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At least 145 records · Page 8

Quantifying deformation during Zry-4 burst testing: a comparison of BISON and a combined in-situ digital image correlation and infrared thermography method

The development and verification of nuclear fuel-cladding performance codes require extensive testing to establish empirical correlations, necessitating more accelerated testing methods that can replace large validation studies. Here, in the present work, a technique was developed and implemented to experimentally quantify the relationship between temperature, cladding internal pressure, and strain in-situ during a burst test, with the specific aim of generating data for code validation and model refinement. Digital image correlation was used to measure hoop, axial, and radial strain, and infrared thermography to quantify axial temperature gradients. Several key experimental modifications to traditional LOCA burst testing were necessary, but are shown to effectively have little impact on burst temperatures. The time/temperature dependent pressure and time/spatially dependent thermal gradient data were used with BISON to simulate cladding burst and strain rates. Although the measured DIC strains reach appreciable amounts at slightly lower temperatures than BISON simulated strains, there is good agreement between the measured and simulated strains in terms of magnitude and rates leading up to burst. However, in the few seconds prior to and during burst, the BISON simulated strains are significantly lower than the measured strains, indicating the potential for model improvement. The combined experiment and simulation technique may be applied to any new cladding concept to accelerate fuel qualification.

36 MATERIALS SCIENCE↗

Phase-field simulations of fission gas bubbles in high burnup UO2 to inform engineering-scale fuel performance modeling

To improve the economics of commercial nuclear energy generation, U.S. utilities are currently seeking licensing approval to operate UO2 fuel to higher burnups. One significant safety issue that must be addressed to obtain approval is the potential for fine fragmentation/pulverization of the fuel during a loss-of-coolant accident (LOCA). The cause of pulverization has been hypothesized to be the rapid increase of pressure in fission gas bubbles in the high burnup region of the fuel during a LOCA. To better understand this phenomenon, a novel phase-field model of the fission gas bubble microstructure in UO2 has been developed and implemented in Idaho National Laboratory (INL)'s Marmot application for phase-field simulation of nuclear materials. Simulations of the bubble response to steady-state and transient conditions were conducted. Simulation results were used to inform a mechanistic model of pulverization in BISON, INL’s fuel performance simulation code.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Molten Salt Reactors and Electrochemical Reprocessing: Synthesis and Chemical Durability of Potential Waste Forms for Metal and Salt Waste Streams

The molten salt reactor (MSR) is one of the leading advanced nuclear reactor candidates to replace current nuclear reactor technologies in the U.S. Besides having more economical and reliable designs, MSRs have are amenable to a closed fuel cycle, in which electrochemical reprocessing can be performed to recycle the used nuclear fuel. This review intends to provide information about potential waste forms for metal and salt waste streams from these salt-based nuclear processes. Metal waste streams arise from reactor components and structural materials. Salt waste streams are generated during reactor operations as fission products build up in salt-fueled systems. Waste forms that have the highest waste loading and/or have shown the most commercial promise are discussed with an emphasis on the current state of efforts to understand the synthesis and chemical durability of metal and ceramic waste forms.

molten salt reactors, electrochemical reprocessing↗

Engineering Scale Drying of Aluminum-Clad Spent Nuclear Fuel: Experiment Report

Engineering-scale tests were performed to evaluate the relative effectiveness of forced gas and vacuum-drying processes on aluminum-clad spent nuclear fuel (ASNF) in preparation for extended dry storage. Drying models were developed to improve confidence in the likely range of conditions at the start of dry storage and to understand the factors most significant to each process. Testing was performed at the Holtec International Forced Helium Dehydration training facility in Camden, New Jersey, by students from the University of South Carolina in collaboration with Idaho National Laboratory. A full-size Type 1a basket, with a full-diameter vessel configuration (based on the Department of Energy standardized canister design), was used in combination with a 10 assembly surrogate ASNF arrangement to provide a proxy for geometry. A resistance heater incorporated in one assembly simulated the influence of 100 W decay heat. This instrumented chamber allowed testing of the removal of bulk water, physisorbed water, and chemisorbed water over a range of operating parameters with either drying process. Thick oxide films were grown on aluminum test plates to mimic the ASNF surface chemistry. These one-use test plates were housed within select assemblies during drying. Post-test analysis of these plates gave a measure of the moisture removed during each test, which was compared to a control. Instrumentation provided detailed thermal, humidity, and gas or pressure data relevant to each test. Model simulations generally compared favorably to instrument data for the tests. While both processes were able to remove bulk water, removal of chemisorbed water was shown to depend heavily on local temperature. To the disadvantage of vacuum drying, operations approaching or exceeding 220°C achieved consistently more dehydroxylation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

2025 Intern Poster

The Hot Fuel Examination Facility (HFEF) at the Materials and Fuels Complex (MFC) houses the largest U.S. inert atmosphere hot cell for nuclear material research. Key features include the precision gamma scanning (PGS), Fuel Accident Condition Simulator (FACS), Neutron Radiography Reactor (NRAD), and the focus of this project, the Metallograph Loading Cell (MET Cell). The MET Cell performs tests on spent nuclear fuel, such as microhardness testing, microscopy, and neutron radiography. However, the MET Cell’s existing pressure and lighting control systems are outdated and inefficient, with inadequate documentation for system changes over time. This project aims to design a new automated control system for the MET Cell, ensuring longevity (minimum ten years), ease of troubleshooting/repair, and integration into the building monitoring system. The design process addressed challenges such as space restrictions, varied voltages within enclosures, sourcing new components, and security limitations. Compliance with NFPA 70, UL508A, MFC Physical Security, and INL Engineering standards was essential. The project involves repurposing an existing PLC to manage lighting and pressure control using digital and analog signals, simplifying wiring, and ensuring thorough documentation for future reference.

42 - ENGINEERING↗

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↗

SCALE Demonstration for Sodium-Cooled Fast Reactor Fuel Cycle Analysis

In support of the US Nuclear Regulatory Commission non-light-water reactor fuel cycle demonstration project, SCALE 6.3.1 capabilities for radionuclide characterization, criticality, and shielding were demonstrated for scenarios in the sodium-cooled fast reactor (SFR) nuclear fuel cycle. Three postulated accident scenarios were selected for analysis in this work. As a basis for all scenarios, irradiated fuel inventories were generated using SCALE/ORIGAMI. To cover multiple SFR design choices, two different types of SFR fuel, uranium/transuranic-loaded and U-based fuels, were considered. For the first scenario, SCALE/MAVRIC was used to calculate the radiation shielding and dose rates inside and outside of the containment building due to a drop of a spent fuel assembly from the fuel-handling system during unloading inside the containment building. For the second scenario, potential critical configurations in an electrofiner were investigated through criticality calculations with SCALE/CSAS. For the third scenario, the activity of the waste salt from an electrorefiner was evaluated using SCALE/ORIGEN. The dose rate produced by the analyzed SFR assemblies is similar to that produced by a typical pressurized water reactor (PWR) fuel assembly with a discharge burnup of 50 GWd/MTU, with the same cooling time of 10 days. The criticality analyses suggested that the different electrorefiner configurations have a large margin to criticality. The activity analysis of the electrofiner waste revealed that shielding and cooling may be required for the waste salt that contains transuranics and fission products produced by the electrorefiner because of the high activity of the waste salt. In general, the application of various capabilities in the SCALE code system for SFR fuel inventory generation, criticality, and shielding was successfully demonstrated for the selected scenarios in the SFR nuclear fuel cycle. Additional analyses can be performed to provide more accurate results when more details of the SFR nuclear fuel cycles are available, for example, the dimension of the electrorefiner and the salt compositions during reprocessing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Demand Driven Cycamore Archetypes

Future nuclear fuel cycle options may present advantages over today’s once-through fuel cycle. Nuclear fuel cycle simulation tools assess the performance of those fuel cycles as well as the dynamics of long-term technology transitions. In many nuclear fuel cycle simulation tools, it has historically been the responsibility of the user to manually define facility deployment schemes and all facility parameters. While this is straightforward in simple fuel cycles, transitions from one fuel cycle to another can be more complex. In particular, deployment schemes for supportive fuel cycle facilities beyond the reactor become complex if the analyst desires to avoid gaps in the nuclear fuel and power supply chain during those transition scenarios. As nuclear fuel cycle analysis approaches questions regarding the feasibility and performance of the deployment schemes and technology choices during technology transition, automation of this historically manual process is necessary. The main objective of this work was to develop and demonstrate Cyclus automation capabilities toward key nuclear fuel cycle transition scenarios. While deploying reactors to meet power demand is trivial, and existed in the earliest versions of CYCLUS, automated, predictive deployment and decommissioning of other facilities is more complex. These include mining, milling, enrichment, fuel fabrication, reprocessing, and others. For example, a balanced closed fuel cycle may require ensuring that there is enough fast reactor fuel for their operation and may drive deployment of a fleet of light water reactors. This concern comprises the main challenge that drove the project effort. The Demand-Driven Cycamore Archetype project (NEUP-FY16-10512) aimed to develop CYCAMORE demand-driven deployment capabilities and thereby automate transition scenario definition. The developed software package, d3ploy, in the form of a CYCLUS Institution agent, deploys Facilities to meet the front-end and back-end demands of the fuel cycle. The University of South Carolina and the University of Illinois applied multiple algorithmic approaches to this challenge. This project developed an in situ demand-driven development schedule calculation through non-optimizing, deterministic-optimizing, and stochastic-optimizing algorithms as CYCLUS archetypes and demonstrated these new archetypes in program-supporting fuel cycle transition scenarios. Both objectives were achieved. This report documents the results and deliverables obtained toward these achievements in detail.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Cluster dynamics simulation of xenon diffusion during irradiation in UO 2

Diffusion of fission gas in UO 2 nuclear fuel impacts several important performance metrics, such as fission gas release, swelling, and thermal conductivity. Current empirical models of fission gas release have significant uncertainty, some of which derives from the bulk diffusion rate and its dependence on, for example, fuel chemistry and irradiation. In this work, we have applied the previously-developed Free Energy Cluster Dynamics (FECD) methodology in the code Centipede to calculate xenon cluster concentrations in UO 2 under intrinsic (high temperature) and irradiation-enhanced (intermediate temperature) conditions in order to develop a model of the xenon diffusion coefficient based on the atomic scale mechanisms responsible for transport. While the diffusion mechanism for xenon in UO 2 is adequately described by the Xe + U 2 O vacancy cluster for intrinsic conditions, a similar process is not capable of capturing measured in-pile fission gas diffusivity at intermediate temperatures. Therefore, a different diffusion mechanism must dominate under this regime. Using calculated atomistic data, we have shown that irradiation-enhanced diffusion at intermediate temperatures occurs via the larger Xe + U 4 O y vacancy clusters, which have lower migration barriers and increase in concentration by several orders of magnitude compared to intrinsic conditions. This mechanism is enabled by the increased uranium vacancy concentration under irradiation due to Frenkel pair production. In addition, the fast migration of uranium interstitials with two attached oxygen interstitials lowers the total uranium interstitial concentration through reactions with sinks. This allows the extended defects, such as Xe + U 4 O y vacancy clusters, to maintain high concentrations by limiting annihilation with attached vacancies. Furthermore, predictions using the Xe + U 4 O y diffusion mechanism are in good agreement with experiment, albeit with some differences in the Arrhenius slope, which we believe may be related to either experimental or model parameter uncertainty. Lastly, an analytical expression suitable for application in fuel performance simulations was derived to capture the predictions of the Centipede simulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Developing New Fuels for High Performance Research Reactors

The National Nuclear Security Administration (NNSA) Material Management and Minimization (M3) program works globally to minimize the civilian use of highly enriched uranium (HEU), a weapon-usable nuclear material. Supporting this effort, M3’s Office of Reactor Conversion and Uranium Supply is developing new fuels capable of converting research reactors from HEU fuel to high-assay low-enriched uranium (HALEU) fuel. Some of the remaining research and test reactors (RTRs) operating on HEU today have unique designs, fuel configurations, and demanding performance requirements that cannot be met with an existing regulatory-approved low-enriched uranium (LEU) fuel. M3, DOE’s national laboratories, and other industry partners are qualifying new high-density LEU fuels to convert these RTRs while maintaining their unique capabilities supporting a wide variety of science and technology research in areas such as medicine, industry, defense, education, and training. Current efforts are focused on two options for the remaining US high-performance research reactor conversions: a monolithic uranium 10wt% molybdenum (U-10Mo) fuel form and a dispersion uranium silicide fuel form. This paper reviews the history and status of M3’s fuel qualification efforts for the U-10Mo LEU fuel form.

Montgomery, Rose [ORNL] (ORCID:0000000286038936)↗

Measuring thermal diffusivity and gap conductance in uranium nitride and Zircaloy relevant for microreactor applications

Heat transfer across nuclear fuels and structural interfaces is an important factor for evaluating the performance of nuclear power systems. Specifically, heat generated as nuclear fuel fissions must be transported through the cladding material and through the reactor to reach the steam turbine for power generation. As new microreactor designs emerge, maximizing the efficiency of this heat transfer process becomes crucial to make them commercially viable. This article examines thermal diffusivity and gap conductance in uranium nitride (UN) fuel and Zircaloy-4 (Zry4) cladding using light flash analysis (LFA). Thermal diffusivity measurements were made on monolithic UN pellets and Zry4 exposed to carbon at peak operating temperatures of microreactors and show that carbon ingress has a minimal effect on thermal diffusivity when compared with identical materials not exposed to carbon. Evaluation of gap conductance at the UN-Zry4 interface was done using one-dimensional two-layer thermal transport models as a function of applied pressure. Here the results show that increasing pressure on the UN-Zry4 interface leads to gains in gap conductance per unit area in fuel-cladding assemblies at microreactor operating temperatures. While many other variables are expected to influence UN-Zry4 interfacial gap conductance (e.g. contact surface roughness, porosity, localized heating, environmental gas pressure), the work offers a demonstration of using a conventional LFA apparatus to determine this parameter at elevated temperatures.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Streamlining the Coupling of BISON and Dakota Through the NEAMS Workbench

Metallic nuclear fuels for use in advanced reactors are an active area of research and development. Robust, accurate metallic fuel performance models are necessary for the design, analysis, and licensing of such reactors. However, metallic fuel performance models require additional development; they are not as mature as uranium dioxide fuel performance models. To support further metallic fuel development, Oak Ridge National Laboratory and the University of Florida have streamlined the coupling of the BISON fuel performance code with Design Analysis Kit for Optimization and Terascale Applications (Dakota) statistical analysis tool through the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Workbench. This work included performing three different sensitivity analyses on metallic nuclear fuel models in BISON. The analyses examined were a general model of the IFR-1 experiment, the X430 experiment T654 pin, and the X430 experiment T651 pin. The results suggest that BISON and Dakota can be integrated through NEAMS Workbench to perform sensitivity and uncertainty analyses and visualize the results.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

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.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

High-burnup boiling water reactor steady-state operating conditions and fuel performance analysis

The primary operational costs for existing nuclear reactors are plant operation costs, maintenance costs, and fuel costs, all of which are influenced by the materials used and the design of the reactor core. Optimizing core design parameters—including burnup limits and enrichment levels—can lengthen cycles, reduce outages, reduce reload batch fractions and spent fuel storage requirements, and lower maintenance and operating expenses, thereby enhancing economic viability. Furthermore, developing higher-fidelity tools to simulate these parameters enables better identification of the available margin, improves overall plant safety, and improves the understanding a given plant’s responses to accident scenarios. Here, in the US, much of the research and development focus has traditionally been on pressurized water reactors (PWRs), but boiling water reactors (BWRs) comprise approximately one-third of the US reactor fleet. Modeling and simulation advances for BWRs and PWRs—particularly those achieved through the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program—are crucial to the long-term viability of the light–water reactor industry. A key research area of the high burnup and increased enriched fuel initiative is focused on addressing issues related to postulated loss-of-coolant accident (LOCA) scenarios. NEAMS has dedicated significant effort to enhancing tools to better support BWRs. A current focus is showcasing the BWR framework for high-burnup LOCA analysis. This high-fidelity steady-state analysis is a first step toward demonstrating a best-estimate, pin-by-pin high-burnup BWR LOCA analysis to assess full-core cladding rupture behavior for a representative BWR. The objective of this effort is to provide a modeling capability that will help elucidate and provide a best-estimate evaluation for cladding rupture susceptibility in BWRs. This modeling capability could then be used to prevent and/or mitigate cladding ruptures in postulated accident scenarios without penalizing operational parameters. Additionally, the results of this work will help identify strategies for finding additional margins or potentially limiting cladding ruptures through core design optimizations to enable more efficient core designs.

Capps, Nathan [Oak Ridge National Laboratory (ORNL↗

Characterization of Fuel Cladding Chemical Interaction on a High Burnup U-10Zr Metallic Fuel via Electron Energy Loss Spectroscopy Enhanced by Machine Learning

Fuel cladding chemical interaction (FCCI) is one of the main performance limiting factors for metallic nuclear fuels. The interaction destabilizes the martensitic microstructure and deteriorates mechanical properties of HT-9 cladding. The detection of low atomic number elements (Z<10) and overlapping of elemental peaks can be problematic in interpreting energy dispersive X-ray spectroscopy (EDS) data. Electron energy loss spectroscopy (EELS) provides precise elemental edge energy values and can detect elements with a low atomic number. This work utilizes EELS to study the distribution of lanthanides and light elements at the interaction region. The sample was prepared from the FCCI region of a U-10Zr (wt.%) solid fuel with HT-9 cladding, irradiated to a burnup of 13.2 at.%. Processing the EELS data included three major steps: 1) enhance the signal to noise ratio by denoising the spectrum with principal component analysis (PCA) method, removing background and performing deconvolution; 2) identify chemical elements with core energy loss edges; 3) confirm different phases using a popular machine learning method, K-means. This work presents qualitative assessment of lanthanides and light elements like carbon (C) and oxygen (O) enhanced by the application of machine learning algorithms. By comparing with EDS elemental maps, EELS provides higher resolution chemical maps, reveals the distribution of carbon at the interaction region supporting the formation of zirconium carbide, a rind-like microstructure feature that was proposed to mitigate the chemical interaction. Furthermore, the plasmon peak map was also found to indicate an energy shift associated with the formation of phases/compounds. K-means clustering method was used on the processed electron energy loss (EEL) spectrum to automatically reveal different phases. The resulting clustered maps from K-means clustering align well with elemental maps confirming certain phases, especially Fe-Ce and Zr-C, in the FCCI region.

EELS↗

The application of synchrotron micro-computed tomography to characterize the three-dimensional microstructure in irradiated nuclear fuel

This research demonstrated the first time that synchrotron X-ray micro-computed tomography (μ-CT) was utilized to analyze the three-dimensional (3-D) morphology of the microstructure of irradiated nuclear fuel. Both absorption contrast and propagation-based phase contrast enhanced μ-CT techniques were evaluated. Porosity and phase region volumes were determined in neutron irradiated uranium 10 wt.% zirconium (U-10Zr) using propagation-based phase contrast enhanced μ-CT. Volumes were determined by image processing software and algorithms, with the porosity volume subsequently compared to the ASTM E562 method. The 3-D porosity of a small region (~ 8 x 10 5 µm 3 ) located in the intermediate fuel redistribution zone that was removed via a focused ion beam was determined to be 7.2% via image processing. A detailed 3-D analysis of the porosity with respect to volume and morphology was provided. Five growth stages of pore evolution were observed including: nucleation, growth, coalescence, interconnected porosity, and extended/interconnected porosity. Four distinct phase regions were identified, including the pores, via both absorption contrast and propagation-based phase contrast enhanced μ-CT. A quantitative comparison of fuel swelling between this localized microscopic U-10Zr fuel region, previously irradiated in the Fast Flux Test Facility, and historic U-10Zr fuels irradiated in the Experimental Breeder Reactor-II (EBR-II) was conducted. It was determined that for similar burnups, the localized swelling in this microscopic fuel region was 7.7%, which was approximately one-half of the value of the macroscopic swelling reported in EBR-II irradiated fuel. With the advent of new specimen preparation tools for irradiated materials, as well as advances in characterization techniques, researchers can now obtain previously inaccessible microstructural insight into irradiated fuels. This possibility naturally lends itself to improved fuel performance models for the nuclear community.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Remote Fiber Based Velocimeter For Interface Strength Measurements

The understanding of the performance of nuclear reactor plate fuels is essential when developing new fuel systems. The condition of pre and post irradiated plate fuels must be characterized effectively and efficiently prior to irradiation and then post irradiation within a high rad environment. The post characterization work must be performed remotely and in an environment hostile to instrumentation. Laser based characterization methods provide the capability to be remote and robust within a hot-cell environment. Laser based characterization can provide high spatial resolution appropriate for scanning and imaging large areas. The INL is currently developing a laser shock system for Post Irradiation Examination (PIE) station for use in the Hot Fuel Examination Facility (HFEF) at the INL. The laser shock system is designed to characterize fuel to cladding and cladding to cladding interface strength. The laser shock-technique induces large amplitude shock waves to mechanically characterize interfaces such as the fuel-clad interface. The shock wave propagates as a compressional wave through the fuel plate to the free (unconfined) backside surface and is reflected back through the test plate as a rarefaction (tensile) wave. This rarefaction wave is the physical mechanism that produces internal delamination failure. The focus or this paper is on the accurate measurement of surface velocity to quantify the amount of energy traveling through the interfaces to the back surface of the fuel plate. The original fiber based velocimeter design was biased by parasitic back reflections. This paper will discuss the discovery of the back-reflection issue and the design changes to resolve the issue. Supporting data will be presented.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗