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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Impact of temperature variations on BISON predictions of Ag release in AGR-1 and AGR-2 experiments

Understanding and quantifying the release of fission products like silver (Ag) from TRistructural ISOtropic (TRISO) fuel particles is important to assess the safe operation of advanced high temperature reactors. Although the silicon carbide (SiC) layer of TRISO particles is effective as the main fission product barrier, Ag can be released from intact TRISO particles. A mechanistic model for the effective Ag diffusivity, D eff , was previously developed as a function of temperature and microstructure variables informed by atomistic modeling of Ag diffusivity on the mesoscale. Here in this study, we use this model to explore how experimental temperature uncertainties impact the overall predicted Ag release. This analysis shows that temperature uncertainties have a significant impact on the overall Ag release predictions. Furthermore, we show that the time average volume average temperature (TAVA) temperature is not an appropriate proxy for temperature histories to predict fission product release. We attribute this to the Arrhenius dependence of Ag diffusivity with respect to temperature. The detailed temperature histories, therefore, provide the most accurate results are are of most importance for modeling efforts. Overall, this work shows the importance of considering the experimental uncertainty of the temperature on computational predictions of fission product transport and release and the need for more accurate temperature histories from future experiments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Multiscale, mechanistic modeling of irradiation-enhanced silver diffusion in TRISO particles

Tristructural isotropic (TRISO) particles are under consideration for use in several proposed advanced nuclear reactor concepts. The silicon carbide (SiC) layer in TRISO acts as a barrier to prevent the release of the fission products. However, despite remarkable retention, silver (Ag) release has been observed from intact particles, which requires investigation since the Ag isotope ( 110m Ag) has a long half-life. Previous work focused on developing a multiscale, mechanistic model for Ag diffusion accounting for temperature and microstructure effect and has been successfully validated. In this work, we expand the previous model to account for irradiation-enhanced Ag diffusivity in SiC and improve its accuracy over a wider grain size and temperature ranges relevant for advanced reactor conditions. A temperature, grain size, and flux dependent diffusivity is therefore derived using the mesoscale code MARMOT and implemented in the fuel performance code BISON. The irradiation-enhanced Ag diffusivity in SiC is compared against experimental data and validated using BISON against Ag release measurements from the Advanced Gas Reactor Fuel Development and Qualification Program (AGR-1 and AGR-2). Herein, we quantify the impact of SiC grain size, irradiation, and temperature on Ag release. In agreement with previous studies, we find accounting for SiC grain size improves agreement between BISON predictions and experimental observations for most cases. In conclusion, we also find that accounting for irradiation improves agreement for cases where Ag release was underestimated, but the impact was less significant than accounting for microstructure.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Micromechanical response of SiC-OPyC layers in TRISO fuel particles

Tristructural isotropic (TRISO)–coated particle fuel is a proposed fuel for multiple advanced reactor concepts. The performance of the particle depends on whether the silicon carbide (SiC) layer remains intact to prevent the release of metallic and gaseous fission products. Mechanical fracture of the SiC layer is a potential failure mode under various fuel configurations and operating environments, including the potential transmission of matrix-originating cracks through TRISO particles. Furthermore, this study uses instrumented indentation techniques on cross-sectioned surrogate particles to examine the mechanical stability of the critical interface between SiC and the outer pyrolytic carbon (OPyC) layer. The observed behavior at the interface is rationalized by examining the radially dependent fracture behavior of the SiC layer and performing a numerical analysis to quantify the residual stresses that develop during the processing and cross-sectioning of the as-fabricated particle. Characterizing the SiC-OPyC interface of surrogate TRISO particles using nanoindentation provides unique insight into the interface's room-temperature residual stress and mechanical stability. The modeling efforts were used to investigate the experimental procedure further, and the results are presented herein to validate this fuel form's potential mechanical failure modes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Unpacking model inadequacy: The quantification of silver release from TRISO fuel by considering empirical and mechanistic approaches

Increasing adoption of the proposed tristructural isotropic (TRISO) particle fuel for both advanced and existing reactors makes it critical to assess and address any uncertainties and inadequacies of TRISO fission product release models. Model inadequacy stems from simplifications made to the computational model when compared to the experiments. The modeling and simulation efforts conducted using the BISON fuel performance code, along with the experimental campaigns carried out under the Advanced Gas Reactor Fuel Development and Qualification Program, afford a unique opportunity to conduct a rigorous modeling inadequacy assessment within the Bayesian uncertainty quantification (UQ) framework. Here, this study compares the standard Bayesian framework against the Kennedy-O'Hagan (KOH) framework, which explicitly represents modeling inadequacy, in regard to UQ for TRISO silver release models. For this purpose, both the traditional Arrhenius equation fitted to experimental data and the more advanced lower-length-scale (LLS)-informed model, which considers microstructure information, are independently considered. Applying the inverse UQ process on the AGR-2 and -3/4 datasets revealed modeling inadequacy to be the most dominant source of uncertainty. Experimental noise uncertainty is also significant; however, model parameter uncertainty can be considered negligible. Interestingly, both the Arrhenius equation and the LLS-informed model demonstrated similar levels of modeling inadequacy. For the forward predictive UQ, the KOH framework improved both the accuracy and quality of quantified uncertainties in comparison to the standard Bayesian framework. This is true for both the Arrhenius equation and the LLS-informed model. In comparing these modeling approaches, both demonstrated similar performance at the engineering scale, while the LLS-informed model expectedly outperformed the Arrhenius equation at the mesoscale. These conclusions highlight the importance of explicitly accounting for modeling inadequacy in the UQ process, and reinforce the need for continuous refinement of physics-based models in order to address the modeling inadequacy.

Advanced reactors↗
DOE OSTI2026

A mechanistic, multiscale model for predicting Pd penetration in TRISO fuels using BISON

TRistructural ISOtropic (TRISO) particles use silicon carbide (SiC) as the primary structural member and barrier against metallic fission product (FP) release. palladiums (PDs), produced by fission in the fuel kernel, can diffuse to and chemically interact with the SiC layer, degrading its structural integrity and ability to contain radioactive FPs. Existing temperature-dependent correlations for predicting Pd penetration rely on experimental data with significant scatter due to varying conditions, potentially complicating ongoing fuel qualification and licensing efforts for advanced reactors that would subject TRISO fuels to operating conditions outside of those examined in the experiments. A mechanistic model of Pd production, transport, and reaction is developed in this work to better understand and predict PD attack of SiC in TRISO particles. molecular dynamicss (MDs) simulations are utilized to calculate the Pd diffusivity in SiC grain bulk and grain boundaries. A mesoscale phase-field diffusion model, informed by the MD diffusivities, is used to develop a reduced order model (ROM) for the effect of SiC microstructure on the Pd penetration rate. The engineering scale BISON model calculates Pd production and transport, utilizing the ROM to predict penetration rates consistent with experimental data. This novel mechanistic ROM captures the effect of temperature, microstructure, and irradiation history on Pd penetration. In conclusion, these new capabilities are expected to support ongoing qualification and licensing efforts associated with near-term TRISO-fueled reactor applications.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
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

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 OSTI2025

Comprehensive defect evaluation of advanced nuclear fuels using high-resolution acoustic signals and optimized sensor separation

Graphite pebble composite structures based on TRistructural-ISOtropic (TRISO) particles are being developed as core nuclear fuels in advanced power reactors, promising safe operation at increased temperatures. Ensuring the structural integrity of these nuclear fuels requires comprehensive and accurate non-destructive evaluation (NDE) techniques to characterize defects and damage in the pebbles. However, traditional acoustic evaluation methods face limitations in defect characterization due to the highly attenuative, and geometrically and compositionally complex nature of these structures. This study proposes an improved acoustic NDE technique for accurate detection and classification of anticipated relevant defects and damage in graphite pebbles using high-resolution acoustic signals and optimized transmit-receive sensor networks. The proposed approach utilizes a triangular three-sensor network as the base unit, comprising three transmit-receive sensors. The sensor separation distance, as well as acoustic excitation center frequency, pulse-width, and bandwidth are optimized to enhance spatial resolution and improve signal-to-noise ratio, enabling effective characterization of the smallest size and widest range of defects in pebbles. Furthermore, the use of the triangular sensor configuration instead of a more conventional transmit-receive sensor pair expands the inspection region from a one-dimensional linear path to a two-dimensional area, increasing spatial coverage. To mitigate challenges associated with processing of complex acoustic signals arising from high-frequency, high-bandwidth excitation in these structures, a machine-learning-based signal processing algorithm is integrated with the sensor network. In the machine-learning-based algorithm, multi-domain features are extracted from the acoustic signals to capture intricate signal characteristics, significantly improving defect identification and classification compared to traditional approaches. The proposed acoustic NDE technique offers considerable promise for practical and reliable defect/damage diagnostics of advanced nuclear pebble fuels.

42 ENGINEERING↗
DOE OSTI2020

Analysis of fission product distribution and composition in the TRISO layers of AGR-2 fuel

The Advanced Gas Reactor Fuel Qualification and Development Program's second irradiation experiment focuses on the performance of fuel particles produced in an industrial-scale coating system. Ongoing post-irradiation examination efforts include exploration of tristructural-isotropic (TRISO)-coated particle fuel in the as-irradiated state and subjected to elevated temperatures to simulate accident conditions (safety testing). Scanning electron microscopy (SEM) analysis with energy dispersive x-ray spectroscopy (EDS) was used to show the distribution of fission products within the TRISO layers. The SEM analysis showed a variation of fission product distribution within the TRISO layers based on irradiation temperature, burnup, individual particle fission product inventory retention, safety testing history and kernel composition. Finally, a key observation is that particles which likely experienced higher temperature showed a greater diversity and distribution of fission products and actinides in the IPyC and SiC layers, implying that temperature is a dominant variable influencing the transport of radionuclides in TRISO particles.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Transformational Challenge Reactor preconceptual core design studies

In the nuclear industry, a manufacturing-informed design approach has the potential to yield the most benefit from advanced manufacturing. By leveraging advanced materials, data science, and rapid testing and deployment, manufacturing-informed design can drive down costs and development times, ultimately improving future commercial viability. This approach is being demonstrated in the US Department of Energy Office of Nuclear Energy (DOE-NE) Transformational Challenge Reactor (TCR) program. Preconceptual design activities for TCR have been focused on analyzing and maturing four reactor core design concepts: two fast-spectrum and two thermal-spectrum systems. Furthermore, the designs were iteratively modified and analyzed, and subcomponents were manufactured in parallel over weeks instead of months or years. To meet key program initiatives (e.g., timeline and material use), several constraints—including fissile material availability, component availability, materials compatibility, and additive manufacturing capabilities—were factored into the design effort, yielding small cores less than one cubic meter in volume with near-term viability. Additionally, the TCR program has made significant progress on development of advanced moderator materials such as yttrium hydride, advancing the feasibility of gas-cooled thermal spectrum systems using less than 250 kg of high-assay low enriched uranium (HALEU) and occupying less than 1 m3. Each of the two resulting thermal designs uses a different fuel form: traditional UO2 ceramic fuel and tristructural isotropic (advanced TRISO) fuel particles embedded inside a SiC matrix. Core neutronics and thermal performance for these systems were assessed and summarized. Evaluation of the performance metrics for these two moderated designs has yielded the downselected TCR design: a TRISO-fueled and yttrium hydride moderated gas-cooled reactor.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Evaluation of pebble scanning strategies for fuel qualification by simple simulated radiography

Reactor designs using tristructural-isotropic (TRISO) particles in pebble fuel forms have been developed in multiple programs and are now being designed and deployed by several companies around the world. Fuel pebbles for these designs commonly contain an inner fueled zone packed with TRISO particles and a fuel-free zone on the surface of the pebble to protect the particles within. Therefore, qualification of pebbles for use in a reactor commonly requires determination that there are no TRISO particles within a given minimum distance to the pebble surface. This determination may be made non-destructively by pebble radiography, in which a series of x-ray projections of the pebble are acquired. In this work, a method to create and image representative digital pebbles was developed to allow for rapid testing of various pebble radiography strategies to evaluate their effectiveness in detecting escapee particles. Using this method, imaging strategies in two and three dimensions were tested with fixed and adaptive angular distributions. Here it was found that an adaptive two-dimensional pebble scanning strategy was the most effective for fuel pebble qualification.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Texture analysis of AGR program matrix materials

We report the fuel form for high-temperature gas-cooled reactors consists of tristructural isotropic (TRISO) particles embedded in a matrix of graphite flake and carbonized resin. The process of overcoating particles prior to compacting yields a circumferential orientation of the graphite flake surrounding the TRISO particles, which is modified to varied extents when overcoated particles are pressed into the final fuel form. As graphite is highly anisotropic, the texture may impact the properties and performance of the fuel. Ellipsometry was used to measure the texture of the matrix for fueled compacts and unfueled “matrix-only” samples. Results indicated local texture related to the spherical particles in compacts associated with overcoating versus a more linear layered structure in “matrix-only” samples.

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 OSTI2023

Evaluation of the spatial self-shielding impact for TRISO-based nuclear fuel depletion

Reactor physics analyses of nuclear cores with nuclear fuel concepts containing tristructural isotropic (TRISO) particles, such as pebbles or compact fuel elements, rely on various degrees of simplification to keep these highly heterogeneous problems computationally tractable. One such limitation regards the level of spatial discretization employed during burnup calculations, where traditionally only a limited number of spatial zones are modeled at the full core level and assume that the spectrum is constant within the fuel elements and TRISO particles in this depletion zone. This type of assumption neglects the impact of spatial self-shielding effect within the kernels (microscale level) as well as within the compact or pebbles (mesoscale level). Furthermore, the Monte Carlo code Serpent 2 contains many relevant features for efficiently modeling this type of geometry, including a collision-based domain decomposition intended for very large burnup calculations, which we leveraged for this work to quantify the impact of capturing neutron flux variations occurring at the micro- and mesoscale level on a series of high-temperature gas-cooled reactor fuel element depletion problems. While spatial self-shielding is observed at both scales, with differences from a volume-averaged burnup of ±7% within the kernels and ±2% between TRISO particles within the fuel element, the conjugated effect on nuclide inventories and multiplication factor are negligible, hence confirming that assuming a single average spectrum value may be sufficient for most applications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Impact of anisotropy on TRISO fuel performance

Manufacturing of tristructural isotropic (TRISO) particles involves the deposition of pyrolytic carbon (PyC) and silicon carbide (SiC) layers using the fluidized bed chemical vapor deposition (CVD) process. The CVD process is known to generate polycrystalline layers with crystallographic textures, which imparts anisotropic thermophysical properties to the layers. Past studies have shown the risk for particle failure increases with an increase in anisotropy. The limit beyond which the anisotropy of PyC layers becomes unacceptable due to failure risk has been identified as a high-priority knowledge gap. This work presents a first systematic study on the effects of anisotropic thermal and mechanical properties on TRISO fuel performance. This computational study, performed using the fuel performance code BISON, investigates how the anisotropy in elasticity and thermal properties affect the stresses, temperature, and failure of a TRISO particle. The influence of other factors, such as operating temperature and particle geometry on the anisotropy effects, also has been analyzed. The studies utilize the recently published anisotropic elasticity and thermal behavior models for TRISO PyC and SiC layers implemented using tensors with full anisotropic capability. The spherical TRISO particles with anisotropic properties were found to have greater maximum tensile stress and significantly higher failure probability than the spherical particles with isotropic properties. In conclusion, the fuel performance predicted using these recently developed models was found to be comparable with the performance obtained using the historical models.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Thermal oxidation of nuclear graphite and pyrolytic carbon coatings

The oxidation of pyrolytic carbon (PyC) deposited via fluidized bed chemical vapor deposition was characterized and compared with that of standard nuclear-grade graphite. The materials were heated at 700 to 1000 °C in a thermogravimetric analysis system under 20% v/v O 2 flow, allowing for direct comparison of dynamic oxidative mass change in each material. Further, three different PyC samples fabricated under different conditions exhibited variation in total mass loss and mass loss rate, varying by as much as 709 mg/cm 2 in total mass loss and 14.2 (mg/cm 2 )/min in mass loss rate at a single temperature. These variations highlight the correlation between PyC microstructure/defect density and oxidation susceptibility. Additionally, changes in the microstructure and composition between PyC and graphite were characterized via scanning electron microscopy and correlated to the mass loss results. The results of this work have implications toward the safety of tristructural isotropic (TRISO) and other coated particle fuels, especially under off-normal conditions, given the limited information that exists about the oxidation behavior of PyC.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Refinement and demonstration of a coupled BISON-Griffin workflow for designing targeted TRISO transient experiments in TREAT

The U.S. nuclear industry is expected to deploy tristructural isotropic (TRISO) particle fuel technologies for commercial reactors within the next decade. In previous work, we defined a preliminary transient design space for TRISO fuels, identified potential gaps in the available data, and began to develop multiphysics modeling tools that could be applied to design targeted Transient Reactor Test Facility (TREAT) experiments to fill these gaps. Here, this work builds on that foundation by (1) updating BISON fuel performance and Griffin reactor physics models to reflect the current TREAT experiment tube and capsule designs, (2) coupling the codes to improve the accuracy and usability of the transient design analyses, and (3) demonstrating their use over an expanded design space that includes fuel burnup. The simulated mechanical responses of the TRISO particles were complex functions of fission product accumulation, fission gas release, and irradiation-induced dimensional change in the pyrolytic carbon layers. The predicted tangential stresses in the particles' silicon carbide layers were least compressive for preheated tests involving fresh fuels but remained compressive throughout the ranges of temperature, heat rate, and burnup considered in this work. Finally, comparisons between the potential TREAT transients and historical test reactor irradiations showed that the TREAT tests would produce significantly lower average energy deposition rates, yielding less severe transients with greater relevance to near-term commercial applications. The use of these predictive capabilities has the potential to increase the value of each test, improving the overall efficiency and cost-effectiveness of transient testing for TRISO and other advanced fuels.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Multiphysics simulation of TRISO fuel compacts and the effects of homogenization on silver release predictions

This work studies the impact of explicit and homogenized modeling approaches on the multiphysics simulation of TRistructural ISOtropic (TRISO) fuel compacts in prismatic High Temperature Gas Reactors (HTGRs) and the silver release predictions. TRISO fuel compacts exhibit complex double heterogeneity that significantly affects heat conduction, neutron transport, and fission products release. In this work, we use Cardinal, a multiphysics tool based on the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, to couple neutron transport and heat conduction. OpenMC is used for neutron transport and the MOOSE heat transfer module is used for the heat conduction. Then, we use BISON for the silver release predictions. Two different modeling approaches—explicit modeling of individual TRISO particles and homogenized representation using effective thermal properties—are compared at high TRISO packing fractions (20% and 40%) across varying power densities. Results demonstrate that homogenization significantly under-predicts peak temperatures, for the case of high power/TRISO, there is a difference of 83.73 K in the maximum temperature. Additionally, homogenization underestimates the silver release predictions compared to explicit modeling. Specifically, the temperature and power density differences lead to significant differences in silver release predictions. This work demonstrates the importance of accurately modeling heterogeneity of the TRISO particles to reliably predict fission product release and assess reactor safety margins.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗