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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 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Chapter 4: Physically informed deep learning networks for simulating microstructure evolution of 3D polycrystals

As discussed in the previous chapter, high energy diffraction microscopy (HEDM) is used to study the micromechanical evolution of a material during in situ loading. HEDM experiments have been used to verify crystal plasticity (CP) simulations [119, 91, 90, 120], for experimental planning, material design, and to further analyze experimental results. However, Fast Fourier transform-based CP (CP-FFT) or finite element-based CP (CP-FE) methods are often too slow to be used in real-time during an experiment. CP-FFT is faster than CP-FE simulations due to the absence of meshing, but can still take hours to simulate the response of a single volume depending on the size and number of strain steps [127]. Reducing computation time would create a larger exploration space in planning and design, and enable faster analysis of experimental results and real-time feedback during an experiment. This research expands upon previous works to develop a workflow for predicting the full-field evolution of a 3D polycrystal. The workflow is simplified from previous works to predict only orientation and elastic strain tensors (from which stress tensors are calculated). The network is physically informed through loss functions and network architecture for a more robust model. The orientation predictions are informed about the cubic crystal symmetry of the material by incorporating disorientation and misorientation information into the network architecture and loss. The Von Mises stress is used to enforce the correct stress-strain trends in the strain tensor predictions. Additional total strain steps from the elastic and elastoplastic region are included to better capture the stress-strain evolution at smaller total strain steps. Material and hardening parameters are additional inputs into the networks to further inform the network and to study the network’s ability to predict different materials other than those used for training.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Developing nanometer scale, atomically precise metallo-catalysts with Molecular Lego

We propose to create atomically precise, highly robust, nanometer scale macromolecules that organize biomimetic metal binding groups in designed three-dimensional pockets to accelerate specific polymerization reactions. These atomically precise catalysts will create atomically precise polymers with improved mechanical and environmental properties from renewable building blocks. We seek to create and study nanometer scale catalysts that mimic metallo-enzymes in their activity and selectivity because these larger catalysts will be able to make more extensive non-covalent contacts with the transition state of the growing polymer. These catalysts will have extended lifetimes because they will better protect the metals and higher activity because additional reactive groups can be brought in close contact with the active site to enhance reactivity. They will be far more tolerant to extremes of temperature and will not denature in non-aqueous solvents because they are held together by multiple, strong, covalent bonds. Our approach to catalysts could be used to develop catalysts to replace noble metal-based catalysts when targeting other reactions, because the geometry of the active site enforced by the Molecular Lego scaffolding will access new reactivity, mimicking how nature uses earth abundant metals for much of its catalysis. We will initially target Lewis acid-based catalysts that assemble aliphatic polyesters with improved stereoselectivity, tacticity and complex alternation of monomers. Aliphatic polyesters have received growing attention as attractive, environmentally benign, and sustainable alternatives to polymers developed from petroleum feedstocks. Aliphatic polyesters are environmentally friendly because they undergo facile hydrolytic degradation to benign products, and they have excellent properties and high biocompatibility. We will assemble these catalysts using unique “Spiroligomers” (aka Molecular Lego) chemistry developed in the Schafmeister group combined with the organometallic chemistry expertise of the Dobereiner group. Polymers are an attractive synthetic target of nanoscale atomically precise catalysts because their resulting structure, stereochemistry and tacticity has profound impact on their properties (crystalline vs amorphous) and provides a readout of the catalytic mechanism. Polymer synthesis also serves as an example of “atomically precise manufacturing” where atomically precise nanoscale catalysts construct polymers with atomic precision at increasing length scales.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

FARM User Guidance and Instructions

The FARM (Feasible Actuator Range Modifier) module is a component of the RAVEN-based FORCE framework for the analysis of Integrated Energy Systems (IES). FARM aids HERON in the solution of the power dispatch problem by evaluating feasible set-point signals to be issued to the control systems of the different IES unit components. Set-points need to satisfy limits on both production variables (i.e., the variables to be optimized such as the electrical power, etc.) and process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.). To enforce all these limits, a two-stage approach is adopted. First, the power dispatcher algorithm in HERON module estimates set-points that meet the constraints on the production variables, e.g., power levels and power ramp rate limits. These constraints are called explicit constraints. Then, if necessary, FARM adjusts these set-points to ensure the respect of the limits on the process variables of interest, given the knowledge of the system dynamics acquired through machine learning algorithms. These constraints are called implicit constraints. From this standpoint, FARM constitutes a bridge between the HERON power dispatcher that adopts a simplified description of the IES unit (low-resolution physics) and the HYBRID high-fidelity models (high-resolution physics). In this report, the general workflow and the software requirements of FARM module are summarized, and the detailed instructions for installing FARM software, running built-in example cases, deriving Linear Parameter-Varying (LPV) state-space models, and using FARM for user-defined power dispatch problems are provided.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Connected and Learning Based Optimal Freight Management for Efficiency

The management of the future heterogenous fleet is a complex decision-making problem. The heterogenous fleet is emerging as decarbonization technologies are deployed by fleets toward lowering the freight operation emissions in Medium and Heavy-duty vehicles. Traditionally, in fleets characterized by a homogeneous Diesel Internal Combustion Engine (ICE) powertrain, the process of fleet planning and operational optimization unfolds sequentially without the necessity to account for powertrain and vehicle-specific characteristics during dispatch decisions. Fleets with trucks less than 5 years old tend to maintain stable vehicle efficiency with minimal operational reliability risks for fleet managers. However, the landscape changes with the incorporation of emerging powertrain technologies, which lack extensive operational data and service experiences. This includes technologies like hybrid, Electric, Fuel Cell, or alternative fuel ICE. Operational decisions for fleets featuring heterogeneous powertrain technologies and facing limited access to alternative fueling and charging stations become intricate, requiring careful consideration and optimization at each dispatch. The difference in efficiency characteristics of emerging technologies, their range limitations, and the restricted availability of charging/alternative fueling infrastructure, coupled with sensitivity to driving conditions (e.g., EV range reduction in low temperatures) and their impact on component aging (such as batteries), become pivotal factors influencing the reliable and efficient freight transportation. To make the path toward low emission freight transportation efficient and reliable, an AI-assisted fleet management software is developed in this project to help fleet managers in optimizing both adoption of emerging powertrain decarbonization, connected and automated technologies and also operating the fleet after such technologies are deployed as schematically. Freight transportation requirements are different depending on the cargos to be shipped, customer requirements and regions of operations. This further highlights the need for software and digital solutions to tailor deployment and operation of emerging powertrain, connectivity, and automation technologies toward the specific fleet operation requirements. The fleet management optimizer was also integrated with a model of the fleet to simulate the operation of the fleet over 1 year of the baseline fleet operation (250,000+ shipments) indicating the significance of day-to-day variations on emissions and energy consumption of a freight transportation fleet. The results demonstrate ≥20% improvement in freight efficiency in terms of WTW CO2 per ton-mile of cargo shipments while all fleet operation constraints are enforced, and the cost (CapEx and OpEx) is minimized.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Optical Microsystems for Molecular Sensing (CRADA Final Report)

As part of the Cyclotron Road program, NuSight Photonics sought to implement and investigate an optical Raman spectroscopy instrument for material and molecular analysis. Raman spectroscopy is widely used for quick and non-invasive material measurement when accurate results are needed – e.g., for monitoring manufacturing process in pharmaceutical plants, or identifying illicit substances and explosives by Law Enforcement. This technique is also growing rapidly in popularity as it is applied successfully to a broad range of applications, from pathology and non-invasive early cancer detection, to food and drug safety. The biggest challenge for Raman spectroscopy to achieve its full potential is the hardware cost, ranging from $\$ $25k to $\$ $250k, with the lower cost solutions significantly limited in sensitivity—or detection limit. NuSight Photonics aimed to tackle this obstacle through a novel hardware approach: Swept-Source Raman Spectroscopy.

36 MATERIALS SCIENCE↗
DOE OSTI2024

FARM supervisory capabilities for thermal energy storage

The FARM (Feasible Actuator Range Modifier) module is a component of the RAVEN-based FORCE framework for the analysis of Integrated Energy Systems (IES). FARM aids HERON in the solution of the power dispatch problem by evaluating feasible set-point signals to be issued to the control systems of the different IES unit components. Set-points need to satisfy limits on both production variables (i.e., the variables to be optimized such as the electrical power, etc.) and process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.). To enforce all these limits, a two-stage approach is adopted. First, the power dispatcher algorithm in HERON module estimates set-points that meet the constraints on the production variables, e.g., power levels and power ramp rate limits. These constraints are called explicit constraints. Then, if necessary, FARM adjusts these set-points to ensure the respect of the limits on the process variables of interest, given the knowledge of the system dynamics acquired through machine learning algorithms. These constraints are called implicit constraints. From this standpoint, FARM constitutes a bridge between the HERON power dispatcher that adopts a simplified description of the IES unit (low-resolution physics) and the HYBRID high-fidelity models (high-resolution physics). In this report, an overview of the major capabilities of the latest release of FARM is provided, along with a summary of the tool demonstration campaign conducted at the Dynamic Energy Technology and Integration Laboratory (DETAIL) facility. These results assess the performance of the control system architecture embedding FARM both as a Validator of the HERON power dispatcher and as a real time Supervisory control scheme. Additionally, the report outlines the areas that FARM might benefit from, along with proposed solutions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Energy Storage and Decarbonization Analysis for Energy Regulators: Technical Analysis for the Illinois Commerce Commission

Jurisdictions around the world are enacting and enforcing an increasing number of policies to fight climate change, leading to higher penetration of variable renewable energy (VRE) and energy storage systems (ESSs) in the power grid. One of the biggest challenges associated with this process is the evaluation of the appropriate amount of ESS required to mitigate the variability of the VREs and achieve decarbonization goals of a particular jurisdiction. This report presents methodologies developed and results obtained for determining the minimum amount of ESS required to adequately serve load in a system where fossil fueled generators are being replaced by VREs over the next two decades. This technical analysis is performed by Sandia National Laboratories for the DOE Office of Electricity Energy Storage Program in collaboration with the Illinois Commerce Commission (ICC). The Illinois MISO Zone 4 is used as a case study. Several boundary conditions are investigated in this analysis including capacity adequacy and energy adequacy to determine the quantity of ESS required for MISO Zone 4. Multiple scenarios are designed and evaluated to incorporate the impact of varying capacity values of VREs and on the resource adequacy of the system. Several retirement scenarios involving fossil-fueled assets are also considered. Based on the current plans of new additions and retirements of generating assets, the results of the technical analysis indicate that Illinois MISO Zone 4 will require a significant quantity of ESS to satisfy their electricity demand over the next two decades.

25 ENERGY STORAGE↗
DOE OSTI2024

Using Parameter Sweep in WaterTAP to Analyze New Water Treatment Technologies

We describe a powerful and generalized parameter sweep tool in this report that was originally developed to analyze the performance of existing and novel water treatment models being developed in WaterTAP. Since WaterTAP is built upon IDAES and Pyomo, the parameter sweep tool can be used to systematically explore and debug the behavior of most Pyomo and IDAES numerical models. In order to enable meaningful analyses, the parameter sweep tool has been designed with the following features: 1) Model flexibility: The parameter sweep tool does not enforce any restrictions on the types of models that can be used with it. As long as a Pyomo model can be solved and the parameter is active and mutable, the tool only needs functions that describe how to run the model, the sweep parameters, and the output quantities of interest. 2) Flexible sampling: The parameter sweep tool has inbuilt functions to generate samples from a random distribution or a multidimensional Euclidean space. Furthermore, the users have to ability to supply samples generated from a tool of their choice. 3) Multiple sweep types: A user can choose from one of 3 types of parameter sweeps depending on their needs. 4) Detailed outputs: Outputs generated by the parameter sweep tool can be stored in detailed H5 file or user-friendly CSV files for post processing. 5) Parallel computing: The parameter sweep supports shared and distributed memory parallel computing to enable the use of high performance computers (HPC) for large-scale analyses. 6) Modular: The parameter sweep tool is self-contained and can easily be integrated within an outer-loop analysis or as desired by the user. 7) Ease of use: The tool is well documented and a simple sweep can be easily executed by following the online documentation in a few lines of code. We demonstrate the use of the parameter sweep tool on a simple water treatment system from the WaterTAP repository and show its parallel scaling performance on an Apple laptop and NREL's Eagle HPC. The parameter sweep tool is actively being used with models currently being developed within WaterTAP and we expect its use to grow beyond it to other IDAES and Pyomo models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

The Design and Evaluation of Zero Trust Architecture for Electric Vehicle Charging Infrastructure: EVs @ Scale Series on EV Charging Station Cybersecurity

Implementing a zero trust architecture can significantly bolster the security of electric vehicle (EV) charging infrastructure. EV charging infrastructure includes numerous networked interfaces, each of which can present potential vulnerabilities. When these vulnerabilities are exploited, they can compromise the entire system, leading to severe operational and security risks. Zero trust is a security model that operates on the principle of "never trust, always verify," which helps manage the attack surface and limit the scope of any potential compromises. Fundamentally, this model ensures that no entity, whether inside or outside the network, is trusted by default. The design principles of zero trust include continuous verification, strict deny-by-default access controls, and micro-segmentation. Continuous verification ensures that every request is thoroughly checked, regardless of its origin. Strict access controls enforce the principle of least privilege, allowing users and devices only the minimum necessary access to perform their functions. Micro-segmentation involves dividing the network into smaller, isolated segments to prevent lateral movement in case of a breach. In the context of EV charging infrastructure, zero trust can be implemented through various strategies. For example, multi-factor authentication (MFA) can be required for engineers to access the management interfaces and control systems of charging stations. Real-time monitoring and analysis of network traffic can help detect and respond to anomalies. Systems that do not need to communicate with each other can be micro-segmented to enhance security. All communications should adhere to predefined policies to be permitted. Additionally, encrypting communications can protect sensitive information exchanged between chargers and management systems. This paper presents a zero trust architecture specifically designed for EV charging infrastructure. Implementing zero trust not only mitigates risks but also builds a resilient infrastructure capable of withstanding and quickly recovering from cyber threats. The architecture addresses six defined security objectives. A comprehensive test plan is developed to assess the architecture against these objectives, and the results of the evaluation are reported. This approach is essential for maintaining the reliability and integrity of EV charging services in an increasingly interconnected and vulnerable digital landscape. This is the first in a planned series of papers exploring the implementation of zero trust in EV charging infrastructure. Each paper will delve into different aspects and applications of zero trust, highlighting how various work processes and requirements can lead to distinct architectural designs. These architectures will be tailored to address specific security challenges and operational needs within the EV charging ecosystem, ensuring a robust and adaptable security framework.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Addressing tokens dynamic generation, propagation, storage and renewal to secure the GlideinWMS pilot based jobs and system

GlideinWMS has been one of the first middleware in the WLCG community to transition from X.509 to support also tokens. The first step was to get from the prototype in 2019 to using tokens in production in 2022. This paper will present the challenges introduced by the wider adoption of tokens and the evolution plans for securing the pilot infrastructure of GlideinWMS and supporting the new requirements. In the last couple of years, the GlideinWMS team supported the migration to tokens of experiments and resources. Inadequate support in the current infrastructure, more stringent requirements, and the higher spatial and temporal granularity forced GlideinWMS to revisit once more how credentials are generated, used, and propagated. The new credential modules have been designed to be used in multiple systems (GWMS, HC) and use a model where credentials have type, purpose, and different flows. Credentials are dynamically generated in order to customize the duration and limit the scope to the targeted resource. This allows to enforce the least privilege principle. Finally, we also considered adding credential storage, renewal, and invalidation mechanisms within the GlideinWMS infrastructure to serve better the experiments’ needs.

Mambelli, Marco↗
DOE OSTI2025

EMPOWERED Distributed Energy Resources Permit Accelerator Pilot

This report summarizes the EMPOWERED Distributed Energy Resources (DER) Permit Accelerator Pilot project. Its primary objective was to streamline the design, installation, permitting, and inspections of targeted Distributed Energy Resource (DER) solutions. Streamlining these processes is critical to strengthening and accelerating the adoption of DER solutions nationwide. Moreover, streamlined processes help expedite the clean energy transition and expand energy resilience by improving understanding and capability among key stakeholders like property owners, code officials, and the general workforce. The project team accomplished this by developing and deploying a set of design and permitting guides for simple DER solutions, which they rolled out via a permitting pilot program. The project team developed nine permitting and inspection guides for simple DER solutions, as follows: 1. Single-Family and Duplex: Electric Vehicle Service Equipment (EVSE), and Storage, Solar + Storage (each in two code cycles) 2. Multi-family and Office: EVSE, Storage, Solar + Storage (each in two code cycles) 3. A permitting process guide to support the implementation of the permitting guides. The guides cover key code requirements via plan review and field inspection checklists for code officials and building owners to follow to streamline the permitting and inspections process for DER solutions. Following the development of the initial set of guides, the project team formed two cohorts, each made up of four jurisdictions, to participate in the Permit Accelerator Pilot. Each cohort received training and technical assistance to support them in incorporating the guides into use. The project successfully engaged jurisdictions in two disparate US regions: Chelsea, Somerville, Natick, and Norwood in metro Boston; and Pima County, Town of Gilbert, Flagstaff, and Sedona in Arizona. Feedback gathered from the project was valuable in refining the guides to better address jurisdictional needs. After the pilot period, the project team developed final versions of the guides based on extensive feedback from the cohorts and from external technical peer review. Feedback included needs and barriers related to implementation, as well as detailed technical improvements from external peer review. The final guides were presented in a series of webinars with a national reach, with 192 attendees from 35 states in the live session of the final webinar, and the final guides are posted online and available for use nationwide. Key findings: • The most receptive jurisdictions were those adjacent to other jurisdictions that had already adopted similar initiatives. The least receptive jurisdictions were those in the midst of adopting new code cycles. • The most common barrier to jurisdictional adoption of new guidelines were internal administrative and process delays, more so than technical barriers. • The main technical barrier to adoption proved to be the concern of fire hazard risks posed by energy storage systems. There is some apprehension in the code enforcement community about the safety of the batteries. Education coordinated with fire and safety services will help alleviate concerns and increase confidence in the acceptance of innovative technologies. • Opportunities to further leverage and advance the guides and related resources include outreach, education, and jurisdictional support; updates to the resources to align with code cycle changes and local requirements; and advancements supporting emerging technologies.

14 SOLAR ENERGY↗
DOE OSTI2025

Assessment of Naturally Occurring Radioactive Material (NORM) in Illicit Drugs Using High-Resolution Gamma Spectroscopy

This report documents results assessing the presence of Naturally Occurring Radioactive Material (NORM) in illicit drugs using high-resolution gamma spectroscopy. Specifically, high-purity germanium (HPGe) measurements were conducted at the Drug Enforcement Administration (DEA) South Central Laboratory on 11 samples (referred to as exhibits) including cocaine, fentanyl, heroin, ketamine, LSD, marijuana, methamphetamines, psilocybin mushrooms, and synthetic cannabinoids.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2025

A Block-Structured Adaptive Mesh Framework to Solve Radiation Transfer Equation in Irregular Embedded Geometries

Radiation transport arises in various scientific, industrial, and medical fields, and understanding its effect in applications is needed to make accurate predictions, safety assessments and performance optimizations. Solving the Radiation Transport Equation (RTE) is challenging due to its integro-differential nature, which involves both differential and integral terms. The differential term describes the change in radiation intensity due to absorption and emission, while the integral term accounts for scattering. The accurate modeling of radiation is further complicated in many applications due to the complex, irregular geometries. Various methods exist for solving the RTE, including the zonal, Monte Carlo, spherical harmonics, discrete ordinates, and finite volume methods. Traditional mesh-based approaches, which rely on structured or unstructured meshes, struggle with irregular geometries due to: a) the difficulty of conforming structured grids to irregular domains, b) challenges in enforcing boundary conditions correctly, and c) the additional computational cost of unstructured mesh methods. This work presents a second-order accurate method for solving the RTE in irregular geometries. The radiation intensity is discretized using the finite-volume method in both spatial and angular directions on regular Cartesian grid blocks. Leveraging the block-structured adaptive mesh refinement (AMR) framework provided by AMReX, our method refines the grid locally to reduce spatial discretization error, ensuring a converged numerical solution while minimizing computational costs elsewhere. A two-stage deferred correction approach is employed: First, a first-order discretization on grid blocks is solved using an algebraic multigrid method in HYPRE. Second, a correction term is applied explicitly to achieve second-order accuracy. The correction term is calculated by approximating the radiation flux on cell faces using a Total Variation Diminishing (TVD) scheme. This approach ensures quick convergence of the multigrid method while preserving higher-order accuracy of the numerical solution. Irregular geometries are resolved as embedded boundaries (EB), resulting in both cut cells and regular cells. In cut cells, we modify the fluxes using face fractions and incorporate additional contributions from EB boundary conditions. To ensure higher-order convergence near the EB interface, the correction term is modified by interpolating the radiation intensity to fictitious ghost points. The implementation takes advantage of modern supercomputers by leveraging AMReX’sMPI/X parallelization strategy where X can be MPI or a GPU accelerator including CUDA, HIP and DPC++. We validate our solver using classical test cases, both with and without EB, demonstrating accuracy and efficiency. Additionally, we analyze the impact of adaptive mesh refinement on solution accuracy and computational cost, highlighting the advantages of our approach for high-resolution radiation transport simulations.

computational fluid dynamics (CFD)↗
DOE OSTI2025

HD ADOPT: Heavy-Duty Vehicle Choice Model Documentation

HD ADOPT is a logit consumer vehicle choice and stock model that analyzes the Class 8 tractor market. The model projects future technology shares, fuel consumption, and greenhouse gas (GHG) emissions under input assumptions of technology progress, energy prices, and policies. ADOPT is distinguished from other vehicle choice models through inclusion of non-linear and heterogenous consumer preferences and characterization of the full range of market options rather than use of composite vehicles. In addition, ADOPT has integrated vehicle simulation capabilities that enable performance assessment and optimization of endogenous technology evolution. Optionally, the model is able to adjust this evolution to enforce compliance with fuel economy and GHG emissions regulations. Primary results include projection of technology shares and future in-use fleet energy demand, petroleum consumption, and GHG emissions. This enables analysis and comparison of future scenarios of technology improvements, economic conditions, and national policies. Recent new features for the HD modeling also enable examination of different on-board hydrogen fuel storage technologies from the lens of consumer preferences for vehicle cost and range. This report documents current ADOPT capabilities and methodologies.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Improved Weld Residual Stress Modeling System in BlackBear

This report presents enhancements to the MOOSE-based BlackBear application aimed at improving its capability to simulate welding and other thermo-mechanical manufacturing processes. Two primary avenues of improvement are pursued. First, to enhance user accessibility, we introduce a centralized default block restriction mechanism that ensures coverage checks are performed within user-specified default blocks. This default setting is applied consistently to all block-describable objects, such as variables, kernels, and more. In addition, we develop a modular action for moving heat source simulations, which integrates path file parsing, subdomain modification, and heat source kernel enforcement into a single, streamlined configuration. Second, to improve solver robustness, we implement an alternative method for assigning initial conditions to the updated active domain during the simulation, thereby enhancing convergence behavior. To validate the framework, we design and conduct several benchmark simulations, including heat conduction with progressive material addition, linear elasticity with time-dependent material deposition, and viscoplasticity model with isotropic hardening under similar conditions. Finally, we demonstrate the effectiveness of the proposed framework through large-scale thermo-mechanical welding simulations in both two and three dimensions.

42 ENGINEERING↗
DOE OSTI2023

Fusion Centers and State Energy Stakeholders: Pathways to Robust Threat Information Sharing

Threats to our nation’s critical infrastructure are escalating in frequency and sophistication. It is essential for public and private sectors to join forces to understand the threats, mitigate risks, and plan to respond and recover from disruption. Fusion centers — organizations purpose-built to facilitate communication and cooperation between federal, state, local, and territorial law enforcement entities — are well-positioned to play a pivotal role in this context. Although fusion centers historically focused on crime and terrorism, there is a need to engage more broadly and build stronger threat information sharing relationships among energy stakeholders within their states.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2025

Regulatory Considerations for Domestic Reprocessing Facility Physical Security

U.S. advanced non-light-water reactor vendors may pursue collocated on-site reprocessing activities. Therefore, these facilities are likely to possess formula quantities, or Category I quantities, of special nuclear material (SNM) during normal operations. The U.S. Nuclear Regulatory Commission (U.S. NRC) has yet to formally establish a regulatory framework for commercial reprocessing. While Category I requirements would explicitly not apply in this circumstance under current regulatory requirements, regulatory certainty does not exist. A novel framework should be developed to ensure public health and safety while also risk-informing the physical security requirements. This report reviews the relevant background of related rulemaking activities and proposes risk-informed physical protection requirements to satisfy these objectives. Insights from NRC security-related rulemaking activities provide a substantial technical basis to approach potential establishment of physical security requirements for reprocessing facilities. If a licensee can provide justification that the material satisfies a sufficient self-protecting radiation dose threshold, the material may not be subject to theft or diversion requirements and only potential sabotage requirements would apply. Furthermore, if the material can be justified to be moderately dilute, a set of risk-informed requirements could provide adequate protection of public health and safety. A revised performance objective for prevention of theft of moderately dilute Category I SNM may be detection to allow prompt recovery by a local law enforcement agency. However, a significant caveat to the proposed categorization scheme is the unknown integration of radiological sabotage with requirements for the protection against theft. Future licensees should consult with the NRC regarding treatment of this regulatory topic. Additionally, the self-protecting radiation dose threshold (either the existing or a proposed future threshold) would need to be considered. An integrated approach may apply graded potential requirements for protection against the design basis threat of radiological sabotage currently applicable to commercial nuclear power plants and Category I SNM facilities defined within 10 CFR 73.1(a).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗