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Description of FY25 Theory and Simulation Performance Target: Development of an integrated modeling framework for fusion reactor design and assessment

The urgency to deliver fusion power is growing now more than ever, with increasing pressure for both public programs and private companies to meet milestones timelines and overcome significant remaining technical challenges to ensure growth of a nascent fusion industry in time to meet rapidly growing clean energy demands. With incredible advancements in computation and years of investment in fusion model development and validation, integrated modeling is poised to fill a key role in accelerating the timeline to a fusion pilot plant (FPP). Future fusion pilot plants will operate in regimes far beyond current experience, and device design will rely on physics-based prediction and extrapolation. Many concepts will also rely on simulation to assess safety (shielding, tritium management, materials activation and lifetimes), economics and scalability before the decision to build. Importantly, integrated simulation can be used to reveal and solve the complexities of system integration that may otherwise not be apparent in physical components or models developed in isolation. New experimental test facilities that produce relevant conditions to validate and resolve key technical challenges for various subsystems (materials, blankets, fuel cycle, etc.) have been repeatedly called for by the fusion community but are not yet realized. Integrated modeling has an important role in identifying realistic load conditions (thermal, electromagnetic, plasma, neutron and photon loads, etc.) and defining the components and experiments for these test facilities in order to ensure meaningful validation that sufficiently reduces modeling uncertainties and technical risk for the full integrated reactor. The Fusion REactor Design and Assessment (FREDA) SciDAC project is building a component-based integrated modeling framework & data structure to enable self-consistent, multi-fidelity, iterative optimization workflows for the fusion reactor design process. FREDA aims to shorten the time to viable designs by providing a set of flexible workflows to support the various stages of the design process using an integrated model hierarchy, ranging from the simple analytic descriptions to the highest fidelity, theory-based plasma and engineering modeling developed by the fusion and fission communities. These tools are expected to be needed for timely support of FPP design in the milestone program and in the FIRE collaboratives. The plasma simulation backbone of FREDA is IPS-FASTRAN with newly developed coupled Core-Edge Pedestal-SOL (CESOL) workflows, which is being extended to the far-SOL region up to the plasma facing components. FREDA incorporates the FERMI engineering modeling suite and will enable self-consistent evaluation of the thermal shields, limiters, blanket, magnets, and other surrounding structures with predictions of temperatures, erosion, dpa, activation, tritium generation and transport, creep, corrosion, material degradation, etc. Parametric generation of 3D CAD enables rapid iteration of component geometry in response to plasma and loading specifications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

MOOSE ProbML: Parallelizable Probabilistic Machine Learning and Uncertainty Quantification Capabilities

The Multiphysics Object Oriented Simulation Environment (MOOSE) is a widely used open- source finite element software for performing multiphysics multiscale simulations in a massively parallel fashion. Recently, the computational team at Idaho National Laboratory (INL) has implemented Probabilistic Machine Learning (ProbML) capabilities in MOOSE—in a parallelized fashion—and enable active learning with large-scale computational models for tasks such as surrogate model development, scale bridging, forward/inverse uncertainty quantification (UQ), Bayesian optimization, etc. This presentation summarizes these developments in MOOSE along with demonstrations on several real applications relevant to nuclear energy. At the fundamental level, samplers like Monte Carlo/Latin Hypercube, variance reduction, parallelized Markov Chain Monte Carlo (MCMC) support uncertainty propagation in both forward and inverse settings. These samplers can be integrated with the Gaussian processes (GP) suite in MOOSE, which offer several variants like scalar GPs, multi-output GPs, and deep GPs, to enable active learning. These GPs can be tuned using gradient-based optimization methods like Adam and its variants or gradient-free methods like the elliptical slice sampler (a variant of MCMC adept under Gaussian settings) for more complex covariance kernels or likelihoods whose gradient computations can be cumbersome. A variety of batch acquisition functions permit parallelized evaluation of the computational model and support different learning objectives with high efficiency like Bayesian inference, global surrogate development, optimization, etc. Furthermore, libtorch integration supports training, evaluation, and re-training of neural networks and other complex machine learning models in active learning settings. The impacts of these developments are shown on several real applications: (1) nuclear fuel inverse UQ and model inadequacy assessment using the Kennedy O’Hagan framework; (2) uncertainty aware surrogate modeling for additive manufacturing to predict field quantities; (3) nuclear reactor rare events analysis; and (4) complex fluid flow prediction using a global surrogate with quantified prediction uncertainty. Finally, the outlook of MOOSE ProbML is discussed for both outer-loop and inner-loop computations in the broad view to accelerate fuels and materials qualification, address gaps in knowledge and data, and assess new reactor/fuel systems.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Advances in Multiscale Modeling of Lignocellulosic Biomass

Applications and associated processing technologies of lignocellulosic biomass are becoming more important as we endeavor to meet societal demand for fuels, chemicals, and materials from renewable resources. Meanwhile, the rapidly expanding availability and capabilities of high-performance computing present an unprecedented opportunity to accelerate development of technologies surrounding lignocellulose utilization. In order to realize this potential, suitable modeling frameworks must be constructed that effectively capture the multiscale complexity and tremendous variety exhibited by lignocellulosic materials. In our assessment of previous endeavors towards this goal, several important shortcomings have been identified: (1) the lack of multiscale integration strategies that capture emergent properties and behaviors spanning different length scales, and (2) the inability of many modeling approaches to effectively capture the variability and diversity of lignocellulose that arise from both natural and process-induced sources. In this perspective, we survey previous modeling approaches for lignocellulose and simulations processes involving its chemical and mechanical transformation, and suggest opportunities for future development to enhance the utility of computational tools to address barriers to widespread adoption of a renewable bioeconomy.

09 BIOMASS FUELS↗

Low Temperature Activation of Methane on Metal-Oxides and Complex Interfaces: Insights from Surface Science

The abundance of inexpensive, natural gas has transformed the energy landscape, whereby revealing new possibilities for sustainable chemical technologies or impacting those that have relied on traditional fossil fuels. The primary component, methane, is underutilized and wastefully exhausted, leading to anthropogenic global warming. Historically, the manipulation of methane remained “ clavis aurea ,” an insurmountable yet rewarding challenge and thus the focus of intense research. This is primarily due to an inability to dissociate C–H bonds in methane selectively, which requires a high energy penalty and is an essential prerequisite for the direct conversion of methane into a large set of value-added products. The discovery of such processes would promise an energy gainful use of natural gas benefiting several essential chemical processes associated with C1 chemistry. This first C–H bond dissociation step of the methane molecule appears in numerous catalytic mechanisms as the rate-determining step or most essential barrier sequence for all subsequent steps that follow in the production of C–C, C–O, or C x –H y –O z bonds found in value added products. A main goal is to catalytically reduce the energy barrier for the first C–H bond dissociation to be able to achieve the activation of methane at low or moderate temperatures. As such there is great value in understanding the fundamental nature of the active sites responsible for bond breaking or formation and thus be able to facilitate better control of this chemistry, leading to the development of new technologies for fuel production and chemical conversion. Surface science studies offer enhanced perspectives for a careful manipulation of bonds over the last layer atoms of catalyst surfaces, an essential factor for the design of atomically precise catalysts and unravelling of the reaction mechanism. With the advent of new surface imaging, spectroscopy, and in situ tools, it has been possible to decipher the surface chemistry of complex materials systems and further our understanding of atomic active sites on the surfaces of metals, oxides, and carbides or metal–oxide and metal–carbide interfaces. The once considered near impossible step of C–H bond activation is now observed at low temperatures with high propensity over a collection of oxide, metal–oxide, and metal–carbide systems in a conventional or inverse configuration (oxide or carbide on metal). The enabling of C–H activation at low temperature has opened interesting possibilities for the specific production of chemicals such as methanol directly from methane, a step toward facile synthesis of liquid fuels. We highlight the most recent of these results and present the key aspects of active site configurations engineered from surface science studies which enable such a simple reactive event through careful manipulation of the last surface layer of atoms found in the catalyst structure. New concepts which help in the activation and conversion of methane are discussed.

36 MATERIALS SCIENCE↗

NRIC EBR-II Test Bed Pre-Conceptual Design Report

Authorized by the Nuclear Energy Innovation Capabilities Act (NEICA), the National Reactor Innovation Center (NRIC) provides private sector technology developers access to strategic infrastructures and assets for commercial nuclear energy research, development, demonstration, and deployment activities. The mission is to support a timely and cost-effective path to the licensing and commercialization of new nuclear energy systems. To meet these needs, NRIC is developing two test beds at Idaho National Laboratory (INL). The ZPPR Test bed (ZTB) and the EBR-II Test bed (ETB). The EBR-II test bed will support the demonstration of systems that operate at less than 10 MWt. The baseline objective is for the EBR-II Dome to act as a safety significant containment structure capable of siting reactors that utilize Safeguards Category 4 material for operations. The major areas addressed in the pre-conceptual design include: • Installation of an access door • Electrical Power • Heat Removal • Ventilation in the Dome • Module handling system Along with the design for ETB a concept of operations (COP) has also been developed. The COP is intended to facilitate a common understanding of ideas, challenges, and issues. As systems continue to evolve in complexity System Engineers and Project Directors will utilize the COP to develop and sustain a common vision of the system for stakeholders.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Precise Control of Dissipative Self-assembly by Light and Electricity

Nature-inspired synthetic dissipative self-assemblies have attracted much attention recently. However, it remains a major challenge to achieve precise control over dissipative supramolecular assembly structures and functions of self-contained systems. Here we combine light and electricity as two clean, and spatiotemporally addressable fuels to provide precise control over the morphology for dissipative self-assembly of a perylene bisimide glycine (PBIg) building block in a self-contained solution. In this design, electrochemical oxidation provides the positive fuel to activate PBIg self-assembly while photoreduction supplies the negative fuel to deactivate the system for disassembly. Further, through programming the two counteracting fuels, we demonstrated the control of PBIg self-assembly into a variety of assembly morphologies in a self-contained system. In addition, by exerting light and electrical dual fuels simultaneously, we could create an active homeostasis exhibiting dynamic instability, leading to morphological change to asymmetric assemblies with curvatures. Such precise control over self-assembly of self-contained systems may find future applications in programming complex active materials as well as formulating pharmaceutical reagents with desired morphologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Biological upgrading of pyrolysis-derived wastewater: Engineering Pseudomonas putida for alkylphenol, furfural, and acetone catabolism and (methyl)muconic acid production

While biomass-derived carbohydrates have been predominant substrates for biological production of renewable fuels, chemicals, and materials, organic waste streams are growing in prominence as potential alternative feedstocks to improve the sustainability of manufacturing processes. Catalytic fast pyrolysis (CFP) is a promising approach to generate biofuels from lignocellulosic biomass, but it generates a complex, carbon-rich, and toxic wastewater stream that is challenging to process catalytically but could be biologically upgraded to valuable co-products. Here, we implemented modular, heterologous catabolic pathways in the Pseudomonas putida KT2440-derived EM42 strain along with the overexpression of native toxicity tolerance machinery to enable utilization of 89% (w/w) of carbon in CFP wastewater. The dmp monooxygenase and meta-cleavage pathway from Pseudomonas putida CF600 were constitutively expressed to enable utilization of phenol, cresols, 2- and 3-ethyl phenol, and methyl catechols, and the native chaperones clpB, groES, and groEL were overexpressed to improve toxicity tolerance to diverse aromatic substrates. Next, heterologous furfural and acetone utilization pathways were incorporated, and a native alcohol dehydrogenase was overexpressed to improve methanol utilization, generating reducing equivalents. All pathways (encoded by genes totaling ~30 kilobases of DNA) were combined into a single strain that can catabolize a mock CFP wastewater stream as a sole carbon source. Further engineering enabled conversion of all aromatic compounds in the mock wastewater stream to (methyl)muconates with a ~90% (mol/mol) yield. Biological upgrading of CFP wastewater as outlined in this work provides a roadmap for future applications in valorizing other heterogeneous waste streams.

(methyl)muconates↗

BISON Robustness and Performance Improvements

BISON is a modern finite-element based nuclear fuel performance code that has been under development at the Idaho National Laboratory (USA) since 2009 [1]. The code is applicable to both steady and transient fuel behavior and can be used to analyze 1D (spherically symmetric), 2D (axisymmetric and generalized plane strain) or 3D geometries. BISON is the fuel performance code used within CASL for LWR fuel under both normal operating and accident conditions. BISON is built using the INL Multiphysics ObjectOriented Simulation Environment, or MOOSE [2, 3]. MOOSE is a massively parallel, finite element-based framework to solve systems of coupled non-linear partial differential equations using the Jacobian-Free Newton Krylov (JFNK) method [4]. This enables investigation of computationally large problems, for example a full stack of discrete pellets in a LWR fuel rod, or every rod in a full reactor core. MOOSE supports the use of complex two and three-dimensional meshes and uses implicit time integration, important for the widely varied time scale in nuclear fuel simulation. An object-oriented architecture is employed which greatly minimizes the programming effort required to add new material and behavioral models. The flexibility of the implicit and fully coupled multiphysics approach comes with a need for constructing suitable approximations for the Jacobian matrix of the coupled system used for either preconditioning a Krylov solve or in a direct Newton solve. Preconditioning options for Bison problems need to be revisited with new preconditioning methods becoming available.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Predicting Safety Rod Reactivity Insertion in the Advanced Test Reactor

The Advanced Test Reactor (ATR), and complimentary zero-power ATR Critical (ATRC) reactor, located at Idaho National Labs (INL), are undergoing conversion from Highly Enriched Uranium (HEU) to Low Enriched Uranium (LEU). Both have a variety of testing locations that can receive large variations in flux due to its unique serpentine design, consisting of five lobes surrounding nine flux traps (see Figure 1). Initial criticality and power distribution throughout the core are controlled by core-external outer shim control cylinders (OSCCs). Distinct test loops allow for testing at specific temperatures, pressures, and irradiation conditions such as flux and fission density. The ATR is one of the key nuclear engineering research and testing facilities within the DOE National Laboratory Complex, and the ATRC supports its operation [1]. Currently, the Office of Material Management and Minimization (M3) within the National Nuclear Security Administration of the DOE is working to convert the remaining research reactors, including the ATR, from 93% HEU fuel to 19.75% LEU fuel (LEU) to support non-proliferation [2]. Extensive materials testing at INL and internationally has demonstrated that a high-density uranium molybdenum (U 10Mo) alloy can meet the performance requirements of the remaining high powered research reactors. The current LEU fuel element design is named the LOWE element. However, there are many technical challenges to address before the conversion to LEU can be successful, including the accurate characterization of the reactor core physics with LEU fuel. To ensure safe operation of the ATR, reactor engineers prepare a CSAP (Core Safety Assurance Package) before each cycle. The purpose of the CSAP is to verify the reactor performance calculation used to determine if the selected fuel loading meets operational, experimental, and safety criteria. Many of the criteria in the CSAP are limits on reactivity insertion in various accident scenarios.

42 ENGINEERING↗

Design and testing of an enriched uranium fueled molten salt irradiation vehicle

Molten salt reactors (MSRs) have garnered increasing attention recently with several demonstration efforts on the way. A key challenge to the licensing basis for these reactors is the lack of experimental data on fueled salts. This is expected to be crucial to the safety evaluation and licensing basis of reactors of this type deployed in the future. While capability for irradiating molten salts has started being reestablished in the recent decade, no enriched fuel irradiation capability has been developed and tested as of yet. A new experiment vehicle under development at Idaho National Laboratory (INL) is presented here. The Molten-salt Research Temperature-controlled Irradiation (MRTI) experiment was developed to host enriched-uranium bearing salt samples to be irradiated at a test reactor within the lab complex. One of the key scientific objectives is to provide irradiated salt samples for post irradiation examination (PIE) to study the impact of fission product generation and neutron/gamma radioactivity on the salt solution and salt-facing wall material. This paper provides a detailed overview of the mechanical design of the experiment, followed by an overview of the fabrication and assembly of an initial prototype vehicle (with non-fuel bearing salt). A summary of the key analyses conducted as a part of the performance and safety evaluation is then provided. Lastly, an overview of the test conducted in prototypic out-of-pile (non-neutron) environment are shown. These evaluations provide the foundation for a planned irradiation of and enriched uranium-bearing chloride salt sample in the near term. The upcoming irradiation will contain 13cm 3 of UCl 3 -NaCl salt (93% enrichment) generating around 20 W/cm 3 of fission energy during irradiation and a temperature range that can be contained between bounds of 525-900°C.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Understanding the effect of crystal anisotropy on grain growth, texturing and transport via the orthorhombic ?-U system [Slides]

The alpha phase of uranium exhibits the orthorhombic crystal structure, resulting in significant physical property anisotropy. These complex properties make the material challenging to work with in engineering settings but provide a rich arena to investigate the fundamental, multi-scale effects of anisotropy on physical behaviors such as grain growth and microstructure evolution under irradiation. We apply molecular dynamics and phase field modeling to study mass transport and grain growth in alpha-uranium. We characterize the mobilities of crystalline defects and the interfacial energy, and We find that the grain boundary energy is highly variable depending on the interface structure and that the relative rates of defect transport change with temperature. We also find that anisotropic thermal expansion has a significant impact on grain growth kinetics and texture development. Our results are used to explain experimental observations and to provide a basis for further hypotheses into the complex physical behavior of alpha-uranium.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Computational Approaches for Clean Energy Materials

Currently, 80% of the global final energy consumption occurs in form of fuels and only 20% as electricity. On the other hand, renewable energy additions come almost exclusively in the form of electricity (dominantly photovoltaics and wind). Thus, a successful energy transition will require enormous growth in renewables, sufficient to convert excess electricity into fuels, as well as the development of non-electricity based solar fuel technologies. As much as photovoltaic capacities have grown over the past 20 years, it is far from clear that current technologies and materials are up to the task to grow from here by yet another factor 100 until 2050. Therefore, sustained research efforts on emerging inorganic semiconductors for solar electricity and fuels are essential for facing the double challenge of climate change and energy security. Computational materials science can make important contributions, guiding and supporting research activities through both materials search and discovery and through detailed studies that help to develop a mechanistic understanding of materials performance and bottlenecks. This presentation will highlight three recent computational projects with relevance for photovoltaics and solar fuels (1) Defect graph neural networks (dGNN) for materials discovery in solar thermochemical hydrogen (STCH) [1]. The dGNN approach facilitates broad and fast materials screening for defect properties. (2) Modeling highly off-stoichiometric systems by evaluating the free energy of defect interaction [2]. This approach allows quantitative prediction of H2 production in complex STCH oxides. (3) First-principles atomic structure prediction for interfaces [3]. This work showed how an atomically thin CdCl2 interlayer phase enables in principle ideal electron transport across the incommensurate SnO2/CdTe interface. [1] M.D. Witman, A. Goyal, T. Ogitsu, A.H. McDaniel, S. Lany, Nat. Comput. Sci. (2023). https://doi.org/10.1038/s43588-023-00495-2. [2] A. Goyal, M.D. Sanders, R.P. O'Hayre, S. Lany, PRX Energy 3, 013008 (2024). https://doi.org/10.1103/PRXEnergy.3.013008. [3] A. Sharan, M. Nardone, D. Krasikov, N. Singh, S. Lany, Appl. Phys. Rev. 9, 041411 (2022). https://doi.org/10.1063/5.0104008.

density functional theory↗

First-of-a-Kind Fuel-bearing Molten Chloride Irradiation Experiment

Molten salt reactors (MSRs) have garnered increasing attention recently with several demonstration efforts on the way. A key challenge to the licensing basis for these reactors is the lack of experimental data on fueled salts. This is expected to be crucial to the safety evaluation and licensing basis of reactors of this type deployed in the future. While capability for irradiating molten salts has been reestablished in the recent decade, no enriched fuel irradiation capability has been developed and tested as of yet. A new experiment vehicle under development at Idaho National Laboratory (INL) is presented here. The Molten-salt Research Temperature-controlled Irradiation (MRTI) experiment was developed to host enriched uranium bearing salt samples to be irradiated at a test reactor within the lab complex. One of the key scientific objectives is to provide irradiated salt samples for post-irradiation examination (PIE) to study the impact of fission product generation and neutron/gamma radioactivity on the salt solution and salt-facing wall material. This paper provides a detailed overview of the mechanical design of the experiment, followed by an overview of the fabrication and assembly of an initial prototype vehicle (with non-fuel-bearing salt). A summary of the key analyses conducted as a part of the performance and safety evaluation is then provided. Lastly, an overview of the test conducted in prototypic out-of-pile (non-neutron) environment are shown. These evaluations provide the foundation for a planned irradiation of an enriched uranium-bearing chloride salt sample in the near term. The upcoming irradiation will contain 13 cm3 of UCl3-NaCl salt (93% enrichment) generating around 20 W/cm3 of fission energy during irradiation and a temperature range that can be contained between bounds of 525-900°C.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A Novel Manufacturing Process of Lightweight Automotive Seats: Integration of Additive Manufacturing and Reinforced Polymer Composite

Lightweight automotive seats offer multiple benefits to original equipment manufacturers in terms of cost savings from various aspects, including less material usage, more integrated processes, and compliance with Corporate Average Fuel Economy Standards. Original equipment manufacturers have been focusing on innovative ways to produce light weight automotive seats. The commercially available automotive seats are currently made of multiple metal components combined through welding and fasteners. The use of additive manufacturing and composite structures is particularly useful for light weighting the automotive components. Additive manufacturing (AM) offers multiple advantages over traditional manufacturing processes such as freedom of design thereby enabling complex structural geometries, mass customization and waste minimization, and control over the fiber alignment through deposition in a predetermined pattern. Combining metal inserts with polymer composites through a novel manufacturing process allows design of lightweight and high-performance materials for automotive components.

99 GENERAL AND MISCELLANEOUS↗

A two-phase substrate model for enzymatic hydrolysis of lignocellulose: application to batch and continuous reactors

Abstract Background Enzymatic hydrolysis continues to have a significant projected production cost for the biological conversion of biomass to fuels and chemicals, motivating research into improved enzyme and reactor technologies in order to reduce enzyme usage and equipment costs. However, technology development is stymied by a lack of accurate and computationally accessible enzymatic-hydrolysis reaction models. Enzymatic deconstruction of cellulosic materials is an exceedingly complex physico-chemical process. Models which elucidate specific mechanisms of deconstruction are often too computationally intensive to be accessible in process or multi-physics simulations, and empirical models are often too inflexible to be effectively applied outside of their batch contexts. In this paper, we employ a phenomenological modeling approach to represent rate slowdown due to substrate structure (implemented as two substrate phases) and feedback inhibition, and apply the model to a continuous reactor system. Results A phenomenological model was developed in order to predict glucose and solids concentrations in batch and continuous enzymatic-hydrolysis reactors from which liquor is continuously removed by ultrafiltration. A series of batch experiments were performed, varying initial conditions (solids, enzyme, and sugar concentrations), and best-fit model parameters were determined using constrained nonlinear least-squares methods. The model achieved a good fit for overall sugar yield and insoluble solids concentration, as well as for the reduced rate of sugar production over time. Additionally, without refitting model coefficients, good quantitative agreement was observed between results from continuous enzymatic-hydrolysis experiments and model predictions. Finally, the sensitivity of the model to its parameters is explored and discussed. Conclusions Although the phenomena represented by the model correspond to behaviors that emerge from clusters of mechanisms, and hence a set of model coefficients are unique to the substrate and the enzyme system, the model is efficient to solve and may be applied to novel reactor schema and implemented in computational fluid dynamics (CFD) simulations. Hence, this modeling approach finds the right balance between model complexity and computational efficiency. These capabilities have broad application to reactor design, scale-up, and process optimization.

09 BIOMASS FUELS↗

Chemical durability and corrosion-induced microstructure evolution of compositionally complex titanate pyrochlore waste forms with uranium incorporation

Chemical durability of compositionally-complex rare-earth titanate pyrochlore solid solutions with or without uranium incorporation was investigated by semi-dynamic leaching testing. A Ti-enriched amorphous passivation film formed on the surface due to the surface alteration-reorganization mechanism with preferential release of the weakly oxygen-bonded rare earth elements. Elemental release was found to be strongly correlated with chemical disorder, with a negligible correlation with entropy. The release rate of the uranium gradually decreased with increasing numbers of components, implying a possibility of designing and optimizing waste form performance with enhanced chemical durability by controlling composition complexity and chemical disorder for effective nuclear waste management.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

SPH modeling of biomass granular flow: Theoretical implementation and experimental validation

The commercialization of biomass-derived energy is impeded by flowability challenges arising from the feeding and handling of granular biomass materials in full-scale biorefineries. To overcome these obstacles, a robust and accurate model to simulate the flow of granular biomass is indispensable. However, conventional mesh-based numerical codes are limited by inherent mesh distortion in simulating large deformation that commonly occurs in granular biomass handling. Here, in this study, we propose a graphics processing unit (GPU)-accelerated meshless Smoothed Particle Hydrodynamics (SPH) code to model the flow of granular biomass materials. A modified void ratio-based mass conversation, a hybrid particle-to-particle/surface frictional boundary treatment, and a hypoplastic constitutive model are implemented. Four numerical examples, an elastic block sliding on inclined planes, sand column collapse, Angle of Repose, and axial compression tests for pine chips, were simulated using the developed SPH code. The results demonstrate good agreement between numerical predictions and analytical and experimental data for all four examples, validating the SPH code and increasing confidence that it can be applied to simulate more complex granular biomass handling processes, such as hopper feeding or auger conveyance.

09 BIOMASS FUELS↗

ZPPR Test Bed (ZTB) Pre-Conceptual Design Report

Authorized by the Nuclear Energy Innovation Capabilities Act (NEICA), the National Reactor Innovation Center (NRIC) provides private sector technology developers access to strategic infrastructures and assets for commercial nuclear energy research, development, demonstration, and deployment activities. The mission is to support a timely and cost-effective path to the licensing and commercialization of new nuclear energy systems. To meet these needs, NRIC is developing two reactor demonstration test beds at Idaho National Laboratory (INL), the ZPPR Test bed (ZTB) and the EBR-II Test bed (ETB). ZTB will support the demonstration of systems that operate at less than 500 kWt. The baseline objective is for the ZPPR Cell to act as a confinement structure capable of siting reactors that utilize Safeguards Category 1 material for operations. The major areas addressed in the pre-conceptual design include: • Installation of an access door • Electrical Power • Heat Removal • Ventilation in the Cell • Reactor Installation Along with the design for ZTB, a concept of operations (COP) has also been developed. The COP is intended to facilitate a common understanding of ideas, challenges, and issues. As systems continue to evolve in complexity System Engineers and Project Directors will utilize and update the COP to develop and sustain a common vision of the system for stakeholders.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗