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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 217 records · Page 12
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DOE OSTI2024

2024 OES-Environmental 2024 State of the Science Report, Chapter 3: Marine Renewable Energy: Stressor-Receptor Interactions

Determining the potential effects of marine renewable energy (MRE) development on the ocean requires consideration of how each component of a tidal, wave, riverine, or other MRE system might affect marine animals, habitats that support marine communities, or processes that make up essential oceanographic and ecological systems. Researchers around the world have been assessing the potential effects of MRE deployments and operations using a variety of instruments, models, analytical methods, and approaches. The most common approach, and the one followed throughout this report, is the framework of stressor-receptor interactions (Boehlert & Gill 2010), where stressors are the components of an MRE device and associated system that may cause stress, injury, or death to a marine animal, habitat, or ecosystem. The receptors are the species, their habitats, and the oceanographic and ecological processes that support them.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Review of Literature and Utility Commission Proceedings Relevant to Integrated System Planning: Annotated Bibliography Prepared to Support the Washington Utilities and Transportation Commission

In 2024 the Washington State Legislature passed the Decarbonization Act for Large Combination Utilities (Engrossed Substitute House Bill 1589 – the Act). The Act requires a large combination electric and gas utility to conduct integrated system planning supporting electrification and gas system decarbonization, including a reduction in the gas rate base. The utility is required to submit the first integrated system plan (ISP) by January 1, 2027. The requirements are to be developed and adopted by the Washington Utilities and Transportation Commission (UTC) by July 1, 2025. In October 2024 Pacific Northwest National Laboratory (PNNL) and Lawrence Berkeley National Laboratory (LBNL) began providing technical assistance to the UTC to support the ISP rulemaking. PNNL and LBNL have prepared this annotated bibliography of research and reports, and state examples of coordinated gas and electric planning, future of gas, and future of heat proceedings in other U.S. States and one Canadian Province. The items described here have been selected by the authors for their potential relevance to the UTC’s integrated system planning rule discussions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Sustaining the Z Facility (FY24 Progress Report)

Based on planning and reviews conducted in 2020, it is clear today that the Z Facility must be sustained through 2040 or longer. This requires a well-developed and executed maintenance and sustainment effort. Z’s Sustainment Plan outlines the approach that Sandia’s Pulsed Power Sciences Center will pursue to assure that the Z Facility maintains its world class research and development program supporting the NNSA’s Science Based Stockpile Stewardship efforts. In FY24, the Pulsed Power Center at SNL planned and executed many substantial sustainment projects as well as maintenance-driven-sustainment aligned to the Sustainment Plan. These projects are listed in this section with brief descriptions of the work executed.

42 ENGINEERING↗
DOE OSTI2025

Solving the Pulsed-Power Driven Inertial Fusion Energy Standoff Problem (Abbreviated Final Report)

The standoff problem in pulsed-power driven IFE (Inertial Fusion Energy) refers to the problem of electrically connecting a fusion target with the driver in a way that preserves the driver/target interface in the presence of a large fusion energy release (100’s of megajoules to 1000 megajoules). High yield fusion drivers for stockpile stewardship applications have similar concerns, but without the complication of the high repetition rate needed for energy production. All proposed IFE or high yield systems have the challenge of protecting the reactor vessel and driver from the energy release, but pulsed power drivers have the additional challenge of establishing an electrical connection in a way that does not create excessive debris or require costly/massive structures that must be expendable. Fortunately, there are conceptual solutions in the form of very low mass transmission lines, usually in the form of wires or foils, since very little mass is needed to overcome the magnetic forces driving the transmission lines apart or provide a low resistance pathway given the short pulse duration of the driver. Several important aspects of the standoff problem were analyzed in the course of this LDRD project. Conceptual means of introducing the low mass transmission lines into the reactor chamber were proposed, including analysis of methods to retain the power flow gap between the electrodes in the presence of the chamber environment. The energy losses due to ohmic dissipation and magnetic acceleration of the low mass transmission lines were evaluated for candidate driver pulses and different transmission line masses, and the fluence of x-ray and neutron energy on the persistent power flow structures that must survive the pulse of energy were evaluated. Finally, means of rapidly pumping down the chamber were explored as a way to return the system to low pressure following the multi-atmosphere post-pulse pressure rise. The overall conclusion from the analysis is that, while the reactor environment creates stressful conditions for a low mass transmission line standoff system, there are concepts expending 10 kg or less of electrode mass each pulse with the potential to mitigate the stresses and successfully drive fusion targets. Whether such a system could lead to a practical and economical fusion reactor would require extensive research and development beyond the scope of the feasibility study.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Monitoring Plan for the Idaho National Laboratory Remote Handled Low Level Waste Disposal Facility

This monitoring plan for Idaho National Laboratory’s Remote-Handled Low Level Waste Disposal Facility was developed to meet the requirements for monitoring low-level waste disposal facilities according to the U.S. Department of Energy (DOE) Order 435.1, “Radioactive Waste Management,” and the guidance provided in the associated technical standard “Disposal Authorization Statement and Tank Closure Documentation” (DOE-STD-5002-2017). The purpose of this monitoring plan is to document a monitoring strategy that includes (1) compliance monitoring activities to demonstrate compliance with regulatory standards/limits and (2) performance monitoring to build confidence the facility is performing as demonstrated in the facility performance assessment (PA) (DOE-ID 2018a), composite analysis (CA) (DOE ID 2012), and CA addendum (DOE-ID 2018b). The de minimus impact to the aquifer predicted by the PA suggests that aquifer compliance monitoring should be augmented with performance monitoring of the drainage course materials and sedimentary interbeds in the vadose zone beneath the facility to provide a more effective means of identifying performance deviations. The monitoring approach delineated in this document was informed by the systems evaluation of natural and engineered facility features presented in the PA, an assessment of aquifer baseline conditions (INL 2017d), the dose analysis conducted in support of the PA and CA, and monitoring data collected during the first four years of facility operations (baseline monitoring phase) (INL 2023b). This plan provides monitoring locations, sampling frequencies, and sampling methods; recommendations for data evaluation; and a description of the monitoring plan implementation. Collected data will be used to demonstrate facility compliance and to identify conditions that are not consistent with the key assumptions made by the PA and CA.

12 - MGMT OF RADIOACTIVE AND NON-RADIOACTIVE WASTE↗
DOE OSTI2026

Multi-trait multi-environment genomic prediction strategies for Miscanthus sacchariflorus

Genomic selection holds the potential to serve as a strategic tool to enhance the genetic gain of complex traits in Miscanthus breeding programs. The development of improved cultivars requires their assessment for various traits across diverse environments to ensure suitable overall performance. Hence, the multi-trait multi-environment (MTME) genomic prediction (GP) models offer an opportunity to improve selection accuracy. This study aims to evaluate the potential of five GP models: (1) three MTME models including genotype-by-trait-by-environment interaction (G×E×T) and (2) two single-trait multi-environment (STME) models (with and without G×E interaction). A Miscanthus sacchariflorus population comprising 336 genotypes evaluated in three environments and scored for four traits (biomass yield YDY, total culm number TCM, average internode length AIL, and culm node number CNN) was analyzed. The predictive ability of the models was evaluated considering three cross-validation schemes resembling realistic scenarios (CV1: predicting new genotypes, CVP: predicting missing traits in a given environment, and CV2: predicting partially observed genotypes). On average, in all cross-validation schemes compared to the STME the predictive ability of the MTME models was 10% to 70% higher for TCM and AIL. On the other hand, for YDY and CNN, both STME models performed similarly or slightly better (between 5 to 64%) than the MTME models in most environments. While the MTME models were not successful for all traits when compared to their STME counterparts, MTME models improved the prediction of the performance of genotypes that were untested across environments or lacked trait information in a specific environment. Overall, our study suggests that MTME GP models can be implemented in Miscanthus breeding programs to improve the predictive ability of the complex traits, shorten breeding cycles, and accelerate selection decisions.

genomic prediction (GP)↗
DOE OSTI2025

ViBRANT Applied as a Closed Loop Flux and Thermal Surrogate

Surrogate testing platforms provide a means to develop a target aspect of a larger system. Some systems target single aspects while others are more wholistic. ViBRANT (Visual Benign Reactor as Analog for Nuclear Testing) aims to be a wholistic system by representing the primary reactor behaviors through an accessible LED driven reactor core, photodiodes, thermocouples, and high-performance software interfaces being developed to the standards required for actual microreactor deployment such as MARVEL. With the ability to drive control drums enabled with full reactor capability (e.g. speed/angle/torque capability/limits for operation and clutch/spring scram capability), drive ViBRANT’s high fidelity 36 pin hexagon core to represent phenomena via LEDs, and capture the analog response of distributed photodiodes/thermocouples, this paper will show the system’s ability to operate in a closed-loop fashion and do well at matching reactor power/temperature distribution in an accessible reactor surrogate environment.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

From observation to replication: machine-learning-driven quantification and replication of fine-scale fish kinematics and behavior

Long-term quantification of fish behavior is essential for aquatic ecology, wildlife telemetry, and biomechanical device development. However, the observation duration required to obtain reliable behavioral and kinematic metrics remains unclear, and few tools exist to physically reproduce natural swimming motion for controlled experimentation. We address these challenges by developing a generalizable framework that models behavioral reliability (Spearman–Brown reliability index) as a function of observation duration and derives metric-specific monitoring thresholds. Using juvenile white sturgeon (Acipenser transmontanus) as a case study, we demonstrate that the minimum duration needed for reliable estimates varies substantially across kinematic features: to exceed a reliability of 0.8, total distance traveled requires 12 days, average curvature (mm?¹) 15 days, tail-beat frequency (Hz) 8 days, and average speed (body length/s) 17 days. We further bridge digital analysis and physical testing by developing a hardware-in-the-loop simulator that reconstructs machine-learning-derived swimming kinematics with high fidelity (correlation coefficient 0.98–0.99, RMSE 1.22–1.27 mm over a 5-minute segment). This platform enables realistic, repeatable motion stimuli for evaluating aquatic sensing technologies and bio-integrated devices under controlled conditions. Together, these contributions provide a scalable approach for designing long-term behavioral studies and a data-driven connection between ecological observation and robotic experimentation.

Hwang, SungJoo↗
DOE OSTI2024

Dashboard for Marine Energy Site Assessment and Monitoring

The marine energy (ME) industry presently relies upon fragmented site assessment solutions that require high resource expenditure for deployment at each site and do not leverage the wealth of readily available tools and information. A wave energy resource assessment dashboard, currently in development, will substantially improve siting, permitting, operations, and maintenance of ME projects by providing an integrated solution that is a one-stop-shop for a developer’s needs. The Site Energy Assessment and MOnitoring Dashboard (SEAMOD) will be of commercial interest to anyone seeking to deploy an ME project and is easily expandable to include tidal and wind energy site assessments. The integrated dashboard is being developed using state-of-the-art database and cloud computing methods and data-assimilative modeling tools that can be coupled with low-cost, rapidly deployable wave buoys and environmental sensing hardware. The combined software and hardware dashboard will reduce wave energy site characterization and wave climate monitoring costs by more than 60 percent and provide assessments that meet international industry standards. To realize a thriving global ME industry, the physical environment at a potential deployment site must be understood, not only for resource characterization, but also for optimization of device and power conversion performance. SEAMOD directly addresses these needs with a commercially marketable product. SEAMOD is a low-cost solution that provides comprehensive ME resource assessments, baseline environmental monitoring, and offshore characterizations required for successful ME development. The key technical objectives for Phase I were a series of software development goals, which when implemented with monitoring solutions, produced an initial proof-of-concept low-cost wave energy resources dashboard. In Phase II, the development of the prototype SEAMOD continued. The basic framework employed was the development of a revised dashboard and monitoring tool customized for ME applications by focusing on IEC site assessment and method requirements. Development was focused on the integration of full hindcast metocean products to provide hindcast resource characterization and environmental information. The final integrated dashboard provides a low-cost solution that delivers comprehensive, scalable, industry-standard energy resource assessments and offshore characterizations required for successful ME development. The integrated dashboard offers visibility of the most recent site modeling, measurements, and historical data. The application and integration of consensus-based standards for wave energy resource assessment, as determined by the International Electrotechnical Commission (IEC), are crucial for the impact and value of SEAMOD. SEAMOD includes monthly, seasonal, and yearly statistics, as well as the total 30-year record, offering temporal resolution of the IEC parameters to aid potential developers in determining the available wave energy resources in their area of interest.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Nanobody screening and machine learning guided identification of cross-variant anti-SARS-CoV-2 neutralizing heavy-chain only antibodies

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) continues to persist, demonstrating the risks posed by emerging infectious diseases to national security, public health, and the economy. Development of new vaccines and antibodies for emerging viral threats requires substantial resources and time, and traditional development platforms for vaccines and antibodies are often too slow to combat continuously evolving immunological escape variants, reducing their efficacy over time. Previously, we designed a next-generation synthetic humanized nanobody (Nb) phage display library and demonstrated that this library could be used to rapidly identify highly specific and potent neutralizing heavy chain-only antibodies (HCAbs) with prophylactic and therapeutic efficacy in vivo against the original SARS-CoV-2. In this study, we used a combination of high throughput screening and machine learning (ML) models to identify HCAbs with potent efficacy against SARS-CoV-2 viral variants of interest (VOIs) and concern (VOCs). To start, we screened our highly diverse Nb phage display library against several pre-Omicron VOI and VOC receptor binding domains (RBDs) to identify panels of cross-reactive HCAbs. Using HCAb affinity for SARS-CoV-2 VOI and VOCs (pre-Omicron variants) and model features from other published data, we were able to develop a ML model that successfully identified HCAbs with efficacy against Omicron variants, independent of our experimental biopanning workflow. This biopanning informed ML approach reduced the experimental screening burden by 78% to 90% for the Omicron BA.5 and Omicron BA.1 variants, respectively. The combined approach can be applied to other emerging viruses with pandemic potential to rapidly identify effective therapeutic antibodies against emerging variants.

Antibodies↗
DOE OSTI2025

The CHIMERAS project: design framework for the Collisionless HIgh-beta Magnetized Experiment Researching Astrophysical Systems

From the near-Earth solar wind to the intracluster medium of galaxy clusters, collisionless, high-beta, magnetized plasmas pervade our universe. Energy and momentum transport from large-scale fields and flows to small-scale motions of plasma particles is ubiquitous in these systems, but a full picture of the underlying physical mechanisms remains elusive. The transfer is often mediated by a turbulent cascade of Alfvénic fluctuations as well as a variety of kinetic instabilities; these processes tend to be multi-scale and/or multi-dimensional, which makes them difficult to study using spacecraft missions and numerical simulations alone. Meanwhile, existing laboratory devices struggle to produce the collisionless, high ion beta (β i ≳ 1), magnetized plasmas across the range of scales necessary to address these problems. As envisioned in recent community planning documents, it is therefore important to build a next generation laboratory facility to create a β i ≳ 1, collisionless, magnetized plasma in the laboratory for the first time. A working group has been formed and is actively defining the necessary technical requirements to move the facility towards a construction-ready state. Recent progress includes the development of target parameters and diagnostic requirements as well as the identification of a need for source-target device geometry. As the working group is already leading to new synergies across the community, we anticipate a broad community of users funded by a variety of federal agencies (including National Aeronautics and Space Administration, Department of Energy and National Science Foundation) to make copious use of the future facility.

astrophysical plasmas↗
DOE OSTI2025

Risk-informed Graded Approach for Reliability and Performance Assessment of Machine Learning and Artificial Intelligence for Advanced Condition Monitoring Techniques

With the shift away from time-based maintenance and toward condition-based maintenance, and to reduce overall maintenance costs, there has been an upsurge in the usage and development of advanced condition monitoring (ACM) techniques for real-time monitoring of nuclear power plant (NPP) components. ACM is particularly useful in the development of digital twins, which are designed to predict the failure or degradation of plant components. Successful implementation of ACM requires an assessment to inform the development of a risk-informed approach to evaluate the use of ACM to meet Nuclear Regulatory Committee (NRC) regulations for in-service testing (IST) programs. This includes the monitoring and diagnostics of reactor components and systems in current, new, and advanced reactors. A key component in ACM is the usage of machine learning (ML) and artificial intelligence (AI) algorithms that can employ real-time data from instrumentation and sensors to detect and predict reactor component degradations. Such predictive capabilities enable early detection of component degradation so as to help plant personnel plan and execute necessary maintenance. For successful implementation of ML/AI in ACM such that regulatory requirements are met, a risk-informed graded approach is needed to assess the reliability and performance of ML/AI for ACM. The American Society for Mechanical Engineers (ASME) developed their Operations and Maintenance (O&M) Code to provide guidance on safe, reliable O&M of NPPs. The IST section of the O&M Code specifically establishes requirements for IST and examination to gauge operational readiness of components in water-cooled NPPs. This paper presents a state-of-the-art review of how reliability and risk assessment can be integrated with ACM to assess component performance by non-nuclear industries. This is followed by different methodologies and approaches for conducting performance and reliability assessments so as to meet IST requirements for NPP components.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Risk-informed Graded Approach for Reliability and Performance Assessment for Advanced Condition Monitoring Techniques

With the shift away from time-based maintenance and toward condition-based maintenance, and to reduce overall maintenance costs, there has been an upsurge in the usage and development of advanced condition monitoring (ACM) techniques for real-time monitoring of nuclear power plant (NPP) components. ACM is particularly useful in the development of digital twins, which are designed to predict the failure or degradation of plant components. Successful implementation of ACM requires an assessment to inform the development of a risk-informed approach to evaluate the use of ACM to meet Nuclear Regulatory Committee (NRC) regulations for in-service testing (IST) programs. This includes the monitoring and diagnostics of reactor components and systems in current, new, and advanced reactors. A key component in ACM is the usage of machine learning (ML) and artificial intelligence (AI) algorithms that can employ real-time data from instrumentation and sensors to detect and predict reactor component degradations. Such predictive capabilities enable early detection of component degradation so as to help plant personnel plan and execute necessary maintenance. For successful implementation of ML/AI in ACM such that regulatory requirements are met, a risk-informed graded approach is needed to assess the reliability and performance of ML/AI for ACM. The American Society for Mechanical Engineers (ASME) developed their Operations and Maintenance (O&M) Code to provide guidance on safe, reliable O&M of NPPs. The IST section of the O&M Code specifically establishes requirements for IST and examination to gauge operational readiness of components in water-cooled NPPs. This paper presents a state-of-the-art review of how reliability and risk assessment can be integrated with ACM to assess component performance by non-nuclear industries. This is followed by different methodologies and approaches for conducting performance and reliability assessments so as to meet IST requirements for NPP components.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

2023 Annual Report: Laboratory Directed Research & Development Program Activities

Each year, Brookhaven National Laboratory (BNL) is required to provide a report of its completed Laboratory Directed Research and Development Program (LDRD) projects to the Department of Energy (DOE) Office of Scientific and Technical Information in accordance with DOE Order 413.2C Chg1 (MinChg) dated August 2, 2018. This summary report provides an overview of all the LDRD projects funded at Brookhaven that concluded in FY 2023 in satisfaction of that requirement.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Standardized Protocol for Real-Time APIs as Required by Title 23 CFR 680.116(c)

Improving the ability of drivers to easily locate working and available chargers is key to improving the public charging experience. Electric vehicle charging providers who are recipients of federal funds through the National Electric Vehicle Infrastructure (NEVI) Formula Program, Charging and Fueling Infrastructure (CFI) Discretionary Grant Program, and other funding programs as identified under Title 23 of the U.S. Code must deploy and maintain an application programming interface (API) to access information about charging stations they operate.1 This includes information about individual charging ports, pricing, and availability in accordance with the Federal Highway Administration’s National Electric Vehicle Infrastructure Standards and Requirements, 23 CFR 680.116(c), herein referred to as the minimum standards (Federal Highway Administration 2023). Specifically outlined in the minimum standards, states and other designated recipients are required to ensure that charging station information including location, connector type, power level, real-time status, and real-time price to charge are available free of charge to third-party software developers through an API. These requirements are intended to enable effective communication with consumers about available charging stations and help consumers make informed decisions about trip planning, including when and where to charge. This document provides a standardized protocol for how to structure data, data update frequency, and practices for making the data required to be shared via API usable for improving public transparency and the customer experience. These are recommendations only and do not modify the Federal Highway Administration’s minimum standards in any way.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Securing Solar for the Grid (S2G) (Final Project Report) [Slides]

This is the final technical report for the SETO-funded project Securing Solar for the Grid (S2G) from FY22-24. The project scope included development and dissemination of standards' requirements, best practices, equipment testing procedures, assessment tools, as well as education and training materials for cyber defense, posture and maturity tailored to solar technologies. The outcomes for this work include: co-led the development of cybersecurity certification standard (UL2941), co-led the development of cybersecurity guide (IEEE1547.3), development of recommendations for supply chain cybersecurity, and development of cybersecurity risk profiles and recommendations for DERMS.

14 SOLAR ENERGY↗
DOE OSTI2024

A Biochar Classification System and Associated Test Methods

In this chapter, a biochar classification system related to its use as soil amendment is proposed. This document builds upon previous work: “Standardized product definition and product testing guidelines for biochar that is used in soil” (IBI, 2015) (aka IBI Biochar Standards) and “Guidelines for biochar production for a sustainable production of biochar: European Biochar Certificate” (EBC, 2012-2022) (aka EBC Biochar Standards). It should be noted that the EBC guidelines constitute the basis for biochar certification through the independent government accredited inspection agency, Bio.Inspecta AG. The present document constrains its scope to materials with properties that satisfy the criteria for biochar as defined by either the IBI Biochar Standards or the EBC Standards (Annex I), as required by the current methodologies developed for accounting carbon credits associated with the biochar use in the voluntary market (e.g., Verra, Puro.Earth). The classification system envisions enabling stakeholders and commercial entities to (i) identify the most suitable biochar to fulfil the requirements for a particular soil and/or land-use, (ii) distinguish the application of biochar for specific niches (e.g., soilless agriculture), and (iii) assess the climate-impact value based on biochar properties, production efficiency, and alternative feedstock uses. It is based on the best current knowledge and will need to be improved as new data and knowledge become available in the scientific literature.

biochar, climate change impacts, soil amendment, c↗