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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Energy Storage Impacts in Resilience Hubs and Other Critical Infrastructure: An Assessment Guide for Developers and Practitioners

Battery energy storage systems (BESS) deployed behind the meter at resilience hubs and other critical infrastructure can provide economic and operational value during normal operations—such as lower and more predictable energy costs—as well as resilience and security benefits during power disruptions by maintaining essential services. However, existing evaluation approaches tend to focus narrowly on engineering performance or rely on broad socio-economic frameworks that are not well suited to behind-the-meter storage. As a result, developers, utilities, and funders often lack consistent methods for defining success, quantifying benefits, and comparing outcomes across projects. This report presents a practitioner-oriented impact assessment framework for evaluating behind-the-meter BESS at resilience hubs and critical infrastructure facilities. The framework is organized into five iterative components—developing an action plan, defining project goals, identifying metrics, collecting data and measuring outcomes, and reporting and using results—and includes a structured metric architecture spanning six impact categories. Designed for real-world constraints such as limited staffing and uneven data availability, the framework was developed, applied, and refined through real projects, and is illustrated with case studies across diverse deployment contexts.

Impact Assessment↗
DOE OSTI2026

Control Room of the Future Testbed Workshop – After-Action Report

The U.S. Department of Energy’s Office of Electricity is supporting a one-year, multi-laboratory effort to define the needs and requirements for a Control Room of the Future testbed, or CROFT. The effort responds to increasing grid complexity driven by large new loads, dynamic generation resources, and the growing adoption of advanced technologies and tools, including artificial intelligence (AI) and machine learning (ML). To support safe, secure, and effective grid modernization, CROFT will focus on how emerging technologies and tools can be rigorously evaluated in realistic operational settings, with attention to human-machine interaction, cognitive load, and workforce readiness. The project team includes Argonne National Laboratory, Idaho National Laboratory, National Laboratory of the Rockies, and Pacific Northwest National Laboratory. As part of the scoping effort, the team conducted two industry-focused workshops: one at DTECH on February 5, 2026, informed by prior industry interviews, and a second on May 4, 2026, adjacent to IEEE T&D. These engagements brought together utilities, vendors, consultants, national laboratories, academia, and government stakeholders to identify and prioritize use cases, barriers, validation needs, data-sharing constraints, and near- and longer-term requirements. This feedback will directly inform CROFT’s architecture and research focus areas, ensuring the testbed is grounded in real-world operational needs and designed to evaluate emerging technologies and tools in realistic control-room environments.

artificial intelligence↗
DOE OSTI2026

Port scanner and Testing Suite

This project addresses the challenge of identifying and managing open network ports across physical and virtual hosts. The current form of verifying ports in use required manually searching individual ports - a process that was both time- consuming and a potential bottleneck for deployment timelines. To resolve this, an automated port scanning tool was developed in Python. The tool supports simultaneous multiple port scans. To ensure functionality and long-term maintainability, a comprehensive testing suite was implemented using Python’s unittest framework. Edge cases, including valid port numbers, reversed ranges, and closed ports, were explicitly tested to ensure robust handling of real-world scenarios. The resulting tool reduces the time required to verify port security across a network, supporting both targeted and host checks and broader Classless Inter-Domain Routing (CIDR) -based network scans. This work demonstrates the value of automation and test-driven development in strengthening network security practices, and provides a foundation for future enhancements.

Rivera, Linda [Fermilab]↗
DOE OSTI2025

POWER ELECTRONICS GRID TIED SYSTEM FINAL REPORT

Across the country, electric utilities are grappling with the persistent hurdles of integrating Distributed Energy Resources (DERs). Managing these assets safely and effectively is a complex endeavor, complicated by varying ownership structures, management philosophies, and the diversity of the technologies themselves. Consequently, the industry has seen a proliferation of bespoke system designs, control strategies, and communication frameworks—forcing utilities to spend significant time and resources developing one-off integration solutions. This project addressed these integration hurdles through a scalable demonstration of intelligent devices designed to coordinate and control diverse resources in low-voltage applications. This concept minimized the need for complex integration by transforming the separate DERs into a dispatchable virtual power plant (VPP) with integrated resiliency functions (called a Node). By collaborating with a utility partner, the project focused on developing rapidly implementable use cases that bridged the gap between theoretical control and real-world deployment

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Soil metagenomics umbrella narrative

Implementing accessible, authentic research experiences in introductory courses is challenging, particularly at institutions serving diverse student populations. To address this gap, we developed and deployed a Course-based Undergraduate Research Experience (CURE) focused on plant-microbe interactions in General Biology II at Northeastern Illinois University (NEIU), a minority-serving institution with a diverse student body. Students grew sugar beets (Beta vulgaris), extracted DNA from the rhizoplane, and used the Department of Energy Systems Biology Knowledgebase (KBase) for bioinformatic analysis to compare microbial relative abundance in fertilized versus unfertilized soil. Over five semesters, the CURE engaged 103 students and leveraged the intuitive KBase platform to make complex sequencing data accessible. Pre/post-course survey data revealed significant increases in student self-assessed research skills, including the ability to explain results and determine the types of data to collect. Furthermore, students reported significant gains in confidence related to experimental design and hypothesis development, alongside a strong increase in familiarity with KBase. Informal faculty feedback indicated high student engagement and appreciation for the real-world connections (e.g. food systems, agriculture, and health). This scalable, low-cost model effectively integrates data science tools into the foundational curriculum, demonstrating a potent strategy for boosting research skills and broadening participation in authentic scientific inquiry among diverse undergraduate students.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

The AWAKEN wind farm benchmark, Part 2: Modeling results

Accurately modeling wind farm performance in complex atmospheric flows remains a challenge. This paper presents the modeling results of the American WAKE experimeNt (AWAKEN) wind farm benchmark, a collaborative effort involving 16 research groups from academia and industry within the International Energy Agency Wind Technology Collaboration Programme Task 57. The study evaluates a diverse suite of simulation tools, ranging from fast-running engineering wake models to high-fidelity large-eddy simulations, against a diurnal case study observed during the AWAKEN campaign. The benchmark utilized a three-phase structure to progressively assess model performance as observational data availability increased. Initial blind predictions showed that higher-fidelity models did not uniformly outperform simpler simulation tools. A distinct spatial bias was observed where models struggled to resolve the interplay between a low-level jet, wakes, and terrain-induced flow acceleration. In subsequent phases, leveraging additional measurements for model improvement led to a reduction in mean absolute error across the model ensemble; however, this effect was most pronounced in engineering wake models, where targeted calibration reduced error by up to 40~\%. Overall, the study demonstrates that inflow characterization remains a primary prerequisite for accuracy, particularly for models relying on coarse forcing datasets. While the limited ability to resolve local terrain-flow interactions under single-day conditions represent a recognized constraint, the overall findings on wake modeling and real-world validation still provide valuable guidance for model application and for mitigating this limitation.

Bodini, Nicola↗
DOE OSTI2026

Evaluation of a Reduced-Order Model for IBR Fault Response Representation via OEM Blackbox Models

This paper presents a fully implemented inverter reduced-order-model (ROM) in an EMT simulation (PSCAD) library component for direct user utilization in protection studies. The developed inverter ROM has the following features: Equivalent to a full inverter-based resource (IBR) inverter model with positive- and negative-sequence current formulation and representation. A Python script is developed to fully automate this process, including training data generation, ROM parameter training, updating parameters, and model verification and validation. The ROM is validated using both IEEE 2800-compliant and non-compliant OEM modes in a real-world system, building confidence of its usability by protection engineers.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Thermal Evaluation of CCS and NACS Reference Devices and Adapters

A review of NLR's work in charging system reliability for charging inlets, connectors, and adapters. The review includes a detailed discussion on (a) the development of a reference device for the thermal performance of charging connectors and adapters, (b) evaluation of charging adapters and their thermal warning and shutdown response, (c) implications of side-load from real-world implementations, and (d) strengthening the conformance evaluation for end caps based on field data.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Repowering: The Other Side of the Reliability Coin

Extreme weather, cracked backsheets, severe PID, poorly built modules, and installation flaws - all can compromise a solar plant's health and force repowering long before end of life. With more than 70% of U.S. PV capacity less than seven years old, the fleet is young, but its rapid expansion has introduced new materials and system designs that are still being tested under real-world conditions. As a result, reliability - not economics - is what most often drives repowering decisions. Repowering is frequently assumed to be an economically motivated choice, but our work shows that reliability concerns are the real trigger. Drawing from industry interviews, case studies, and modeling, we highlight the physical, electrical, and policy barriers owners face when deciding whether to repair, repower, or decommission. At the same time, repowering can create opportunities: renewed interconnection periods, improved energy yields, and strategic upgrades to extend system value. We present a quantitative framework using NLR's System Advisor Model (SAM) and PV in Circular Economy (PV ICE) tool to evaluate trade-offs across financial, material, and energy impacts. These findings provide practical guidance for navigating the realities of repowering today and underscore the critical role of reliability in shaping the future performance and sustainability of the PV fleet.

14 SOLAR ENERGY↗
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 OSTI2026

Development of Post-Consumer Textile Waste Degradation Protocol and Related Downstream Transformations: Cooperative Research and Development (Final Report)

Tereform, Inc. (Tereform) is developing molecular deconstruction processes to transform waste materials into chemical building blocks. During the CRADA, Tereform deconstructed real-world post-consumer substrates into chemical monomers, validated their performance on laboratory scales, demonstrated feasibility of the degradation products in downstream transformations, and successfully scaled the reaction to kilogram-scale. These results were used to develop and refine technoeconomic analysis and lifecycle assessments to evaluate the economic feasibility and environmental impacts of the process.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Tandem Photovoltaics Core Program Final Technical Report

The Tandem Photovoltaics Core Program was a multi-year initiative aimed at advancing hybrid tandem solar cell technologies to enhance solar module efficiency beyond the limits of single junction devices. This project focused on the development, testing, and scaling of prototype photovoltaic devices, with the goal of achieving commercial relevance and driving industry adoption. The work was divided into three tasks: 1) Comparative Analysis of Tandem Technologies: This task focused on quantifying energy yield under real-world conditions and assessing economic viability of tandems relative to silicon-based modules. The project's modeling framework incorporated performance data, cost of materials, and manufacturing process impacts to optimize tandem designs 2) Tandem Integration and Prototyping: In this task, we developed innovative tandem designs by combining metal halide perovskite (MHP) top cells and silicon (Si) bottom cells. The project focuses on both mechanical integration and direct deposition techniques to enable compatibility with commercially relevant Si technologies, such as passivated contact or PERC cells. 3) Scale-up and Reliability: This task addressed the challenges of large-area fabrication by developing scalable deposition methods and robust interconnection schemes for tandems. The project looked at different accelerated testing such as thermal cycling, damp heat exposure, and potential induced degradation, to ensure long-term stability of devices in field conditions. Tandem solar cells can greatly increase module efficiency beyond conventional single junction (SJ) devices, which are approaching their theoretical limit. There are many ways to fabricate a tandem cell or module in terms of materials used, configuration, and terminal connection. This SETO core project focused critical factors in enabling tandems to enter the market, including hardware integration, technoeconomic analysis (TEA), and energy yield analysis. We focused on MHP/Si hybrid tandem solar cells and modules as a model system for their versatility in module design comparisons, providing valuable insights for other tandem options. While champion cells with areas <1cm2 are regularly demonstrated by groups around the world, it is significantly more challenging to translate these advances into modules, and fewer institutions and companies are working at the module level. This project addressed questions about module fabrication, testing, and reliability that are hard to answer without actually fabricating prototypes. We also performed analysis and road-mapping activities to understand the potential for a wider variety of tandems, including all-perovskite tandems fabricated in collaboration with the Perovskite PV core program. Detailed technical results from this project are described for each task in Section 7.

14 SOLAR ENERGY↗
DOE OSTI2026

Barriers and Opportunities for Energy Technology Adoption in Juneau, Alaska

This report presents findings from a qualitative study examining barriers and opportunities for air source heat pump (ASHP) and electric vehicle (EV) adoption in Juneau, Alaska, with a particular focus on manufactured and multifamily housing. The analysis draws on community insights from end users and middle actors to better understand how technology adoption unfolds in contexts with distinct logistical, infrastructural, and housing constraints. The report is organized according to key barriers and opportunities identified through stakeholder input, providing a structured understanding of adoption dynamics across technologies and housing types. These insights are intended to inform program design and support more effective electrification strategies tailored to local conditions. The study team employed qualitative methods to capture both in-depth and high-level perspectives on technology adoption. Data collection included: 1) two 2-hour focus groups with a total of five end users and seven middle actors, enabling detailed and structured discussion and 2) ten semistructured interviews with manufactured home owners, multifamily landlords, and one tenant, providing complementary insights across housing contexts. Focus groups captured accounts of shared challenges and opportunities while interviews offered more concise reflections on individual experiences. Together, these methods enabled a more comprehensive understanding of both systemic barriers and lived experiences with ASHPs and EVs. The findings reveal that adoption of electrification technologies is shaped by a combination of economic, logistical, and informational factors that vary across housing types, technology characteristics, user groups, and other demographic factors. Addressing these factors requires tailored strategies that reflect local conditions and user experiences. The insights in this report can provide a foundation for organizations such as AEL&P to refine program design, support more effective outreach, and anticipate shifts in energy demand associated with increased electrification. More broadly, the study highlights the importance of incorporating community perspectives when developing electrification initiatives to ensure they are both practical and responsive to real-world constraints.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Continual Learning for Particle Accelerators

Particle accelerators operate under dynamically changing conditions, which often lead to data distribution drifts. These drifts pose significant challenges for Machine Learning (ML) models, which typically fail to maintain performance when faced with such non-stationary data. In particle accelerators, the primary sources of these data drifts include changes in accelerator settings and non-measured parameters such as machine degradation and environmental factors. Previous research has proposed conditional models to handle multiple beam configurations effectively; however, it is challenging to train the ML models on all possible configuration settings. Additionally, conditional models alone can not address performance degradation caused by drifts due to non-measured factors. These limitations contribute to a significant gap between ML development and its deployment in real-world operational settings. To bridge this gap, in this paper, we identify some of the key areas within particle accelerators where continual learning can help mitigate drift-induced performance degradation. In addition, we present a practical use case where a conditional Auto-Encoder model coupled with memory-based continual learning has been employed to demonstrate stable performance even when underlying data drifts

Rajput, Kishansingh [Thomas Jefferson National Acc↗
DOE OSTI2026

Archi: Agentic Operations at the CMS Experiment

We present Archi, an open-source, end-to-end framework for scientific collaborations that combines the systematic ingestion and organization of heterogeneous data sources with the deployment of configurable, private, and extensible agents that retrieve and reason over them. An instance of Archi has been deployed for the Computing Operations team of the CMS experiment at CERN's LHC since February 2026 as a support agent for technical operators, offering retrieval and analysis capabilities by combining documentation, historical data, and live monitoring systems. We evaluate the system on operator feedback and a question set collected from production usage, graded by human and automated panels. The system proves effective at operational tasks, resolving real-world queries posed by CMS operators. We also observe that locally-hosted, open-weight models perform competitively, enabling fully private management of sensitive data.

Lugato, Pietro [MIT; CERN]↗
DOE OSTI2026

Advancing Mass Timber Buildings: Novel Methods Improve Thermal Assessment and Material Use

For nearly a century, thermal demand calculations for buildings have relied on simplified models developed to match the technical constraints of their era. The first standards, introduced in Germany and Austria in 1929, established climate zones and material conductivity coefficients that, with only incremental updates, still underpin many current assessments. Yet, methods such as Hot box testing, originally designed for lightweight insulation, continue to be applied for mass timber buildings, overlooking thermodynamic characteristics confer real-world advantages. Recent research at Oak Ridge National Laboratory incorporates updated methodologies, aligned with ASHRAE Standard 55 (ASHRAE, 2023) accounting for factors such as thermal inertia, inner surface temperatures, emissivity, solar gains, and dynamic outdoor conditions. These factors better reflect observed heating and cooling loads and highlight opportunities for efficient use of materials in mass timber construction. This work provides a framework for designing comfortable, resilient, and resource-efficient buildings while aligning with performance expectations in energy codes.

Pickett, Robert [International Mass Timber Allianc↗
DOE OSTI2026

Evaluation of a Reduced-Order Model for IBR Fault Response Representation via OEM Blackbox Models: Preprint

Driven by the need to capture the electromagnetic transients of transmission lines, inverter switching behavior, and detailed control systems, electromagnetic transient (EMT) studies have become increasingly important in industry, such as IBR interconnection study and fault study. However, original equipment manufacturer (OEM) inverter models typically include extensive parameters and proprietary settings that are unavailable to protection engineers. This paper introduces a data-driven, reduced-order model (ROM) developed as a PSCAD library component for use in EMT-based fault studies. The ROM replicates key OEM model behaviors without requiring detailed knowledge of control design or parameterization. The accompanying Python automation scripts streamline data generation, parameter fitting, and validation. The ROM's performance is demonstrated through comparison with both IEEE 2800-compliant and non-compliant OEM models in a real-world power system. Relay responses show nearly identical results, while simulation runtime is reduced by an average of 32.8\%, highlighting the ROM's practicality for protection engineers.

14 SOLAR ENERGY↗
DOE OSTI2026

A Real2Sim Digital Twin Pipeline for Photorealistic Robot Simulation: Evaluating VLA Policy Deployment on a Bimanual Mobile Robot

Digital twins that are automatically constructed from robot sensor data offer a promising pathway for scalable Real2Sim and Sim2Real transfer. However, it remains an open question whether photorealistic reconstruction alone is sufficient to support reliable deployment of vision-language-action (VLA) policies. We present a generative-AI-assisted Real2Sim pipeline that generates simulation-ready digital twins from real-world RGB observations with minimal manual intervention. The pipeline uses prompted segmentation to isolate scene components and a generative 3D model to directly produce simulation assets, eliminating the need for traditional multi-view reconstruction or manual 3D modeling.\r\nTo evaluate simulation fidelity, we deploy and compare policies from two VLA models in both the real robot and the reconstructed\r\nsimulation under identical tasks and initial conditions. We compare joint-level action trajectories and analyze how divergence evolves over time in closed-loop execution. Although the reconstructed environments are visually accurate, we observe increasing trajectory divergence during closedloop operation. These results indicate that photorealistic reconstruction alone is insufficient to preserve closed-loop control behavior\r\nin VLA policies, particularly in contact-rich manipulation settings where small perceptual errors compound over time.

97 MATHEMATICS AND COMPUTING↗