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The Meaning of Risk for Safety, Security, and Safeguards in the Design of Advanced Nuclear Reactors

What is the meaning of risk as it applies to the design of advanced reactors in the disciplines of safety, security, and safeguards? How can we find common terminology for the concept of risk and how can we find interfaces between these disciplines? These are important questions that should be explored in order that they may be applied in an integrated manner for the most effective and efficient design approaches. Eliminating or minimizing risks is a key design driver that motivates and informs the development of nuclear reactors. For safety, risk is well understood and applied in Probabilistic Risk Assessments. For security, the risk-based concepts of vulnerability assessments and vital areas are all considered in designing security systems. For safeguards, the concept of risk is not formally defined, as it relates to the design and operation of nuclear reactors. International nuclear safeguards seek to reduce the risk of proliferation in the nuclear fuel cycle and as such the concept of risk does exist. Therefore, the current understanding of the “3S’ approach, which seeks to find the interfaces and conflicts between safety, security, and safeguards requires a thorough understanding of the role that the reduction of risk plays in all three disciplines. The intersection of risk for safety and security is now being developed as there is a strong correlation between reactor design and operations and their vulnerability to sabotage. The intersection of risk for security and safeguards has to date chiefly been focused on the nuclear material control and accounting systems, which are relied on by both the operator (State) and the IAEA. This paper explores the concept of risk in each of the three disciplines, how they interact, potential conflicts and interfaces , how these might be addressed and leveraged, and a notional framework for how this could be achieved.

Kovacic, Donald N↗

Methods and system for siting advanced nuclear reactors and evaluating energy policy concerns

There is a growing sociopolitical desire to develop cleaner energy sources in the United States and maintain energy security. Regardless of politics, many coal-fired electric plants have already been shut down and many utilities are vowing to retire their current coal-fired assets within the next two decades. Replacement power assets require consideration of appropriate siting. A geographic information system (GIS)-based multicriteria decision analysis approach is useful to assist utility and energy companies, as well as policymakers, to evaluate potential areas for siting new plants in the contiguous United States. A GIS-based framework is simply a database of location information that allows for mapping, querying, modeling, and analyzing data based on location. The spatial output can be structured to be visual, allowing for easier analysis of location data. The need to site additional power assets, including renewable resources and clean power sources, such as nuclear, led to the development of the Oak Ridge Siting Analysis for power Generation Expansion (OR-SAGE) tool discussed in this paper. The tool takes inputs such as population growth, water availability, environmental indicators, and tectonic and geological hazards to provide an in-depth visual analysis for siting options. Energy companies and other stakeholders can use OR-SAGE to procure feedback quickly and effectively on land suitability based on technology specific inputs. Policymakers can use OR-SAGE to analyze the impacts of future energy technology decisions, while balancing competing resource use. Overall, this paper discusses the recent use of OR-SAGE for these purposes and plans for future development.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Quantifying Capital Cost Reduction Pathways for Advanced Nuclear Reactors

The framework developed in this study is provided both as an excel sheet (https://inl.gov/content/uploads/2023/11/Nuclear-Reactor-Cost-Reduction-Pathway-Spreadsheet-Tool.xlsx) and a Python (Jupyter) Notebook (link: https://github.com/accert-dev/ACCERT/tree/main/Cost%20Reduction). Capital cost considerations are one of the primary inhibitors to the large-scale deployment of nuclear power plants. While it is widely accepted that first units will likely be expensive and relatively uncompetitive, it is reasonable to expect that subsequent units, built in relative quick succession, will be cheaper as they benefit from the so-called “learning effects”. However, the large degree of uncertainty associated with this parameter renders it challenging for first movers to invest in the first few expensive units. To resolve this impasse, the U.S. Department of Energy’s Advanced Nuclear Liftoff study advocated for the formation of large, committed order books of plants of the same technology to spread the costs across several units and kickstart the nuclear supply chain. The study also advocated best practices for avoiding overruns and keeping reactors on budget. This report builds on these key recommendations by attempting to quantify specific pathways toward cost reduction for nuclear energy. A capital cost estimation framework was built to untangle the effect of learning into a subset of key cost drivers, referred to as “levers”. Collectively, the choice of these levers is intended to reflect the decision-making of high-level stakeholders like plant owners and the government. In addition to the size of the firm orderbook, these levers included (a) cost drivers that are most often attributed to cost overruns such as architect/engineering (A/E) proficiency, construction proficiency, procurement service proficiency, design completion prior to the start of construction, and design maturity, and (b) cost reduction strategies such as modular construction, cross-site standardization, safety classification of the reactor building, and of the balance of plant. Two advanced reactor designs were leveraged as use cases and bottom-up cost estimates made with assumptions consistent with a well-executed first-of-a-kind project (WE-FOAK, i.e., almost no overruns) were used as baselines for the models. Cost correlations were surveyed from the literature to determine the impact of important variables on projected timelines and costs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Integration of a Wigner effect-based energy storage system with an advanced nuclear reactor

In this work, an innovative energy storage concept based on the purposeful creation of defects in crystalline material by neutron irradiation is presented. Lattice defects are generated when heavy particles collide with the atoms in a crystal structure, i.e., if the incoming particles have enough energy, recoil atoms are displaced from their initial lattice sites. Most of the displaced atoms will eventually combine with nearby vacancies, but some of them will come to rest in non-ideal locations. The energy held by displaced atoms is called Wigner energy. Lattice defects can migrate and form clusters, and the Wigner energy can be released from these groupings if sufficient activation energy is provided. In the nuclear industry, this effect is well-known since it represented an issue for graphite-moderated reactors. This work presents the conceptual design of an engineering system that exploits this physical process to store the energy of neutrons in advanced reactor concepts. In the first part of the paper, the theoretical performance of an energy storage system based on the Wigner effect is described. Given the lattice properties and the compatibility with the harsh reactor environment, graphite was selected as the candidate material for the irradiation targets. Both experimental data and molecular dynamics simulations confirmed that this system can achieve performance comparable with state-of-the-art batteries in terms of stored energy density. In the second part of the paper, the engineering challenges of this innovative technology and the proposed solutions are described. After defining the optimal irradiation conditions, the different steps of the operation of the proposed energy system (from energy storing to energy harvesting) were defined. Finally, the integration of this concept with advanced reactor designs, i.e., a Sodium-cooled Fast Reactor and a Molten Salt-cooled Reactor, was investigated and the corresponding performance was evaluated.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Uncertainty estimation of bifurcated solutions in the Rayleigh–Bénard problem for advanced nuclear reactors applications

Multiphysics models of nuclear reactors frequently comprise nonlinear systems of equations. The nonlinear nature of these models could lead to solution bifurcations, where a small change in a certain parameter, e.g., the thermophysical properties of the coolant, can lead to a sudden change in the system’s behavior. At the point in parameter space where this happens, called a critical point, the Jacobian matrix of the model’s nonlinear operator becomes singular potentially permitting multiple solutions to coexist. In this paper, we perform uncertainty estimation (UE) in a parameter range that includes bifurcated solutions within the context of Rayleigh–Bénard problem. We perform this analysis assuming uncertain temperature difference, and tilt angle for the iterative solution algorithm with a unit Prandtl number (Pr = 1). Also, we perform this analysis under uncertain thermophysical properties for both FLiBe molten salt and liquid sodium as working fluid. We deploy two approaches to compute statistical moments for the resulting distributions of selected flow-field variables. The first approach is the blind computation of the mean and the standard deviation without any consideration of solution bifurcation, while the second approach utilizes k-means clustering to cluster each branch’s solutions together and compute separate statistical moments for each branch. The statistical distributions are obtained by perturbing the selected parameters about nominal values that correspond to a solution on one of the valid branches, and that solution is used as initial guess for the iterative solution algorithm. We found that perturbation of any parameter when its nominal value is close to its critical point always leads to branch jumping, i.e., the iterations converge to a solution on a branch different from the branch of the initial guess. This produces a statistical ensemble comprised of fundamentally different solutions leading to wrong mean values and uncertainty estimates, whereas clustering provides an efficient way to deal with this type of computation. This work is important for developing Gen IV nuclear systems because many of these systems rely on natural convection for cooling especially in accident conditions.

97 - MATHEMATICS AND COMPUTING↗

Conceptual Design of Temperature-Controlled Fueled-Salt Irradiation Experiment to Support Demonstration of Advanced Nuclear Reactors

The irradiation testing of fuel-bearing molten salts is critical to supporting the development and demonstration of molten salt reactors (MSRs). These experiments can inform several important reactor design and safety parameters, including source term modeling, evolution of thermophysical properties with burn-up, and the degradation of structural materials under reactor relevant conditions. Idaho National Laboratory is designing an instrumented and heated high temperature molten salt-fueled irradiation capsule to study the behavior of the fuel salt during in-pile irradiation. This paper details the neutronics, thermal, and mechanical analysis performed to-date. Parametric studies are performed to assess a range of material, different experiment dimensions, two in-reactor positions, and the fuel enrichment used. Principal recommendations are to opt for a peripheral reactor position to alleviate neutronic constraints, a thin salt annulus to alleviate thermal constraints, and high-temperature alloys that provide additional safety margins.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Status Report 2: Advanced Nuclear Reactors Utilized for Synthetic Fuel Creation

Synthetic fuels (synfuels) are hydrocarbon fuels that source energy from electricity. Synfuels have the potential to significantly reduce greenhouse gas emissions throughout the transportation sector. To achieve this substantial reduction in greenhouse gas emissions, the electricity must be sourced from zero- or near-zero-carbon fuel sources such as solar, wind, hydroelectricity, and nuclear power. Synfuels are produced from a combination of carbon and hydrogen sources. Hydrogen can be sourced from water electrolysis with near-zero-carbon electricity and heat (e.g., nuclear), while carbon dioxide can be sourced from ethanol and ammonia plants. In the hydrocarbon fuel synthesis process, hydrogen and carbon dioxide can be reacted to produce carbon monoxide and water, via the so-called reverse watergas shift reaction. Carbon monoxide can then react with additional hydrogen to form hydrocarbons, with carbon chains ranging from C1–C30 in the reaction known as the Fischer-Tropsch (F-T) synthesis reaction. The synthesized hydrocarbon molecules can then be hydro-processed with additional hydrogen and distilled into different carbon chain lengths so as to be compatible with existing conventional gasoline, jet, and diesel fuels. Carbon-free synfuel production comes with a “green premium” over the manufacture of identical products via conventional fossil fuels. Reports from Argonne National Laboratory (ANL) reveal that hydrogen costs dominate the cost of carbon-free synfuel production. This suggests that for the cost of green synfuel to approach that of conventional petroleum fuel, the cost of hydrogen must be approximately $\$1$/kg. Of the primary low-carbon energy sources, only nuclear carries the potential to produce hydrogen at below $\$2$/kg. (Still a bit above the lofty $\$1$/kg goal, but perhaps manageable). To further identify the potential for creating low-cost synfuels capable of competing with legacy technologies, the Department of Energy Office of Nuclear Energy has funded a multi-program, multi-lab effort among ANL, Idaho National Laboratory (INL), the Integrated Energy Systems (IES) program, and the Light Water Reactor Sustainability (LWRS) program. This collaboration effort will determine the possibility of using current and next generation nuclear reactors to create low-cost carbon-free synfuels for sale in the U.S. energy and commodities market.

10 SYNTHETIC FUELS↗

Development of Refractory Alloys and Refractory Coatings for Advanced Nuclear Reactors

The next generation of nuclear reactors will benefit from materials that enable operation at higher temperatures (>500°C), higher irradiation doses (up to 200 displacements per atom (dpa)), and the use of more corrosive and reactive coolants. This work package represents the first experimental steps towards a longer-term effort to develop refractory materials for nuclear energy applications which will enable operation under these conditions. Specifically, this work package focuses on additive manufacturing of refractories as both a refractory liner coating deposited onto the interior surface of a metallic tubular backbone and as bulk refractory alloys. During fiscal year 23 (FY23), several refractory metal coating systems and bulk alloys were examined and selected using a decision criteria matrix. The refractory metal coating systems included molybdenum, tungsten, and zirconium as refractory coatings on backbones of either carbon-carbon (C/C) or silicon carbide-silicon carbide (SiC/SiC) ceramic matrix composites. The bulk refractory alloys included C-103, WTa, and WNiFe as bulk alloys. During FY24 additional bulk refractory alloys and metallic backbones were evaluated using the decision criteria matrix based on input from the AMMT leadership team. These included 316 SS and 316H SS for the metallic backbones and Mo-La, Ta, and Nb1Zr as bulk refractory alloys. The primary focus for the FY24 effort was placed on establishing the capabilities to deposit refractory coatings based on the results of the scoring in the decision criteria matrix and finalizing the additively manufactured TZM studies which were incorporated into the AMMT program from the microreactor program. Further efforts were dedicated to establishing the capabilities to additively manufacture down-selected bulk refractory alloys.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

PMDT: AI-Enabled Predictive Maintenance Digital Twins for Advanced Nuclear Reactors

Our team made substantial technical progress on various fronts during the course of the program. Multiple milestones were geared towards demonstrating the feasibility of machine learning based predictive maintenance digital twins towards reducing O&M costs, whereas some other milestones actually focused on identifying technical gaps and developing technologies such as humble AI to provide necessary robustness to the ML-based models. We were able to demonstrate in many cases that Machine learning-based methods can be successfully adapted for Nuclear plant environments especially for remote monitoring applications. Detailed analyses were carried out with plant and full scope simulation data along with capabilities of enhanced analytics to assess and set realistic expectations on cost reductions in O&M. These assessments are paving the way for investments towards reactor design improvements as well project planning for SMR projects as they develop and mature in the next few years. Technology developed under this program got direct visibility to GE Hitachi and their utility customers and resulted in positive intents to deploy some of the elements from design phase. The project additionally resulted in several reports, publications, software and data generation that will be useful in deployment and O&M services for BWRX300 fleets.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Thermal Hydraulic Modeling of an Advanced Nuclear Reactor using open-source MOOSE tools

The aim of this study is to develop model of a small High Temperature Gas cooled Reactor (HTGR) including the balance of plant. This microreactor produces electricity using the thermal power of the nuclear reaction. This work utilizes the MOOSE Multiphysics simulation tools, which are mainly developed at Idaho National Laboratory (INL, Idaho, United States of America). Its thermal-hydraulics and Heat conduction Modules are used to study the fluids behavior in the primary loop and power conversion system and their interactions with the heating structures. More specifically, one verifies that the temperatures, pressures and mass flow rates of the fluids in both loops are consistent and that, at the same time, all the power transfers occur as expected. Moreover, the various mechanical components characteristics (turbine, compressor, pump) are adapted to the reactor operating conditions. This first analysis is conducted using simplified and one-dimensional model for the core. Ultimately, the obtained results are used to build a higher fidelity core model. This step aims to verify that the initial simplified simulation is consistent with the three-dimensional core modeling. In addition, the calculated material temperatures are checked. This study provides a fairly complete model of the thermal hydraulic phenomena for a particular design of High Temperature Gas cooled Reactor.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Hierarchical microstructures: a potential route to enhanced stability in structural materials for advanced nuclear reactors

The drive to increase efficiency in nuclear energy systems is leading to the need for materials that operate at higher temperatures and stress levels for extended periods, while maintaining stable microstructures to ensure their performance is not compromised. A novel route to producing materials that can perform well in such environments is the creation of hierarchical microstructures. A hierarchical microstructure is a microstructure in which features are present at multiple length scales simultaneously. In this work, a hierarchical microstructure is fabricated in a nickel-base superalloy, featuring nanometer-size gamma precipitates inside larger gamma-prime particles, which are in turn embedded in the gamma matrix phase. The hierarchical features of the microstructure lead to enhanced stability of the gamma-prime precipitates during annealing; the particle size does not follow the expected t^(1/3) growth law predicted by the classic LSW theory. Phase-field simulations are used to understand the unexpected stability of the gamma-prime precipitates.

36 MATERIALS SCIENCE↗