Exposed Kernel Heating Tests
Presentation on cracked AGR-2 TRISO particles and AGR-3/4 compacts subjected to FACS tests with and without prior reirradiation.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
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Post-irradiation Heating Tests of As-Irradiated AGR-3/4 TRISO Fuel Compacts
Four post-irradiation heating tests of fuel compacts from the U.S. Advanced Gas Reactor (AGR)-3/4 irradiation experiment were completed. In addition to tristructural isotropic (TRISO)-coated driver fuel, each compact contained designed-to-fail (DTF) particles with fuel kernels coated only in pyrocarbon so as to simulate exposed kernels. Tests at 1600/1700°C, 1400°C, and 1200°C were performed to measure fission product release as a function of time and temperature. Silver release was highest in the 1200°C test, supporting the observation that silver release rates are highest in the 1100–1300°C range. Compared to tests of AGR-1 compacts with no exposed kernels, the Cs-134 and Kr-85 releases were noticeably higher in AGR-3/4. The exposed kernels’ contributions to Eu and Sr release are inconclusive, due to the difficulty in distinguishing among the combined effects of higher irradiation temperatures in these particular AGR-3/4 compacts, the presence of the DTF particles, and the Fuel Accident Condition Simulator (FACS) test temperatures. These data can be used to make inferences about fission product retention in exposed kernels as a function of time and temperature.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
AGR-5/6/7 Final Release-to-Birth Ratio Data Analysis
AGR-5/6/7 is the last of a series of Advanced Gas Reactor (AGR) experiments conducted in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL) in support of development and qualification of tristructural isotropic (TRISO) low-enriched fuel for use in the high-temperature gas cooled reactor (HTGR). AGR configuration and irradiation conditions are based on prismatic HTGR technology that is distinguished primarily through the use of helium coolant, a low-power-density ceramic core capable of withstanding very high temperatures, and TRISO-coated particle fuel. The AGR tests provide valuable irradiation-performance data to support fuel process development, qualify fuel for normal operation and accident conditions, and support development and validation of fuel performance and fission-product (FP) transport models and codes. Each AGR test consists of multiple independently controlled and monitored capsules containing fuel compacts placed in a graphite cylinder shrouded by a steel shell. Release-to-birth ratios (R/B) for fission-gas isotopes released from each capsule are calculated from release rates, measured by germanium detectors in the Fission Product Monitoring System (FPMS) installed downstream from each capsule, and birth rates calculated using numerical models of FG generation. The R/Bs are a critical measure of the ability of the fuel kernel, the particle coating layers, and the compact matrix to retain fission-gas atoms, preventing their release into the sweep-gas flow, and the impact of initially defective particles and/or particle-coating failures that occur during irradiation. For fission-gas isotopes, particle failure is defined as failure of all coating layers, allowing gaseous fission atoms to escape from a particle. During the first five cycles (162B ? 165A), R/Bs were stable in the 10-8?10-6 range, and no in-pile particle failures were observed, based on the gross gamma counts. The maximum R/B value of around 2 ? 10-6 for Kr-85m resulted from the presence of as-fabricated exposed kernels (based on the high exposed kernel fraction), the dispersed uranium, and high fuel particle temperatures in Capsule 1. Comparison of capsule-measured R/Bs from these early cycles to predictions using the previously developed AGR R/B model demonstrated FG release from the AGR-5/6/7 TRISO fuel was comparable to that of previous experiments. In addition, the Kr-85m R/B per-exposed-kernel values are comparable to R/B values obtained in AGR-3/4 irradiation experiment and four irradiation experiments performed during 1980s: (1) HRB-17/18, (2) COMEDIE-BD1, (3) HFR B1, and (4) HRB-21. In contrast, all measured R/B values are lower than predictions by the commonly used Richards and German models, which are intentionally conservative. A large number of in-pile particle failures occurred in Capsule 1 by the end of Cycle 166A. During the final four cycles (166A ? 168A), apparent damage to the Capsule 1 gas line appeared to cause FG leakage from that capsule into the other four capsules, resulting in an increase in fission gas (FG) detected in the effluent for all capsules. Isolation of the Capsule 1 gas line during the last three cycles also prevented measurement of its FG release. Thus, R/Bs in all capsules after Cycle 166A are highly uncertain because of undefined amount of leakage from Capsule 1, especially for long-lived isotopes. A few hundred in-pile particle failures were estimated for Capsule 1 before the end of Cycle 166A, but the total number of failures is unknown due to the lack of FG release data in the later cycles. Based primarily on evidence from the gross gamma counts during Cycle 168A, approximately 15 particles failed in Capsule 3 and four particles failed in Capsule 2. In-pile failures in Capsule 3 were anticipated because this capsule was designed to operate beyond the HTGR normal operating temperature range. In contrast, no in-pile failures were identified in the top two capsules (4 and 5) based on the absence of the typical spikes in gross gamma counts and low failure estimates using the AGR model, developed in INL/EXT-14-32970, for R/B of the short-lived isotopes (Kr-89 and Xe-137) with minimal leakage from Capsule 1.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
AGR-5/6/7 Irradiation Test Final As-run Report
This document presents the as-run analysis of the Advanced Gas Reactor (AGR)-5/6/7 irradiation experiment. AGR-5/6/7 is the last of a series of experiments conducted in the Advanced Test Reactor (ATR) at Idaho National Laboratory in support of the development and qualification of tri-structural isotropic low-enriched fuel for use in high-temperature gas-cooled reactors. The test train contained five separate capsules that were independently controlled and monitored. Each capsule contained multiple 24.91-mm-long and 12.25-mm-dimeter compacts filled with low-enriched uranium carbide/oxide tri-structural isotropic fuel particles. The objectives of the AGR-5/6/7 experiment were to: • Irradiate reference-design fuel particles to support fuel qualification. • Establish operating margins for the fuel, beyond normal operating conditions. • Provide irradiated-fuel performance data and irradiated-fuel samples for post-irradiation examination and safety testing. The primary objective of the AGR-5/6 test (Capsules 1, 2, 4, and 5) was to verify the successful performance of the reference-design fuel under normal operating conditions. The AGR-7 test (Capsule 3) was designed to explore fuel performance at higher temperatures. Its primary objective was to demonstrate the capability of the fuel to withstand conditions beyond normal operating conditions, in support of plant design and licensing. AGR-5/6/7 will also provide irradiated-fuel performance data based on the fission gas release from particles during irradiation. To achieve the test objectives, the AGR-5/6/7 experiment was irradiated in the northeast flux trap of the ATR with a planned duration of 500 effective full-power days. The northeast flux trap was selected because its larger diameter provided greater flexibility for test-train design compared to the Large B positions used for the AGR-1 and AGR-2 irradiations, significantly enhancing test capabilities for the combined irradiation campaigns. Due to delays in the ATR schedule, the AGR-5/6/7 irradiation was significantly shorter than the originally planned 13-cycle schedule. Irradiation began on February 16, 2018 and ended on July 22, 2020, spanning nine ATR cycles (162B–168A) over two and a half years. Thus, the AGR-5/6/7 fuel compacts were irradiated for a total of approximately 360.9 effective full-power days. Final burnup values, on a per-compact basis, ranged from 5.66 to 15.26% fissions per initial heavy metal atom, while fast fluence values ranged from 1.62 to 5.55 × 1025 n/m2 (E >0.18 MeV). Time-averaged volume-averaged fuel temperatures on a capsule basis at the end of irradiation ranged from 756°C in Capsule 5 to 1313°C in Capsule 3 excluding days with significantly lower temperature during the two short powered axial locator mechanism cycles, 163A and 167A. By the end of irradiation, 48 out of 54 installed thermocouples had failed (the bottom three capsules lost all thermocouples). During the first five cycles (162B – 165A), the fission-gas isotope release-rate-to-birthrate (R/B) ratios were stable in the 10-8–10-6 range, and no in-pile particle failures were observed based on the gross gamma counts. During this time, the high exposed kernel fraction and high fuel particle temperatures in Capsule 1 led to a maximum R/B value of around 2 ? 10-6 for Kr-85m. The fission gas release in all capsules started to increase from the second half of Cycle 166A, when a large number of in-pile particle failures occurred in Capsule 1 and a gas line problem in this capsule caused fission gas leakage at various degrees into the other four capsules. This gas line problem also prevented a fission gas release measurement for Capsule 1 during the last three cycles due to gas flow isolation. By the end of irradiation, it is estimated that approximately 15 particles failed in Capsule 3, which was considered possible because the experiment was designed to operate beyond the high-temperature gas-cooled reactor normal operating temperature range. A few hundred in-pile particle failures were estimated for Capsule 1 by the end of Cycle 166A, but the total number of failures is unknown due to the lack of fission gas release data in the later cycles. Additionally, four potential in-pile failures were identified for Capsule 2 during the last cycle, Cycle 168A. In contrast, no in-pile failures were identified in the top two capsules (4 and 5) based on the absence of the typical spikes in gross gamma counts and low failure estimates using the AGR-3/4 R/B per exposed kernel model.
11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Reirradiation and Post-reirradiation Heating Tests of Loose AGR-2 TRISO Particles and AGR-3/4 Fuel Compacts
To address the lack of data on the behavior of short-lived fission products I-131 (t1/2 = 8.02 d) and Xe-133 (t1/2 = 5.24 d) in the TRISO fuel system, loose AGR-2 particles and kernels were reirradiated in NRAD and subjected to post-reirradiation heating in the FACS furnace. This provided data on the release of fission products from exposed kernels, and the results were used to establish FACS condensation plate collection efficiencies for temperatures of 1000, 1200, and 1400°C where previously, the only collection efficiencies were for 1600°C tests. These new collection efficiencies were then applied to the NRAD-FACS tests of entire AGR-3/4 fuel compacts. Understanding the relative behavior of short-lived I-131, for example, is important because it is a significant contributor to offsite dose during postulated accidents, and Xe-133 has previously been used as a conservative indicator of I-131 behavior. These data will be used to support refinement of fission product transport models and HTGR source-term analyses.
11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
ORNL Analysis of Leach-Burn-Leach Round-Robin Test Samples
An international round-robin test to examine the consistency in leach-burn-leach (LBL) analysis of tristructural-isotropic- (TRISO-) coated particle fuel was conducted by three research organizations from the Generation IV International Forum member countries of the People’s Republic of China, the Republic of Korea, and the United States of America. Two sets of round-robin test samples were exchanged for analysis. One set of samples consisted of a series of nonuranium-bearing, TRISO-coated zirconium dioxide particles seeded with up to four depleted uranium-bearing, TRISO-coated uranium dioxide (UO 2 ) particles, which had intentionally damaged coating layers to simulate either particles with either exposed-kernel defects (i.e., particles with a cracked TRISO coating that should be detected during preburn leaching) or particles with silicon carbide (SiC) defects (i.e., particles with an intact pyrocarbon coating and a hole in the SiC layer that should be detected during postburn leaching). These simulated samples also contained added powder with known quantities of impurities from a coal standard. The other sample set consisted of representative sublots of UO 2 -TRISO particles fabricated in a production-scale coater, except they all contained depleted uranium instead of enriched uranium. In this report, the methodology used at Oak Ridge National Laboratory to conduct LBL analysis of the round-robin samples is presented, and the general results are summarized.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Adrastea: An Efficient FPGA Design Environment for Heterogeneous Scientific Computing and Machine Learning
We present Adrastea, an efficient FPGA design environment for developing scientific machine learning applications. FPGA development is challenging, from deployment, proper toolchain setup, programming methods, interfacing FPGA kernels, and more importantly, the need to explore design space choices to get the best performance and area usage from the FPGA kernel design. Adrastea provides an automated and scalable design flow to parameterize, implement, and optimize complex FPGA kernels and associated interfaces. We show how virtualization of the development environment via virtual machines is leveraged to simplify the setup of the FPGA toolchain while deploying the FPGA boards and while scaling up the automated design space exploration to leverage multiple machines concurrently. Adrastea provides an automated build and test environment of FPGA kernels. By exposing design space hyper-parameters, Adrastea can automatically search the design space in parallel to optimize the FPGA design for a given metric, usually performance or area. Adrastea simplifies the task of interfacing with the FPGA kernels with a simplified interface API. To demonstrate the capabilities of Adrastea, we implement a complex random forest machine learning kernel with 10,000 input features while achieving extremely low computing latency without loss of prediction accuracy, which is required by a scientific edge application at SNS. We also demonstrate Adrastea using an FFT kernel and show that for both applications Adrastea is able to systematically and efficiently evaluate different design options, which reduced the time and effort required to develop the kernel from months of manual work to days of automatic builds.
Young, Aaron↗
Concepts for Actinide Recovery from TRISO Used Nuclear Fuel
The work described in this report has developed a preliminary conceptual flowsheet based on limited published literature for the head-end of a TRISO oxycarbide UNF reprocessing plant. The essential function of the head-end is to prepare the UNF for subsequent separation of actinides. The main steps of the conceptual TRISO UNF head-end reprocessing flowsheet are: 1. Fragmentation of the graphite moderator to expose the fuel particles. 2. Separation of fuel particles from fragmented graphite moderator by sieving and fluidization. 3. Fragmentation of the fuel particles to expose the fuel kernel. 4. Dissolution of the fuel kernel in nitric acid. Noteworthy at this step is the formation of organic acids (mainly oxalic and mellitic acids) from the carbon associated with the fuel and TRISO coatings. These acids can interfere with actinide separations and solvent extraction hydraulic performance and carbon dioxide gas generation. 5. Clarification of the dissolved fuel solution to separate the coating fragments. 6. Dissolver off-gas treatment with specific emphasis on managing generation of carbon dioxide gas containing carbon-14. The quantity of carbon dioxide is projected to be 100 to 1000 times greater than that arising from dissolving LWR UNF. Pre or post treatment of the exposed fuel kernels could be undertaken to mitigate the formation of organic acids but there still exists a significant off-gas treatment challenge. The literature on reprocessing uranium nitride UNF was reviewed but a flowsheet was not specifically developed since its scope and uncertainties are expected to be encompassed by the oxycarbide flowsheet. Overall, the predominant feature of processing TRISO UNF is carbon management to reduce waste volume and mitigate the formation of carbon dioxide and organic acids. This report recommends broad areas of research that will help to further define the head-end flowsheet.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Boosting RDataFrame performance with transparent bulk event processing
RDataFrame is ROOT’s high-level interface for Python and C++ data analysis. Since it first became available, RDataFrame adoption has grown steadily and it is now poised to be a major component of analysis software pipelines for LHC Run 3 and beyond. Thanks to its design inspired by declarative programming principles, RDataFrame enables the development of highperformance, highly parallel analyses without requiring expert knowledge of multi-threading and I/O: user logic is expressed in terms of self-contained, small computation kernels tied together by a high-level API. This design completely decouples analysis logic from its actual execution, and opens several interesting avenues for workflow optimization. In particular, in this work we explore the benefits of moving internal data processing from an event-by-event to a bulkby-bulk loop. This refactoring dramatically reduces the framework’s runtime overheads; in collaboration with the I/O layer it improves data access patterns; it exposes information that optimizing compilers might use to auto-vectorize the invocation of user-defined computations; finally, while existing user-facing interfaces remain unaffected, it becomes possible to additionally offer interfaces that explicitly expose bulks of events, useful e.g. for the injection of GPU kernels into the analysis workflow. In order to inform similar future R&D, design challenges will be presented, as well as an investigation of the relevant timememory trade-off backed by novel performance benchmarks.
Guiraud, Enrico↗
MatRIS: Addressing the Challenges for Portability and Heterogeneity Using Tasking for Matrix Decomposition (Cholesky)
The ubiquitous in-node heterogeneity of HPC and cloud computing platforms makes software portability and performance optimization extremely challenging. Described here, the MatRIS multilevel math library abstraction framework employs tasking to alleviate these difficulties. MatRIS includes the IRIS task-based runtime on the bottom level and exposes different layers of abstraction to render algorithms architecturally agnostic. MatRIS ensures the decomposition and creation of tasks that represent the necessary encapsulation of the optimized kernels from both vendor and open-source math libraries. Once built, MatRIS can select different combinations of accelerators at runtime, making it portable even on diverse heterogeneous architectures. By leveraging the IRIS runtime’s features for managing heterogeneity, MatRIS deploys algorithms that remove the need to specify orchestration and data transfer. This study describes how the serial task abstraction of a tiled Cholesky factorization is made portable and scalable in the case of multi-device and multi-vendor heterogeneity on a node with NVIDIA and AMD GPUs by using MatRIS. First, we demonstrate that Cholesky in MatRIS provides multi-GPU scalability that offers competitive performance versus cuSolverMG. Then, we present the challenges and opportunities for heterogeneous execution.
Monil, M. A. H.↗
Developmental exposure to corn grown on Lake Erie dredged material: a preliminary analysis
While corn is considered to be a healthy food option, common agricultural practices, such as the application of soil amendments, might be introducing contaminants of concern (COC) into corn plants. The use of dredged material, which contain contaminants such as heavy metals, polychlorinated biphenyls (PCBs) and polycyclic aromatic hydrocarbons (PAHs), as a soil amendment is increasing. Contaminants from these amendments can accumulate in corn kernels harvested from plants grown on these sediments and potentially biomagnify in organisms that consume them. The extent to which secondary exposure to such contaminants in corn affect the mammalian central nervous system has been virtually unexplored. In this preliminary study, we examine the effects of exposure to corn grown in dredge amended soil or a commercially available feed corn on behavior and hippocampal volume in male and female rats. Perinatal exposure to dredge-amended corn altered behavior in the open-field and object recognition tasks in adulthood. Additionally, dredge-amended corn led to a reduction in hippocampal volume in male but not female adult rats. These results suggest the need for future studies examining how dredge-amended crops and/or commercially available feed corn may be exposing animals to COC that can alter neurodevelopment in a sex-specific manner. This future work will provide insight into the potential long-term consequences of soil amendment practices on the brain and behavior.
59 BASIC BIOLOGICAL SCIENCES↗
Using SpF to Achieve Petascale for Legacy Pseudospectral Applications
Pseudospectral (PS) methods possess a number of characteristics (e.g., efficiency, accuracy, natural boundary conditions) that are extremely desirable for dynamo models. Unfortunately, dynamo models based upon PS methods face a number of daunting challenges, which include exposing additional parallelism, leveraging hardware accelerators, exploiting hybrid parallelism, and improving the scalability of global memory transposes. Although these issues are a concern for most models, solutions for PS methods tend to require far more pervasive changes to underlying data and control structures. Further, improvements in performance in one model are difficult to transfer to other models, resulting in significant duplication of effort across the research community. We have developed an extensible software framework for pseudospectral methods called SpF that is intended to enable extreme scalability and optimal performance. Highlevel abstractions provided by SpF unburden applications of the responsibility of managing domain decomposition and load balance while reducing the changes in code required to adapt to new computing architectures. The key design concept in SpF is that each phase of the numerical calculation is partitioned into disjoint numerical kernels that can be performed entirely inprocessor. The granularity of domain decomposition provided by SpF is only constrained by the datalocality requirements of these kernels. SpF builds on top of optimized vendor libraries for common numerical operations such as transforms, matrix solvers, etc., but can also be configured to use open source alternatives for portability. SpF includes several alternative schemes for global data redistribution and is expected to serve as an ideal testbed for further research into optimal approaches for different network architectures. In this presentation, we will describe our experience in porting legacy pseudospectral models, MoSST and DYNAMO, to use SpF as well as present preliminary performance results provided by the improved scalability.
DYNAMO↗
SpF: Enabling Petascale Performance for Pseudospectral Dynamo Models
Pseudospectral (PS) methods possess a number of characteristics (e.g., efficiency, accuracy, natural boundary conditions) that are extremely desirable for dynamo models. Unfortunately, dynamo models based upon PS methods face a number of daunting challenges, which include exposing additional parallelism, leveraging hardware accelerators, exploiting hybrid parallelism, and improving the scalability of global memory transposes. Although these issues are a concern for most models, solutions for PS methods tend to require far more pervasive changes to underlying data and control structures. Further, improvements in performance in one model are difficult to transfer to other models, resulting in significant duplication of effort across the research community.We have developed an extensible software framework for pseudospectral methods called SpF that is intended to enable extreme scalability and optimal performance. High-level abstractions provided by SpF unburden applications of the responsibility of managing domain decomposition and load balance while reducing the changes in code required to adapt to new computing architectures. The key design concept in SpF is that each phase of the numerical calculation is partitioned into disjoint numerical kernels that can be performed entirely in-processor. The granularity of domain-decomposition provided by SpF is only constrained by the data-locality requirements of these kernels. SpF builds on top of optimized vendor libraries for common numerical operations such as transforms, matrix solvers, etc., but can also be configured to use open source alternatives for portability. SpF includes several alternative schemes for global data redistribution and is expected to serve as an ideal testbed for further research into optimal approaches for different network architectures.In this presentation, we will describe the basic architecture of SpF as well as preliminary performance data and experience with adapting legacy dynamo codes. We will conclude with a discussion of planned extensions to SpF that will provide pseudospectral applications with additional flexibility with regard to time integration, linear solvers, and discretization in the radial direction.
Pseudospectral (PS)↗
IRMA
IRMA (In)elastic Representation of Materials As S(α,β) evaluations IRMA turns one phonon model into three outputs that usually require three separate tool chains: an evaluated nuclear-data file, predicted neutron-scattering spectra, and scattering kernels for Monte Carlo transport. The three outputs draw on a single, consistent description of the material, so the evaluation, the spectroscopy that can validate it, and the transport that uses it always agree about the physics. Nuclear data. IRMA writes ENDF-6 File 7 thermal scattering evaluations on automatically constructed (α, β) grids. This part reimplements and generalizes NJOY's LEAPR: the classic kernels reproduce freshly generated NJOY2016 tapes digit for digit and published reference tapes to about 1e-4, and the generalized paths add the exact coherent one-phonon term, anisotropic Debye-Waller tensors, coherent elastic for arbitrary crystals, and a per-species partition for polyatomic materials. The tapes feed NJOY, AMPX, FUDGE, and every transport code downstream of them. Neutron spectroscopy. The irma.spectra forward model projects the same physics onto an instrument's kinematics and resolution: INS spectra for VISION and generic indirect geometries, and 2-D S(Q,E) powder maps for direct-geometry spectrometers, from a phonopy model or straight from a phonon DOS. It can be used to predict a proposed measurement before beam time; in analysis, it supplies the calculated single-scattering counterpart of a measured spectrum, from the same material description the evaluation was built from. Monte Carlo transport. The irma.ncrystal exporter writes per-temperature scattering kernels for the companion NCrystal plugin, so McStas, OpenMC, and other NCrystal-aware codes sample the same physics. The exported kernels carry the per-site anisotropic Debye-Waller tensors, keeping directional coherent-elastic physics that NCrystal's standard scalar treatment does not represent. With the same physics inside a transport code, an entire beamline becomes a virtual experiment: IRMA's end-to-end validation ran a custom McStas implementation of the ARCS spectrometer, assembled from the existing McVine and McStas models, against measured data. From a bare crystal structure. The irma mlip front end builds the phonon model itself: a structure file and a choice of potential are enough. Nine pretrained machine-learned interatomic potentials are supported, on a laptop CPU, with no first-principles calculation; an approximate phonon model for a new material costs minutes, not a DFT campaign, and the build emits prefilled inputs for all three outputs. The result is a good starting point rather than a finished evaluation: survey-quality physics with every parameter exposed for review. A converged atomistic calculation enters the same way, as a phonopy model, when higher fidelity is needed.
Ramic, Kemal [Oak Ridge National Laboratory (ORNL)↗
UN-SiC TRISO Post Irradiation Examination Developmental Work
As part of efforts to strengthen INL?s post irradiation analysis capabilities with non-Advanced Gas Reactor (AGR) tristructural isotropic (TRISO) fuels, two developmental activities were conducted. The first activity was to determine how best to analyze uranium nitride TRISO fuel kernels using electron probe microanalysis, while the second activity focused on developing a method to deconsolidate TRISO fuel particles that have been encased in a silicon carbide matrix. Because these two activities were unrelated, they have been presented separately in this report. Initial EPMA analyses showed nitrogen contents that far exceeded the concentration expected for UN--a line compound. Further examination showed that current literature values for the mass absorption coefficient (MAC) for the N ka X-ray absorbed by U ranged from approximately 1600 to 9500, with most values tending toward 9500. Measuring UN with five different progressively increasing accelerating voltages followed by using the modeling program xMAC suggests the actual MAC is approximately 2115. Additional MAC modifications were required to produce reasonable analytical results. Because of the inaccuracies of necessary MAC coefficients, UN analysis via scanning electron microscopy (SEM) is likely to produce inaccurate results. This is because SEM software does not typically allow the user to alter MACs. Tests have been performed to examine the feasibility of an electrochemical technique to liberate irradiated TRISO fuel from a SiC matrix without damaging the outer pyrolytic carbon layer of the fuel particle. The method is performed by electrochemically exposing the SiC to magnesium metal forming Mg2Si and C. Following exposure, the small SiC samples showed slight mass increases with no evidence of conversion to Mg2Si and C nor obvious degradation of the SiC samples.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Simulation and Analysis on Reactor Pressure Vessel (RPV) subjected to Pressurized Thermal Shock (PTS) under SBLOCA scenario by using Cardinal to support the fracture mechanics analyses
The structural components that comprise nuclear reactors and their supporting structures are subjected to harsh operating environments that can challenge their integrity, especially after exposure for extended durations or under accident condition. As one of the most significant components of a Reactor, the Reactor Pressure Vessel (RPV) is exposed to an aggressive environment during the operation time (e.g. more than 40 years). Ageing degradation mechanisms (e.g. thermos-fatigue) could grow initial defects up to a critical size, increasing the susceptibility to failure in the RPV. The conventional methods are mostly based on simple crack and structure geometries. Very limited studies consider the real conditions of the RPV subjected to a thermal shock due to a Loss of Coolant Accident (LOCA). During a LOCA event, the most severe conditions take place when the emergency core cooling (ECC) water is injected inside the cold legs filled initially with hotter water and/or steam. The rapid cooling of the down-comer and the internal RPV surface followed probably by re-pressurization of the RPV causes large temperature gradients and variation of pressure which induces thermal-mechanical stresses. In order to develop the model for integrity assessment of a reactor pressure vessel (RPV) subjected to pressurized thermal shock (PTS), a multi-physics simulation, which includes the thermo-hydraulic, thermo-mechanical and fracture mechanics analyses is necessary. The multi-physics simulations are performed using Cardinal, a wrapping of the GPU-oriented spectral element Computational Fluid Dynamics (CFD) code NekRS and other multi-physics sub-modules within the MOOSE framework. Cardinal now fully supports MOOSE stochastic perturbations of NekRS models with varying boundary conditions, initial conditions, material properties, and any other quantity which is defined by a kernel (such as coefficients in a momentum source model). The implementation is designed in a flexible manner so that scalar values are sent from MOOSE into a user scratch space in NekRS, which can then be applied for any purpose within the NekRS case files (both on the host and device). When modeling PTS, several factors can impact the results significantly. In this report, the impacts of the geometry of the model, Reynolds number and buoyancy effect are investigated. Two geometry, i.e., a simplified model and a realistic RPV model, with both laminar and turbulent flow condition are adopted for the PTS simulation with and without buoyancy effect. The purpose of the investigation is to understand the impact of these factors on the prediction of temperature history of RPV. The accurate prediction on the temperature evolution, which will be exported to Grizzly code for further analyses on the progression of aging mechanisms and their effects on the integrity of RPV structures, is very crucial. Based on the understanding of these factors, a more sophisticated model is built to analysis the PTS under SBLOCA scenario. A literature survey is conducted to pick the SBLOCA scenario for the multi-physics simulation. The analysis helps to explain the form and the transformation of the cold plum when the ECC is activated under SBLOCA. This model can be can be applied to study the PTS effect for different RPV configurations. The results can help to assess structural component degradation for advanced reactors.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗