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At least 667 records · Page 37

Linear source method of characteristics in HELIOS2

The Studsvik Scandpower code HELIOS2 is a fast lattice transport code that has gained wide use for reactor fuel cycle analysis in commercial, regulatory, and research environments. It contains two transport solvers - Collision Probabilities (CP) and Method of Characteristics (MoC) - with a general geometry ability and generalized depletion for a variety of fuel types, experimental facilities, and isotope production applications. The HELIOS2 lattice code has been extended with the development of a linear source MoC option. The linear source equations are derived within the scope of the HELIOS2 general geometry and non-cyclic ray tracing. The implementation was tested for fine and coarse spatial mesh models of the 2D C5G7 MOX computational benchmark, which provides a pure and extreme test of a transport solver. The linear source yields at least comparable accuracy with reduced computational resource requirements relative to the flat-source approximation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Alternative Power and Propulsion for Space Systems

What are the main sources of power and propulsion for space systems and what are their advantages, disadvantages, how do they work, and what are the politics behind them? The following topics will be analyzed solar panels, batteries, radioisotope thermoelectric generator (RTG), advanced Stirling radioscopic generator (ASRG), reactors, nuclear thermal rockets (NTP), thermionic experiment with conversion (TOPAZ), electrothermal plasma thruster (VASIMR), ion propulsion, and finally nuclear pulse propulsion. The production of Pu-238 is extremely controversial but a vital source of fuel for many of these space systems. Soral and Batteries are the most common and the least controversial forms of power used in space systems today. However, is ineffective for deep space exploration as they only function for up to four years without needing to be recharged. This is where nuclear systems come into play. Nuclear systems such as an RTG will “live” up to 88 years. For example, Voyager 1 is powered by an RTG It has been traveling since 1977 and has left out solar system in 2012 and has yet to run out of power. However, this type of technology (nuclear) has many hurtles it needs to jump through before advancements in can go much further.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Dynamics of deuterium retention and desorption from plasma-facing materials in fusion reactor-relevant conditions

Hydrogen isotopes retention and desorption during and after discharges in fusion devices are still not well understood due to the complex device conditions and limitations of in-situ diagnostics and measurements. Here, we simulated well-diagnosed recent experiments at the DIII-D facility to benchmark our ITMC-DYN integrated package of modeling deuterium diffusion, retention, and desorption during and after D discharge irradiation. Modeling results were compared with detail experimental data of D desorption fluxes for various irradiation conditions. We predicted the temporal evolution of free and trapped D distribution in tungsten (W) plasma-facing material (PFM). Effects of key parameters namely diffusion coefficient, recombination rate, trapping energies against different defect types, were examined in these simulations. Existing experimental data of these parameters in literature varies significantly which makes it harder to identify key mechanisms and physics responsible for hydrogen isotope retention and desorption. The purpose of this work is to accurately simulate recent well-diagnosed reactor experiments given the uncertainties in such parameters and identify mechanisms responsible for the retention and desorption. We implemented the best identified diffusion, recombination, and trapping parameters in ITMC-DYN package that integrate both various collisional and thermal processes. We predicted, for example, that sample cooling between discharges in DIII-D operations can significantly affect the spatial distribution of trapped D in W under reactor irradiation conditions. Correct prediction of desorption spectra from samples irradiated during 10 DIII-D discharges showed that up to 35% of D can be retained in high binding energy defects such as vacancy clusters or voids.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Transition Core Modeling for Extended Enrichment & Accident-Tolerant Fuels Using Polaris/PARCS

Commercial light water reactor (LWR) operators and fuel vendors are currently interested in increasing the low-enriched uranium (LEU) fuel enrichments from the current limit of 5.0 $^w/_o$ $^{235}U$ up to 10 $^ w/_o$ $^{235}U$ (referred to as "LEU+") in their current fleets; they are also interested in using accident-tolerant fuel (ATF) with both LEU and LEU+ fuel. This report aims to identify modeling challenges and accuracy concerns in transition core analysis using the SCALE Polaris lattice physics code and U.S. Nuclear Regulatory Commission core simulator PARCS. At the time this study was started, no publicly available LEU+ core designs existed for boiling water reactor (BWR) or pressurized water reactor (PWR) systems. Therefore, fuel lattices were shuffled within a multi-assembly model to mimic neutronically challenging lattice combinations seen in transition cores, such as a fresh LEU+ lattice next to depleted LEU lattices. In addition to multi-assembly models, whole-core BWR transition core calculations were performed for ATF and LEU+ fuel using an existing Hatch-1 Cycle 3 core model. A whole-core BWR model was chosen due to the more heterogeneous core designs compared to those for a PWR core. Since the original core is an old checkerboard core design and no core or fuel design optimization was performed for the modeled fuel types, these core calculations were intended only to provide: (1) Comparisons of core characteristics of interest, such as the pin power distributions and peaking factors, Doppler temperature coefficients (DTCs), and control blade worths (CBWs) under challenging core designs, (2) Identification of reactor physics challenges in modeling LEU+ and ATF cores, and (3) A stress test for the Polaris/PARCS two-step modeling approach, including characterization of the relative accuracy for predicting characteristics of interest such as pin power distributions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Designing an impedance-based technique for studying corrosion on cladding materials

In nuclear cladding materials, changes in structure and chemistry over the lifetime of claddings can have a significant impact on fuel and reactor performance. Currently, chemical evolution over the lifetime of the fuel and cladding materials can only be inferred using post-irradiation examination. As an alternative to post-irradiation measurements, electrochemical impedance spectroscopy (EIS) can provide an in-pile measurement of changes in chemistry in oxides and hydrides. The objective of this study is to develop an impedance based sensing technology for measuring spatial- and time-resolved in-pile changes in cladding chemistry in order to understand the mechanisms of hydride formation, hydride dealloying and associated cladding corrosion so that a mitigation strategy and technology can be developed for reactor safe operation. Two prototype impedance-based sensors were designed and assembled using Zr-4 as working electrode and Pt as counter and reference electrode. One sensor is tubular type and the other one is plate-type. These sensors will be tested in static autoclave to investigate the effects of various environmental conditions (including temperature, pressure, and water chemistry) on cladding material corrosion mechanisms. These in-situ EIS sensors would provide corrosion-layer parameters in high-temperature water, such as (1) total layer thickness, (2) the evolution of oxide structures as uniform layer dielectric or sublayer(s), and (3) the possible electrochemistry of the volume corrosion process and the solid/liquid interface, such as the cyclic nature of corrosion of Zr alloys in high-temperature water. This work was focused on electrochemical sensor development, targeting cladding oxides/hydrides under thermodynamic equilibria; characterization of samples using Kelvin probe force microscopy (SKPFM), Raman spectroscopy, and scanning electron microscopy (SEM) with energy-dispersive X-ray spectroscopy (EDS) to provide high-resolution co-localized characterization of zirconium oxide and metal/oxide interface.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A New Inelastic Neutron Spectrometer HODACA

In this study, a new multiplex-type inelastic neutron scattering spectrometer, HOrizontally Defocusing Analyzer Concurrent data Acquisition spectrometer (HODACA), was recently developed and built at the C1-1 cold neutron beam port in the neutron source reactor JRR-3 at Japan Atomic Energy Agency. The spectrometer is suitable for dynamics measurements in the energy range of -1 meV ≲ ℏω ≲ 7 meV, catering to a broad array of research fields in physics and material science. HODACA combines 24 detectors and 132 pieces of analyzer crystals and has an estimated measurement efficiency that is 70 times greater than the existing conventional triple-axis spectrometer at the C1-1 beam port. The concept, design, specification, and results of commissioning experiments are described.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

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↗

Development and Demonstration of a Risk Assessment Approach for Approval of a Transportation Package of a Transportable Nuclear Power Plant for Domestic Highway Shipment

The U.S. Department of Defense (DoD) Strategic Capabilities Office (SCO) has tasked PNNL to address the regulatory challenges associated with confirming the safe transport of Transportable Nuclear Power Plants (TNPPs) containing irradiated nuclear fuel. A previous report—Proposed Risk-Informed Regulatory Framework for Approval of Microreactor Transportation Packages (PNNL-31867)—determined that the expected radioactive inventory in the irradiated fuel of a TNPP would likely require shipment in an NRC-approved Type B package (or spent nuclear fuel cask) but that a TNPP “package” is unlikely to meet the entire suite of NRC requirements set forth in Part 71 of Title 10 of the Code of Federal Regulations (CFR) for a Type B package. It was therefore concluded that shipment of this initial TNPP transportation package, as well as possibly others, under existing regulations would likely require NRC approval using the 10 CFR 71.12 (“Specific exemptions”) process that relies on risk-informed decision making supported by quantitative risk assessment (i.e., Probabilistic Risk Assessment).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Automated Control for Nuclear Thermal Propulsion Start-Up using MOOSE-based Applications

This report presents a Griffin/Bison/RELAP-7 numerical model of a prototypical NTP system that features fuel assemblies arranged in rings, and which was designed to simulate rapid startup transients. The physics modeled include full-core neutronics, assembly-wise heat conduction, and conjugate heat transfer, with the balance of plant mainly imposed through boundary conditions. In addition, various forms of automated reactivity control were deployed by using the MOOSE to autonomously drive the model and simulate the reactor transitioning from assumed initial conditions to nominal power in a fraction of a minute. To generate the cross-sections of the neutronics model, and in an effort to simultaneously account for the tremendous axial temperature gradients in the reactor and to limit the number of state points required for cross-section generation, the average component temperatures and hydrogen densities in the cooling channels were correlated to the average fuel and moderator temperatures, and fixed axial profiles were derived for nominal conditions and then used during the transient. With this approximation, a tractable cross-section library tabulated with fuel/moderator temperatures and CD angles was generated using Serpent. The full-core SPH correction procedure and the CD decusping technology in Griffin, respectively, ensure preservation of the multiplication factor and reaction rates at state points, along with a reasonably accurate reactivity worth between tabulated CD angles, despite using a coarse mesh. Feedback from other physics was calculated by modeling one representative fuel assembly per ring, along with the corresponding fuel and moderator cooling channels. To limit power overshoots during startup, another layer of multiphysics coupling was added to the model in order to automatically control the drums. Two different technologies presented herein showed outstanding performance in this regard: (1) a novel hybrid PID controller based on both power and reactivity signals, and (2) a PGC that relies on kinetics parameters and reactivity coefficients to predict future behavior and adjust the desired signal accordingly. A challenging benchmark was devised, featuring a power demand curve that exponentially increases by a factor of 500 within 30 seconds, then levels out after that. Both control approaches create a simulated power curve that closely follows the power demand curve and limits power overshoots to 1% or less. While the former approach requires more tuning of the internal parameters, the latter requires additional knowledge of the reactivity feedback coefficients and rates of change of the corresponding variables, including fuel and moderator temperature, which could be difficult to dynamically measure for a real NTP system. Fortunately, some inaccuracy in these quantities will not drastically degrade the PGC performance. Subsequently, a more realistic startup sequence was considered, in which the mass flow rate and outlet pressures are ramped up to model bootstrap and thrust build-up phases prior to reaching steady-state conditions, demonstrating the ability of the hybrid PID and PGCs to handle such transients, with both types of controllers exhibiting very similar behavior. Nevertheless, a significant chamber temperature overshoot was observed, caused by the demanded power signal and assumed mass flow rate. This issue could be mitigated by deploying a reactor controller that follows the chamber temperature signal and actuates both the control valves and drums (rather than using a power signal based solely on the drums to control reactivity). Enhancement of the hydrogen fluid properties available in MOOSE, as well as a better understanding of prototypical initial conditions, are also needed to further enhance this startup model. Finally, a study was performed to model decay heat post-shutdown, and to prepare for extending this model to predict shutdown behavior and post-shutdown pulsed cooling requirements.

33 ADVANCED PROPULSION SYSTEMS↗

Review of Graphite Properties Relevant to Micro-Reactor Design

Microreactors are advanced reactors that are designed to be small, scalable, and portable with up to 20 MW power. These reactors could operate independently, or as part of a microgrid, without need of a frequent refueling. Micro-reactors are designed to be deployable to provide electric power in remote locations, therefore providing greater flexibility. Several micro-reactors are under development in the US. These reactors are based on advanced gas-cooled or heat-pipe concepts. While Graphite can be found in various applications, some high-temperature reactors plan to employ Graphite in their core components due to its role as a moderator and its ability to maintain its structural integrity when subjected to elevated temperatures and high neutron fluence. Although there is significant experience with use of Graphite in nuclear applications, there are still unknowns that should be addressed. Graphite properties depend on the graphite type and affected by the fabrication procedures. Material properties are functions of the temperature and irradiation dose. The fundamental properties also affected by the oxidation environment. Therefore, in-depth understanding of graphite properties, including the effect of irradiation, oxidation and other influencing parameters are required to evaluate the design accurately. This draft aims to provide a comprehensive review of material properties for Graphite relevant to micro reactor design. For this work, two distinct grades of graphite were considered, namely IG-110 and Mersen-2114. Physical, thermal, and mechanical properties for these grades were comparatively evaluated. The properties that are discussed in this draft aim to serve as a basis for design and safety analysis.

42 ENGINEERING↗

Creating a Simulation Platform for Research and Development of Advanced Control Methods

Advanced nuclear reactors are essential to meet the changing energy requirements throughout both the United States and the rest of world. In addition to other features, they are designed to enable deployment in remote locations and operate in a fully (or near-fully) autonomous manner, which will require a new control paradigm. To realize autonomously operating reactors, the U.S. Department of Energy’s Nuclear Energy Enabling Technologies Advanced Sensors and Instrumentation (NEET ASI) program conducts research and development into the enabling technologies and methods needed, including digital twins, machine learning, and risk modeling, in addition to various types of control methods. These technologies and methods are the key foundations needed to achieve fully autonomous systems. To develop and evaluate the technologies and methods necessary for achieving autonomous operations, it is critical to identify a software tool capable of integrating all the required elements. In surveying the available solutions, no software platforms were identified that could accomplish what was needed without introducing drawbacks. This challenge was the motivation for the current effort: to develop a software platform that can seamlessly integrate autonomouscontrol-enabling technologies and methods, allowing for accelerated research and development and transfer of ideas. The resulting platform, known as the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND), is Python-based, and leverages open-source tools to provide flexibility and facilitate building upon prior research. It is designed to enable advanced reactor developers to deploy and test advanced control technologies and methods coupled with their own models, solutions, and hardware. Given the substantial undertaking of developing such a platform, the current effort focused on laying down scalable, flexible software foundations and infrastructure, then demonstrating the platform via a use case. These foundations included developing generic modules, which contain the base variable and system blocks (the information and functional building blocks, respectively, that can be used to design a simulation) and the data handling and storage blocks needed to exchange information between the various blocks; as well as enablingtechnology-specific modules. This platform was evaluated via a use case, which was to simulate and control a process for the Microreactor Automated Control System (MACS) test bed. While MACS is not currently directly coupled to any specific microreactor physics, it was initially developed in concert with the Microreactor Applications Research Validation and Evaluation (MARVEL) microreactor, and so the MARVEL physics are used here. As part of this use case, several enabling-technology-specific blocks within COMMAND were integrated, including a proportional integral derivative (PID) control block, a Reactor Excursion and Leak Analysis Program (RELAP5-3D) block, and an anomaly detection block. The COMMAND software platform was successfully demonstrated to achieve the scalability and flexibility objectives of this effort and will be leveraged by the program’s research efforts to advance state of the art control methodologies towards autonomous operations of advanced reactors. As new use cases are created and implemented, it is anticipated that COMMAND will continue to grow and evolve to meet new requirements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Effects of carbonitrides and carbides on microstructure and properties of castable nanostructured alloys

In this work, to develop advanced reduced-activation ferritic-martensitic (RAFM) steels for fusion reactor structural applications, both carbonitride- and carbide-strengthened castable nanostructured alloys (CNAs) were explored for higher densities of MX (M = Ti/Ta/V/etc. and X = C/N) nanoprecipitates. Additionally, systematic comparisons between the two types of CNAs indicated generally similar microstructures and comparable tensile properties and creep resistance. However, the carbide-CNAs did show some advantages over the carbonitride-CNAs in terms of the uniformly distributed higher density of MC nanoprecipitates, greater Charpy impact upper shelf energies, less deuterium retention and swelling, and potentially less transmutation-induced composition changes and consequently thermodynamically more stable carbides. The carbide-CNAs showed the best-balanced high performance in the examined properties, in contrast to the significantly varied performance of oxide-dispersion-strengthened alloys and the generally lower performance of current RAFM steels.

36 MATERIALS SCIENCE↗

Electron tomography of unirradiated and irradiated nuclear graphite

Graphite is the moderator material of several Generation IV nuclear reactor concepts, as well as the British Advanced Gas-cooled Reactors (AGR). Porosity can heavily influence the material properties, mechanical irradiation response, and neutron induced shrinkage or swelling of nuclear-grade graphite. Due to the sub-micron size of several types of pores found in graphite, only a high-resolution imaging technique such as electron tomography are capable of visualizing these features in three dimensions. In this research, we used electron tomography to characterize as-received and neutron irradiated samples of IG-110 nuclear-grade graphite to show for the first time the 3D structure of both native and irradiation-induced nano-cracks. This technique also reveals unique characteristics of graphite such as the structure that surrounds pores and could be used to inform molecular dynamic simulations of irradiated graphite and experimental techniques such as gas-absorption. This work also shows the utility of this technique for the study of other nuclear porous carbon-based materials.

36 MATERIALS SCIENCE↗

Hydrodynamic Characterization of a Shallow Rectangular Spouted Bed Using Bed Pressure Signals and Image Processing Methods

To support the design of spouted bed reactors, experiments are performed in a rectangular spouted bed to measure the peak pressure drop (Δ P max ) and the internal and external spouting velocities ( U is and U es ). Four particle types spanning under Geldart D and B are used. U is and U es are measured from bed pressure drop and expansion ratio profiles, respectively, with the U es / U is ratio of each particle type obtained. Additionally, correlations predicting the Δ P max of Geldart D and B particles are developed by reviewing published correlations and investigating the nozzle effect. Good prediction is achieved with a slope of 0.997 and an adjusted R 2 of 0.998 in a 95% confidence interval. U es is predicted through correlations developed by adding effects of d p / D i and H 0 in the Mathur–Gishler equation. The calculated U es agrees well with the experimental data, achieving a slope of 0.998 and an adjusted R 2 of 0.998 in a 95% confidence interval.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Explainable tokamak-agnostic forecasting of fusion plasma instability via megahertz turbulent fluctuations

Scientific applications of artificial intelligence (AI) often remain limited by device-specific training and unexplained “black-box” approaches, creating fundamental barriers to cross-system generalization. This challenge is critical for nuclear fusion, where future reactors will have limited operational data for AI training. Here, we demonstrate that our neural network, trained solely on megahertz-scale turbulence measurements from one machine (DIII-D), forecasts Type-I edge localized mode (ELM) onsets in a different tokamak (KSTAR) through zero-shot weight transfer following physics-consistent preprocessing without device-specific retraining. Through an explainable AI framework combining gradient-weighted class activation mapping with physics validation, we reveal that our network can internalize physics relationships governing the ELM instabilities rather than memorizing device-specific patterns. The network perceives spatiotemporal features that correlate consistently with independently calculated instability growth rates, magnetohydrodynamic stability limits, and pedestal structure dynamics. Statistical analyses of dimensionally-reduced saliency features reveal the identical triangular features between the saliency representations, instability growth rates, and prediction probability across tokamaks, providing evidence that our forecasting system can show tokamak-agnostic generalization. This work contributes to a foundation for explainable scientific AI systems, where cross-system developments are essential for transcending traditional domain-specific constraints.

AI↗

Understanding the depletion of electrons in dusty plasmas at atmospheric pressure

The nucleation and growth of NPs in the gas phase using atmospheric-pressure plasma systems is an important approach to synthesizing novel dimensionally-controlled materials. In this paper, we investigated the effect of the NPs on a typical type of continuous-flow, substrate-free plasma at atmospheric pressure to understand their potential contribution to electron density changes. A tandem plasma system was set up consisting of one plasma reactor that produced carbonaceous NPs from mixtures of argon and hexane, and another identical plasma reactor where the as-grown particles were injected and non-intrusive electrical and optical measurements were performed. The electron densities obtained from conductivity measurements and a plasma fluid model were found to decrease in the presence of NPs. However, control experiments revealed that the main source of the electron depletion was residual vapor or reaction byproducts in the form of molecular species or nanoclusters and not the particles themselves. These results were validated by constant number Monte Carlo simulations which showed that at the experimentally-measured conditions, the NPs were not of sufficiently high enough concentration to reduce the electron density; however, if molecules or clusters are ionizable, they remain in sufficient concentration to deplete electron densities. Our study shows that at atmospheric pressure, because of their typically larger electron density values, particle-producing plasmas are distinct from those at low pressure, and nanoparticle formation does not have the same impact while molecular-scale species may be a more important consideration.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Multi-scale fission product release model with comparison to AGR data

TRistructural ISOtropic (TRISO) particle fuel is central to several advanced, high-temperature reactor designs. Each particle consists of a fuel kernel encapsulated by three layers of carbon and ceramics that prevent the release of fission products and ensure physical integrity. Despite outstanding retention properties, fission product release has been observed from intact particles. To better understand and quantify fission product release from TRISO particles, a multiscale, mechanistic model of fission product transport is being developed by the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. Previous work focused on silver (Ag) transport and improved Ag release predictions. The work described in this report builds on this experience to better understand cesium (Cs) transport in silicon carbide (SiC), the main barrier to the release of fission products. Atomistic simulations provide bulk and grain boundary (GB) Cs diffusivities in SiC, which are used by phase field simulations in the mesoscale code Marmot to determine the temperature, microstructure, and irradiation-dependent Cs diffusivity at the mesoscale in SiC. This approach attributes the different temperature regimes experimentally observed for Cs diffusivities in SiC to a transition from bulk-dominated diffusivity at high temperatures to a GB-dominated regime at low temperatures, providing new insight. The multiscale, mechanistic effective diffusivity is then implemented in the fuel performance code BISON and further validated by comparing Cs release predictions from Advanced Gas Reactor (AGR)-1 and AGR-2 post-irradiation measurements. The new model improves BISON’s predictability. This document also reports improvements made on Ag transport modeling by accounting for different GB types having different diffusivities. Moreover, this report details preliminary efforts to model palladium (Pd) attack of the SiC at the mesoscale using a phase field approach. Pd attack and its impact on accelerated Ag transport remains a misunderstood phenomenon, and we use the model to demonstrate that the formation of lamellae that has been observed in experiments can be explained by the reaction of Pd with SiC to form alternating layers of graphite and Pd 2 Si. This effort aims to improve our understanding of the reaction and eventually provide a model for BISON to account for Pd penetration and its effects on fission product release.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Preliminary Thermo-Mechanical Analysis of Irradiated MURR LEU Fuel Element

The University of Missouri Research Reactor (MURR) is a multi-disciplinary research and education facility providing a broad range of analytical, materials science, and irradiation services to the research community and the commercial sector. MURR is one of five U.S. high performance research reactors (USHPRR), plus one critical facility, that is actively collaborating with the National Nuclear Security Administration (NNSA) Material Management and Minimization (M3) Office of Reactor Conversion and Uranium Supply to convert from the use of highly enriched uranium (HEU, ≥ 20 wt% U-235) to low-enriched uranium (LEU, < 20 wt% U-235) fuel. A new type of very high-density LEU fuel based on an alloy of uranium and 10-weight percent molybdenum (U-10Mo) is expected to allow the conversion of some USHPRR, including MURR, to LEU fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗