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DOE OSTI2023

SAS4A/SASSYS-1 Version 5.7 and 5.6 Release Notes

SAS4A/SASSYS-1 (SAS) is a simulation tool used to perform deterministic analyses of anticipated events as well as design basis and beyond design basis accidents for advanced liquid-metal-cooled nuclear reactors. In this report, the major developments that were implemented in Versions 5.7 and 5.6 are summarized and an overview of all changes made between versions is presented. SAS Version 5.7 and 5.6 introduced a number of modeling improvements that allow users to capture important phenomena, such as pump heating and metallic fuel performance.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

CTF Validation and Verification: Version 4.3

Coolant-Boiling in Rod Arrays- Two Fluids (COBRA-TF) is a thermal/hydraulic (T/H) simulation code designed for light water reactor (LWR) analysis. It uses a two-fluid, three-field (i.e., fluid film, fluid drops, and vapor) modeling approach. Both subchannel and 3D Cartesian forms of nine conservation equations are available for LWR modeling. The code was originally developed by Pacific Northwest Laboratory in 1980 and has been used and modified by several institutions over the last several decades. COBRA-TF is also used at the Pennsylvania State University (PSU) by the Reactor Dynamics and Fuel Modeling Group (RDFMG) and has been improved, updated, and subsequently became the CTF. One part of the improvement process includes validating the methods in CTF. This document seeks to provide a certain level of certainty and confidence in the predictive capabilities of the code for the scenarios it was designed to model—rod bundle geometries with operating conditions that are representative of prototypical pressurized water reactor (PWR)s and boiling water reactor (BWR)s in both normal and accident conditions. This is done by modeling a variety of experiments that simulate these scenarios and then presenting a qualitative and quantitative analysis of the results that demonstrates the accuracy to which CTF is capable of capturing specific quantities of interest.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

CTF Theory Manual: Version 4.3

Coolant-Boiling in Rod Arrays—Two Fluids (COBRA-TF) is a thermal/hydraulic (T/H) simulation code designed for light water reactor (LWR) vessel analysis. It uses a two-fluid, three-field (i.e., fluid film, fluid drops, and vapor) modeling approach. Both subchannel and three-dimensional Cartesian forms of its governing equations are available for the solution. The code was originally developed by Pacific Northwest Laboratory in 1980, and had been used and modified by several institutions over the last few decades. COBRA-TF also found use at the Pennsylvania State University (PSU) by the Reactor Dynamics and Fuel Modeling Group (RDFMG) and has been improved, updated, and subsequently rebranded as CTF. CTF was later adopted in the early 2010s by Oak Ridge National Laboratory (ORNL) for use in the Consortium for Advanced Simulation of Light Water Reactors (CASL) program, which led to a significant advancement of the code software quality, modeling accuracy, testing systems, and capabilities for improved support of modeling of common LWR nominal and transient behavior. As part of the improvement process, it was necessary to generate sufficient documentation for the public domain code which had lacked such material upon being adopted by RDFMG. This document serves as a theory manual for CTF, detailing the many two-phase heat transfer, drag, and important accident scenario models contained in the code, as well as the numerical solution process utilized. Additional documents available in the CTF documentation suite include the user manual and verification and validation manual.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

MST e-News Summer 2023

David Andersson (Materials Science in Radiation and Dynamic Extremes, MST-8) is the recipient of the 2023 American Nuclear Society (ANS) Mishima Award. The award recognizes outstanding contributions of an individual in research and development work on nuclear fuels and materials. Andersson is a staff scientist on MST-8’s Modeling of Radiation Effects team. An expert in atomistic modeling of nuclear fuels—both traditional UO 2 light water reactor fuel and advanced accident tolerant fuel concepts—he has been involved in numerous international and national multiscale simulation efforts to develop models for use in nuclear fuel performance simulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Determination of Average Burnup in AGR-3/4 Compacts 1-4 and 7-4

The Advanced Gas Reactor (AGR) Fuel Development and Qualification Program third and fourth irradiation experiments (AGR-3/4), originally planned as separate tests, were combined in one test train for irradiation in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). The irradiation test began on December 14, 2011, and ended on April 12, 2014 (Collin 2016). The originally planned AGR-3 and AGR-4 irradiation experiments were both focused on obtaining data on fission product transport to support the improvement of modeling. The AGR-3 experimental plan was focused on gaseous and metallic fission product release from the kernels and diffusion in the coatings during irradiation and post-irradiation safety testing. The AGR-4 experimental plan was focused on diffusivities and sorptivities in the compact matrix and reactor graphite. These two goals were combined in the AGR-3/4 irradiation, which consisted of 12 independently monitored capsules that each contained four AGR-3/4 compacts in a single stack surrounded by an inner ring of matrix or graphite and an outer ring of graphite. Two capsule types were used: a standard capsule and a so-called fuel body, in which the outer graphite ring included a floor and cap that fully enclosed the fuel. The fuel body design supported post-irradiation safety testing of the intact fuel and ring assembly to provide data on fission product transport and release from the matrix and graphite at accident temperatures.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Expansion of Hazards and Probabilistic Risk Assessments of a Light-Water Reactor Coupled with Electrolysis Hydrogen Production Plants

This report builds upon the body of work sponsored by the Department of Energy (DOE) Light-Water Reactor Sustainability (LWRS) Flexible Power Operation and Generation (FPOG) program that presented generic probabilistic risk assessments (PRAs) for the addition of a heat extraction system (HES) to light-water reactors to support the co-location of a high temperature hydrogen electrolysis facility (HTEF). Probabilistic and deterministic hazards assessments and risk analyses are leveraged throughout this report. Several improvements and new analyses are included in this report. First, higher amounts of detail in the specifications of the generic HTEFs are used to produce scaled results for a 100, 500, and 1000 MW nominal hydrogen production facility. An additional hazard assessment of 1000 kg of hydrogen storage is performed. The facility hazards and footprint are assessed to determine the safe distance required for placement near the nuclear power plant (NPP). Second, specific designs for corresponding HESs for the different levels of support required by the HTEFs are analyzed in the PRA model. Third, a hazards analysis of the specified HTEFs leads not only to effects of the quantified risk assessment for the NPP, but also qualitative hazards assessment for the community. Finally, a seismic analysis and a high winds analysis have each been added to the PRA. The results investigate the applicability of the potential licensing approaches which do not require a full United States (U.S.) Nuclear Regulatory Commission (NRC) licensing review. The PRAs are generic and include listed assumptions. The HTEF design built for this project has further eliminated many conservative assumptions from the prior PRAs in this series. The PRA results indicate that the 10 CFR 50.59 licensing approach is justified due to the minimal increase in initiating event frequencies for all design basis accidents, with none exceeding 7.7%. The PRA results for core damage frequency and large early release frequency support the use of NRC Regulation Guide 1.174 as further risk information that supports a change without a full licensing amendment review. The hazard analyses and PRA confirm the need for engineered blast barriers of storage tanks and the common production header leaving the HTEF. The hazards analyses and PRA also confirm with high confidence that using the assumptions of design in this report that the safety case for licensing an HES addition and an HTEF sited with its unprotected high-pressure stage components 187 meters from the NPP’s transmission towers (the most fragile structure, system, and component) is strong.

08 HYDROGEN↗

DOE OSTI2023

Advanced Simulation and Computing: ASC FY24 Implementation Plan

The DOE National Nuclear Security Administration (NNSA) Stockpile Stewardship Program (SSP) is an integrated technical program for maintaining the safety, security, and reliability of the U.S. nuclear stockpile. The SSP incorporates nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. The suite of data analyzed comes from activities including previous nuclear tests, stockpile surveillance, experimental research, and development and engineering programs. This integrated national program requires the continued use of experimental facilities and the computational capabilities to support the SSP missions. These component parts, in addition to an appropriately scaled production capability, enable NNSA to support stockpile requirements. The ultimate goal of the SSP, and thus of the Advanced Simulation and Computing (ASC) program, is to ensure that the U.S. maintains a safe, secure, and effective strategic deterrent. The ASC program is a cornerstone of the SSP, providing simulation capabilities and computational resources to support the annual stockpile assessment and certification process, study advanced nuclear weapons design and manufacturing processes, analyze accident scenarios and weapons aging, and provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This work requires a balance of resources, including technical staff, hardware, simulation software, and computer science solutions. The ASC program focuses on increasing the predictive capabilities in a three-dimensional (3D) simulation environment while maintaining support to the SSP. The Program continues to improve its unique tools for understanding and solving progressively more difficult stockpile problems (sufficient resolution, dimensionality, and scientific details), and quantifying critical margins and uncertainties. Resolving each issue requires increasingly difficult analyses because the aging process has progressively moved the stockpile further from the original test base. While the focus remains on the U.S. nuclear weapons program, where possible, the Program also enables the use of high-performance computing (HPC) and simulation tools to address broader national security needs, such as foreign nuclear weapon assessments and nuclear counterterrorism. The 2022 Nuclear Posture Review (NPR) calls for NNSA to “deliver a modern, adaptive nuclear security enterprise based on an integrated strategy for risk management, production-based resilience, science and technology innovation, and workforce initiatives.” Furthermore, “NNSA will establish a Science and Technology Innovation Initiative to accelerate the integration of science and technology (S&T) throughout its activities.” Executing this strategy necessitates the continued emphasis on developing and sustaining high-quality scientific and engineering staff, as well as supporting computational and experimental capabilities. These components constitute the foundation of the nuclear weapons program. The continued success of the SSP and LEPs is predicated upon the ability to credibly certify the stockpile, without a return to underground nuclear tests (UGTs). Shortly after the nuclear test moratorium entered into force in 1992, the Accelerated Strategic Computing Initiative (ASCI) was established to provide an extensive simulation capability to underpin stockpile certification. While computing and simulation have always been essential to the success of the nuclear weapons program, the program goal of ASCI was to execute NNSA’s vision of using these tools in support of the stockpile stewardship mission. The ASCI program was essential to the successful demonstration of the SSP, providing critical nuclear weapons simulation and modeling capabilities. ASCI officially evolved into the ASC program in fiscal year (FY) 2005, but the mission remains essentially the same: provide the simulation and computational capabilities that underpin the ability to maintain a safe, secure, effective nuclear weapon stockpile, without returning to underground nuclear testing. The capabilities that the ASC program provides at the national laboratories play a vital role in the nuclear security enterprise and are necessary for fulfilling the stockpile stewardship and life extension requirements outlined for NNSA. The Program develops modern simulation tools that provide insights into stockpile aging issues, provide the computational and simulation tools that enable designers and analysts to certify the current stockpile and life-extended nuclear weapons, and inform the decision-making process when any modifications in nuclear warheads or the associated manufacturing processes are deemed necessary. Furthermore, ASC is enhancing the predictive simulation capabilities that are essential to evaluate weapons effects, design experiments, and ensure test readiness. The ASC program continues to improve its unique tools to solve stockpile problems— with a focus on sufficient resolution, dimensionality, and scientific detail—to enable Quantification of Margins and Uncertainties (QMU) and to resolve the increasingly difficult analyses needed for stockpile stewardship. The needs of the Stockpile Management and Production Modernization programs (formerly Directed Stockpile Work) also drive the requirements for simulation and computational resources. These requirements include planned LEPs, stockpile support activities, and mitigation efforts against the potential for technical surprise. All of the weapons within the current stockpile are in some stage of the life extension process. The simulation and computational capabilities are crucial for successful execution of these life extensions and for ensuring NNSA can certify these life-extended weapons without conducting a UGT.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Development of Plant Reload Optimization Framework Capabilities for Core Design and Fuel Performance Analysis

The United States (U.S.) nuclear industry faces a challenge in maintaining required levels of safety while ensuring economic competitiveness to stay in business. Safety remains a key parameter for all aspects of light water reactor (LWR) nuclear power plant (NPP) operations. Safety can become more economical by using a risk-informed ecosystem, such as the one being developed by the Risk-Informed Systems Analysis (RISA) Pathway under the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program. The LWRS Program promotes a wide range of research and development activities with the goal of maximizing both the safety and economic efficiency of NPPs through improved scientific understanding, especially given many plants are now considering second license renewals. The RISA Pathway has two main goals: (1) deploy methodologies and technologies that better represent safety margins and cost and safety factors and (2) develop advanced applications that enable cost-effective plant operation. The Plant Reload Optimization Platform development project aims to build a reactor core design tool that includes reactor safety and fuel performance analyses, and also uses artificial intelligence to support optimization of core design solutions. This report summarizes Fiscal Year 2022 (FY-22) activity in platform capability developments in RAVEN. This platform performs simulations using industry codes for core design (i.e., PARCS) and fuel performance (i.e., TRANSURANUS) which will allow expansion of the capabilities to include advanced fuel designs such as accident-tolerant fuel (ATF)s with high burnup.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Differences In High Burnup Fuel Management Strategies to Minimize FFRD and Increase Economic Viability

The nuclear industry is pursuing approval of an increase in the length of the pressurized water reactor (PWR) cycle from 18 months to 24 months to reduce reactor downtime and enhance the economic competitiveness of nuclear energy. Such an increase in reactor cycle length will require that the maximum rod average burnup exceeds the current regulatory limit of 62 GWd/MTU, and it could peak at approximately 75 GWd/MTU, posing potential reactor safety and performance concerns. One such concern is that fuel fragmentation, relocation, and dispersal (FFRD) could occur during a severe loss-of coolant accident (LOCA) in which a fuel rod balloons and bursts, and pulverized fuel fragments are dispersed throughout the reactor’s primary coolant system. Previous analyses have identified which reactor operating conditions leave the core more susceptible to FFRD and have shown that FFRD susceptibility is strongly linked to fuel rod burnup and linear heat rate (LHR) history. The work described in this report uses an optimization strategy known as parallel simulated annealing (PSA) and a coarse mesh Purdue Advanced Reactor Core Simulator (PARCS) reactor physics model to develop two core fuel loading patterns, each with a different optimization objective. One core optimization maximized the core’s cycle length while still respecting regulatory limits on the radial peaking factor and soluble boron concentration with a peak rod average burnup of 75 GWd/MTU. The second optimization was aimed at minimizing FFRD susceptibility while still targeting a 24-month cycle length and respecting regulatory limits. PARCS model predictions were verified using the high-fidelity Virtual Environment for Reactor Applications (VERA). The two core designs were compared to highlight core design strategies to minimize FFRD susceptibility and to maximize economic viability.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

AFC FY 2023 HFIR Irradiation Test Matrix – Supported by the Design of a Ring Specimen Irradiation Vehicle

The development and deployment of accident-tolerant cladding materials in light water nuclear reactors requires the collection of neutron-irradiated properties of these materials with specific consideration to the material properties orientation (i.e., tube geometry). To that end, a test plan to irradiate several cladding tube and ring specimens in the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL) was proposed, along with the development of a new capsule design that features ring specimens with a preexisting gauge section. This ring specimen geometry removes the need to machine a gauge section on the irradiated specimen and thus allows for direct application of a ring-pull test post-irradiation. The test matrix includes uncoated and chromium-coated Zircaloy-4 and advanced zirconium alloy cladding specimens, pre-characterized at ORNL. Plans are to irradiate the specimens at about 4 and 10 dpa—corresponding to two and five cycles at the HFIR centerline—with a target specimen gauge section temperature of 330°C.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Status Report on Regulatory Criteria Applicable to the Use of Artificial Intelligence (AI) and Machine Learning (ML)

Although the interest in the use of artificial intelligence (AI) and machine learning (ML) in nuclear energy is increasing rapidly, at present their implementation is limited. This rapid increase in interest is not surprising considering that implementing AI and ML technology would allow for continuous monitoring, facilitate the implementation of predictive maintenance with optimized staffing plans, enable automation and autonomy opportunities that could drastically reduce fixed operation and maintenance costs, and provide training for operations and maintenance. Other industries are using AI for construction, and in the nuclear arena AI could provide great benefit in decommissioning activities. The ability of AI and ML to operate in real time vastly increases their potential impact. Before AI can be used in design, operations, or as a regulatory tool, the specifics on the regulations applicable to the use of AI for nuclear power applications need to be established. The difficulty is that the specific use cases will dictate the applicability of regulations. For example, even within the application domain associated with operations, the regulations might vary if the AI is used to create a virtual reference for plant operations or is used for training, optimization of maintenance intervals, prioritization of maintenance activities, etc. Different still is if the AI is to be used for design or setting technical specifications, which will introduce additional requirements. US Nuclear Regulatory Commission (NRC) licensing reviews are based on an applicant’s design meeting its performance assessment based on (1) safety goals and objectives, (2) deterministic and/or probabilistic analysis of accident scenarios, and (3) quantitative assessment of design alternatives against the safety goals and objectives using accepted engineering tools, methodologies, and performance criteria. The current regulatory framework does not explicitly address AI or autonomous control. However, as implementing AI technology will require the use of a digital platform, it must meet the requirements of an instrumentation and control (I&C) system. The regulatory requirements for AI, which will be incorporated into the I&C system, will be very dependent on how it is used (i.e., its functionality, safety classification, etc.). The licensing process is primarily risk-based with the identification of components and systems as nonsafety, important to safety, or safety related. A risk-informed approach allows further gradation of components and systems based on risk metrics such as core damage frequency or large early release fractions. Thus, the use cases and the risk categorization of impacted systems and components will determine the regulatory requirements. Regardless of how AI is used it presents new opportunities for risk-informing operating, maintenance, and regulatory decisions. Trustworthiness, transparency, and the ability to validate and verify the results will be paramount in showing that the systems and plant still meet their performance requirements. This report describes the results of research to identify regulatory implications of AI technologies and their uses. Specifically, this report reviews current regulatory guidance relevant to the application of AI for design (including design changes or new designs including advanced reactors), construction, operations, training, maintenance, research, testing, and as a regulatory tool. AI can be automated at different levels from purely informative purposes to autonomous controls. The focus of this review included determination of constraints on the application of AI technology, identification of any regulatory gaps or uncertainties, and clarification of anticipated technical basis information likely to be important for regulatory acceptance of these technologies. Currently, any use of AI at nuclear power plants is focused on nonsafety-related applications. The NRC and other regulatory bodies are evaluating providing guidance to address gaps rather than create new regulations to address the use of AI and ML. This approach seems to be the best to encourage AI development without adding regulatory uncertainty.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

FY23 Progress on Computational Modeling of the Water-Based NSTF

This report summarizes the system-level modeling effort by Argonne National Laboratory (Argonne) of the Natural convection Shutdown heat removal Test Facility (NSTF) in FY23. As a continuation of the modeling effort from FY22, this year’s work focuses on improving the RELAP5-3D model developed previously for two-phase flow simulations. The RELAP5-3D model is updated to more accurately capture the heat loss experienced by the facility. The updated model is compared against experimental data for benchmarking purposes of the RELAP5-3D input model. By correctly accounting for heat loss, the updated RELAP5-3D model can now predict the two-phase baseline case more accurately. The onset and the duration of instability are captured well by the model. Furthermore, analyses are performed to better understand the instability mechanism experienced by the flow where the expansion of the boiling boundary in the chimney is studied in details and the fundamental frequencies of the oscillations are obtained. The updated RELAP5-3D model is further compared against four fault conditions, namely the reduction of riser header inlet flow area, depletion of system inventory, blocked riser channels, and static boiling scenario. For each fault condition, minor modifications and tuning are performed to improve the predictions of the model. The purpose of the analyses is to investigate the capability of RELAP5-3D in predicting complex two-phase flows in possible accident scenarios in actual Reactor Cavity Cooling System (RCCS). Overall, the model is able to capture the behaviors and trends of these fault conditions relatively well. Some discrepancies remain between the experimental data and the predictions, many of which are likely due to the differences in the predicted and experimental vapor generation rate. Future work will focus on the continued development of the current RELAP5-3D input model of the NSTF to both improve the accuracy of the model’s predictive capability and continue supporting the experimental program needs. The mutually beneficial relationship between analysis and experimental efforts has become integral to the parent NSTF program, and the greater objective to fully understand and accurately predict the heat removal performance of a full scale RCCS concept.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

Demonstration of the Plant Fuel Reload Process Optimization for an Operating PWR

The United States (U.S.) nuclear industry is facing a strong challenge to maintain regulatory-required levels of safety while ensuring economic competitiveness to stay in business. Safety remains a key parameter for all aspects related to the operation of light water reactor (LWR) nuclear power plants (NPPs) and can be achieved more economically by using a risk-informed ecosystem such as that being developed by the Risk-Informed Systems Analysis (RISA) Pathway under the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program. The LWRS Program is promoting a wide range of research and development (R&D) activities with the goal to maximize both the safety and economically efficient performance of NPPs through improved scientific understanding, especially given that many plants are considering second license renewal. The RISA Pathway has two main goals: (1) the deployment of methodologies and technologies that enable better representation of safety margins and the factors that contribute to cost and safety; and (2) the development of advanced applications that enable cost-effective plant operation. This report summarizes the research outcomes in FY-2021, which the project progressed from the planning and methodology development phase to the early demonstration phase. The highlights of these activities are: (1) the development of a multi-objective optimization process using Genetic Algorithms (GAs); (2) the development and test of an approach for optimization process acceleration using artificial intelligence (AI) that significantly reduces the computational burden; (3) the demonstration of the fuel reload optimization framework for a generic pressurized water reactor (PWR); and (4) the demonstration of limiting design basis accident (DBA) scenarios for evaluation of the transition from deterministic to risk-informed approach for fuel reload optimization.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Advanced Modeling and Simulation to Characterize Advanced Boiling Water Reactor Source Terms to Support a Regulatory Approval Pathway for Right-Sized Emergency Planning Zone. Advanced Boiling Water Reactor (A-BWR) Project Phase 2

The United States Department of Energy (US DOE) is currently supporting the development of various small modular reactor (SMR), microreactor and advanced reactor designs. These reactors have improved safety features as compared to conventional Large Light Water Reactors (LLWRs), which include features that improve potential reduction of radiological source terms in the event of design and beyond-design basis accidents. Specifically, some reactors feature a relatively smaller containment volume with respect to the available surface area for fission product deposition; these include Integrated Pressurized Water Reactors (iPWRs), such as the NuScale SMR and SMR-type Boiling Water Reactors (BWRs) such as General Electric-Hitachi’s BWRX-300 design.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

Compare predictions of transient fission gas release by empirical and mechanistic models to experiments in high burnup UO 2 fuel

Understanding and predicting fuel performance at high burnup require improving our understanding of transient fission gas release. High-burnup operations enable new mechanisms of fission gas release, which affect fuel performance. The Nuclear Regulatory Commission has recently published its interpretation of existing fuel fragmentation, relocation, and dispersal data in a research information letter. There, transient fission gas release was identified as one of the main factors that contributes to fuel fragmentation, relocation, and dispersal, and therefore limits fuel extension to high burnup. However, transient fission gas release is a complex phenomenon that cannot be fully described by simple empirical descriptions. This report summarizes the development of a mechanistic model for high-burnup transient fission gas release in the fuel performance code BISON. This research was supported by the Nuclear Energy Advanced Modeling and Simulation program during fiscal year 2023 to improve our understanding of high-burnup transient fission gas release and ability to predict it as a function of operation history. To support the development of a mechanistic transient fission gas release model, the existing Simple Integrated Fission Gas Release and Swelling (Sifgrs) model in BISON has been completely refactored to make it more modular and extensible. This effort supports the model's application to high-burnup conditions, its extension to other fuel forms, and the continuous improvement of its current features. Once refactoring was completed, models for high-burnup structure formation, fission gas transfer from non-restructured fuel to high-burnup structure, high-burnup structure intragranular and intergranular fission gas behavior, high-burnup structure bubble evolution, fuel pulverization, and the resulting transient fission gas release were tested and implemented in the Simple Integrated Fission Gas Release and Swelling (Sifgrs) model or tightly coupled to it. The new mechanistic model was then compared to an empirical model developed in parallel by a Nuclear Energy University Program project using a Studsvik high-burnup loss-of-coolant-accident assessment case. Finally, the report details the preliminary BISON results for a benchmark activity organized by the Nuclear Energy Agency to evaluate fuel performance codes' predictive capabilities for burst fission gas release. This work represents an important step toward a mechanistic understanding of fission gas release in high-burnup conditions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

CTF Validation and Verification: Version 4.4

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Semi-Annual Report for Horizontal Compact High Temperature Gas Reactor (HC-HTGR) Development during Performance Period April 2023 – September 2023

Horizontal Compact High Temperature Gas Reactor (HC-HTGR) is being designed by a multi-disciplinary team of nuclear, mechanical, and structural engineers under the support of a DOE-NE Advanced Reactor Demonstration Program’s Advanced Reactor Concepts-20 (ARC-20) award. The objective of this ARC-20 project is to deliver a conceptual design for the proposed HC-HTGR in 3 years and support its commercialization as a safe, low-cost HTGR. Argonne National Laboratory (Argonne) is responsible for the design and analysis of the reactor cavity cooling system (RCCS) as a safety system for passive decay heat removal of the reactor concept. Additionally, Argonne is providing analysis of the primary coolant system to ensure temperatures within the core remain below safety margins during steady-state and potential accident scenarios. This fourth semi-annual report summarized the progress made at Argonne on the two tasks during the second half of FY23. As a part of the RCCS design task, recent efforts have been made to complete a conceptual design of the RCCS for the HC-HTGR, including the design update of the water panel and system configuration favorable in point of view of fabrication and system operation. Design calculations were conducted under various heat load conditions to validate the system design. Transient simulations using RELAP5-3D were conducted to investigate system dynamics under transients of interest and to evaluate the system performance in the design condition. The results demonstrated the overall system feasibility that the RCCS design maintains structures temperatures lower than maximum allowable temperature with sufficient system inventory without any active heat sink. In the primary system thermal hydraulics task, the preliminary analysis was performed for a long term pressurized conduction cooldown (PCC) transient. This analysis used a combination of a fully resolved and coarse homogenized mesh to predict the temperature distribution for the steady-state initial condition and the PCC transient. The steady-state initial condition was determined using a fully resolved full core model with 3D solid to 1D fluid coupling. The fully resolved mesh was also used to model the first 20 seconds of the PCC. The temperature difference between fuel pins and the graphite matrix becomes minimal and the dominant heat transfer shifts to a larger scale radially towards the RCCS. After 20 seconds, a homogenized coarse mesh is used, greatly reducing the computational costs of the model. These results demonstrate that the core is designed to passively remove enough decay heat in a protected loss of primary coolant flow to prevent an unsafe rise of core temperatures.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

Evaluation of Thermal Neutron Scattering Cross Section of Uranium Silicide with Ab Initio Lattice Dynamics

Uranium silicide (U 3 Si 2 ) is a candidate material for the high-density nuclear fuel in commercial light water reactors [1], [2]. Its higher uranium density, 11.3 g-U/cm3, compared to that of uranium dioxide (UO 2 ), 9.7 g-U/cm3, can improve the performance of a nuclear reactor while using low enriched uranium (LEU) and diversify the choice of cladding materials [1]–[3]. It also has a higher thermal conductivity than UO 2 , which can reduce the thermal stress on the material caused by a temperature gradient across the fuel pellet and provide a larger margin for some postulated accidents [1], [2], [4]. Furthermore, compared to U3Si, another high-density fuel candidate, it has better resistance to in-pile swelling due to less irradiation-induced rapid amorphization [1], [3]. Corresponding to its importance in nuclear engineering, many previous studies have reported the properties of U3Si2. Experiments showed that U 3 Si 2 is a paramagnetic (PM) metal, where a slight linear increase in magnetic susceptibility was measured with increasing temperature [5], [6]. In addition, thermodynamic quantities such as thermal expansion coefficient, heat capacity, and thermal conductivity were experimentally determined over a wide temperature range [1], [7], [8]. In several computational studies, ab initio atomistic simulations based on density functional theory (DFT) were performed to calculate various properties including elastic constants, electronic density of states (DOS), and phonon dispersion curves [9]–[12]. Nevertheless, thermal neutron scattering cross sections, which are critical to the prediction of the parameters in reactor physics that are ultimately related to reactor criticality, have not yet been evaluated for U3Si2. The scattering cross section can be calculated from the phonon DOS, or the energy spectrum of lattice vibrations, of the crystalline system [13], [14]. However, there is also no experimental data available for the phonon DOS of U 3 Si 2 . While some computational studies reported the phonon DOS and/or dispersion curves from ab initio simulations [9]–[12], the accuracy cannot be guaranteed because it is unclear whether the spin-polarization behavior of PM U 3 Si 2 was properly described. In the present study, the thermal neutron scattering cross section for U 3 Si 2 is evaluated for the first time by calculating the phonon DOS for U3Si2 from ab initio lattice dynamics (AILD) simulations based on DFT. First, U 3 Si 2 is modeled based on the experimental structure, and AILD simulations are performed on the modeled U3Si2 to optimize the structure. Next, AILD simulations are performed for supercells with atomic displacement to calculate Hellmann-Feynman forces. Based on the calculated forces, partial phonon DOSs for U and Si are obtained, and the thermal neutron scattering law (TSL) for U 3 Si 2 is finally evaluated. To verify the accuracy of the calculations in the present study, the calculation results are compared with experimental data on the structure and heat capacity of U3Si2 [1], [7], [8], [15].

Geometry Optimization↗