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Advancements in modeling fuel pulverization and cladding behavior during a LOCA

During a loss-of-coolant accident (LOCA), it is possible for nuclear fuel rods to undergo a three-step process known as fuel fragmentation, relocation, and dispersal (FFRD). The chance of FFRD occurring increases as the fuel burnup increases. To support the nuclear industry's desire to increase the discharge burnup of nuclear fuels in light-water reactors (LWRs), it is imperative to understand the mechanisms driving the evolution of FFRD. In this work, a multiscale modeling approach is used to garner insight into underlying mechanisms leading to the fine fragmentation (also known as pulverization) of nuclear fuel during a LOCA. This report includes a summary of the atomistic and phase-field studies to develop a new pulverization criterion for use in the engineering-scale Bison fuel performance code. Details are also provided on cladding model improvements related to hydrogen/hydride embrittlement and damage and anisotropic thermal creep. The new models are used on the existing integral and separate effects LOCA validation cases available in Bison.

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Advancements in modeling fuel pulverization and cladding behavior during a LOCA

During a loss of coolant accident (LOCA), there is the possibility of nuclear fuel rods to undergo a three step process known as fuel fragmentation, relocation, and dispersal (FFRD). The chance of FFRD occurring increases as the fuel burnup increases. To support the nuclear industry's desire to increase the discharge burnup of nuclear fuels in light water reactors (LWRs) it is imperative to understand the mechanisms driving the evolution of FFRD. In this work, a multiscale modeling modeling approach is used to garner insight into underlying mechanisms leading to the ne fragmentation (also known as pulverization) of nuclear fuel during a LOCA. This report includes a summary of the atomistic and phase-field studies to develop a new pulverization criterion for use in the engineering scale Bison fuel performance code. Details are also provided on cladding modeling improvements related to hydrogen/hydride embrittlement and damage, and anisotropic thermal creep. The new models are used on the existing integral and separate effects LOCA validation cases available in Bison.

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Compare Mechanistic Predictions for Doped UO 2 Mechanical Response and Other Properties with Empirical Models and Experimental Measurements

The U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation program develops predictive capabilities using computational methods for the analysis and design of advanced reactor and fuel cycle systems. This program has been supporting the development of BISON, a high-fidelity, high resolution fuel performance tool at the engineering scale. As part of its development, additional modeling capabilities and improvements have been developed for relevant fuel forms. In this work, a fuel creep deformation model for Cr-doped fuel has been implemented into BISON, along with improvements to the empirical UO 2 fuel creep model based on experimental data and improvements to the radial power factor calculation for doped fuels. This work allows for more accurate simulation analyses for both UO 2 and doped-UO 2 fuels.

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Bayesian Analysis of TRISO Fuel: Quantifying Model Inadequacy, Incorporating Lower-Length-Scale Effects, and Developing Parallel Active Learning Capabilities

The U.S. Department of Energy (DOE)’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program aims to develop predictive capabilities by applying computational methods to the analysis and design of advanced reactor and fuel-cycle systems. This program has been providing engineering-scale support for the continued development of BISON, a high-fidelity, high-resolution fuel performance tool. Fuel behavior in nuclear reactors is governed by a complex network of mechanisms that interact with various other physics aspects in the reactor system. Any model developed to represent fuel behavior will likely be idealized, resulting in uncertainties when comparing their predictions against the observed data. In Fiscal Year (FY)-23, we initiated the Uncertainty Quantification (UQ) work by using Bayesian methods to establish a level of model trustworthiness and further improve it, with a particular emphasis on TRI-Structural isOtropic (TRISO) nuclear fuel. This year, we further expanded on that UQ work by investigating an approach to quantifying model inadequacy and accounting for lower-length scale (LLS) effects in TRISO silver (Ag) release modeling. Furthermore, we are implementing parallel active learning capabilities to reduce the computational cost (i.e., required computational resources and elapsed time) of performing UQ. Specifically, we utilized The Kennedy O’Hagan framework for Bayesian uncertainty quantification (KOH) to account for model inadequacy in TRISO Ag release predictions made by BISON. The KOH framework represents an improvement over the standard Bayesian framework used in FY-23. Explicitly accounting for model inadequacy in the Bayesian framework helps establish the level of experimental noise uncertainty in the Advanced Gas Reactor (AGR) data. We compared the inverse UQ results obtained from both the standard Bayesian and KOH frameworks in light of the AGR-2/3/4 data, and also compared the predictive UQ results obtained from these two frameworks in light of the AGR-1 data. Next, we investigated the impact of considering LLS effects in the Ag release simulations. We developed an expanded database of LLS simulated effective diffusivities for Ag, covering a wide range of microstructures and temperatures. Using this database, we developed a framework for incorporating LLS effects into the engineering-scale Ag release UQ. We developed both parametric and non-parametric approaches for bridging the length scales. We then investigated the inverse UQ results in light of the AGR-2/3/4 data and the predictive UQ results in light of the AGR-1 data, and compared the LLS-informed approach and the Arrhenius equation, which does not include microstructure information. Finally, we discussed implementing parallel active learning capabilities in the Multiphysics Object Oriented Simulation Environment (MOOSE)/BISON to reduce the computational cost (i.e., computational resources and elapsed time) of Bayesian UQ. For verification purposes, we first tested these new capabil ities on a species interaction problem. We then demonstrated them on the TRISO Ag release application, showing that parallel active learning capabilities can enhance the accuracy of UQ while also substantially reducing the computational cost in comparison to the reference methods developed in FY-23.

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Modeling and Simulation of Fuel Dispersal During the Loss-of-Coolant Accident

This document is the compilation of the milestone portion to a larger end of project NEUP report. The executive summary of the modeling portion is provided below: In the event of cladding rupture during a postulated LOCA in a pressurized water reactor, fuel particles, along with fission gases, can be expelled into the reactor core from the fractured fuel rod, a phenomenon referred to as fuel dispersal. The initial stage of fuel dispersal is strongly influenced by the high-pressure ejection of fuel fragments, the size and geometry of the ruptured cladding, and the depressurization history of the fuel rod during the postulated LOCA transient. Depending on the location of the burst orifice relative to the quench front, the dispersal event represents an intricate three-phase flow and heat transfer phenomenon, where high-temperature fuel particles carried by the fission gases interact with the coolant within the narrow subchannels of the fuel assemblies, inducing localized phase change. Given the unique multiphysics nature of this phenomena, the current study develops a dedicated computational framework to predict the mass distribution and cooling of dispersing fuel particles, facilitating post-accident assessment and management of the fuel assemblies. Considering the scale of nuclear reactor applications, a continuum three-fluid model is proposed for simulating the transport of solids within the reactor core. With high-temperature fuel fragments within the liquid media, nucleation sites inducing phase changes are dispersed within the flow domain. Coupled with the fact that the transient dispersal event occurs on different time scales than other three-phase flow applications, this study derives a time-averaged three-fluid flow model without losing generality. The assumptions regarding the continuum treatment of the solid phase and the modeling of fuel dispersal behavior are incorporated to simplify the governing equations and derive applicable closure relations. The computational validation of the model was conducted using adiabatic experimental results obtained from ongoing research at Oregon State University, focusing on characterizing fuel dispersal behavior during simulated LOCA conditions. Settlement characteristics of the solids, quantified by the probability distribution of equivalent particles, closely matched the probability density functions reported in experimental studies. The transport of fuel particles within a scaled 5 × 5 lattice of a pressurized-water reactor rod bundle geometry was modeled through a two-fluid Eulerian framework. The required boundary conditions were evaluated from the fuel performance code BISON in a postulated large-break LOCA scenario. The modeling framework considered solid fuel particles as granular matter, interacting with the gaseous dry steam phase and fission gases through the governing interfacial momentum exchange between the participating fluids. The simulation results provided the volume fraction of the solids obtained at the bottom surface of the enclosing tank geometry. Postulated LOCA leading to fuel dispersal phenomena involves the strong coupling between fuel thermomechanics, cladding deformation, thermal-hydraulics, and fuel particle transport. Incorporation of such a strong coupling in numerical simulation is performed by coupling the multiphysics solvers. In the case of fuel dispersal, a strong coupled simulation can be performed by coupling the BISON code for fuel performance, the TRACE code for system-level thermal hydraulics, and fuel particle transport in Multiphysics Object-Oriented Simulation Environment (MOOSE). For such intricate infrastructure, the MOOSE Framework eases the data transfer between codes. The recent version of MOOSE has incorporated the Navier-Stokes module for the fluid flow. An exploratory exercise was done to gain familiarity with finite volume capabilities in the MOOSE framework to incorporate the Spalart-Allmaras (SA) turbulence model. New finite-volume and auxiliary kernels were introduced to assemble the SA transport equation, compute turbulent viscosity, and evaluate wall distance and diagnostic turbulence terms, fully integrated with existing Navier-Stokes modules. A turbulent lid-driven cavity at a Reynolds number of approximately 10,000 is used for verification. MOOSE shows the robust solver convergence and produces the turbulent features. But it underpredicts the velocity profile and turbulent quantities, emphasizing the need to develop improved SA near-wall treatments (e.g., low-Re corrections or wall functions) as a key direction for future work.

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High-Fidelity Modeling of Fuel-To-Coolant Thermomechanical Transport Behaviors Under Transient Conditions

This report summarizes the work completed under NEUP project number 21-24006. The objectives of this project are to advance the high-fidelity modeling capabilities and important phenomena that is important for high-burnup UO 2 and accident tolerant fuels (ATF) during transient conditions. Accurate modeling of the time-dependent phenomena that impact material performance must be used to determine the figures of merit and safety margin. Phenomena such as fuel fragmentation, cladding oxidation, pellet-clad interaction, clad ballooning, and clad rupture are examples that pose challenges to modeling during these transients. This project focused on the development of high-fidelity tightly coupled multiphysics models that can capture the time-dependent material response and associated thermal hydraulic conditions during these events. These models can then be validated against existing separate effects tests and in-pile integral experiments and will be used to model Transient Reactor Test facility (TREAT) loss-of-coolant accidents (LOCA) experiments. To achieve the project objective, we used a combination of NEAMS and NRC codes to model various LOCA test sets for the separate effects and in-pile integral experiments. BlueCRAB tool set, which can accurately predict material response at a sub-fuel pin level, as well as modeling the entire reactor system response to these events. Fuel performance was modeled using BISON (various versions) and FAST (version 1.2.1). BISON and FAST can model on a sub-fuel pin level the fuel performance under transient conditions. Both have simplified thermal hydraulic models that are capable of providing basic coolant boundary conditions. To better capture the thermomechanical interaction between the fuel, clad, and coolant, more sophisticated thermal hydraulic models are necessary.

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Accelerated fission rate irradiation design, pre-irradiation characterization, and adaptation of conventional PIE methods for U-10Mo and U-17Mo

Metallic U alloys have high U density and thermal conductivity and thus have been explored since the beginning of nuclear power research. Alloys of U with modest amounts of Mo, such as U-10 wt % Mo (U-10Mo), are of particular interest because the γ-U crystal structure in this alloying addition shows prolonged stability in reactor service. Historically, radiation data on U-10Mo fuels were collected in Na fast reactors or lower temperature research reactor conditions, but little is known about irradiation behavior, particularly swelling and creep, at irradiation temperatures between 250 and 500°C. This work discusses the methodology and pre-irradiation characterization results from a U-Mo irradiation campaign performed in the High Flux Isotope Reactor at Oak Ridge National Laboratory. U-10Mo and U-17Mo samples irradiations are being completed at temperatures ranging from 250 to 500°C to three targeted fission densities between 2 × 10 20 and 1.5 × 10 21 fissions per cubic centimeter. Swelling measurement of the specimen sizes studied here required development and assessment of new methods for volume determination before and after irradiation. Laser profilometry and X-ray computation tomography (XCT) were used to provide preirradiation characterization of samples to determine the error and applicability of each to determine swelling following irradiation. These outcomes are contextualized through use of BISON simulations performed to assess the predicted expansion of U-Mo fuels subjected to the irradiation conditions of this work. Use of existing BISON fuel performance models predicted a maximum of 7% swelling under the irradiation conditions of this study. Pre-irradiation characterization revealed the as-cast U-Mo fuel samples were uniformly large-grained fully cubic U crystals with small U-C/N bearing precipitates and pores distributed throughout. Samples were found to contain a bulk porosity between .4 and 3% because of the casting process. Local porosity in areas far from large, interconnected pores was found by Slice-and-View to be under .2%. Nanometer-sized precipitates rich in C and N were identified in all samples, likely because of impurities during the fabrication process. Dendritic bands were also observed throughout the samples. These bands were characterized by variable Mo content that deviated from the overall Mo content by 2–3 wt %. No other microstructural features were correlated to these bands. Mechanical properties were found to be slightly strengthened compared to literature reports of bulk U-Mo fuels due to the nano-scale precipitates throughout the sample.

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Modeling and simulation of hydrogen behavior in Zircaloy-4 fuel cladding

As a result of corrosion during normal operation in nuclear reactors, hydrogen can enter the zirconium-alloy fuel cladding and precipitate as brittle hydride platelets, which can severely degrade the cladding ductility. Under a heterogeneous temperature distribution, hydrides tend to accumulate in the colder areas, creating local spots of degraded cladding that can favor crack initiation. Therefore, an estimation of the local hydride distribution is necessary to help predict the risk of cladding failure. The hydride distribution is governed by three competing phenomena. Hydrogen in solid solution diffuses under a concentration gradient due to Fick’s law and under a temperature gradient due to the Soret effect. Precipitation of the hydride platelets occurs once the hydrogen solubility limit is reached. A model of these phenomena was implemented in the 3D fuel performance code BISON in order to calculate the hydrogen distribution for arbitrary geometries, such as a nuclear fuel rod, and is now available for BISON users. Simulations have been performed on simple geometries to validate the model and its implementation. The simulations predict that before precipitation occurs, hydrogen tends to accumulate in the colder spots due to the Soret effect. Once the solubility limit is reached, hydrogen precipitates and forms a rim close to the outer edge of the cladding. The simulations also predict that the reactor shut down has little effect on already precipitated hydrides but causes the remaining hydrogen to precipitate homogeneously into hydrides.

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Uncertainty Quantification and Sensitivity Analysis Applications to Fuel Performance Modeling

Best-estimate fuel performance codes such as BISON currently under development at the Idaho National Laboratory, utilize empirical and mechanistic lower-length-scale informed correlations to predict fuel behavior under normal operating and accident reactor conditions. Traditionally, best-estimate results are presented using the correlations with no quantification of the uncertainty in the output metrics of interest. However, there are associated uncertainties in the input parameters and correlations used to determine the behavior of the fuel and cladding under irradiation. Therefore, it is important to perform uncertainty quantification and include confidence bounds on the output metrics that take into account the uncertainties in the inputs. In addition, sensitivity analyses can be performed to determine which input parameters have the greatest influence on the outputs. In this paper we couple the BISON fuel performance code to the DAKOTA uncertainty analysis software to analyze a representative fuel performance problem. The case studied in this paper is based upon rod 1 from the IFA-432 integral experiment performed at the Halden Reactor in Norway. The rodlet is representative of a BWR fuel rod. The input parameters uncertainties are broken into three separate categories including boundary condition uncertainties (e.g., power, coolant flow rate), manufacturing uncertainties (e.g., pellet diameter, cladding thickness), and model uncertainties (e.g., fuel thermal conductivity, fuel swelling). Utilizing DAKOTA, a variety of statistical analysis techniques are applied to quantify the uncertainty and sensitivity of the output metrics of interest. Specifically, we demonstrate the use of sampling methods, polynomial chaos expansions, surrogate models, and variance-based decomposition. The output metrics investigated in this study are the fuel centerline temperature, cladding surface temperature, fission gas released, and fuel rod diameter. The results highlight the importance of quantifying the uncertainty and sensitivity in fuel performance modeling predictions and the need for additional research into improving the material models that are currently available.

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TRISO Fuel Performance Modeling

Overview of TRISO fuel performance modeling TRISO fuel performance code PARFUME TRISO fuel performance modeling with BISON PARFUME and BISON comparison

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M3 milestone: Advanced contact 2021

This report describes advanced contact approaches and implementations in FY21 for use in emerging reactors with geometries that differ from LWR/EBR-II cylindrical fuel. Contact remains a challenging and crucially important component of our modeling toolkit. While significant improvements have been made through mortar and automatic differentiation, we explored advanced approaches (i.e., dual mortar) that yields better conditioned systems and will improve the robustness and performance of BISON contact problems. This effort is relevant to emerging reactor types, such as micro reactors and the corresponding complex and numerous contact surfaces. In this report, improvements of the mortar-based contact formulation are described. Benchmark problems and BISON assessment cases are included to demonstrate the improvements and advantages that are brought by the recent capability. Remaining issues are discussed and corresponding development plans are outlined.

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PARFUME/BISON Fission Product Release Predictions versus AGR-3/4 Heating Test Measurements

The fuel performance modeling codes PARFUME (PARticle FUel ModEl) and BISON were used to predict the release of fission products silver, cesium, and strontium from as-irradiated fuel compacts containing tristructural isotropic (TRISO) coated particles during heating tests post irradiation. The AGR-3/4 fuel compacts were irradiated as part of the third and fourth series of planned experiments to support the Advanced Gas Reactor (AGR) program. The heating tests were conducted at temperatures between 1200°C and 1700°C to simulate reactor accident conditions. The measured fission product release fractions from the heating tests were compared to modeling predictions calculated by PARFUME and BISON to evaluate how the codes compare to experimental results. Comparisons between the experimental measured fission product release fractions from silver, cesium and strontium indicate that both modeling codes overpredict the fission product release fractions demonstrating that the diffusivities used in the codes are overestimated. This results in a conservative estimate predicted by the codes when evaluating the fission product release relative to experimental data as it pertains to silver, cesium, and strontium.

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Thermal Analysis of the Sirius-3 Nuclear Propulsion Fuel Experiments

To support long space missions, NASA is designing and testing different fuels for nuclear thermal propulsion. These designs include a number ceramic metallic fuels which are to be irradiated in the Tranisent Test Reactor to test the fuel’s performance at protypical conditions. The irradiation campaign of these fuels is referred to as the Sirius experiments, and includes single and stacked experiment samples. In this paper we present the thermal analysis of the Sirius-3 experiment. For this analysis, temperatures from a Bison finite element model are compared to the temperatures obtained from an experiment thermocouple where good agreement between the two are found. Because agreement of the thermocouple and Bison finite element model, insight into the heat flow is provided to experimenters as they design future experiments. As an example of this insight, the rods through the fuel specimen as shown in Sirius A and B [1] were removed and replaced with hold down rings for the Sirius-2C

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Fuel Performance Evaluation of THOR-C Experiments

The Temperature Heatsink Overpower Response Commissioning (THOR-C) and THOR-Metal (THOR-M) experiments will be performed as part of an ongoing project for testing sodium fast reactor fuels with the Japan Atomic Energy Agency (JAEA). The THOR-C experiments consist of fresh metallic fuel pins and have been analyzed using the ABAQUS, Ansys codes and the BISON fuel performance code. THOR-M-Loss of Flow-1 (THOR-M-LOF-1) is designed to test an EBR-II irradiated fuel pin under LOF conditions. Simulation of the THOR-MLOF-1 experiment required first simulating the base irradiation of the fuel pin in EBR-II. MFUEL module of SAS4A/SASSYS-1 [1] is a physics-based metallic fuel performance model applicable to the normal operation, transient scenarios and fuel failure modeling including scenarios with bulk fuel melting. The model has been validated using EBR-II normal operation, separate effect transient tests as well as TREAT M-Series transient tests [2]. In this study, MFUEL models has been utilized together with a new capsule heat transfer model developed in this project. The new heat transfer model was necessary due to (1) significant amount of heat losses that required 2D heat transfer, (2) the presence of a titanium heat sink, rejecting a significant amount of heat, and (3) stagnant coolant conditions, which are inconsistent with SAS4A/SASSYS-1 (SAS) heat transfer model. Updates to SAS4A/SASSYS-1 and MFUEL has been described below, followed by a preliminary validation effort using the results from THOR-C-2 fresh fuel capsule experiment. A previous study for THOR-C-2 analysis using BISON code is also utilized in this study to model this test [3]. [1] D. O’Grady, A. J. Brunett, L. Ibarra, A. Karahan, T. Kim, T. S. Sumner, R. Thomas, T. H. Fanning, “The SAS4A/SASSYS-2 Version 5.7 Safety Analysis Code System,” Argonne National Laboratory,ANL/NSE-SAS/5.7, (2023). [2] A. Karahan, T. Kim, T. Fanning, D. O’Grady, “Validation of MFUEL Metal Fuel Performance Models of SAS4A/SASSYS-1,” Argonne National Laboratory, ANL/NSE-23/11, (2023). [3] M. Mihelish, A. Zabriskie, K. Paaren, P. Medvedev, C. Jensen, “Fuel Performance Predictions for the TREAT THOR-C Experiments,” Idaho National Laboratory, INL/RPT-23-73397, Revision 0, (2023)

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Multiscale, mechanistic calculation of the effective silver diffusion coefficient in polycrystalline silicon carbide: application to silver release in AGR-1 TRISO particles

The silicon carbide (SiC) layer in tristructural isotropic (TRISO) fuel particles serves as a barrier to prevent the escape of fission from the fuel kernel. The release of silver (Ag) is a concern due to the long half-life of the 110mAg isotope. In this study, the effective diffusion coefficient of the fission product Ag through the grain boundary (GB) network is calculated using a combination of atomistic and phase-field methods. Atomistic calculations of Ag diffusivity in SiC bulk and GBs are leveraged to develop a mesoscale effective Ag diffusion coefficient (Deff) in SiC. Since GBs serve as pathways for Ag diffusion, Deff is defined as a function of temperature, microstructure variables, and fluence. Deff is implemented in the fuel performance code Bison to predict Ag release from AGR-1 TRISO fuel particles. We hereby quantify the impact of SiC grain size and irradiation on Ag release and improve Bison's predictions.

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Understanding the effect of irradiation and silicon carbide microstructure on silver diffusion in TRISO particles

The silicon carbide (SiC) layer in tristructural isotropic (TRISO) fuel particles serves as a barrier to prevent the escape of fission from the fuel kernel. The release of silver (Ag) is a concern due to the long half-life of the 110mAg isotope. In this study, a combination of atomistic and phase-field methods focuses on quantifying the effect of irradiation and SiC microstructure on Ag diffusion. Atomistic calculations provide the Ag diffusivity in SiC bulk and GBs, also providing an estimate of the effect of irradiation defects on Ag diffusivity in bulk SiC. These lower length scale efforts are leveraged to develop a mesoscale effective Ag diffusion coefficient (Deff) in SiC. Deff is defined as a function of temperature, microstructure variables, and fluence. Deff is implemented in the fuel performance code Bison to predict Ag release from AGR-1 and AGR-2 TRISO fuel particles. We hereby quantify the impact of SiC grain size and irradiation on Ag release and improve Bison's predictions.

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X501 Experiment Simulation and PIE Data Comparison

Fuel performance simulations have been developed for X501 MA bearing fuel in BISON. The results of these simulations are compared with PIE results to assess the applicability of metallic fuel models in BISON to MA bearing metallic fuel.

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Initial development of an RIA envelope for dispersed nuclear fuel

A reactivity insertion accident (RIA) is a design basis accident in which reactivity is rapidly injected as a result of a control rod ejection or blade drop scenario. The resultant power increase can result in fuel rod failure and subsequent release of radioactive material into the reactor’s primary system. For light water reactors, failure under RIAs is typically a result of fuel melt, pellet-cladding interaction, or rod over-pressurization. Fuel melt occurs when the fuel system is unable to transport heat out of the fuel system. Pellet-cladding interaction occurs when an aggressive fuel pellet expansion pushes on an embrittled cladding beyond its strain limit. Rod over-pressurization occurs when a fuel rod exceeds the critical heat flux and departs from nucleate boiling, causing the rod internal pressure to rapidly increase, exceeding the systems pressure, and balloon until it bursts. To prevent failure, regulators have developed safety requirements that limit the injected enthalpy based on the state of the fuel system. However, dispersed fuel could enable the removal or relaxation of regulator-imposed safety criteria. Dispersed fuel embeds fuel particles in a highly conductive metal. Dispersed particles can have a particle radius of 1 µm to greater than 100 µm. Traditional fuel systems are plagued by poor thermal conductivity, especially at higher burnups, thus reducing the ability of the fuel system to respond to an RIA. However, dispersed fuel could improve the ability of the fuel system to transport injected energy away from the fissile material and into the coolant more efficiently. Furthermore, dispersing the fuel particles mitigates hard contact that typically occurs in the traditional zirconium-uranium dioxide fuel system, thus removing pellet-cladding mechanical interaction as a potential failure mechanism. This paper evaluates fuel particles dispersed in a metal matrix using the BISON fuel performance code to develop an initial failure threshold based on melt temperature of the fuel particle and/or cladding material as a function of fission density for beginning-of-life and end-of-life conditions. BISON results show that (1) reducing the size of the particles allows fission density to increase as a function of time, (2) particle-to-particle proximity must be considered to evaluate the limiting conditions, and (3) improving the fuel particle thermal conductivity improves thermal performance.

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