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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

FY 2025 Multidimensional Data Correlation Platform: Unified Software Architecture for Advanced Materials and Manufacturing Technologies Data Management and Processing

The Advanced Materials and Manufacturing Technologies (AMMT) program continues to advance a data-driven approach to demonstrate the utility of additive manufacturing for fabricating components for nuclear applications. A key scientific goal is to leverage data to better understand manufacturing outcomes and thereby improve the performance, reliability, and lifespan of nuclear components. Ultimately, this effort supports the development of standards for certification and qualification of additively manufactured components, enabling broader industry adoption. In support of this objective, the AMMT program is building and deploying a data management platform to record, index, analyze, and make available the manufacturing data generated across the AMMT program. In FY 2023, the team conceptualized the architecture of the platform and, in FY 2024, deployed the first functional version at the Oak Ridge National Laboratory (ORNL) Manufacturing Demonstration Facility (MDF). In FY 2025, the platform was officially opened to all AMMT members. To enable this expansion, core modifications and enhancements were developed, including improvements to the user interface and workflows for data entry and retrieval. Most notably, robust security and access control mechanisms were implemented to protect data and manage information sharing. This effort featured a logging system, protected views, and controlled access mechanisms. This report documents these enhancements and the transition of the platform into program-wide use.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A Risk-Informed Performance-Based Methodology to Manage Fire Protection Systems in Nuclear Facilities

Fire protection systems (FPSs) and features are installed in U.S. Department of Energy (DOE) Hazard Category 1, 2, or 3 nuclear facilities to protect property (maximum possible fire loss thresholds), life, and nuclear safety (i.e., structures, systems, and components). These FPSs and features are designed and maintained in accordance with the prescriptive guidance provided in applicable building codes and National Fire Protection Association codes and standards. Management, operations, and maintenance activities of FPSs involve significant effort. A DOE facility’s documented safety analysis or other safety basis document could also rely on FPSs to provide either a safety significant or safety class function to mitigate fire hazards and minimize radiological consequences. In some cases, the designation of safety significant or safety class may be determined to provide a layer of defense-in-depth to minimize nuclear safety risks independent of the fire risk. DOE standards allow the use of performance-based design alternatives developed by the fire industry but do not consider the defense-in-depth layers of protection provided in DOE facilities to prevent or mitigate the risks associated with unintended release of radioactive materials into the environment. Pacific Northwest National Laboratory developed a decision-making methodology tailored for DOE non-reactor nuclear facilities to manage FPSs and features by integrating nuclear safety risk insights into a performance-based analysis. This risk-informed, performance-based (RIPB) methodology can be used to provide the technical basis for classifying an FPS as safety class and safety significant, tailoring administrative controls (e.g., technical safety requirements), and ranking the importance of FPSs to prioritize maintenance, upgrades, and replacement activities. The RIPB methodology is a graded approach to inform DOE facility owners and Fire Protection Program managers of the most risk-significant FPSs and equipment, and those systems would be cost-beneficial to relax rigor if there is a need to re-design the FPS coverage or deviate from DOE and National Fire Protection Association standards for those systems that would be less significant. This paper describes the framework used to develop the RIPB methodology and the outcome of implementing this methodology in a use-case nuclear facility. This paper also discusses the impact to DOE policies and standards and the safety margins and defense-in-depth measures credited in nuclear safety assessments in a facility’s documented safety analysis and the benefits of implementing an RIPB methodology in lieu of a prescriptive method to comply with fire protection requirements.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

United States–Brazil Joint Study: A Preliminary Assessment of Opportunities and Challenges for Small Modular Reactors in Brazil

This report supplies the technical information to enable a broader understanding of different technology choices for nuclear reactors in Brazil. The assessment characteristics of this process include reactor technology, economic costs for deployment, and regulatory analyses of small modular reactors, advanced reactors, and microreactors. The analysis documented in this report provides economic and technological information to assist Brazil, whose official indicative scenarios show an increase in operating nuclear power from 2 Gigawatt in 2022 to 8–10 Gigawatt by 2050, in policy making and long-term energy planning. To protect company proprietary information, the information in this report was limited to publicly available information and therefore can only inform preliminary reactor technology assessments. This report does not recommend or endorse any specific reactor developer or technology.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Facilitating Data Collection of Maintenance Events to Populate the Hydrogen Component Reliability Database (HyCReD)

The Hydrogen Component Reliability Database (HyCReD) is a collaborative project between the National Renewable Energy Laboratory, the University of Maryland, and hydrogen stakeholders to improve safety and reliability for hydrogen facilities by implementing component reliability data taxonomies that support hydrogen infrastructure failure rate analysis. The project aims to quantify failure rates of hydrogen components through high-quality data collection and analysis on root causes and maintenance needed. HyCReD provides a common database for cataloging hydrogen component failures which exists for reliability research in many other mature industries [2]. The database fills a gap for the hydrogen community by providing a scientifically rigorous approach to quantitative risk assessment (QRA), prognostic health management (PHM), and reliability-centered maintenance (RCM) analysis. High level results will be aggregated and anonymized to protect company sensitive information; detailed results will be used to help address issues of hydrogen components. These advanced analytics will support accelerated deployment of hydrogen infrastructure by enabling better: design and safety of projects (safety codes and standards development), infrastructure reliability and cost (component failure rates, maintenance protocols), and component R&D needs (robust supply chain). A key to a successful HyCReD implementation is facilitating the ease of reporting and data quality in the database that can be used for analysis. Maintenance data was a previously identified gap in initial efforts to populate and validate the database taxonomies [3]. Collection of maintenance data will be instrumental in identifying failure modes and rates, identifying incipient component failures or reduced performance, cataloging best practices for maintenance routines and methods for prognostic health management, and quantifying the risk and effect of different failure modes. Several key priorities are identified for streamlined data collection to achieve quality and detailed failure data: Applicability, Ease of Use, Accessibility, and Information Security. The HyCReD team has now begun deployment of the database to several companies and groups that have signed non-disclosure agreements to facilitate the data collection of failures in industry hydrogen refueling station infrastructure. This paper will provide an update into the process of HyCReD deployment including the development of a coding guide for facility personnel to reference and ensure data quality and consistency from one station to another as well as implementation of contextually dependent data fields of system taxonomy and formatted entries to provide ease of use. The goal is to communicate the lessons learned from the roll-out to technicians and engineers in the field, and the addition of need for high level of security to protect all stakeholders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Blockchain-Based Smart Contracts Use for Photovoltaic Energy Trade Transactions

In recent decades, interest in renewable energy via solar energy has increased, especially in California and Nevada. In a region that can produce enough solar power for self-use, prosumers must use or sell surplus energy. Solar energy self-consumption is essential in modern energy transactions in the grid. This paper proposes an approach towards grid services that includes photovoltaic hardware to store the excess energy in battery storage. Such energy can then be sold to power companies while the transaction is handled using blockchain. Software, security architecture and data flow requirements based on the Ethereum Blockchain are included. Furthermore, this solution protects the private information of seller and buyer and secures transactions.

14 SOLAR ENERGY↗
DOE OSTI2021

Model fusion with physics-guided machine learning: Projection-based reduced-order modeling

The unprecedented amount of data generated from experiments, field observations, and large-scale numerical simulations at a wide range of spatiotemporal scales has enabled the rapid advancement of data-driven and especially deep learning models in the field of fluid mechanics. Although these methods are proven successful for many applications, there is a grand challenge of improving their generalizability. This is particularly essential when data-driven models are employed within outer-loop applications like optimization. In this work, we put forth a physics-guided machine learning (PGML) framework that leverages the interpretable physics-based model with a deep learning model. Leveraging a concatenated neural network design from multi-modal data sources, the PGML framework is capable of enhancing the generalizability of data-driven models and effectively protects against or inform about the inaccurate predictions resulting from extrapolation. We apply the PGML framework as a novel model fusion approach combining the physics-based Galerkin projection model and long- to short-term memory (LSTM) network for parametric model order reduction of fluid flows. We demonstrate the improved generalizability of the PGML framework against a purely data-driven approach through the injection of physics features into intermediate LSTM layers. Our quantitative analysis shows that the overall model uncertainty can be reduced through the PGML approach, especially for test data coming from a distribution different than the training data. Moreover, we demonstrate that our approach can be used as an inverse diagnostic tool providing a confidence score associated with models and observations. The proposed framework also allows for multi-fidelity computing by making use of low-fidelity models in the online deployment of quantified data-driven models.

42 ENGINEERING↗
DOE OSTI2025

Demonstration and Concept of Operations for a Zero-Knowledge Protocol Passive Imaging Measurement for Arms Control

Here, we present an imaging system that employs zero-knowledge protocols to protect sensitive geometrical information, along with procedures to increase confidence in the result. The goal of this work is to enable the inclusion of warhead confirmation measurements in future arms control treaties. We present a demonstration of both true positive and true negative measurements that validate models and establish authenticating procedures toward meeting acceptance requirements for use in nuclear facilities. We use a two-dimensional time-encoded fast neutron imaging system with an anti-symmetric mask pattern; the fast neutron count values exceeding minimum or maximum thresholds indicate that two measured items are not identical. Laboratory measurements over twenty trials show that alarm rates for negative confirmation measurements are within uncertainties of model predictions. Positive confirmation measurements indicate that alarm rates are large enough to encourage treaty compliance.

Sweany, Melinda Dominique [Sandia National Laborat↗
DOE OSTI2021

Distribution Grid Modeling Using Smart Meter Data

The knowledge of distribution grid models, including topologies and line impedances, is essential for grid monitoring, control and protection. However, such information is often unavailable, incomplete or outdated. The increasing deployment of smart meters (SMs) provides a unique opportunity to tackle this issue. This paper proposes a two-stage framework for distribution grid modeling using SM data. In the first stage, the network topology is identified by reconstructing a weighted Laplacian matrix of distribution networks. In the second stage, a least absolute deviations (LAD) regression model is developed for estimating line impedance of a single branch based on the nonlinear (inverse) power flow model, wherein a conductor library is leveraged to narrow down the solution space. The LAD regression model is originally a mixed-integer nonlinear program whose continuous relaxation is still non-convex. Furthermore, we specially address its convex relaxation and discuss the exactness. The modified regression model is then embedded within a bottom-up sweep algorithm to achieve the identification across the network in a branch-wise manner. Numerical results on the IEEE 13-bus, 37-bus and 69-bus test feeders validate the effectiveness of the proposed methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Improved Particle Swarm Algorithm Using Rubik’s Cube Topology for Bilevel Building Energy Transaction

Following the rapid growth of distributed energy resources (e.g., renewables, battery), localized peer-to-peer energy transactions are receiving more attention for multiple benefits, such as reducing power loss and stabilizing the main power grid. To promote distributed renewables locally, the local trading price is usually set to be within the external energy purchasing and selling price range. Consequently, building prosumers are motivated to trade energy through a local transaction center. This local energy transaction is modeled in bilevel optimization game. A selfish upper level agent is assumed with the privilege to set the internal energy transaction price with an objective of maximizing its arbitrage profit. Meanwhile, the building prosumers at the lower level will response to this transaction price and make decisions on electricity transaction amount. Therefore, this non-cooperative leader-follower trading game is seeking for equilibrium solutions on the energy transaction amount and prices. Additionally, a uniform local transaction price structure (purchase price equals selling price) is considered here. Aiming at reducing the computational burden from classical Karush–Kuhn–Tucker (KKT) transformation and protecting the private information of each stakeholder (e.g., building), swarm intelligence-based solution approach is employed for upper level agent to generate trading price and coordinate the transactive operations. On one hand, to decrease the chance of premature convergence in global-best topology, Rubik’s Cube topology is proposed in this study based on further improvement of a two-dimensional square lattice model (i.e., one local-best topology-Von Neumann topology). Rotating operation of the cube is introduced to dynamically changing the neighborhood and enhancing information flow at the later searching state. Several groups of experiments are designed to evaluate the performance of proposed Rubik’s Cube topology-based particle swarm algorithm. The results have validated the effectiveness of proposed topology and operators comparing with global-best version PSO and Von Neumann topology-based PSO and its scalability on larger scale applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Policy-relevant differences between secondhand and thirdhand smoke: strengthening protections from involuntary exposure to tobacco smoke pollutants

Starting in the 1970s, individuals, businesses and the public have increasingly benefited from policies prohibiting smoking indoors, saving thousands of lives and billions of dollars in healthcare expenditures. Smokefree policies to protect against secondhand smoke exposure, however, do not fully protect the public from the persistent and toxic chemical residues from tobacco smoke (also known as thirdhand smoke) that linger in indoor environments for years after smoking stops. Nor do these policies address the economic costs that individuals, businesses and the public bear in their attempts to remediate this toxic residue. We discuss policy-relevant differences between secondhand smoke and thirdhand smoke exposure: persistent pollutant reservoirs, pollutant transport, routes of exposure, the time gap between initial cause and effect, and remediation and disposal. We examine four policy considerations to better protect the public from involuntary exposure to tobacco smoke pollutants from all sources. We call for (a) redefining smokefree as free of tobacco smoke pollutants from secondhandandthirdhand smoke; (b) eliminating exemptions to comprehensive smoking bans; (c) identifying indoor environments with significant thirdhand smoke reservoirs; and (d) remediating thirdhand smoke. We use the case of California as an example of how secondhand smoke-protective laws may be strengthened to encompass thirdhand smoke protections. The health risks and economic costs of thirdhand smoke require that smokefree policies, environmental protections, real estate and rental disclosure policies, tenant protections, and consumer protection laws be strengthened to ensure that the public is fully protected from and informed about the risks of thirdhand smoke exposure.

Public, Environmental & Occupational Health↗
DOE OSTI2021

Adapting Secure MultiParty Computation to Support Machine Learning in Radio Frequency Sensor Networks

In this project we developed and validated algorithms for privacy-preserving linear regression using a new variant of Secure Multiparty Computation (MPC) we call "Hybrid MPC" (hMPC). Our variant is intended to support low-power, unreliable networks of sensors with low-communication, fault-tolerant algorithms. In hMPC we do not share training data, even via secret sharing. Thus, agents are responsible for protecting their own local data. Only the machine learning (ML) model is protected with information-theoretic security guarantees against honest-but-curious agents. There are three primary advantages to this approach: (1) after setup, hMPC supports a communication-efficient matrix multiplication primitive, (2) organizations prevented by policy or technology from sharing any of their data can participate as agents in hMPC, and (3) large numbers of low-power agents can participate in hMPC. We have also created an open-source software library named "Cicada" to support hMPC applications with fault-tolerance. The fault-tolerance is important in our applications because the agents are vulnerable to failure or capture. We have demonstrated this capability at Sandia's Autonomy New Mexico laboratory through a simple machine-learning exercise with Raspberry Pi devices capturing and classifying images while flying on four drones.

42 ENGINEERING↗
DOE OSTI2022

How nuclear weapons tests were named

What do Galileo, Husky Pup, Turquoise and Barracuda have in common? They are names of nuclear weapons tests conducted at what is now called the Nevada National Security Site (NNSS). Over 1,000 U.S. nuclear tests were conducted at various sites between 1945 and 1992, and each of the tests was inaugurated with a name, as documented in the Lab’s vast weapons test collections housed in the National Security Research Center (NSRC). To protect the classified information about nuclear weapons and maintain security, nuclear weapons tests were assigned names. This has been true from the beginning with Trinity, the first atomic bomb test in 1945. Lab Director J. Robert Oppenheimer later said the test name may have been inspired by his love of poetry.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Inventory of Public Key Cryptography in US Electric Vehicle Charging

Electric vehicles (EVs) and charging infrastructure are networked systems, which employ high-level communications in support of charging and grid service decisions. Public key cryptography (PKC) underlies much of the security and privacy protections of the information exchange. We are entering a new epoch where quantum computing threats must be seriously considered. A sufficiently large quantum computer, so named Cryptographically Relevant Quantum Computer (QRQC), will be able to perform the mathematical operations to efficiently attack the underpinnings of traditional PKC, thus jeopardizing the digital foundations for trust, communications security, and data security. Estimates suggest a QRQC can break public key encryption and digital signatures in the manner of tens to hundreds of hours, compared to traditional computing that would demand more than 10 18 years in a brute force-style attack. A consensus belief of quantum theorists, quantum experimenters, and cryptographers suggest that the quantum threat will be likely realized in the next twenty years. To address the threat, post-quantum cryptography, which is cryptosystems that are designed to be secure against both traditional and quantum computing threats, must be adopted. Migration from traditional PKC to quantum-resilient cryptography is a global undertaking and likely represents the largest transition in computing history. The nascent state of EV public key infrastructure, combined with limited adoption of the vehicle secure charging features, presents an opportunity to establish a preference for quantum-resistant cryptography as a step on the migration path. Delays will stunt the efforts as rapidly accelerating EVs sales and huge infrastructure investments will create large growing bases of long-lived vehicles and infrastructure. Migration preparations can commence while NIST continues the process to standardize post-quantum cryptography (PQC), which are quantum-resilient algorithms designed to be secure against traditional and quantum computing threats. The first step in preparing EV charging is to identify the presence of traditional public key cryptography algorithms and applications. With this objective in mind, this report is intended to advise the vehicle manufacturers, charging station manufacturers, charging station operators, charge network providers and other EV charging stakeholders with information on traditional PKC application and the potential risks when PKC becomes insecure. This report, the first in a series of reports discussing the topics existing at the confluence of post-quantum cryptography adoption and EV charging, identifies traditional public key applications employed and identifies potential consequences of leaving EV charging infrastructure vulnerable to quantum computing. The focus remains squarely on the of EV charging and infrastructure with respect to PKC and is believed by the authors to complement the NIST SP 1800-38 Migration to Post-Quantum Cryptography. While the report is centered on infrastructure, there are implications to vehicles.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Quality Guidelines for Energy System Studies: Process Modeling Design Parameters

The National Energy Technology Laboratory (NETL) conducts systems analysis studies that require a large number of inputs, from ambient conditions to parameters for Aspen Plus ® (Aspen) process blocks. The sheer number of assumptions required makes it impractical to document all of them in each issued report. The purpose of the Quality Guidelines for Energy System Studies (QGESS) is to document the assumptions most commonly used in system analysis studies and the basis for those assumptions. In order to develop the systems analysis models presented in various NETL reports, significant vendor data have been obtained, and these data enhance the model outputs. Much of the vendor data obtained are considered proprietary and not suitable for public release or attribution to a specific vendor. As such, several sub-systems common in NETL reports and their process parameter data are not reported in this document to protect proprietary vendor information. The values and ranges of values presented in this report represent assumptions that have been made in previous studies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Quantum Key Distribution for Critical Infrastructures: Towards Cyber-Physical Security for Hydropower and Dams

Hydropower facilities are often remotely monitored or controlled from a centralized remote control room. Additionally, major component manufacturers monitor the performance of installed components, increasingly via public communication infrastructures. While these communications enable efficiencies and increased reliability, they also expand the cyber-attack surface. Communications may use the internet to remote control a facility’s control systems, or it may involve sending control commands over a network from a control room to a machine. The content could be encrypted and decrypted using a public key to protect the communicated information. These cryptographic encoding and decoding schemes become vulnerable as more advances are made in computer technologies, such as quantum computing. In contrast, quantum key distribution (QKD) and other quantum cryptographic protocols are not based upon a computational problem, and offer an alternative to symmetric cryptography in some scenarios. Although the underlying mechanism of quantum cryptogrpahic protocols such as QKD ensure that any attempt by an adversary to observe the quantum part of the protocol will result in a detectable signature as an increased error rate, potentially even preventing key generation, it serves as a warning for further investigation. In QKD, when the error rate is low enough and enough photons have been detected, a shared private key can be generated known only to the sender and receiver. We describe how this novel technology and its several modalities could benefit the critical infrastructures of dams or hydropower facilities. The presented discussions may be viewed as a precursor to a quantum cybersecurity roadmap for the identification of relevant threats and mitigation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Rubik’s Cube Topology Based Particle Swarm Algorithm for Bilevel Building Energy Transaction

Following the rapid growth of distributed energy resources (e.g. renewables, battery), localized peer-to-peer energy transactions are receiving more attention for multiple benefits, such as, reducing power loss, stabilizing the main power grid, etc. To promote distributed renewables locally, the local trading price is usually set to be within the external energy purchasing and selling price range. Consequently, building prosumers are motivated to trade energy through a local transaction center. This local energy transaction is modeled in bilevel optimization game. A selfish upper level agent is assumed with the privilege to set the internal energy transaction price with an objective of maximizing its arbitrage profit. Meanwhile, the building prosumers at the lower level will response to this transaction price and make decisions on electricity transaction amount. Therefore, this non-cooperative leader-follower trading game is seeking for equilibrium solutions on the energy transaction amount and prices. In addition, a uniform local transaction price structure (purchase price equals selling price) is considered here. Aiming at reducing the computational burden from classical Karush-Kuhn-Tucker (KKT) transformation and protecting the private information of each stakeholder (e.g., building), swarm intelligence based solution approach is employed for upper level agent to generate trading price and coordinate the transactive operations. On one hand, to decrease the chance of premature convergence in global-best topology, Rubiks Cube topology is proposed in this study based on further improvement of a two-dimensional square lattice model (i.e., one local-best topology-Von Neumann topology). Rotating operation of the cube is introduced to dynamically changing the neighborhood and enhancing information flow at the later searching state. Several groups of experiments are designed to evaluate the performance of proposed Rubiks Cube topology based particle swarm algorithm. The results have validated the effectiveness of proposed topology and operators comparing with global-best version PSO and Von Neumann topology based PSO and its scalability on larger scale applications.

Feng, Xiaochun↗
DOE OSTI2023

The Construction of Reduced Order Models for the HYBRID Repository

Reduced order models (ROMs) present an opportunity to reduce the computational burden of IES analysis using HYBRID models without significantly sacrificing data accuracy. Other applications of ROMs are digital twins, stochastic optimization studies, model exporting, and protection of proprietary information. In this paper the capability of creating ROMs of the models within the HYBRID repository will be demonstrated. Specifically, a linear regression ROM of a gas turbine and a dynamic mode decomposition with control (DMDc) ROM of a lithium-ion battery are constructed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

International Radiation Monitoring Information System (IRMIS) – a versatile EPR tool for all member states [Slides]

IRMIS provides Competent Authorities, IEC, and other relevant International Organizations with a data sharing tool that helps to report and share information, evaluate radiation monitoring data to assess if the public is safe, identify protective actions, keep the public informed by Member State Competent Authority, and maintain transparency of data handling and processing.

61 RADIATION PROTECTION AND DOSIMETRY↗