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DOE OSTI2024

FORCE Update 2024

The Framework for Optimization of Resources and Economics (FORCE) tool suite is the U.S. Department of Energy’s Nuclear Integrated Energy Systems (IES) Program flagship tool suite for technoeconomic IES analysis of IES. This tool suite is useful for analysis designed to evaluate and improve the technoeconomics of energy production systems, particularly for systems including nuclear technology. In this report, we document the development activity for the FORCE tool suite to extend its capabilities as performed during fiscal year 2024. In addition to reliability and accessibility, capability is one of the three standards guiding the development of the FORCE tool suite and the software codes that are its constituent parts. Extending the capabilities of the FORCE tool suite allows analysis both within the IES program as well as industry, university, and laboratory partners to perform analysis with more accuracy, insight, and impactful narrative. Four areas of capability development were the focus of activity this year: economic parameter uncertainty quantification, multiresolution analysis, components-to-optimization workflow automation, and statespace construction workflows for real-time optimal control. In economic parameter uncertainty quantification, the ability of HERON to capture risk due to scenarios (weather and energy demand uncertainty) was expanded to also include uncertainties in financial parameters such as capital cost or operation and maintenance costs. By including these sources of uncertainty, which are sometimes very large compared with scenario uncertainty, HERON is better able to capture the risk posed by investment in various IES technology. Because of this, analysts can also consider the reduction in risks that can be realized by choice of some technologies. In multiresolution analysis, development activity extended on work completed previously. In fiscal year 2023, methods for decomposing time series signals, such as demand, solar and wind availability, and price profiles, were analyzed and down-selected to those most effective at splitting signals into different resolutions. These resolutions allow considering the influence of different energy demand and supply behaviors across different time scales. For example, energy demand might be divided into seasonal, weekly, and hourly profiles. In fiscal year 2024, this preliminary work was extended and implemented within the Risk Analysis Virtual Environment (RAVEN) risk and uncertainty analysis platform, which is used throughout the FORCE framework. This development of the “multi-resolution time series analysis” (MR-TSA) module in RAVEN allows training synthetic history generators on complex time series. These synthetic history generators can then be used in HERON for generating scenarios that represent possible market and weather scenarios that can be analyzed on different time scales. We envision completing this work in the future, implementing multiresolution dispatch optimization strategies that can make the most beneficial use of these stratified time histories. In components-to-optimization workflow development, workflows for translating user inputs of components into algorithms for algebraic optimization were selected and implemented. Similar algorithms within the Holistic Energy Resource Optimization Network (HERON) were separated from the main code base of HERON and gathered with the components-to-optimization workflows in the new Dispatch Optimization Variable Engine (DOVE) software library. This modularization allows FORCE users to analyze dispatch optimization and energy system duty cycles independently of HERON, which previously was a burdensome task. Additionally, these dispatch optimization algorithms, set up in an independent library, can now be used across all software applications within FORCE, especially including the real-time optimal control software Optimization of Real-time Capacity Allocation (ORCA). Allowing FORCE software to share dispatch optimization algorithms within a single library allows for improved software maintenance and reliability. In statespace characterization workflow development, alternative workflows for optimizing dispatch with additional technical accuracy was the focus, particularly to improve the real-time optimization decision making in ORCA. Using algorithms and workflows initially developed for the Feasible Actuator Range Modifier (FARM), workflows for determining the statespace representation of IES were identified and demonstrated. The resulting dispatch optimization required a more robust optimization algorithm than that originally used in HERON (and moved to DOVE), which required adding an alternate workflow to DOVE that can more accurately match the behavior of physical systems using a partial differential equation representation. In conclusion, capability developments in the FORCE tool suite in fiscal year 2024 have improved the ability of the FORCE tool suite to perform

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Summary of Technical Peer Review on the Risk Assessment Framework proposed in Report INL/RPT-22-68656 for Digital Instrumentation and Control Systems

This report summarizes the peer review activities initiated by Idaho National Laboratory (INL) during fiscal year (FY) 2023 for the evaluation and improvement of the methodology developed under the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk Informed Systems Analysis (RISA) Pathway, digital instrumentation and control (DI&C) risk assessment project. In FY 2019, the RISA Pathway initiated a project to develop a risk assessment strategy for delivering a technical basis to support effective and secure DI&C technologies for digital upgrades/designs. A framework was proposed for this strategy, which aims to (1) provide a best-estimate, risk-informed capability to quantitatively and accurately estimate the risk impact of plant modernization, considering the introduction of high safety-significant safety-related (HSSSR) DI&C systems, (2) support and supplement existing risk-informed DI&C design guides by providing quantitative risk information and evidence, (3) offer a capability of design architecture evaluation of various DI&C systems, (4) assure the long-term safety and reliability of HSSSR DI&C systems, and (5) reduce uncertainty in costs and support integration of DI&C systems in the plant. The R&D efforts of this project from FY 2019 through FY 2022 were focused on methodology improvement and demonstration of the proposed framework for the risk assessment and design optimization of safety-critical DI&C systems. Collaborations with the nuclear industry have been initiated to support the reliability and risk assessment of their DI&C systems by using the proposed framework. In FY 2023, the framework has reached to a point for a technical peer review and obtain stakeholder feedback. This peer review activity includes coordination of the reviews performed by a group of industry stakeholders, documentation of the peer review suggestions, providing resolutions and responses to the peer review comments. The objective of this technical peer review is to obtain representative feedback on the proposed framework to improve the technical qualities of its methodology and readiness for deployment to the industry. Feedback may identify potential areas for improvement and further development. The Subject Matter experts were invited to review the latest project report documenting the methodology developed in the project and provide evaluations of the technical qualities of the proposed framework and relevant methods. The reviewed project report is “An Integrated Framework for Risk Assessment of High Safety-significant Safety-related Digital Instrumentation and Control Systems in Nuclear Power Plants: Methodology and Demonstration” INL/RPT-22-68656 (short as “INL/RPT-22-68656” in this report). This peer review report documents the technical questions provided for technical peer review and introduces the technical peer reviewers from the stakeholders including nuclear utilities, regulators, and universities. Comments from technical peer reviewers and the resolutions and responses to these comments are outlined. Insights and lessons learned from the technical peer review are summarized in conclusions and future work. The primary audience of this report are DI&C designers, engineers, and probabilistic risk assessment (PRA) practitioners. This includes stakeholders, such as the nuclear utilities and regulators who consider the deployment and upgrade of DI&C systems, DI&C software developers and reviewers, and cybersecurity specialists.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Joint Design of Multimodal Transit Networks and Shared Autonomous Mobility Fleets

Providing quality transit service to travelers in low-density areas, particularly travelers without personal vehicles, is a constant challenge for transit agencies. The advent of fully-autonomous vehicles (AVs) and their inclusion in mobility service fleets may allow transit agencies to offer better service and/or reduce their own capital and operational costs. This study focuses on the problem of allocating resources between transit patterns and operating (or subsidizing) shared-use AV mobility services (SAMSs) in a large metropolitan area. To address this question, a joint transit network redesign and SAMS fleet size determination problem (JTNR-SFSDP) is introduced, and a bi-level mathematical programming formulation and solution approach are presented. The upper-level problem modifies a transit network frequency setting problem (TNFSP) formulation via incorporating SAMS fleet size as a decision variable and allowing the removal of bus routes. The lower-level problem consists of a dynamic combined mode choice-traveler assignment problem (DCMC-TAP) formulation. The heuristic solution procedure involves solving the upper-level problem using a nonlinear programming solver and solving the lower-level problem using an iterative agent-based assignment-simulation approach. To illustrate the effectiveness of the modeling framework, this study uses traveler demand from Chicago along with the regions existing multimodal transit network. The computational results indicate significant traveler benefits, in terms of improved average traveler wait times, associated with optimizing the joint design of multimodal transit networks and SAMS fleets compared with the initial transit network design.

bi-level programming↗
DOE OSTI2023

An Integrated Framework for Risk Assessment of Safety-related Digital Instrumentation and Control Systems in Nuclear Power Plants: Methodology Refinement and Exploration

This report documents activities performed by Idaho National Laboratory (INL) during Fiscal Year (FY) 2023 for the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk Informed Systems Analysis (RISA) Pathway, digital instrumentation and control (DI&C) risk assessment project. In FY 2019, the RISA Pathway initiated a project to develop a risk assessment strategy for delivering a technical basis to support effective, and secure DI&C technologies for digital upgrades/designs. A risk assessment-informed framework was proposed for this strategy, which aims to (1) provide a best-estimate, risk informed capability to quantitatively estimate the safety margin obtained from plant modernization, especially for safety-related DI&C systems, (2) support and supplement existing risk informed DI&C design guides by providing quantitative risk information and evidence, (3) offer a capability of design architecture evaluation of various DI&C systems, (4) assure the long-term safety and reliability of safety-related DI&C systems, and (5) reduce uncertainty in costs and support integration of DI&C systems in the plant. To achieve these technical goals, the LWRS-developed framework provides a means to address relevant technical issues by: (1) defining a risk informed analysis process for DI&C upgrade that integrates hazard analysis, reliability analysis, and consequence analysis, (2) applying risk informed tools to address common cause failures (CCFs) and quantify corresponding failure probabilities for DI&C technologies, particularly software CCFs, (3) evaluating the impact of digital failures at the component level, system level, and plant level, and (4) providing insights and suggestions on designs to manage the risks, thus to support the development and deployment of advanced DI&C technologies in nuclear power plants (NPPs). Adding diversity within a system or components is the primary means to eliminate and mitigate CCFs, but diversity also increases system complexity and may not address all sources of systematic failures. Optimization of diversity and redundancy applications for the safety-critical DI&C systems remains a challenge. To deal with the technical issues in addressing potential software CCFs in safety-related DI&C systems of NPPs and supporting relevant design optimization, the proposed framework provides: (a) A best-estimate, risk informed capability to address new technical digital issues quantitatively, focusing on software CCFs in safety-related DI&C systems of NPPs; (b) A common and a modularized platform for DI&C designers, software developers, cybersecurity analysts, and plant engineers to predict and prevent risk in the early design stage of DI&C systems; (c) Technical bases and risk informed insights to assist users address the risk informed alternatives for evaluation of CCFs in safety-related DI&C systems of NPPs; and (d) A risk informed tool that offers a capability of design architecture evaluation of various DI&C systems to support system design decisions in diversity and redundancy applications. The research and development efforts of this project in FY 2023 are focused on refining current methods on software CCF modeling and estimation and exploring additional innovative approaches to risk assessment of DI&C systems to enable a more comprehensive and complete assessment of various safety-related DI&C design architectures. The primary audience of this report are DI&C designers, engineers, and probabilistic risk assessment (PRA) practitioners. This includes stakeholders, such as the nuclear utilities and regulators who consider the deployment and upgrade of DI&C systems, DI&C software developers and reviewers, and cybersecurity specialists. It should be noted that all the analyses are performed for the demonstration of the methodology, not for the evaluation of an actual digital control system. Results are obtained based on limited design information and testing data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

An Integrated Framework for Risk Assessment of High Safety Significant Safety-related Digital Instrumentation and Control Systems in Nuclear Power Plants: Methodology and Demonstration

This report documents the activities performed by Idaho National Laboratory (INL) during Fiscal Year (FY) 2022 for the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk Informed Systems Analysis (RISA) Pathway, digital instrumentation and control (DI&C) risk assessment project. In FY 2019, the RISA Pathway initiated a project to develop a risk assessment strategy for delivering a technical basis to support effective and secure DI&C technologies for digital upgrades/designs. A framework was proposed for this strategy, which aims to (1) provide a best-estimate, risk-informed capability to quantitatively and accurately estimate the risk impact of plant modernization, considering the introduction of high safety-significant safety-related (HSSSR) DI&C systems, (2) support and supplement existing risk-informed DI&C design guides by providing quantitative risk information and evidence, (3) offer a capability of design architecture evaluation of various DI&C systems, (4) assure the long-term safety and reliability of HSSSR DI&C systems, and (5) reduce uncertainty in costs and support integration of DI&C systems in the plant. To achieve these technical goals, the framework provides a means to address relevant technical issues by: (1) defining a risk-informed analysis process for DI&C upgrade, that integrates hazard analysis, reliability analysis, and consequence analysis, (2) applying risk-informed tools to address common cause failures (CCFs) and quantify corresponding failure probabilities for DI&C technologies, particularly software CCFs, (3) evaluating the impact of digital failures at the component level, system level, and plant level, and (4) providing insights and suggestions on designs to manage the risks, thus to support the development and deployment of advanced DI&C technologies on nuclear power plant (NPPs).

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Optimal Design of Food Packaging Considering Waste Management Technologies to Achieve Circular Economy

Plastic packaging plays a fundamental role in the food industry, avoiding food waste and facilitating food access. The increasing plastic production and the lack of appropriate plastic waste management technologies represent a threat to the environmental and human welfare. Therefore, there is an urgent need to identify sustainable packaging solutions. Circular economy (CE) promotes reducing waste and increasing recycling practices to achieve sustainability. In this work, we propose a CE framework based on multi-objective optimization, considering both economic and environmental impacts, to identify optimal packaging designs and waste management technologies. Using mixed-integer linear programming (MILP), techno-economic analysis (TEA), and life cycle assessment (LCA), this work aims to build the first steps in packaging design, informing about the best packaging alternatives and the optimal technology or technologies to process packaging waste. For the economic analysis, we consider the minimum increase in price (MIP) when adding recycling to the cost of each packaging solution, while for the environmental analysis, the greenhouse gas emissions impact was considered. A case study on ground coffee packaging is used to illustrate the proposed framework. The results demonstrate that the multilayer bag option is the most convenient when considering both the chosen economic and environmental impacts.

Life Cycle Analysis↗
DOE OSTI2021

International Collaboration Activities in Geologic Disposal Research: FY2021 Progress

This report describes the FY21 status of international collaboration regarding geologic disposal research in the Spent Fuel and Waste Disposition (SFWD) Campaign. Since 2012, in an effort coordinated by Lawrence Berkeley National Laboratory, SFWD has advanced active collaboration with several international geologic disposal programs across the world. Such collaboration has allowed the SFWD Campaign to benefit from a deep knowledge base in regards to alternative repository environments developed over decades and has provided a framework for active peer-to-peer research participation in international groups which conduct, analyze, and model performance-relevant processes. Via international collaboration, the SFWD Campaign also benefits from substantial international investments in research facilities (such as underground research laboratory testing and modeling) and achieves cost savings via joint funding of expensive field experiments. To date, SFWD’s International Disposal R&D Program has established formal collaboration agreements with multiple international initiatives and various international partners, and national lab scientists associated with SFWD have conducted a large number of specific collaborative R&D activities that align well with its R&D priorities.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

A Deep Generative Model for Non-Intrusive Identification of EV Charging Profiles

The proliferation of electric vehicles (EVs) brings environmental benefits and technical challenges to power grids. An identification algorithm which can accurately extract individual EV charging profiles out of widely available smart meter measurements has attracted great interests. This paper proposes a non-intrusive identification framework for EV charging profile extraction, which is driven by deep generative models (DGM). First, the proposed DGM is designed as a representation layer embedded into the Markov process and used to model the joint probability distribution of available time-series data. A novel contribution is to approximate posterior distributions by neural networks whose parameters are obtained by variational inference and supervised learning. Second, the EV charging status is inferred from the DGM via dynamic programming. Lastly, the desired EV charging profile can be reconstructed by the rated power of EV models and inferred status. Compared with the benchmark Hidden Markov Models, the proposed framework can better handle noise in data with less computational complexity and better overall accuracy performances with smaller recall. The proposed framework is validated by numerical experiments on the Pecan Street dataset.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Spatially and Temporally Detailed Water and Carbon Footprints of U.S. Electricity Generation and Use

Electricity generation in the United States entails significant water usage and greenhouse gas emissions. However, accurately estimating these impacts is complex due to the intricate nature of the electric grid and the dynamic electricity mix. Existing methods to estimate the environmental consequences of electricity use often generalize across large regions, neglecting spatial and temporal variations in water usage and emissions. Consequently, electric grid dynamics, such as temporal fluctuations in renewable energy resources, are often overlooked in efforts to mitigate environmental impacts. The U.S. Department of Energy (DOE) has initiated the development of resilient energyshed management systems, requiring detailed information on the local electricity mix and its environmental impacts. This study supports DOE's goal by incorporating geographic and temporal variations in the electricity mix of the local electric grid to better understand the environmental impacts of electricity end users. We offer hourly estimates of the U.S. electricity mix, detailing fuel types, water withdrawal intensity, and water consumption intensity for each grid balancing authority through our publicly accessible tool, the Water Integrated Mapping of Power and Carbon Tracker (Water IMPACT). While our primary focus is on evaluating water intensity factors, our dataset and programming scripts for historical and real-time analysis also include evaluations of carbon dioxide (equivalence) intensity within the same modeling framework. This integrated approach offers a comprehensive understanding of the environmental footprint associated with electricity generation and use, enabling informed decision-making to effectively reduce Scope 2 water usage and emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

GriddingMachine, a database and software for Earth system modeling at global and regional scales

Land and Earth system modeling is moving towards more explicit biophysical representations, requiring increasing variety of datasets for initialization and benchmarking. However, researchers often have difficulties in identifying and integrating non-standardized datasets from various sources. We aim towards a standardized database and one-stop distribution method of global datasets. Here, we present the GriddingMachine as (1) a database of global-scale datasets commonly used to parameterize or benchmark the models, from plant traits to vegetation indices and geophysical information and (2) a cross-platform open source software to download and request a subset of datasets with only a few lines of code. The GriddingMachine datasets can be accessed either manually through traditional HTTP, or automatically using modern programming languages including Julia, Matlab, Octave, Python, and R. The GriddingMachine collections can be used for any land and Earth modeling framework and ecological research at the regional and global scales, and the number of datasets will continue to grow to meet the increasing needs of research communities.

58 GEOSCIENCES↗
DOE OSTI2021

Hybrid Imitation Learning for Real-Time Service Restoration in Resilient Distribution Systems

Self-healing capability is a critical factor for a resilient distribution system, which requires intelligent agents to automatically perform service restoration online, including network reconfiguration and reactive power dispatch. Here, the article proposes the imitation learning framework for training such an agent, where the agent will interact with an expert built based on the mixed-integer program to learn its optimal policy, and therefore significantly improve the training efficiency compared with exploration-dominant reinforcement learning (RL) methods. This significantly improved training efficiency makes the training problem under N-k scenarios tractable. A hybrid policy network is proposed to handle tie-line operations and reactive power dispatch simultaneously to further improve the restoration performance. The 33-bus and 119-bus systems with N-k disturbances are employed to conduct the training. The results indicate that the proposed method outperforms traditional RL algorithms such as the deep-Q network.

42 ENGINEERING↗
DOE OSTI2021

Home Energy Professionals Certifications ISO/IEC 17024: 2021 Policies and Procedures Manual

The U.S. Department of Energy (DOE) enlisted its National Renewable Energy Laboratory (NREL) to coordinate the development of a framework for new certifications in the weatherization and home performance industry. The Home Energy Professional certifications support DOE's Weatherization Assistance Program (WAP) and the broader residential home performance industry through the credentialing process of defined job task analysis for energy auditors and quality control inspectors. The HEP certifications are not intended to supplant or infringe upon any existing industry-recognized credentials, however, the WAP and the home performance industry have utilized the advanced HEP certifications to promote quality work and standardized job task analysis since 2010. On an ongoing basis, NREL brings industry practitioners and subject matter experts together to develop, review, and revise the certification schemes in accordance with the International Organization for Standardization (ISO)/International Electrotechnical Commission (IEC) 17024 standard, "Conformity assessment - General requirements for bodies operating certification of persons" (ISO/IEC 17024). This handbook covers the policies and procedures for the process of developing, maintaining, and validating the certification schemes. Each policy and procedure includes the relevant ISO/IEC 17024 section at the beginning.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Report Outlining Computed Tomography Strategy and Microscopy Approach to Qualifying AM 316 Materials

This report is part of work package CR-22OR0406012, Automated, High-Throughput Materials Characterization Techniques , under the Advanced Materials and Manufacturing Technologies program (AMMT). The project’s primary objective is to leverage our AI-based rapid and high-throughput automated characterization framework to qualify additively manufactured 316 materials comprehensively, focusing on optimizing the additive manufacturing process and evaluating the performance of 3D-printed stainless steel components. This report outlines our strategy for leveraging the automated characterization process for qualifying 316H materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Effect of Lateral Conduction in a Rectangular Fuel Plate and Optimum Stripe Widths for the OPAL Reactor

The impetus for this work is the Proliferation Resistance Optimization (PRO-X) program, which was created by the National Nuclear Security Administration (NNSA) of the US Department of Energy (DOE) to provide a framework for developing reactor designs that minimize the production of special nuclear materials while maximizing performance for peaceful uses. The Argentine company INVAP and Argonne National Laboratory collaborated to share knowledge and expertise regarding the thermal analysis of research reactors. Working together, they designed a series of test problems based on the Open Pool Australian Light Water (OPAL) reactor, whose fuel is in the form of flat plates cooled by water flowing through narrow rectangular channels. ANL used their PLTEMP/ANL code. INVAP used their TERMIC code (and its new multi-plate version, TERMIC-MP). Then, INVAP and ANL compared the two sets of results. 1-D models were used during the collaboration since for research reactor analysis, largely 1-D thermal-hydraulics models are commonly used because they are simple to apply and technically defendable. The collaboration between the two organizations aims for improvements in thermal-hydraulic models. Improvements to methods and models can reduce modeling uncertainties and excessive conservatism, allowing greater reactor performance without reducing predicted safety margins. Therefore, these improvements potentially expand the design space, making additional designs feasible, which, in turn, may achieve better fuel utilization and proliferation resistance in the designs. This report provides justification for the lateral node size (stripe width) chosen for the 1-D computer models during the collaboration. The lateral heat conduction in OPAL fuel plates is evaluated using the two-dimensional conduction capability of PLTEMP/ANL to determine a representative hot-stripe width that can be conservatively used for one-dimensional steady-state thermal-hydraulic analysis. Basically, a representative hot-stripe width needs to be selected so that the actual heat flux averaged over this stripe width is greater than or equal to the maximum heat flux obtained by the two-dimensional analysis. Detailed results in this report show that a hot-stripe width of 8.125 mm can be conservatively used for the one-dimensional thermal-hydraulics analysis of all plates. Therefore, eight equal stripes (8.125 mm each) are recommended to be modeled in the MCNP and PLTEMP/ANL full core models of the OPAL reactor.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Silicon Carbide Composite Cladding Qualification

This report examines the process to qualify a new fuel-cladding type focusing on the data requirements and types of irradiation testing necessary to meet the regulatory burden and related guidance applicable to fuel qualification of accident-tolerant fuel. The report considers the use of accelerated fuel qualification techniques and lead-test specimen programs that may shorten the timeline for qualifying fuel for use in a nuclear reactor at the desired burnup. The assessment framework particularly emphasizes the identification of key fuel manufacturing parameters, the specification of a fuel performance envelope to inform testing requirements, the use of evaluation models in the fuel qualification process, and the assessment of the experimental data used to develop and validate the empirical models and empirical safety criteria.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

QUCODE: End-to-End Qubit Co-Design

The design of a quantum computer can be broken down into different steps, e.g., the material science aspect of designing qubits and devices, considerations of controlling the state of the qubits and their environment, the computer science aspects of mapping algorithms to the available primitives of the quantum computer, and the programming of an application in terms of the available algorithms. Research in these areas is currently fairly isolated, and there is framework for an end-to-end design approach where a desired application informs the choice of materials for the qubits and their environment, and vice versa.We identify knowledge gaps and opportunities for research that builds on existing PNNL capabilities.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Cyclotron Road Partnership (CRADA Final Report)

The Cyclotron Road program was launched in 2015 by LBNL, with support from the DOE Advanced Manufacturing Office (AMO), to accelerate technical innovation in the energy sector. The program brought scientist-entrepreneurs to LBNL to access unique research assets and expertise. In 2016, LBNL partnered with Activate Global, Inc., a 501(c)(3) non-profit, to expand the program and provide enhanced access to capital and business support services. Under this Cooperative Research and Development Agreement (CRADA), LBNL provided technical support and expertise, while Activate engaged with private sector, philanthropic, and government partners to support innovators and research-phase small businesses, aiming to translate high-impact materials and manufacturing technologies from lab to market. The program received funding from various sponsors, including the DOE, DARPA, and the California Energy Commission, and was managed through a collaborative framework that maintained accountability by the participant organization and Berkeley Lab regarding roles and tasks relevant to this collaboration.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

SAM Finite Volume Method Development Status Update: GCR Application, Restart, and MultiApp

The System Analysis Module (SAM) is being developed as a modern system analysis code for advanced non-light-water-reactor safety analysis under the U.S. DOE NEAMS program. Previous feasibility studies have demonstrated that a staggered-grid finite volume method (SG-FVM), implemented under the MOOSE framework, can deliver more than an order of magnitude speedup over the existing continuous Galerkin finite element method (CG-FEM) solver for liquid-cooled, incompressible but thermally expandable flow systems. This work extends the previous effort to compressible, gas-cooled reactor applications, where pressure couples directly into the mass equation adding additional nonlinearity into the equation system. New code capabilities are implemented for pebble bed high-temperature gas-cooled reactor (PB-HTGR) analysis, including a pebble bed CoreChannel component, built-in pebble bed effective thermal conductivity model and channel-to-channel crossflow model. The capabilities are tested, benchmarked, and demonstrated for problems with increased level of model and physical complexities, including the HTTU effective thermal conductivity test, the SANA passive cooling test, and a demonstration case using the GPBR200 reactor design covering steady-state operation, DLOFC and PLOFC transients. Across all cases, the SG-FVM solver demonstrated strong robustness and efficiency, and the solutions agree well with reference results and data. The finding of this work proves that SG-FVM is a viable and efficient solver pathway for compressible, gas-cooled reactor system analysis in SAM. In addition, work has been done to successfully support SAM-FVM recover/restart code feature that is essential to reactor safety analysis applications, and MultiApp code feature that is essential to multi-scale and multi-physics simulations. In summary, this work continued from previous feasibility studies, and further demonstrated that the SG-FVM will serve as a strong foundation for SAM’s advanced solver algorithm for future deployment.

Zou, Ling↗