) application compatibility with QFw, allowing sub-problems to be solved in parallel at scale. We then benchmark DQAOA and TFIM (transverse field Ising model) circuits across supported simulators, showing how performance varies significantly with problem type. All simulations are deployed on the Frontier supercomputer using QFw's MPI-based orchestration for distributed, multinode execution. These results underscore the need for simulatoragnostic infrastructure to enable systematic evaluation and highperformance scaling of quantum workloads. QFw provides a practical and extensible path toward reproducible quantum algorithm development across diverse application domains.

Chundury, Srikar [ORNL] (ORCID:0009000183359259)↗
DOE OSTI2024

Testing and Analysis of Grid Forming Inverter Control for Achieving Resilient and Economic Operation of an Islanded Microgrid

This investigation examines the feasibility of operating a battery energy storage system (BESS) in parallel with synchronous generation by using grid forming (GFM) control in order to achieve frequency control objectives while mitigating increases to operating costs in the context of an islanded microgrid. The BESS GFM control system, which is based on conventional droop techniques, is modeled along with the overall microgrid using the Real Time Digital Simulator (RTDS) to allow for integration of genset controller hardware. A series of simulations are performed to test the voltage and frequency regulation capability of the BESS control system when the primary frequency regulating genset is tripped offline. The results of the simulations suggest that the GFM control scheme will successfully maintain frequency and voltage stability, which will enable operation without a back-up genset while not compromising the microgrid resiliency to contingencies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Optimizing Management of Persistent Data Structures in High-Performance Analytics

Large-scale data analytics workflows ingest massive input data into various data structures, including graphs and key-value datastores. These data structures undergo multiple transformations and computations and are typically reused in incremental and iterative analytics workflows. Persisting in-memory views of these data structures enables reusing them beyond the scope of a single program run while avoiding repetitive raw data ingestion overheads. Memory-mapped I/O enables persisting in-memory data structures without data serialization and deserialization overheads. However, memory-mapped I/O lacks the key feature of persisting consistent snapshots of these data structures for incremental ingestion and processing. The obstacles to efficient virtual memory snapshots using memory-mapped I/O include background writebacks outside the application’s control, and the significantly high storage footprint of such snapshots. To address these limitations, we present Privateer, a memory and storage management tool that enables storage-efficient virtual memory snapshotting while also optimizing snapshot I/O performance. Here, we integrated Privateer into Metall, a state-of-the-art persistent memory allocator for C++, and the Lightning Memory-Mapped Database (LMDB), a widely-used key-value datastore in data analytics and machine learning. Privateer optimized application performance by 1.22× when storing data structure snapshots to node-local storage, and up to 16.7× when storing snapshots to a parallel file system. Privateer also optimizes storage efficiency of incremental data structure snapshots by up to 11× using data deduplication and compression.

Computer science↗