Experimental Breeder Reactor-II Research Articles

Development of Whole System Digital Twins for Advanced Reactors: Leveraging Graph Neural Networks and SAM Simulations

In this work, we introduce a novel method to develop whole system digital twins (DTs) for advanced nuclear reactors. This method treats a complex reactor system as a heterogeneous graph: with the system components as different types of graph nodes and their physical interconnections as edges. Based on the heterogeneous graph, a graph neural network combining graph convolution and temporal node attention is developed as the DT, facilitating a comprehensive understanding of the system’s dynamic behavior. By utilizing the System Analysis Module (SAM) code for simulating various operational transients, we develop a graph-based database that trains the DT. This DT is characterized by two primary functions: It can infer the entire system’s status using sparse node information, and it can predict the progress of transients based on current and historical system information. Our approach is validated through case studies on the Experimental Breeder Reactor II (EBR-II) system and a generic Fluoride-salt-cooled High-temperature Reactor (gFHR), demonstrating the DT’s accuracy in forecasting operational transients. The DT’s rapid computation capabilities enhance its potential for supporting advanced reactor operations, offering benefits in intelligent simulation, autonomous control, and anomaly detection, paving the way for improved safety analysis and intelligent component health management for advanced reactor systems and reducing their operations and maintenance cost.

Qualification and Quantification of Porosity at the Top of the Fuel Pins in Metallic Fuels Using Image Processing

Approximately 130,000 metal fuel pins were irradiated in the Experimental Breeder Reactor II (EBR-II) during its 30 years of operation to develop and characterize existing and prospective fuels. For many of the metal fuel irradiation experiments, neutron radiography imaging was performed to characterize fuel behavior, such as fuel axial expansion. While several fuel expansion results obtained from neutron radiography imaging have been published, the analysis of neutron radiography for the purpose of describing statistical properties of porous matter formed on top of the fuel pins, also referred to as fluff in previous publications, is significantly less represented in the literature with just a single paper so far. This study aims to validate and augment results reported in previous publications using automated image processing. The paper describes the statistical properties of the porous matter in terms of nine parameters derived from radiography images and correlates those parameters with such fuel properties as composition, expansion, temperature, and burnup. The reported results are based on 1097 fuel pins of eight different fuel compositions. For three major fuel types, U-10Zr, U-8Pu-10Zr, and U-19Pu-10Zr, a clear negative correlation is found between the Pu content and five parameters describing the amount of porous matter generated. The parameters describing granularity properties, however, showed either negative correlation or nonlinear dependency from fuel composition. The parameters describing the amount showed a positive correlation with fuel axial expansion, while granularity parameters showed a negative correlation with axial expansion. The dependency on cladding temperature was found to be weak. A positive correlation is demonstrated for volume parameters and fuel burnup. In general, reported results confirm and validate findings published in previous studies using a much larger number of pins and automated processing techniques, which easily lend themselves to reproducibility, thus avoiding subjective bias.

A comparative study on deep learning models for condition monitoring of advanced reactor piping systems

Advanced nuclear reactors offer innovative applications due to their portability, reliability, resiliency, and high capacity factors. To operate them on a wider scale, reducing maintenance life-cycle costs while ensuring their integrity is essential. Autonomous operations in advanced nuclear reactors using augmented Digital Twin (DT) technology can serve as a cost-effective solution by increasing awareness about the system’s health. A key component of nuclear DT frameworks is the condition monitoring of safety systems, such as piping-equipment systems, which involves acquiring and monitoring the plant’s sensor data. This research proposes a condition monitoring methodology utilizing deep learning algorithms, such as multilayer perceptions (MLP) and convolutional neural networks (CNNs), to detect degradation and its severity in nuclear piping-equipment systems. Sensor signals are processed to obtain the power spectral density and the Short-Time Fourier transform, and feature extraction methodologies are proposed to develop degradation-sensitive data repositories. The performance of MLP, one-dimensional (1D) CNN, and 2D CNN within the proposed condition monitoring framework is compared using a finite element model of a 3D piping system subjected to seismic loads as the application case study. Various approaches, such as dropout, k-Fold validation, regularization, and early stopping of training the network, are investigated to avoid overfitting the models to the input sensor data. The predictive capability and computational capacity of the deep learning algorithms are also compared to detect degradation in the Z-pipe system of the Experimental Breeder Reactor II (EBRII). The Z-pipe system is subjected to harmonic excitations that represent normal operating loads, such as pump-induced vibrations. The findings of the study indicate that the proposed artificial intelligence (AI)-driven condition monitoring framework demonstrates superior prediction accuracies with a 2D CNN, whereas the MLP exhibits higher computational efficiency.

Determining the effects of U/Pu ratio on subsolidus phase transitions in U-Pu-Zr metallic fuel alloys

Ternary alloys consisting primarily of uranium, plutonium, and zirconium (U-Pu-Zr) are among the leading candidate fuel systems considered for fast spectrum nuclear reactors. Despite historical operation data from the testing of U-Pu-Zr rods in the Experimental Breeder Reactor-II, considerable uncertainty about the evolution of phases and microstructure across the ternary composition space exists. Due to sluggish kinetics and other difficulties in handling metal actinide specimens, quantitative measurements of phase-transitions in U-Pu-Zr alloys remain sparse in scientific literature, with most investigators reporting either phase-transition temperatures or phase identification data, but not both from the same specimens. The purpose of this paper is to critically compare experimental and calculated phase transition data and correlate with the microstructure and phase characterization data of as-cast and annealed U-Pu-Zr alloys. Phase transition peaks were measured using differential scanning calorimetry in the subsolidus regions (723−948 K) of three ternary U-Pu-Zr alloys with the same zirconium concentration but various U/Pu ratios. Overlapping peaks were deconvoluted using a Frazier-Suzuki peak fitting algorithm, and the critical peak temperatures and enthalpies were calculated. In general, increasing concentrations of Pu were associated with enhanced thermal stability of the body-centered cubic γ phase upon both heating and cooling. Experimental phase transition temperatures in this study tended to agree well with the predictions of the established ternary phase diagrams and other reported phase transition temperatures in literature. Additionally, the TAF-ID thermodynamic database was used to calculate a U-Pu-40 at.% Zr pseudobinary diagram as well as ternary diagrams from 773 to 973 K. The equilibrium phase transition temperatures tended to be considerably lower than measured peak temperatures upon both heating and cooling. Recommendations for improving the quality of data in future U-Pu-Zr characterization studies are also discussed.

Advanced characterization-informed machine learning framework and quantitative insight to irradiated annular U-10Zr metallic fuels

U-10Zr Metal fuel is a promising nuclear fuel candidate for next-generation sodium-cooled fast spectrum reactors. Since the Experimental Breeder Reactor-II in the late 1960s, researchers accumulated a considerable amount of experience and knowledge on fuel performance at the engineering scale. However, a mechanistic understanding of fuel microstructure evolution and property degradation during in-reactor irradiation is still missing due to a lack of appropriate tools for rapid fuel microstructure assessment and property prediction based on post irradiation examination. This paper proposed a machine learning enabled workflow, coupled with domain knowledge and large dataset collected from advanced post-irradiation examination microscopies, to provide rapid and quantified assessments of the microstructure in two reactor irradiated prototypical annular metal fuels. Specifically, this paper revealed the distribution of Zr-bearing secondary phases and constitutional redistribution across different radial locations. Additionally, the ratios of seven different microstructures at various locations along the temperature gradient were quantified. Moreover, the distributions of fission gas pores on two types of U-10Zr annular fuels were quantitatively compared.

Evaluation of BISON metallic fuel performance modeling against experimental measurements within FIPD and IMIS databases

Simulations were conducted using the BISON fuel performance code on an automated process to read initial and operating conditions from two databases—the Fuels Irradiation and Physics Database (FIPD) and Integral Fast Reactor Materials Information System (IMIS) database. These databases contain metallic fuel data from the Experimental Breeder Reactor-II (EBR-II) and the Fast Flux Test Facility (FFTF). The work demonstrates use of an integrated framework to access EBR-II fuel pin data for evaluating fuel performance models contained within BISON to predict fuel performance of next-generation metallic fuel systems. Between IMIS and FIPD, there is enough information to conduct 1,977 unique EBR-II metallic fuel pin histories from 29 different experiments, and 338 pins from FFTF MFF-3 and MFF-5 with varying levels of details between the two databases. Each of these fuel performance histories includes a high-resolution power history, flux history, coolant channel flow rates, and coolant channel temperatures, and new model developments in BISON since the initial demonstration of this integrated framework. Fission gas release (FGR), cumulative damage fraction, fuel axial swelling, FCCI wastage thickness, cladding profilometry, and burnup were all simulated in BISON and compared to post-irradiation examination (PIE) results to evaluate BISON fuel performance modeling. Implementation of new fuel performance models into a generic BISON input file coupled with IMIS and FIPD yielded results with a better representation of physics than the initial evaluation of the integrated framework. Cladding profilometry, FGR, and fuel axial swelling were found to be in good agreement with PIE measurements for most of the pins simulated. The chosen mechanical contact solver was found to significantly impact the axial fuel swelling and cladding strain predictions when used in conjunction with the U-Pu-Zr hot-pressing model since it bound the fuel to prevent further swelling and increased hydrostatic stresses. This work suggests that fuel performance modeling in BISON under steady-state conditions represents the PIE data well and should be reassessed when new PIE data become available in IMIS and FIPD databases and when improved physical models to better capture fuel performance are added to BISON.

Impact of the Melt-Refining Process on the Performance of Sodium-Cooled Rotational Fuel-Shuffling Breed-and-Burn Reactors

This study assesses a Rotational Fuel-Shuffling Breed-and-Burn (RFBB) fast reactor that operates in breed-and-burn (B&B) mode with a rotational fuel-shuffling scheme and remains within the 200 displacements per atom (DPA) radiation damage constraint of currently verified cladding materials. The design is based on a commercial-scale fast burner reactor called the Super Power Reactor Innovative Small Module (S-PRISM) reactor. To reduce the high DPA values of discharged fuels, the melt-refining process developed in the Experimental Breeder Reactor-II (EBR-II) project is adopted in this study. The effects of the melt-refining process on the performance of the RFBB are investigated via five scenarios and compared with a core to which the melt-refining process is not applied: Scenario I, “Homogenization,” occurs without the removal of fission products (FPs) during the melt-refining process; Scenario II, “Homogenization and FP Removal,” occurs with the removal of FPs to a fraction similar to that in the melt-refining process developed in the EBR-II project; Scenario III, “Homogenization, FP Removal, and Make-Up,” is similar to Scenario II but makes up fuel losses with natural uranium; Scenario IV, “With 1% TRU [transuranics] Losses,” is similar to Scenario III but is evaluated with 1% of actinides not recovered; Scenario V, “With 10% TRU Losses,” is similar to Scenario III but is evaluated with 10% of actinides not recovered. The results show that it is neutronically and thermal hydraulically feasible to establish a B&B mode with the rotational fuel-shuffling scheme and by reconditioning the fuel whenever its cladding reaches its proven 200 DPA radiation damage limit. In Scenario V, the core is subcritical due to a large number of actinides not being recovered during the melt-refining process. The cores of the other scenarios are all critical. The cores of scenarios in which FPs are removed during the melt-refining process have higher excess reactivity than that of the core of Scenario I (“Homogenization”) and that of the core to which the melt-refining process is not applied. The numerical analyses also show that in scenarios that include making up fuel losses during melt refining, the core is fed with more natural uranium make-up fuel during operation and thus has lower burnup. Other characteristics, such as power density distributions, neutron flux profiles, and fertile and fissile nuclide density distributions, are all stable during operation.

EBR-II MOX Fuel Characterization Enabling ARES Phase I Testing

Pretransient characterization was performed for the Experimental Breeder Reactor II (EBR-II) mixed-oxide (MOX) fuel pellets from the SPA-2/-2B Operational Reliability Testing collaboration between Japan and the United States. Continued collaboration under the Advanced Reactor Experiments for Sodium Fast Reactor Fuels project will investigate the transient performance of these rods in the Transient Reactor Test facility at Idaho National Laboratory in the MOXTOP-THOR experiment. The results will fill a gap in existing transient performance data for MOX as these rods have a peak burnup of 14.3 at. % (~134.4 GWd/t) in the EBR-II. Fuel pellet properties were gathered from available resources and their irradiation and decay history evaluated. Further reactor physics calculations were performed to support the experiment design, reactor operations, and safety analyses necessary to enable the programmatic success of this effort. Of the three irradiated fuel pins, two will undergo transient testing, and all three will undergo post-irradiation examination. The methodology development and analysis activities utilized in this paper enable current experiment design work and provide the pathway through which measured data of this type can be further evaluated.

Validation of Feedback Reactivity Evaluation Models for Plant Dynamics Analysis Code During Unprotected Loss of Heat Sink Event in Sodium-Cooled Fast Reactors

Abstract Feedback reactivity caused by core deformation is one of the inherent safety features in a sodium-cooled fast reactor (SFR). To validate the evaluation models of the reactivity feedback equipped in the in-house plant dynamics analysis code, named Super-COPD, we have been conducting the benchmark analyses for the unprotected loss of heat sink (ULOHS) tests of balance of plant (BOP)-302R and BOP-301 as one of the representative issues in Experimental Breeder Reactor-II (EBR-II), a pool-type experimental SFR in the United States. During the transient of the ULOHS tests, the reactor power decreased to the decay heat level due to the negative reactivity caused by the radial expansion of the core. Developing the evaluation models of the reactivity feedback is essential for predicting the plant behavior in unprotected events, such as ULOHS events, and the numerical analyses modeling the feedback reactivity were conducted. By comparing the numerical results and the experimental data, the increment temperature profiles of the core inlet and the decreasing reactor power profile calculated by Super-COPD were comparable with experimental data. The applicability of the evaluation models for the reactivity feedback was indicated during the ULOHS event. In addition, through the sensitivity analyses on the cold pool model, it was found that the modification of the plenum model of the cold pool to take into account the thermal stratification was required to improve the core inlet temperature profile.

Qualification of Metallic Fuel Data for Advanced SFR Applications

Metallic fuel is proposed for use in various advanced sodium-cooled fast reactor (SFR) designs, including small modular reactors and microreactors. To support advanced SFR research and development, a metallic fuel database has been developed at Argonne National Laboratory. The database was built on extensive metallic fuel data collected during the Integral Fast Reactor Program, mainly from irradiation experiments in the Experimental Breeder Reactor-II (EBR-II). In order to manage the large amount of data and associated documents and to qualify the data, a Quality Assurance Program Plan (QAPP) was established for the legacy metallic fuel data following the American Society of Mechanical Engineers (ASME) Nuclear Quality Assurance (NQA-1) 2008/2009 Addenda Standard. Metallic fuel data qualification is being performed following the QAPP. The plan has been approved by the U.S. Nuclear Regulatory Commission and can be referenced in licensing applications for nuclear power plants. The process for qualifying metallic fuel data is presented. The structure for implementing the QAPP and the qualification methods are introduced. The principle for prioritizing the metallic fuel data for quality assurance is summarized. An overview of the metallic fuel data available and considered for qualification is also provided.

Validation Efforts for the Versatile Test Reactor

The Versatile Test Reactor (VTR) that is being designed today is heavily reliant upon the Argonne Reactor Codes (ARC) modeling software for predicting the operational performance of the VTR. Given its usage in the VTR, a set of validation cases appropriate for the VTR must be assembled. The measurements taken in ZPPR-15, Experimental Breeder Reactor II (EBR-II), and Fast Flux Test Facility were chosen and analyzed with the ARC software as part of creating the necessary validation basis. The results of the ARC software on the measured data are discussed here, and they demonstrate the accuracy of the ARC software on fast spectrum reactors.

Transmission Electron Microscopy based Characterization of a U-20Pu-10Zr Fuel Irradiated in Experimental Breeder Reactor-II

U-Pu-Zr metallic fuels are important fuel candidates for future advanced and/or test reactors. To better understand the fuel performance and guide future fuel design, a U-20Pu-10Zr (in weight) metallic fuel irradiated in the Experimental Breeder Reactor-Ⅱ was revisited using advanced electron microscopies. This fuel cross section was irradiated to a burnup of 6.15 % at a cladding temperature of ∼500°C. Several transmission electron microscopy samples were extracted from different but representative radial locations of the fuel cross section using focused ion beam technique. Phase identification and chemical analysis with sub-micron spatial resolution were carried out using a scanning transmission electron microscopy. Multiple phenomena that are critical to fuel performance, such as Zr redistribution, were revealed in an unpreceded highly detailed manner. An improved understanding of fuel reconstruction in U-Pu-Zr metallic fuel under reactor irradiation is provided.

Finely Divided Metal as Nuclear Reactor Fuel

A new form for metallic nuclear reactor fuel is proposed consisting of finely divided particles (tens of micrometers) mixed with sodium for thermal bond. Fuel pins filled with this form of fuel would have greater fuel density than with solid slugs fabricated at 75% smear density. Greater fuel density reduces enrichment requirements for initial fuel loading. A larger surface-to-volume ratio allows more fission product gases and metallic fission products to diffuse out of fuel particles, resulting in less swelling, greater burnup before processing, and simple preliminary thermomechanical spent fuel processing steps that might be used several times before the more expensive pyroelectric process develolped for the Experimental Breeder Reactor II (EBR-II). Less frequent pyroelectric processing, simple preliminary processing, and a larger surface-to-volume ratio reduce total processing cost. Preliminary processing produces separate fission products, in particular cesium and strontium, in metallic rather than salt or mineral form, thereby simplifying and reducing storage cost. Intrinsically structurally weak fuel would not rupture fuel pin cladding by swelling. The expense and complexity of the process would be offset by reduced total system cost.

Behavior of metallic fast reactor fuels during an overpower transient

● An extended overpower transient (∼32%) was conducted in EBR-II to test the response of 19 binary- and ternary-design metallic alloy fuel elements. ● Post-irradiation examination demonstrated that the overpower transient does not compromise the integrity of fuel elements. ● Post-transient fuel performance should not be significantly altered by the overpower transient. A slow-ramp (0.1%/s), extended overpower (∼32%) transient was conducted in the Experimental Breeder Reactor-II (EBR-II) on 19 metallic alloy fuel elements, including both binary (U-Zr) and ternary (U-Pu-Zr) fuel designs. The elements were clad in either Type 316 SS or HT9. Before the transient, the elements were pre-irradiated under steady-state or steady-state plus duty-cycle (periodic 15% overpower transient) conditions in various EBR-II sub-assemblies and reached burnups ranging from ∼5 to ∼12 at%. The fuel pins were then consolidated into the X512 sub-assembly for the overpower transient. Cladding integrity was maintained for all fuel pins throughout the entirety of normal operation and the overpower transient test. Post-irradiation examination (PIE) demonstrated that mild restructuring was evident within the fuel phase. However, these changes were not significant enough to expect changes in irradiation performance under normal operating conditions if the fuel elements were returned to service. These results empirically validate that limits on sodium fast reactor operational transients ( e.g. power ramps) could be applied with adequate safety margins to fuel failure or non-reversible damage.

Investigation of constituent redistribution in U-Pu-Zr fuels and its dependence on varying Zr content

This contribution investigates fuel constituent segregation and fuel-cladding chemical interactions (FCCI) in three U-Pu-Zr fuel pins irradiated to ∼11% burnup in Experimental Breeder Reactor-II as part of the X441 DP-1 experiment. In examined pins, Zr content ranged from 6 to 10 and 14 wt.%, while Pu concentration was constant at 19 wt.% Pu. The primary goal of the investigation was to determine the role Zr content plays in fuel performance and this manuscript provides assessment of both constituent redistribution and FCCI as a function of axial position. FCCI was observed in all pins, though no cladding failure was noted. Optical and scanning electron microscopy (SEM) results show that variation in Zr content alters the number and relative size of constituent redistribution zones in the fuel. For example, larger Zr-rich central regions and smaller U-rich intermediate regions were observed in 14 wt.% Zr fuels. More importantly, all examined fuels have four or more discrete constituent redistribution regions, where each region has dissimilar morphological features. The existence of four to six distinctive regions deviates from traditionally accepted three region redistribution model , highlights complexity of constituent redistribution in this metal fuel , and identifies the need to conduct additional studies using state-of-the-art instrumentation.

A propagation-based fault detection and discrimination method and the optimization of sensor deployment

Industrial processes can be affected by faults having a serious impact on operation when not promptly detected and diagnosed. In this paper, a propagation-basedfaultdetectionanddiscrimination(PFDD) method is proposed to develop a strategy for fault diagnosis while in the design phase of a system. The PFDD method constructs the system model using the IntegratedSystemFaultAnalysis(ISFA) technique. Based on the system model, the propagation of hardware and software faults are simulated qualitatively. Given the results of the simulation, the process by which a fault propagates can be characterized using the qualitative features of system variables including the deviation of the system variables from their expected values, the variation of the system variables over time, and the order in which each variable is influenced during the propagation of the fault. The strategy by which a fault can be detected and discriminated is defined using those features. The PFDD method supports the detection and discrimination of faults in both steady states and transient states. Based on the PFDD method, the optimization of sensor deployment in a system is discussed. A brute force algorithm is developed to examine the system’s capability at diagnosing faults and the cost of sensor deployment for all possible configurations of sensors. The optimal sensor deployment strategy can be derived accordingly. However, the brute force method is only applicable to small-scale systems due to its high computational cost. A genetic algorithm is used to optimize sensor deployment in large-scale systems. The PFDD and sensor deployment optimization methods are applied to the Experimental Breeder Reactor II (EBR-II) for verification.

Initial demonstration of automated fuel performance modeling with 1977 EBR-II metallic fuel pins using BISON code with FIPD and IMIS databases

Using the BISON fuel performance code, simulations were conducted using an automated process to read initial and operating conditions from the Fuels Irradiation and Physics Database (FIPD) and Integral Fast Reactor materials information system (IMIS) database, which contains metallic fuel data from the Experimental Breeder Reactor-II (EBR-II). This work demonstrates use of an integrated framework to access the vast majority of EBR-II experimental fuel pin data to support rapid development of fuel performance models for next-generation metallic fuel systems. With this capability, validation for fuel qualification can be performed rapidly. Between IMIS and FIPD, there is enough information to conduct 1977 unique EBR-II metallic fuel pin histories from 24 different experiments, at varying levels of detail between the two databases. Each of these histories includes a high-resolution power history, flux history, coolant channel flow rates, and coolant channel temperatures. Fission gas release (FGR), cumulative damage fraction (CDF), fuel axial swelling, cladding profilometry, and burnup were all simulated in BISON. The results were compared to post-irradiation examination (PIE) results for the initial demonstration of automated BISON modeling. BISON simulations conducted with IMIS and FIPD were in rough agreement with PIE measurements and calculations. Cladding profilometry, FGR, and fuel axial swelling were found to be in rough agreement with PIE measurements, depending on the physics used within the BISON input files. The mechanical contact solver chosen was found to significantly impact axial fuel swelling and cladding strain predictions. CDF values were assessed to see whether pin failure may have been predicted (CDF ≥ 1). This work suggests that continued development of an automated tool for BISON should focus on inclusion of the Fast Flux Test Facility (FFTF) experimental data for a larger database for metallic fuel, improved physical models to better capture fuel performance, such as fuel-cladding interactions, and a more detailed comparison with available PIE data to further the BISON model development.

FIPD: The SFR metallic fuels irradiation & physics database

The DOE Advanced Reactor Technology (ART) program has supported efforts to recover and preserve metallic fuel data generated throughout the US sodium-cooled fast reactor (SFR) program. Those efforts have been focused on establishing databases of the experimental data that were mainly generated during the Integral Fast Reactor (IFR) program including data generated at Experimental Breeder Reactor-II (EBR-II), Fast Flux Test Facility (FFTF), and Transient Reactor Test Facility (TREAT) reactors, as well as out of pile data. The data is essential for future licensing activities of metallic fuel based advanced fast reactors. This paper describes the development of the SFR Metallic Fuels Irradiation & Physics Database (FIPD) and covers the scientific knowledge available in the database. The architecture of the FIPD is described by showing the available reactor operation data, fabrication, and post-irradiation examination (PIE) data, and other documents. The applications of the fuel database are also discussed.

Cladding Profilometry Analysis of Experimental Breeder Reactor-II Metallic Fuel Pins with HT9, D9, and SS316 Cladding

BISON finite element method fuel performance simulations were conducted using an existing automated process that couples the Fuels Irradiation & Physics Database (FIPD) and the Integral Fast Reactor Materials Information System database by writing input files and comparing the BISON output to post-irradiation fuel pin profilometry measurements contained within the databases. The importance of this work is to demonstrate the ability to benchmark fuel performance metallic fuel models within BISON using Experimental Breeder Reactor-II fuel pin data for a number of similar pins, while building off previous modeling efforts. Changes to the generic BISON input file include implementing pin specific axial power and flux profiles, pin specific fluences, frictional contact, and irradiation-induced volumetric swelling models for cladding. A statistical analysis of irradiation-induced volumetric swelling models for HT9, D9, and SS316 was performed for experiments X421/X421A, X441/X441A, and X486. Between these three experiments, there were 174 post-irradiation examination (PIE) profilometries used for validating the swelling models presented using a standard error of the estimate (SEE) method. Implementation of the volumetric swelling models for D9 and SS316 claddings was found to have a significant impact on the BISON profilometry simulated, where HT9 clad pins had an insignificant change due to low fluence values. BISON profilometry simulated for HT9, D9, and SS316 fuel pins agreed with PIE profilometry measurements, with assembly SEE values being 4.4 × 10−3 for X421A, 2.0 × 10−3 for X441A, and 2.8 × 10−3 for X486. D9 clad pins in X421/X421A had the highest SEE values, which is due to the BISON simulated profilometry being shifted axially. While this work accomplished its purpose to demonstrate the modeling of multiple fuel pins from the databases to help validate models, the results suggest that the continued development of metallic fuel models is necessary for qualifying new metallic fuel systems to better capture some physical performance phenomena, such as the hot pressing of U-Pu-Zr and the fuel cladding chemical interaction.

Investigation of fuel microstructure at the top of a metallic fuel pin after a reactor overpower transient

The influence of a reactor overpower transient on irradiated metallic fuel performance was investigated in this work. Such transient studies support safety and performance optimization of future sodium fast reactors. A ternary metallic fuel alloy (U-19Pu-10Zr) in HT-9 cladding which was irradiated in the Experimental Breeder Reactor II (EBR-II) to a burnup of 11 at. %, and then subjected to a 30% overpower transient was studied. The sample was selected from the top of a fuel pin where failure is expected to first appear in the EBR-II pin design. This can occur when the pin is subjected to conditions beyond its design envelope. Main elemental distribution, phase characterization, fission product behavior, chemical form and fuel-cladding chemical interaction were analyzed in this study. Simulation of the temperature profile during the transients were performed using BISON and show that the moderate transient did not maintain prolonged high temperature. For the first time, the porous structure commonly found at the top of metallic fuel pin (termed “fluff” structure given its appearance) was examined in detail via postirradiation characterization. The fluff contains the major fuel elements (U, Pu, Zr) and presents a highly porous microstructure (over 40% area fraction). The presence of fission products relevant to source term was investigated. However, semi-volatile and volatile elements (namely Cs, I, Xe, Eu), expected in this region, could not be detected probably due to sample preparation. Europium, also expected in this region, was only detected in precipitates along with the other rare earth elements. Finally, no fluff (fuel) fragments detached from the fuel slug were detected in the plenum region, indicating the fluff stability under the tested moderate ramp. These analyses indicate that the moderate transient experienced by the fuel pin did not significantly influence fuel performance under this transient condition.