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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Neutron and x-ray computed tomography of a natural uranium tristructural isotropic (TRISO) fuel compact

A natural uranium-based, unirradiated tristructural isotropic (TRISO) fuel compact was nondestructively imaged using both X-ray (XCT) and neutron computed tomography (nCT). While XCT of compacts can provide information on fuel kernels, imaging artifacts preclude examination of the graphite matrix. In this work, nCT was used for the first time on a TRISO compact to examine the graphite matrix. A crack was clearly resolved within the graphite matrix, proving that nCT is a viable tool for nondestructive volumetric examination of the matrix material in TRISO fuel compacts. The XCT and nCT data were then fused together to create a more comprehensive dataset containing both matrix and fuel kernels.

36 - MATERIALS SCIENCE↗
DOE OSTI2022

TRISO SiC Failure Probability for Reactivity Initiated Accidents in High-Temperature Gas-Cooled Reactors

This work analyzes the failure process of the silicon carbide (SiC) layer in tristructural isotropic (TRISO) during reactivity-initiated accident scenarios for a high-temperature gas-cooled reactor (HTGR) with BISON. Two cases are considered—a group control rod withdrawal (CRW) and a control rod ejection (CRE)—reproduced from a previous study. Failure probability is modeled using Weibull statistics, and worst-case scenario Weibull parameters are adopted to simulate the envelopes in BISON with a one-dimensional TRISO model. CRW scenario results are characterized by higher values of maximum energy deposition and final temperature and volumetric strain with respect to the CRE ones, but the latter have remarkably higher SiC failure probability, mainly due to the offset in strain rates between the two cases. This work also confirms the validity and conservatism of the performance envelopes produced in a previous work by replicating the envelope formulation using RELAP5-3D and RAVEN with a different sampling technique and obtaining consistent results. A sensitivity analysis using the Sobol variance decomposition method on SiC failure probability is then performed involving a set of inputs on both CRW and CRE. The two most important parameters are Weibull modulus and characteristic stress, and their relative importance depends on the specific case. The proposed interpretation of the results is that both energy deposition and strain rate influence the relative degree of importance of the failure parameters. Computation of 95% confidence intervals around worst-case scenario SiC failure probability values is also carried out for four different sets of Weibull parameters. Heren a new criterion for SiC TRISO quality classification built upon safety-based ranges of Weibull parameters is proposed to be integrated in future Fuel-Production Quality Assurance Plans.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Fate and transport of unruptured tri-structural isotropic (TRISO) fuel particles in the event of environmental release for advanced and micro reactor applications

Advanced nuclear reactor designs and advanced fuel types offer safety features that may reduce environmental consequences in an accident scenario when compared to conventional reactors and fuels. One advanced reactor fuel is tri-structural isotropic (TRISO) fuel particles which are approximately 0.9 mm in diameter. TRISO particle mobility, assuming the particle is unruptured and the encapsulated radionuclides are contained, was explored through a theoretical examination of mobility through atmospheric, soil and groundwater, surface water, and non-human biota transport pathways. TRISO particles are too large and dense to travel in the atmosphere except under extreme conditions. TRISO particles are too large to penetrate most soil profiles and so cannot be transported with groundwater. TRISO particles will settle out of the water column in surface waters but the transport will depend on the energy of the body of water and likelihood of extreme dispersion events. TRISO particles could be transported by non-human biota. The size of TRISO particles could allow them to be intentionally moved by non-human biota if they are ingested as a gastrolith or if they are mistaken for something in the organism’s diet. Generally, TRISO particles will have reduced environmental mobility compared to releases of radionuclides in the event of an accident in a conventional nuclear reactor. The extent of transport has implications in emergency planning zone designations and other considerations for licensing and deploying TRISO-fueled reactors. Finally, further research and experimental work exploring TRISO particle mobility is required to understand the full environmental mobility of TRISO particles.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

RU Net for Automatic Characterization of TRISO Fuel Cross Sections

TRistructural ISOtropic (TRISO) particle fuel is a type of nuclear fuel known for its high-temperature and high-burnup performance. Each sub-millimeter diameter TRISO particle consists of uranium-oxycarbide (UCO) or UO2 fuel kernel, coated with buffer, inner pyrolytic carbon (IPyC), silicon carbide (SiC), and outer pyrolytic carbon (OPyC) layers. The SiC layer acts as the main containment barrier for the TRISO particle to retain the fission products, while the IPyC and OPyC layers provide additional barriers to the release of fission products, especially fission gases. During irradiation, phenomena like kernel swelling, buffer densification, and IPyC fracture may impact fuel performance. Post-irradiation microscopy on entire compact cross sections or samples of individual particles deconsolidated from compacts is often used to identify these irradiation-induced changes in morphology. However, each fuel compact generally contains thousands of TRISO particles. To get statistical information on these phenomena, it is cumbersome work if done manually. For example, to get information about swelling/densification behaviors of different layers or kernels after irradiation, researchers previously manually measured the perimeter of each TRISO layer in hundreds of particles after four rounds of iterative grinding and polishing encompassing more than 2000 cross-section images for a total of four fuel compacts. To attempt to reduce the subjectivity inherent in that process and accelerate data analysis, we conducted a study on the automatic TRISO layer segmentation on cross-sectional microscopic images using Convolutional Neural Networks (CNNs). CNNs are a class of machine learning algorithms specifically designed for processing structured grid data that have gained popularity in recent years due to their remarkable performance in various computer vision tasks, including image classification, object detection, and image segmentation. In this research, we have generated the large irradiated TRISO layer dataset with more than 2000 cross-section TRISO microscopic images and the corresponding annotated images. Based on these annotated images, we have employed different CNNs for automatic segmentation of different TRISO layers. These include RU-Net (developed in this study), as well as three existing architectures: U-Net, Residual Network (ResNet), and Attention U-Net. The preliminary results show that the model based on RU-Net has the best performance in terms of intersection-over-union (IoU). Through the aid of these CNN models, we can expedite the analysis of TRISO particle cross-sections, significantly reducing the manual labor involved and improving the objectivity of the segmentation results.

Convolutional Neural Networks↗
DOE OSTI2022

3D analysis of TRISO fuel compacts via X-ray computed tomography

In this study, low-enriched uranium oxycarbide (LEUCO) and surrogate tristructural isotropic (TRISO)- coated-particle compacts with particle volumetric packing fractions of 25%, 40%, and 48% were imaged utilizing X-ray-computed tomography. Subsequent 3D image analysis identified and further quantified kernel size, sphericity, and observed porosity. In addition, the spatial distribution, coordination number, and kernel-nearest neighbors were analyzed and compared for the different packing fractions. Metrics such as observed porosity and sphericity enabled quantification and screening for abnormal kernels within TRISO compacts. Assessment of TRISO particle location confirmed and further quantified a non-uniform distribution of TRISO particles with the spatial distribution in the radial direction being roughly described as a dampened sinusoidal function. The amplitude and frequency of this non-uniform distribution increased with increasing packing fraction. Measured kernel-nearest neighbor distances indicated two regions along the radial surfaces of compacts where TRISO particles are more likely to be in intimate contact with one another. These regions were found: (1) at upper and lower faces of compacts (i.e., corners); (2) offset ~10% of a compact's length from the axial center near the exterior surface. Within these regions, small quantities of defective TRISO surrogate particles (48% packing fraction) and defective LEUCO TRISO particles (40% packing fraction) were found. No defective particles were found within 25% packing fraction LEUCO TRISO compacts.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

High volume packing fraction TRISO-based fuel in light water reactors

We report that for a decade, fully ceramic microencapsulated (FCM) fuel, containing tri-structural isotropic (TRISO) fuel particles in a silicon carbide (SiC) matrix, has been investigated as an accident-tolerant fuel for light water reactors (LWRs). Other examples exist of TRISO-based concepts for LWR fuels with different matrix materials. Previous studies assumed TRISO particle volume packing of approximately 0.44 in SiC (or another) matrix, the highest realistic packing fractions possible with conventional manufacturing. Recent advances in advanced manufacturing have yielded the development and demonstration of a fuel form that consists of conventionally manufactured TRISO particles in a 3D-printed SiC matrix with significantly higher possible TRISO packing fractions (0.5–0.7). This increased uranium loading enhances the viability of using TRISO-based particle fuel forms in LWRs. The viability of high-packing-fraction TRISO-based particle fuel forms in LWRs is assessed from the perspective of fuel cycle length, achievable fuel burnup, reactivity coefficients, and fuel cycle performance. Higher-packing-fraction TRISO-based fuel enables either longer cycle lengths (by ~25% at a packing fraction of 0.55 relative to 0.44) at a constant enrichment or decreased enrichments (by ~25% at a packing fraction of 0.55 relative to 0.44) at a constant cycle length. Studies of different fuel kernel types (uranium nitride, uranium oxycarbide, and uranium carbide) yield similar results, although the cycle length of uranium oxycarbide is shorter than for uranium nitride or uranium carbide (due to the lower density of uranium oxide). This work also characterized the production of 14 C resulting from neutron absorption in 14 N during operation for uranium mononitride fuel kernels; the ratio of 14 C/N was 1–2 at. % at discharge. For the fuel cycle evaluation, the activity of spent nuclear fuel and high-level waste at 100 and 100,000 years was lower for high-packing-fraction fuels than for conventional LWR fuel. Environmental impact metrics were similar overall, but higher on the front end of the fuel cycle and lower on the back end of the fuel cycle. Reactivity coefficients of higher-packing-fraction TRISO-based fuel were reasonable compared with those of conventional fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Accelerated thermal property mapping of TRISO advanced nuclear fuel

TRistructural ISOtropic (TRISO) fuel is a leading-edge nuclear fuel form representing a departure from the more traditional nuclear fuel forms utilized in the reactor fleet of today. Rather than a monolithic fuel pellet of uranium dioxide, integral fuel forms containing TRISO fuel are composed of thousands of microencapsulated uranium-bearing fuel kernels and individually coated with multiple layers of pyrolytic carbon and silicon carbide. These multilayered ceramic coatings serve as an environmental barrier to ensure radioactive and chemically reactive fission products are contained within the reactor fuel elements, but also participate in the transfer of heat generated in the nuclear fuel to the coolant – the primary purpose of a nuclear reactor. Since traditional thermal property measurement techniques, such as laser flash analysis, would be unable to resolve the thermal properties of the individual TRISO coating layers, a simplified frequency-domain thermoreflectance technique has been developed to rapidly map the thermal properties of TRISO particles. Using this technique, the thermal properties of TRISO particles have been mapped from room temperature up to 1000 °C to examine the spatial variation and temperature-dependency of the thermal properties within each layer. Additionally, spatial-domain thermoreflectance was used to examine the anisotropy of the thermal properties for each layer at different locations within a single TRISO particle, and across multiple TRISO particles to assess the intra- and inter-particle uniformity of thermal properties, respectively. To elucidate the underlying causes for the measured variations in thermal properties, scanning electron microscopy and Raman spectroscopy were used to examine variations in microstructure and chemical bonding within the different coating layers. Results from this work are then compared with previous examinations of TRISO fuel particles and microstructurally driven mechanisms for the variations in the measured thermal properties of the different carbonaceous layers are discussed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Seeing the whole picture: Methods for getting the most from micro X-ray computed tomography of TRISO nuclear fuel particles

Tristructural isotropic (TRISO) coated fuel particles are a nuclear fuel form under extensive study for use in advanced nuclear reactor concepts. TRISO fuels are subjected to high temperature neutron irradiations and then examined to assess their performance by determining fission product retention and studying morphological changes. Micro X-ray computed tomography is one method of nondestructively studying the effects of TRISO performance. This work addresses the need for image processing to remove X-ray tomographic reconstruction artifacts that prevent the study of TRISO features, as the TRISO particles’ high Z kernel can introduce metal artifacts that degrade the image quality in the surrounding low Z coating layers. These metal artifacts were reduced by imaging the TRISO particles with both high- and low-energy X-rays and applying a mask to the radiographs obtained with low-energy X-rays to digitally remove the dense fuel kernel region. These masked radiographs were then used to produce a tomographic reconstruction which was combined with the tomographic reconstruction of the high-energy data. This enabled the relatively-low-density TRISO buffer layer to be examined in more detail, providing information on irradiation induced dimensional changes of the coatings. This methodology, which helps see the full picture of a TRISO particle, is not limited to nuclear fuels but can be applied to systems that contain highly attenuating material surrounded by less dense materials.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Methods development towards automated, physics-informed, quantitative quality control of TRISO-SiC

Tristructural-isotropic (TRISO) fuel particles have been developed as a high-performance fuel for use in high-temperature gas-cooled reactor (HTGR) systems due to their high efficiency and stability under both normal and off-normal conditions. Broader deployment of this technology in advanced nuclear applications may benefit from quantitative quality assurance and quality control (QA/QC) methods that directly link TRISO properties to downstream performance. A key TRISO property is the SiC layer microstructure, which influences fission product retention during irradiation. However, existing QA/QC for the TRISO-SiC microstructure comprises only a qualitative visual inspection; therefore, there is a clear opportunity for the development of quantitative methods for TRISO QA/QC. Here, to this end, previous work has demonstrated an image processing approach to grain boundary (GB) identification and subsequent extraction of microstructural metrics; however, extensive twinning within the SiC layer complicates such analyses because twin GBs significantly influence microstructural metrics but are not expected to contribute to fission product transport. This study presents the initial development, training, and testing of an ML-based image segmentation algorithm designed to identify and remove twin GBs from standard backscattered electron micrographs, providing an industrially applicable, quantitative, and physically meaningful QA/QC approach for the TRISO-SiC microstructure. Although pixel-wise performance metrics for the twin predictions are low, the change in grain area and the number of GB pixels after twin removal predicted by the ML workflow are within 1% of the true values calculated using crystallographic data. This suggests that the model is well capable of predicting overall twin boundary structures and grain morphology, and continued advancement of this approach could enable automated, scalable, and physics-informed QA/QC for TRISO-SiC microstructures, supporting the reliable qualification of coated particle fuels for next-generation reactor systems.

Computer vision↗
DOE OSTI2026

RU-net for automatic characterization of TRISO fuel cross sections

During irradiation, phenomena such as kernel swelling and buffer densification may impact the performance of tristructural isotropic (TRISO) particle fuel. Post-irradiation microscopy is often used to identify these irradiation-induced morphologic changes. However, each fuel compact generally contains thousands of TRISO particles. Manually performing the work to get statistical information on these phenomena is cumbersome and subjective. Here, to reduce the subjectivity inherent in that process and to accelerate data analysis, we used convolutional neural networks (CNNs) to automatically segment cross-sectional images of microscopic TRISO layers. CNNs are a class of machine-learning algorithms specifically designed for processing structured grid data. They have gained popularity in recent years due to their remarkable performance in various computer vision tasks, including image classification, object detection, and image segmentation. In this research, we generated a large irradiated TRISO layer dataset with more than 2,000 microscopic images of cross-sectional TRISO particles and the corresponding annotated images. Based on these annotated images, we used different CNNs to automatically segment different TRISO layers. These CNNs include RU-Net (developed in this study), as well as three existing architectures: U-Net, Residual Network (ResNet), and Attention U-Net. The preliminary results show that the model based on RU-Net performs best in terms of Intersection over Union (IoU). Using CNN models, we can expedite the analysis of TRISO particle cross sections, significantly reducing the manual labor involved and improving the objectivity of the segmentation results.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

TRISO fuel performance analysis: Uncertainty quantification toward optimization

Tri-structural isotropic (TRISO) fuel particles are a fuel form being considered for potential use in next-generation nuclear reactors (i.e., high-temperature gas-cooled reactors). Though the TRISO fuel manufacturing process has continually advanced in recent years, particle comparisons still reveal statistical variations and uncertainties in terms of geometric configurations and material properties. Given that the physical processes ongoing in TRISO fuel particles during reactor operation are highly correlated with each other, a small degree of uncertainty in one model may lead to significant uncertainty in another. This makes appropriate uncertainty quantification of TRISO fuel particles essential. However, one may wonder about the extent to which the current version of TRISO particles has been optimized, and whether any room remains for further improvements. This paper quantifies TRISO fuel performance model uncertainties that stem from geometric and material data. For this analysis, the BISON code was used, and the Advanced Gas Reactor (AGR)-2 experiment served as a reference case. A total of 10 5 calculations was performed for the uncertainty and optimization analysis, altering the geometric and material data within their uncertainty range. Lastly, the optimization potential of TRISO particles is evaluated from a fuel performance perspective.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

BISON TRISO Modeling Advancements and Validation to AGR-1 Data

BISON is a finite element-based nuclear fuel performance code. Among its unique characteristics are its ability to model 1D, 2D, and 3D geometries and its applicability to a wide variety of nuclear fuels. For the last eight years, BISON has included a beginning capability to model tri-structural isotropic (TRISO) fuel. Recently, interest in TRISO fuel has grown, and a significant effort has been made to improve BISON’s capabilities in this area. Capability development has occurred for each material present in TRISO fuel particles: the buffer, inner pyrolytic carbon, silicon carbide, and outer pyrolytic carbon layers, as well as the fuel kernel. New elastic, creep, swelling, thermal expansion, thermal conductivity, and fission gas release (FGR) models are available. New models for the graphite matrix are also now available. Another important addition is the ability to perform statistical failure analysis of large samples of fuel particles. This new capability, which continues to grow, enables evaluation of failure due to pressure or crack formation by analyzing many thousands of particles. This enables realistic calculations of fission product release from the many particles in a TRISO-fueled reactor. These capabilities were checked via regression and verification tests. A large number of code benchmarking problems were also run, showing that BISON’s results closely match those of other software tools. Finally, a significant validation effort was completed in which fission product release, measured as part of the AGR-1 capsule experiments, was compared to BISON outputs. BISON outputs compared very well to the experimental data and to PARFUME results. Interest in BISON’s TRISO capabilities is growing, with the U.S. Nuclear Regulatory Commission (NRC) and Westinghouse Electric Company receiving training during the past year. Multiple other entities have expressed interest in or are actively using BISON. Kairos Power, LLC, has a strong partnership with Idaho National Laboratory (INL) regarding the use of BISON for TRISO analysis. While its capabilities still continue to grow, BISON has already become a powerful tool for TRISO analysis.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Simulation of a TRISO MiniFuel irradiation experiment with data-informed uncertainty quantification

An irradiation experiment using tristructural isotropic (TRISO) fuel particles and the miniature fuel (MiniFuel) irradiation vehicle was performed in Oak Ridge National Laboratory’s High Flux Isotope Reactor (HFIR) to support development of the Kairos Power fluoride salt–cooled, high-temperature reactor (KP-FHR). Here, this paper describes modeling predictions of temperatures and fuel burnup for the as-built experiment. An uncertainty quantification (UQ) analysis was performed to determine the effect of TRISO particle volume and position on the temperature predictions at various fuel heat generation rates (HGRs). This UQ study utilized fuel kernel position and volume measurements previously collected using X-ray computed tomography (XCT) techniques and Monte Carlo sampling methods to generate fuel compact cases that were then analyzed using a finite element thermal model. The UQ analysis indicated that uncertainty in calculated temperatures caused by varying TRISO particle arrangement is relatively small, even at high fuel HGR. Final predictions of particle temperatures throughout the irradiation are shown to be relevant to KP-FHR normal and off-normal operating conditions and to previous TRISO irradiation experiments. The combination of XCT with UQ analyses will inform post-irradiation examination (PIE) of the irradiated fuel compacts, and these analyses can be used to develop fuel performance models for coated particle fuel forms. Both PIE of separate-effects irradiation data and enhanced fuel performance modeling support accelerated qualification of TRISO fuels for a broad range of advanced reactor applications. The novel approach demonstrated here of measuring TRISO particle configurations with XCT methods and generating representative fuel compacts for finite element modeling and UQ analysis could be leveraged by the broader particle fuel community in the development of other TRISO fuel experiments in which these variables may have a significant impact on key outcomes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Destructive Analysis of TRISO Particles: Crush/Burn/Leach Followed by Davies-Gray Titration and IDMS

The accurate accounting of nuclear materials is a cornerstone of international nuclear safeguards. One emerging challenge in this domain is the fabrication of TRIstructural ISOtropic (TRISO) particle fuels. Although these innovative fuel forms are critical for advanced reactor applications, their robust refractory ceramics and coating compositions present significant obstacles to destructive analysis (DA) methods. Ensuring full and quantitative recovery from these particles is essential for accurate mass accountancy. The current study was initiated to address these challenges, first by validating a previously established destructive method developed by Oak Ridge National Laboratory (ORNL) for the quantitative recovery of uranium from TRISO particles and then following that process with uranium content determination through isotope dilution mass spectrometry (IDMS) and Davies-Gray titration. This study expands on the scope of a digestive method that was developed under the Advanced Gas Reactor Fuel Development and Qualification program and is currently implemented in both the Coated Particle Fuel Development Laboratory and Irradiated Fuels Examination Laboratory at ORNL. The success of the previous Advanced Gas Reactor work relied on developing a DA method to evaluate the fabrication process and reactor experiments. The methodology described in this report was designed to rigorously investigate the efficacy of the crush/burn/leach sample preparation of TRISO particles; it aims to quantify uranium recovery while also assessing the effects of TRISO constituents (e.g., silicon and zirconium) on analytical precision and accuracy. By comparing the results from the titration method and IDMS, we sought to determine whether existing analytical procedures accepted by the International Atomic Energy Agency (IAEA) could be effectively translated to TRISO fuel forms. The team employed an approach that involved processing replicate TRISO samples, optimizing the milling (i.e., crushing) step and performing serial leaches. The elemental composition of the analytical samples was examined to prepare for interference studies in the second year of this project. The integration of gamma spectrometry to verify residual uranium activity further strengthened the validation. Statistical methods were applied to the collected data to evaluate the uncertainties arising from sampling, sample preparation and uranium quantification. These uncertainties were then compared to the IAEA’s international target values (ITVs). Additional data collected in upcoming project work will strengthen the uncertainty estimates. Ultimately, it is hoped that this project will contribute materially to the body of work related to characterization of TRISO based fuels for the purpose of material accountancy and its applications to international safeguards.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Comparison of unirradiated and irradiated AGR-2 TRISO fuel particle oxidation response

The silicon carbide (SiC) coating in a tristructural isotropic (TRISO) particle acts as a barrier to fission product release during reactor operation and accident scenarios. Oxidation and subsequent failure of the SiC layer during a rare air ingress event is a proposed mechanism for fission product release in a high-temperature gas-cooled reactor (HTGR). Although previous oxidation studies have analyzed unirradiated TRISO particle response, this study compared the oxidation behavior of irradiated and unirradiated TRISO particles from the second Advanced Gas Reactor Fuel Development and Qualification Program irradiation experiment (AGR-2). Particles with exposed SiC were subjected to six varying oxidizing tests in the Furnace for Irradiated TRISO Testing (FITT), examined for failure fraction with the Irradiated Microsphere Gamma Analyzer (IMGA) and characterized with focused ion beam and scanning/transmission electron microscopy techniques to analyze the oxide layer. Uncorrelated unirradiated particle failures throughout the series of exposures suggests that external factors inherent to the experiment increased particle failure sensitivity. However, irradiated particle observations indicated an increased failure response at 400 h 1400 °C in both 2% and 21% O 2 atmospheres above failure associated with external factors. Oxide thickness measurements after 400 h at 1400 °C revealed a greater oxidation rate than predicted by parabolic growth, which was attributed to the increased complexity of the oxide structure at longer exposure times. Altering the atmosphere from 21% to 2% O 2 reduced the average oxide thickness by approximately 12%–14% in both irradiated and unirradiated particles at 400 h 1400 °C. Altogether, the minor variations observed between irradiated and unirradiated particles in this study led to the conclusion that unirradiated TRISO particles can be used to approximate irradiated TRISO oxidation kinetics.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Versatile TRISO fuel particle modeling in Bison

Tri-structural isotropic (TRISO) fuel particles are a key component in several previous and current reactors as well as in a variety of novel nuclear reactor designs. Interest in TRISO fuel is on the rise, necessitating considerable computer modeling of TRISO fuel behavior in order to support related design and licensing activities. The Bison nuclear fuel performance code, which offers a full set of capabilities for modeling TRISO fuels, makes it easier to explore the various important aspects of TRISO fuel behavior. One key advantage of Bison is its ability to create meshes in 1D, 2D, and 3D. Users can customize these meshes for specific geometries, mesh densities, and use cases. This enables a wide variety of analyses, including thermal, structural, mass diffusion, homogenization, and statistical failure analyses. Furthermore, the meshing capability simplifies analysts’ workflows. The inherent mesh generation capability eliminates the need for separate mesh-generating software and mesh file management. Also, the fact that the meshes are customizable makes it straightforward to automate an investigation over a range of geometric parameters or mesh densities. Here, the present paper highlights the ease with which Bison may be used to create meshes for both simple and relatively complex TRISO fuel particles, and it explores the types of analyses enabled by these meshes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Development of a BISON validation case for the TRISO transient irradiations in NSRR using effective heat capacity methods

The current tristructural isotropic (TRISO) fuel assessment and validation database in BISON primarily covers steady- state irradiation and high-temperature furnace testing. Transient assessment cases are potentially needed to support U.S. industry efforts in designing and deploying commercial reactors using TRISO fuels. Historical transient tests in- volving TRISO fuels used highly conservative conditions compared to the typical high-temperature gas-cooled reactor accident scenarios. Despite this, modeling historical transient tests is fundamental for evaluating BISON’s predictive capabilities, adapting material properties for high-temperature and high-particle-power regimes, and developing a sys- tematic validation approach for TRISO transient applications. This work developed a 1D model of transient experiments carried out at the Nuclear Safety Research Reactor using BISON. BISON’s predictions of energy deposition, UO 2 melting onset, and molten volume fractions are compared against experimental measurements. Melting was modeled using an effective specific heat capacity model for UO 2 . We found that BISON’s predictions are in reasonable agreement with experimental data for low-energy-deposition cases, and that BISON overpredicts melting at higher energy depositions. We also discuss the potential causes of discrepancies between the simulated and measured results and propose ways to further develop the model. Although these simulations used conservative conditions compared to those expected for actual TRISO-fueled reactors, they extended the range of conditions reflected in the data in the existing BISON database for TRISO fuels.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Micro-tensile Properties of Fueled Irradiated AGR-2 TRISO-coated Particle Buffer, IPyC, and SiC Interlayer Regions

Tristructural isotropic (TRISO) coated nuclear fuel particles are proving to be a versatile fuel form for new reactor designs. Understanding the bounding strength and failure mode of each coating interface is important to both fuel quality evaluation and failure prediction. A mechanism of key significance is failure of the silicon carbide (SiC) layer to retain fission products due to incomplete tearing of the buffer layer. This is a two-step mechanism involving both mechanical failure in the buffer and inner pyrolytic carbon (IPyC) layers and degradation of the SiC layer through palladium silicides at the IPyC-SiC interface. However, the mechanical properties of TRISO particle coating layers have yet to be fully characterized due to the small dimension of TRISO fuel particles and high radioactivity. To investigate this mechanism, in situ micro-tensile properties of the buffer, IPyC, SiC, buffer-IPyC, and IPyC-SiC interlayer regions of fueled TRISO particles have been tested at both as-fabricated and irradiated conditions. Determination of the mechanical properties of these TRISO particle regions will lead to a better understanding of the SiC layer failure mechanism and enable progress towards TRISO fuel qualification.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗