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At least 595 records · Page 33

Enhancing HT-WGS catalyst performance with stable monovalent copper species via electron supply from defect-induced MgO

Magnesium oxide (MgO) exhibits excellent synergy with cerium oxide (CeO2), serving as either textural or electronic promoters during catalytic reactions. However, achieving well-dispersed CeO2-MgO is technically challenging because they are known not to form solid solutions, and the crystal growth of CeO2 suppresses the structure formation of MgO, leading to MgO being in an inhomogeneous amorphous state within CeO2-MgO. For this reason, most of research groups have been struggling with synthesizing well-dispersed CeO2-MgO. This leads them to focusing on the interaction between the active metal and cerium, overlooking the true role of magnesium. In this study, we successfully synthesized well-dispersed CeO2-MgO via a spray pyrolysis-assisted evaporation-induced self-assembly method, followed by the impregnation of Cu. The location and dispersion of Cu nanoparticles were highly dependent on the MgO distribution. Additionally, we revealed that this significantly influenced the catalytic activity and stability towards the HTS reaction and furthermore supplies electrons to monovalent Cu species, helping maintain the stable electron structure and oxidation state of Cu species considered as active sites. These findings suggest that optimizing the MgO distribution in CeO2-MgO is a promising strategy for developing efficient catalysts for the HTS reaction, emphasizing the role of MgO in designing high-performance catalysts.

Kim, Min-Jae↗

Spent Nuclear Fuel Mechanical Loads in the General Package Drop Scenario

The US Department of Energy Spent Fuel and Waste Science and Technology program is performing research to determine the mechanical loading conditions applied to spent nuclear fuel (SNF) during normal conditions of transportation to inform mechanical tests of SNF and close an important knowledge gap related to the practical disposition of SNF in the US. A recent multi-national collaborative test campaign measured SNF assembly impact response to the 30 cm horizontal package drop scenario, which is a common regulatory basis test of SNF package design. Researchers at Pacific Northwest National Laboratory (PNNL) are using the test data to validate explicit finite element models to calculate the mechanical loads and structural response of spent nuclear fuel assemblies in the as-tested 30 cm horizontal package drop scenario. Once the as-tested package drop model is validated, the next step is to apply the model to the general 30 cm drop scenario, which includes all impact angles, all fuel assembly types, and all burnup conditions. PNNL is developing a damage model that will incorporate the results of finite element parametric studies to establish trends in SNF mechanical loading to various input parameters, like impact orientation and burnup. The damage model will have the capability to estimate mechanical loads for any single set of input parameters, but it will first be used to describe the upper bounds of potential SNF loading in the 30 cm drop scenario. This paper describes PNNL’s progress toward developing the general solution to the problem of spent nuclear fuel mechanical loads in the 30 cm package drop scenario and it describes the next steps in closing the knowledge gap.

Klymyshyn, Nicholas A.↗

Advanced Moderation Module for High-Temperature Micro-Reactor Applications

Development and deployment of micro-reactors that provide competitive efficiency, prevailing compactness, and inherent safety is an immediate focus of the U.S. nuclear industry. For thermal neutron micro-reactors operating at elevated temperature for optimized efficiency, such as micro molten-salt reactors (MSRs), heat-pipe reactors, and very-high temperature reactors (VHTRs), high-performance moderator based on metal hydride can enhance the neutron economy and therefore achieve reduced weight and enhanced portability. As unclad metal hydride inevitably decomposes at elevated temperature, an enclosure is required for hydride moderator to deliver desired performance at elevated temperatures. Conventional moderator enclosure solutions based on high-temperature alloys introduce extraneous neutron penalty into the micro-reactor, affecting the neutronic benefits provided by the hydride moderator. Additionally, the compatibility between the high-temperature alloy enclosure and the micro-reactor matrix is also a potential issue. In this report, we disclose an Advanced Moderator Module (AMM) concept enabled by an innovative enclosure solution combining the advantages of refractory metals, ceramic matrix composites (CMCs), and advanced coating technology to serve as hydrogen permeation barrier up to very-high temperatures. A schematic description of the AMM structure is illustrated in Figure A1. The AMM contains a moderating material core made of metal hydride with high thermal stability, such as YH 2-x . The hydride core is enclosed by an H 2 barrier layer coated on a ductile refractory metal liner to minimize hydrogen loss during high-temperature operation. A ceramic matrix composite (CMC) cladding is adopted to provide further structural strength, especially during power transients. Between the CMC cladding and metal liner, an extra diffusion barrier coating is inserted to suppress the chemical interaction at elevated temperatures. Hence, based on a series of innovative material solutions, the AMM is capable of containing the metal hydride core at elevated temperature (>900oC) inside coated and lined CMC envelop with negligible hydrogen loss throughout the microreactor lifetime. The benefit of the AMM technology was assessed based on a comprehensive multi-stage reactor-physics analysis. Advanced moderation based on hydride metals (such as YH2-x) enables reaching optimum moderation with higher fuel content than traditional VHTR technology, which is required to design compact micro-reactor cores targeting long-life operation. The AMM enclosure technology provides lower thermal neutron absorption rates than traditional solutions (based on stainless steel or Mo-based alloy such as TZM), which reduces the fissile enrichment requirements by 6-8% on a TRISO-fueled design based on the EMPIRE core. Finally, combining the hydride moderator with neutron transparent enclosure solutions provides significant potential to boost neutronics performance of micro-reactors in terms of increased core lifetime or reduced size and weight by 30-50% on a micro-reactor based on the Holos Quad technology. The progress and plans for on-going development and demonstration efforts are also discussed in this report. The current demonstration of AMM is focused on the hydrogen diffusion barrier demonstration under thermal cycling, while radiation tolerance demonstration is planned. The next step of the demonstration plan will be the assembly of miniature AMM for high-temperature testing, which can be used as a prototype for future pilot scale demonstration.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

High-Temperature Rotating Disk Electrode Study of Platinum Bimetallic Catalysts in Phosphoric Acid

Understanding the H 3 PO 4 effect on the catalyst’s activity under a relevant condition is important for high-temperature polymer electrolyte membrane fuel cell (HT-PEMFC) catalyst research. Here, we report a high-temperature rotating disk electrode (HT-RDE) study of oxygen reduction reaction (ORR) in H 3 PO 4 . With the regular electrochemical protocol, we found that H 3 PO 4 reduction could occur during cyclic voltammetry study and form a reductive species—phosphorus acid (H 3 PO 3 ). Further, to obtain reliable ORR measurement, we optimized the protocol to avoid the H 3 PO 3 generation. The ORR activity of carbon-supported PtM (M = Fe, Co, Ni, Ru, Pd, and Ir) bimetallic alloy catalysts measured with this HT-RDE method showed higher ORR activity than Pt. To understand the alloying effect, we combine experiments in diluted solutions to distinguish the alloying effect on Pt–O binding and Pt–H 3 PO 4 binding. The results indicate that H 3 PO 4 mainly reduces available sites for ORR, with little effect on neighboring site’s Pt–O binding via Pt–H 3 PO 4 interaction, which is also supported by the density functional theory calculation of the Pt–O binding energy with/without H 2 PO 4 . Further study in a phosphoric acid-doped quaternary ammonium-biphosphate ion pair coordinated polyphenylene (PA-QAPOH) membrane electrode assembly (MEA) shows that the active alloy catalyst has better performance in both the HT-RDE and MEA. Also, the MEA gives higher ORR activity than the HT-RDE because of the higher pressure and less phosphoric acid content of the MEA. Yet, the gap between the HT-RDE and MEA is significantly smaller than that between the room temperature (RT)-RDE and MEA, suggesting the importance of temperature and H 3 PO 4 concentration in understanding ORR in HT-PEMFCs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Solutal-buoyancy-driven intertwining and rotation of patterned elastic sheets

Abstract The intertwining of strands into 3D spirals is ubiquitous in biology, enabling functions from information storage to maintenance of cell structure and directed locomotion. In synthetic systems, entwined fibers can provide superior mechanical properties and act as artificial muscle or structural reinforcements. Unlike structures in nature, the entwinement of synthetic materials typically requires application of an external stimulus, such as mechanical actuation, light, or a magnetic field. Herein, we use computational modeling to design microscale sheets that mimic biology by transducing chemical energy into mechanical action, and thereby self-organize and interlink into 3D spirals, which spontaneously rotate. These flexible sheets are immersed in a fluid-filled microchamber that encompasses an immobilized patch of catalysts on the bottom wall. The sheets themselves can be passive or active (coated with catalyst). Catalytic reactions in the solution generate products that occupy different volumes than the reactants. The resulting density variations exert a force on the fluid (solutal buoyancy force) that causes motion, which in turn drives the interlinking and collective swirling of the sheets. The individual sheets do not rotate; rotation only occurs when the sheets are interlinked. This level of autonomous, coordinated 3D structural organization, intertwining, and rotation is unexpected in synthetic materials systems operating without external controls. Using physical arguments, we identify dimensionless ratios that are useful in scaling these ideas to other systems. These findings are valuable for creating materials that act as “machines”, and directing soft matter to undergo self-sustained, multistep assembly that is governed by intrinsic chemical reactions.

Manna, Raj Kumar (ORCID:0000000322729487)↗

Efficient light-emitting diodes based on oriented perovskite nanoplatelets

Solution-processed planar perovskite light-emitting diodes (LEDs) promise high-performance and cost-effective electroluminescent devices ideal for large-area display and lighting applications. Exploiting emission layers with high ratios of horizontal transition dipole moments (TDMs) is expected to boost the photon outcoupling of planar LEDs. However, LEDs based on anisotropic perovskite nanoemitters remain to be inefficient (external quantum efficiency, EQE <5%) due to the difficulties of simultaneously controlling the orientations of TDMs, achieving high photoluminescence quantum yields (PLQYs) and realizing charge balance in the films of assembled nanostructures. Here, we demonstrate efficient electroluminescence from an in situ grown perovskite film composed of a monolayer of face-on oriented nanoplatelets. The ratio of horizontal TDMs of the perovskite nanoplatelet film is ~84%, which leads to a light-outcoupling efficiency of ~31%, substantially higher than that of isotropic emitters (~23%). In consequence, LEDs with a peak EQE of 23.6% are achieved, representing highly efficient planar perovskite LEDs.

36 MATERIALS SCIENCE↗

Variance reduction techniques for Monte Carlo neutron noise simulations

The small fluctuations of the neutron flux caused by small perturbations of the macroscopic cross-sections take the name of neutron noise. Advanced Monte Carlo methods have been recently proposed in order to solve the neutron noise equations in the frequency domain, which allows establishing reference solutions to validate faster but approximate deterministic solvers. Due to the presence of particles carrying two statistical weights (for the real and imaginary components of the noise field), both of which may be positive or negative, Monte-Carlo simulations of neutron noise pose distinct challenges in terms of variance reduction. In this work we investigate two variance-reduction techniques, namely branchless collisions and weight cancellation, and probe their effectiveness for a benchmark con- figuration concerning the noise field induced by a pin with oscillating cross sections in a fuel assembly.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

SMALE: Enhancing Scalability of Machine Learning Algorithms on Extreme-Scale Computing Platforms

Deployment and execution of machine learning tasks on extreme-scale computing platforms face several significant technical challenges: 1) High computing cost incurred by dense networks – The computing workload of deep networks with densely-connected topology increases rapidly with the network size, imposing a non-scalable computing model of extreme-scale computing platforms; 2) Non-optimized workload distribution – Many advanced deep learning algorithms, e.g., sparsification and irregular net-work topology, produce very unbalanced workload distribution on extreme-scale computing platforms. The computation efficiency is greatly hindered by the incurred data and computation redundancies as well as long tails of the node with extensive workload; 3) Constraints in data movement and I/O bottle-neck – Inter-node data movement in extreme-scale computing platforms are associated with high energy and latency costs, and subject to the constraints of I/O bandwidth; and 4) Generalization of algorithm realization and acceleration on computing platforms – The large varieties of machine learning algorithms and structures of extreme-scale computing platforms make the derivation of a generalized algorithm realization and acceleration method very challenging, which, however, is the requirement by domain scientists and interested users. We call the above challenges Smale’s Problems in Machine Learning and Understanding for High-Performance Computing Scientific Discovery. The objective of our three-year research project is to develop a holistic innovation set at structure, assembly, and acceleration layers of machine learning algorithms to address the above challenges in algorithm deployment and execution. Three tasks are particularly performed, including: At the algorithm structure level, we investigate the techniques that can structurally sparsify on the topology of deep networks for computing workload reduction. We also study clustering and pruning techniques that can optimize the workload distributions over the extreme-scale computing platforms; At the algorithm assembly level, we derive a unified learning framework for unsupervised transfer learning and dynamic growing capabilities. Novel training methods are also exploited to enhance the training efficiency of the proposed framework; At the algorithm acceleration level, we will develop a series of techniques that can accelerate the computation of sparse matrix operations, which are one of the core executions in deep learning and optimize memory access of the concerned platforms. Our proposed techniques attack the fundamental problems in machine learning algorithms running on extreme-scale computing platforms by vertically integrating the solutions at three closely entangled layers, paving the long-term scaling path of machine learning applications under DOE context. Three tasks corresponding to the above respective research orientations are performed during the three-year project period with our collaborators at ORNL. The outcome of the proposed project is anticipated to form a holistic solution set of novel algorithms and network topologies, efficient training techniques, and fast acceleration methods to promote the computing scalability of the machine learning applications of particular interest to DOE.

97 MATHEMATICS AND COMPUTING↗

Improved Fuel Cycle Capability of Griffin for Fast Reactor Applications

Griffin is a MOOSE based reactor multiphysics analysis application jointly developed by Idaho National Laboratory and Argonne National Laboratory under the Department of Energy Office of Nuclear Energy Nuclear Energy Advanced Modeling and Simulation Program. This fiscal year, the fuel cycle capability has been significantly extended by improving the assembly shuffling option to allow flexible fuel reloading in the multi-cycle depletion calculation and incorporating decay between cycles. An equilibrium core calculation capability was also implemented to find an equilibrium core. Additionally, an enrichment search capability was added to determine the enrichment condition that allows a core to reach an equilibrium cycle with the end-of-cycle k-effective meeting a user-specified target value. The updated fuel management capability has been extensively tested using the three-dimensional ABTR problem with different batch schemes, exhibiting reasonable solutions in terms of manual shuffling, equilibrium cycle, and enrichment search calculations. The cross section generation workflow capability for fast reactors was further verified to produce microscopic cross sections as well as Griffin core inputs for an ring-heterogeneous configuration. Rigorous verification tests using the ABTR problem demonstrated that the RH core calculations, with cross sections and Griffin inputs generated from the cross section workflow of Griffin, produced accurate solution for fast reactor problems. In addition, an option to convert delay neutron parameter data generated from MC 2 -3 in the DLAYXS format into XML format was added to support transient calculations using MC 2 -3-generated data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Chemiresistor sensor based on ion-imprinted polymer (IIP)-functionalized rGO for Cd(II) ions in water

This study reports the design and development of a novel chemiresistor (CR) sensor using ion imprinted polymer (IIP)-functionalized reduced graphene oxide (rGO) [IIP/rGO-CR] for cadmium ions (Cd(II)) determination in water. The sensor consisted of a CR transducer made of rGO channel bridging source and drain electrodes prepared by self-assembly and thermal reduction of graphene oxide (GO) on Au interdigitated electrodes chip fabricated on Si/SiO 2 substrate. The IIP was then grafted on rGO using surface-initiated reversible addition-fragmentation chain transfer (RAFT) polymerization with polyethylenimine (PEI) and methylacrylic acid (MAA) as dual functional monomers and Cd(II) ions as template through UV light-initiated copolymerization. The IIP functionalized on rGO acted as an effective recognition element that modulated the resistance of rGO-CR upon binding of Cd(II), enabling Cd(II) detection at ppb level in aqueous solutions. The prepared IIP/rGO-CR sensor worked effectively in the linear range of 2~200ppb and achieved a limit of detection (LOD) of 0.83 ppb, which is lower than the World Health Organization guidelines of 3ppb for drinking water quality. The developed sensor of IIP/rGO-CR showed a high selectivity against a variety of trace and heavy metal ions found in water and good stability for up to 60 days when stored at room temperature for Cd(II) determination in water. Further, the sensor was successfully applied to analyzing Cd(II) spiked in tap, lake and river waters with a 94.5%–113.5% recovery, demonstrating a high degree of accuracy even in complex water samples. Finally, our results illustrated that the CR sensor of IIP functionalized rGO provides a potential platform for sensitive, robust and low-cost environmental analysis of Cd(II) in water.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Selective Electrocatalysis Imparted by Metal-Insulator Transition for Durability Enhancement of Automotive Fuel Cells.

Repetitive start-up and shut-down events in polymer electrolyte membrane fuel cells for automotive applications lead to serious corrosion of the cathode due to an instantaneous potential jump that results from unintended air leakage into the anodic flow field followed by a parasitic oxygen reduction reaction (ORR) on the anode. Here we report a solution to the cathode corrosion issue during the start-up/shut-down events whereby intelligent catalyst design is used to selectively promote the hydrogen oxidation reaction (HOR) while concomitantly suppressing the ORR on the anode. Platinum thin layers supported on hydrogen tungsten bronze (Pt/HxWO3) suppressed the ORR by converting themselves into an insulator following exposure to oxygen, while selectively promoting the HOR by regaining metallic conductivity following subsequent exposure to hydrogen. The HOR-selective electrocatalysis imparted by a metal-insulator transition in Pt/HxWO3 demonstrated a remarkably enhanced durability of membrane electrode assemblies compared to those with commercial Pt/C catalysts.

Jung, Sang-Mun↗

Thermodynamic equilibrium and kinetic fundamentals of oxide dissolution in aqueous solution

Dissolution of oxides in aqueous solutions is fundamentally important for a range of applications and a critical process that determines the chemical durability of industrial ceramics, the performance of nuclear waste forms, and the chemical weathering of minerals. The thermodynamic equilibrium and kinetics of dissolution reactions are key to determining the rate at which oxides dissolve. The increase in collaborative research across disciplines in materials research necessitates a common background to tackle shared scientific problems across different fields. This review selectively examines the fundamentals of dissolution theories that have been developed in chemistry, geochemistry, and materials science, and assembles them into a single collective document for the broader materials science community. Applications of the theories are highlighted using examples from specific areas, but can be similarly applied to other areas. Challenges and future research needs for a predictive-level understanding are discussed in light of the current literature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Challenges in the post-licensing stage of U.S. hydropower development: Current status and some potential solutions

The issuance of a Federal Energy Regulatory Commission (FERC) license is an important milestone in the development process of new U.S. hydropower projects. The complexity and uncertain timeline of the licensing process have been often cited as a key deterrent to new hydropower installations in the United States. However, very little attention has been paid to post-licensing timelines and attrition rates. This article explores the challenges faced by developers in bringing their FERC-licensed hydropower projects to the construction stage. Post-licensing activities to be completed before starting construction include obtaining additional permitting from other federal or state agencies, completing the technical design, securing financing, and in most cases, negotiating a power purchase agreement. For the set of projects that obtained a FERC license between 2007 and 2018, we assembled a dataset—combining information from FERC dockets and responses from a questionnaire to developers—to calculate attrition rates and development timelines and to examine the reasons for delays and cancellations.

13 HYDRO ENERGY↗

Electrostatic‐Attraction‐Driven Self‐Assembled Graphene‐Disordered Rocksalt Composite Cathode for Lithium‐Ion Batteries

Disordered rocksalt cathodes hold promise for achieving high-capacity lithium-ion batteries while using low-cost, earth-abundant elements. However, their electrochemical performance remains critically limited by their poor electronic conductivity. Conventional strategies such as high-energy ball milling with excess carbon additives can improve conductivity but remain challenging to scale and often produce defects and increase surface area, thereby accelerating capacity degradation. Herein, we report an alternative approach of electrostatic-attraction-driven self-assembly to fabricate Li 1.2 Mn 0.6 Ti 0.2 O 1.8 F 0.2 (LMTOF) particles uniformly wrapped with electronically conductive graphene sheets without associated materials degradation. The graphene-wrapped LMTOF demonstrates significantly improved cycling stability (89% capacity retention after 100 cycles) and superior rate capability compared with an LMTOF-carbon composite electrode fabricated using the conventional high-energy ball-milling process. Post-cycling analysis reveals reduced oxygen evolution, suppressed unwanted side reactions, and improved structural integrity for the graphene-LMTOF composite. This work highlights the advantages of solution-based carbon wrapping and offers a scalable strategy to prepare high-performance DRX cathodes for lithium-ion batteries.

carbon composite↗

Gradient-Informed Design Optimization of Select Nuclear Systems

In this work, we present a gradient-informed design optimization of nuclear reactor core components based on neutronics objectives with both continuous and discrete materials. The main argument in favor of using gradient-informed design optimization is that it scales well with increasing dimensionality of the design space. First, a challenge problem with 121 free parameters is solved with a gradient-informed method and then with a genetic algorithm. Then, a challenge problem to optimize the flux profile of a simplified assembly with eight axial zones is solved. Both challenge problems are solved using directly calculated derivatives from Tools for Sensitivity and Uncertainty Analysis Methodology Implementation (TSUNAMI) in the SCALE package. Furthermore, we demonstrate how a discrete optimization problem—selection of materials for 121 voxels—can be lifted into a continuous problem with mixed materials. In the continuous space, adjoint-based gradients are well-defined, and gradient descent is applicable. Then, a forcing function is introduced that with the selection of an appropriately sized hyperparameter can be used to guide the optimized continuous solution back into a discrete solution. This paper presents an account of the challenges that were faced when applying a gradient-informed optimization algorithm using a Monte Carlo calculation to estimate the gradient information and compares a gradient descent optimization method to a genetic algorithm optimization of the same geometry. Overall, this work demonstrates the potential use of adjoint-based gradient calculations in design optimization of nuclear systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

ARC-100 Reactor Security-by-Design Summary 2025

This report applies the security-by-design methodology developed in a previous National Nuclear Security Administration–sponsored work to the ARC-100, a sodium-cooled fast reactor (SFR) being developed by ARC Clean Technology, Inc (ARC). The report contains no proprietary information specific to the ARC 100 reactor. The insights developed in this report are high-level, and generally applicable to other sodium fast reactor designs. The information presented here is the result of a qualitative safety-based analysis and would not inform any potential adversary beyond what would be found in a docketed safety analysis report. The scope of this present report covers ARC-100’s reactor core, used fuel storage, used fuel assembly wash station, cesium trap, sodium cold trap, noble gas decay tanks, used fuel dry storage facility, damaged fuel storage facility, and radioactive waste building. These systems are also compared to a generic SFR design assumed in the previous study. The security assessment results show changes in structures, systems, and components (SSCs) safety importance relative to the generic SFR SSCs. Several SSCs have higher importance rankings than others, and it is recommended that protection efforts are prioritized for these SSCs. Results from this work will furnish a technical justification for the feasibility of these solutions for the ARC reactor's design and, where applicable, identify any regulatory benefits conferred by the proactive design aspect within a risk management framework. This initiative will contribute to a more secure design of the ARC reactor and support its licensing process.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Microbial Taxonomy Run Amok

DNA sequencing has led to an explosion in discovery of microbial phylogenetic novelty, especially that represented by uncultivated taxa, to which the traditional system of prokaryotic taxonomy has not adapted. A lack of expansion of the International Code of Nomenclature of Prokaryotes (ICNP, 'the Code') to effectively capture this information has created a 'wild west' situation where names are published or appear in popular reference databases without further verification or validation. The rapid propagation of variant and questionable naming methods has led to widespread confusion and undermines prior accomplishments. Furthermore, we exemplify inconsistencies that have arisen from this practice and endanger the interoperability of scientific findings. The immediate solution to this problem is to develop and adopt universal best practices that are accepted by expert researchers, major publishers, the International Committee on Systematics of Prokaryotes (ICSP), and international microbiological societies.

59 BASIC BIOLOGICAL SCIENCES↗

Studsvik R2 materials test reactor Ad Hoc depletion strategy for the derivation of the fuel isotopic composition of the MPCMIV benchmark

The Ad Hoc Depletion Strategy elaborated by the NINE company, developed in support of the organization of the MPCMIV (Multi-physics Pellet Cladding Mechanical Interaction Validation) benchmark input and output specifications, is presented. This work aims at illustrating the strategy itself and then showing the results obtained with its application over the Studsvik R2 Testing Reactor, which is analyzed in the benchmark. The objective of the application of the strategy is to compute the fuel elements isotopic compositions at the beginning of some core loadings of interest for the benchmark. To this objective, it is necessary to implement first the simulation model of the three single assembly types and perform the infinite lattice depletions, then, to build the full core model and to perform the simulation of the core cycle. All the models and simulations were carried out with the use of the Monte Carlo particle transport code Serpent 2. Finally, the simulations results are assessed against Studsvik isotopic compositions of the fuel elements discharged from the R2 Reactor at the end of the core loading. Several assumptions were necessary during all the steps of the strategy, to overcome the lack of information regarding the core management. For this reason, the solution found at the end of the current analysis may not be completely optimized and further improvements regarding the model assumptions will be tested in a future work. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗