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At least 1,729 records · Page 96

Design of a SiC-Si moving packed-bed particle-to-sCO 2 heat exchanger for high temperature concentrating solar power applications

Particle-based concentrating solar power systems integrated with sCO 2 power cycles offer high thermal efficiencies but require durable heat exchangers to transfer heat from high-temperature particles to the sCO 2 working fluid. Here, this study presents the design and optimization of a silicon carbide-silicon moving packed-bed heat exchanger for fabrication via binder jetting additive manufacturing. The heat exchanger was designed to withstand a 20 MPa sCO 2 pressure and operate at particle inlet temperatures up to 750 °C. The final design features 152 sCO 2 channels distributed across 19 plates, with elliptical corners and a minimum wall thickness of 3 mm. Flow restrictors at the sCO 2 channel inlets significantly improved flow uniformity, reducing thermal stresses and achieving a structural reliability of 99 % under representative operating conditions. The heat exchanger delivers a thermal duty of 9 kW and a volumetric power density of approximately 1 MW/m 3 in the channel region. Sensitivity studies confirmed the heat exchanger’s robustness under varying operating conditions, demonstrating its viability as a high-performance alternative to metallic heat exchangers for particle-based high-temperature concentrating solar power applications.

Barua, Bipul [Argonne National Laboratory (ANL), A

Performing Numerical Analysis of Cybersecurity Options Using Dynamic Risk Analysis Tool EMRALD

Cyberattacks can have many different attack paths, durations, and goals. There are also many different mitigation options involving hardware, software, and/or humans. Considering a cyber threat should involve defense-in-depth methods and a quantitative or numerical evaluation of overall effectiveness against dynamic, time-dependent attacks to make cost and risk-informed decisions. Typical cyberattack modeling methods only provide a qualitative evaluation. The main areas of cybersecurity are confidentiality, integrity, and availability. For companies with cyber-physical systems such as advanced nuclear reactors, cyber-related safety is a requirement set by North American Electric Reliability and the U.S. Nuclear Regulatory Commission. They are also concerned about availability or reliability as a business case. As cyber threats are evolving to a business-for-hire structure, more attacks may focus on disrupting business success and reliability, causing financial and economic stability risk. Companies want to know business reliability and recovery from those threats, and that requires modeling physical behavior of the targets. Dynamic-state-based and Markov-based modeling provides a method for better cyber scenario modeling with different tools having issues such as state-base explosion. Dynamic modeling enables time and conditional features not found in other numerical evaluation methods. EMRALD (Event Modeling Risk Assessment using Lined Diagrams) is a dynamic risk analysis modeling and simulation tool and has features that reduce modeling issues. It has been used to model different time-dependent events including plant behavior and operator procedures. As a general modeling tool, EMRALD can also be used to model cyberattack scenarios with varying mitigation options and quantify effectiveness, producing numerical data for risk-informed decisions. This paper uses EMRALD to demonstrate that dynamic numerical risk analysis can be used for cyber threat modeling to provide insights for design decision-making and optimize defense strategies. Keywords: cyber modeling; cyber-physical systems; numerical cyber modeling

97 - MATHEMATICS AND COMPUTING

Microreactor Optimization Using Simulation And Economics (mouse)

Microreactor Optimization Using Simulation and Economics (MOUSE) is a tool that integrates both nuclear microreactor design and reactor economics to provide comprehensive evaluations and optimizations. This tool enables stakeholders to explore the interplay between technical and economic variables, guiding them towards effective and competitive microreactor solutions. For the reactor core simulations, MOUSE leverages the OpenMC Monte Carlo Particle Transport Code to perform detailed core simulations for various microreactor designs. The included OpenMC models are 2D core designs of a Liquid Metal Thermal Microreactor (LMTR), a Gas-Cooled TRISO-Fueled Microreactor (GCMR), and a Heat Pipe Microreactor. Beyond core design, MOUSE includes simplified calculations for: - Calculating the masses of heat exchangers within the system. - Mechanical power of pumps. - Estimating the area occupied by various buildings within the nuclear plant. For the economic analysis, MOUSE provides detailed bottom-up cost estimates, encompassing a wide range of costs including preconstruction costs, direct costs, indirect costs, training costs, financial costs, operation & maintenance (O&M) costs, and fuel costs. These cost estimations are developed using data from the MARVEL project and additional literature sources, enabling the calculation of total capital costs and levelized cost of energy for both first-of-a-kind and nth-of-a-kind microreactors. MOUSE also enables analysis of the cost drivers and competitiveness in the electricity market. MOUSE allows users to modify a wide array of technical and economic parameters to evaluate different scenarios and their impacts. Examples of these parameters include: Fuels, coolants, or reflector materials Enrichment levels Control drum materials and geometry Fuel pin geometry and materials Moderator pin geometry and materials Reactor core and reflector dimensions Packing factor for the TRISO particles Nuclear reactor power and reactor burnup Number of sensors Shielding thickness Reactor vessel and guard vessel dimensions Operational staff requirements Number of emergency shutdowns Levelization period Interest rate Construction duration Since MOUSE is powered by the WATTS toolkit, it supports optimization studies, parametric analyses, and uncertainty calculations/propagation. The optimization techniques enable users to identify optimal design and economic configurations. The parametric analysis tools allow users to explore the sensitivity of various parameters, while uncertainty propagation helps quantify the impact of uncertainties on overall performance and cost. User Interface and Workflow: Currently, MOUSE is a command-line-based tool. Users can input various reactor design or economic parameters, modify the designs, run simulations, and visualize results through comprehensive data visualization and reporting capabilities. The typical workflow involves setting up the reactor model, defining economic parameters, running simulations, and analyzing the results to make informed decisions. By combining advanced design calculations with detailed economic modeling, MOUSE provides a robust framework for optimizing nuclear microreactor technologies, enhancing their competitiveness, and guiding stakeholders towards innovative and cost-effective solutions.

Hanna, Botros [Idaho National Laboratory (INL), Id

ROADRUNNER uranium nitride MiniFuel: Experimental design, fabrication and pre-irradiation baseline characterization for accelerated burnup testing

Uranium nitride (UN) is a promising fuel candidate for advanced reactor systems owing to its high uranium density and thermal conductivity; however, its qualification remains constrained by the scarcity of well-controlled irradiation performance data. Here, to address this limitation, the ROADRUNNER (Research On ADvancing the peRformance of UraNium Nitrides in Extreme enviRonments) campaign employs the MiniFuel platform in the High Flux Isotope Reactor (HFIR) to enable accelerated burnup irradiation testing under tightly controlled and largely isothermal conditions. This paper presents the experimental design, fuel fabrication, and pre-irradiation baseline characterization of the ROADRUNNER UN MiniFuel campaign. Thirty-six UN minidisc specimens were fabricated with systematically varied as-fabricated density (86–96% of theoretical density), carbon impurity content (961–5240 ppm), oxygen content (≤ ∼2000 ppm), and grain size (2.5–24 μm). The irradiation matrix spans nominal fuel temperatures of 873 K, 1173 K, and 1473 K and target burnups of 3.75%, 6.0%, and 7.5% fissions per initial metal atom (FIMA). Neutronic and thermal analyses were performed to define specimen-specific burnup accumulation and temperature histories, establishing the boundary conditions for subsequent in-pile behavior. Comprehensive pre-irradiation characterization—including dimensional metrology, density verification, impurity analysis, X-ray diffraction, Raman spectroscopy, scanning electron microscopy, X-ray computed tomography, and confocal profilometry—provides a detailed baseline for post-irradiation examination. Pre-irradiation data were further used to generate predictive estimates of fission gas release and swelling using existing empirical correlations. This quantitative comparison reveals substantial inter-model divergence at intermediate and elevated temperatures that exceeds propagated input uncertainties, highlighting structural gaps in the historical irradiation database. The ROADRUNNER irradiation campaign is currently underway in HFIR, with initial firs cycle completed in late 2025 and remaining targets scheduled through 2027. The experimental design and baseline dataset presented here establish the framework needed to interpret forthcoming post-irradiation measurements and to provide discriminating data for the validation and refinement of physics-based UN fuel performance models.

Lopes, Denise Adorno [Oak Ridge National Laborator

Plume Impingement Software Module for Real-Time Proximity Operations

Successfully executing proximity operations in space, such as docking or in-orbit servicing, requires sophisticated spacecraft design that accounts for induced environments. As a chaser vehicle’s attitude control thrusters fire, they create rarefied plumes that can impact the target vehicle, with the potential to overload components, exceed thermal limits, and spin the target vehicle out of control. High-fidelity simulations of the thruster plume impingement environment require the direct simulation Monte Carlo (DSMC) method, but DSMC is too computationally expensive to simulate proximity operations that involve thousands of thruster firings. For this analysis to be tractable, engineering models of the plume flowfield and impingement events are used to simulate these trajectories [1]. Currently, on-orbit plume impingement environments are modeled through an inefficient open-loop analysis cycle where the vehicle’s flight controller and plume impingement teams iterate on the trajectories until they pass the target vehicle’s plume requirements. As complex on-orbit missions evolve and become more frequent, lengthy design cycles will become operational bottlenecks. To address this gap, this work develops an advanced plume impingement module capable of operating at real-time scale that can be integrated with existing mission planning tools and onboard flight systems. The plume module leverages state-of-the-art plume simulation techniques [2] to deliver fast, physics-based impingement predictions in a software architecture that can be tailored to diverse proximity operations scenarios. A prototype of this plume impingement module is built to demonstrate the feasibility of real-time performance. This prototype completes plume impingement calculations in microseconds per target geometry mesh point. The software serves as a foundational capability for plume-aware trajectory design, operational risk assessment, and future autonomous decision-making systems.

Plume Impingement

Sticking Coefficients of Fusion Reactor Impurities from Molecular Dynamics Simulations for the Design of Cryopumps

A cryopump can be utilized as an impurity removal component of a direct internal recirculation (DIR) system for the fusion fuel cycle. The DIR facilitates a low fuel inventory by continuously pumping unburnt fuel while removing impurities from the fusion exhaust stream. A cryopump can target multiple impurity species by maintaining a temperature lower than the gas triple-point temperature that promotes desublimation. The desublimation/condensation of gases in cryopumps can be characterized by the sticking coefficient, which is defined as the probability for a gas particle to stick to a (cryo-)surface upon collision. The sticking coefficient is one of the important design/operation parameters for cryopumps, and it depends on a variety of surface and gas properties. Here, in this study, molecular dynamics simulations were utilized to estimate the sticking coefficients of typical fusion gas impurity species N 2 , CO 2 , and CH 4 over a Cu surface for a range of gas temperatures and surface coverages. The molecular dynamics study showed that the sticking coefficients for gases decrease with an increase in gas temperature. The presence of a single full monolayer of condensate on the metallic surface showed an adverse effect on the sticking of gases; however the sticking improved with two full monolayers of condensate on the surface. The sticking of gases over the mixed condensate on a surface was more favorable than the condensate of the same species for N 2 and CH 4 , with an exception for CO 2 , which showed a decrease in sticking over the mixed condensate.

cryopump

Multi-hadron systems via Lattice QCD

This project supported a broad set of research in theoretical nuclear physics which has been designed to support current and future experimental DOE facilities. The broad summary of physical observables of interest in this project were the bread-and-butter observables obtained in experimental nuclear and particle physics experiments, namely scattering amplitude including multi-hadronic states. The primary goal of this project was to design a systematically improvable paradigm for accessing such amplitudes directly from the Standard Model of Particle Physics. The main tools that were used and explored in this project were scattering theory, lattice QCD, and future quantum computers. The physics outputs included various novel formalisms, exploratory lattice QCD calculations, and a new proposal for studying any scattering observable using future quantum computers.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS

Transition of SRT Source Term Software to Modern Version Control System to Enable More Efficient Verification, Validation, and User Engagement

The Simplified Radionuclide Transport (SRT) code assists in reactor design and licensing by providing a detailed analysis of radionuclide transport under specific transient scenarios. This analysis is essential for ensuring that reactors meet safety and regulatory standards before they are authorized to operate. Mechanistic source term analysis, which involves a realistic evaluation of radionuclide behavior from the source to the environment, is a key component of this process. It provides a comprehensive understanding of potential release scenarios, supporting the development of robust safety measures.

22 GENERAL STUDIES OF NUCLEAR REACTORS

Cost analysis of alternative large-scale high-temperature solid oxide electrolysis hydrogen production facilities

We extend our past cost analysis of gigawatt-scale solid oxide electrolysis (SOE) facilities that produce high purity hydrogen gas from water by estimating construction and operating costs for three new alternative design cases: (1) offsite feed steam generation; (2) near-atmospheric pressure (NAP) stack; and (3) onsite electric boiler feed steam generation. Pressure effects on hydrogen electrode-(cathode-)supported SOE cell (SOEC) stack performance are estimated for the same assumed cell and stack construction and used to determine facility-wide stack capital costs for achieving a fixed H2 production at different pressures. Modular balance of plant (BOP) process equipment capital costs are estimated for each new alternative design case using our past equipment sizing, design, and cost data and scaling relationships. Furthermore, we update BOP equipment sizing and design for the NAP case using Aspen®. Vendor quotes for electric boilers are used to estimate costs for the electric boiler design case. Factory and onsite assembly and installation costs for SOEC stacks and BOP equipment are calculated using our past simplified first-principles approach. First-of-a-kind (FOAK) and N th -of-a-kind (NOAK) production maturity cost estimates are included for all results. The case with NAP stacks offers the lowest facility total capital cost (TCC, ~23% lower than base) while use of small electric boilers requires the highest TCC (~3% higher than base). H 2 production prices decrease from the base of ~$\$2.17$ /kgH 2 to ~$\$1.92$/kgH 2 for 1 GW e DC SIP facilities utilizing NAP stacks supplied by offsites steam situated in large modules and blocks for $\$0.030$/kWh e and $0.009/kWh t prices for electricity and thermal energy, respectively. We report all costs in 2021 US dollars.

Balance of plant (BOP) process equipment

Intelligent Experiments through Real-Time AI: Fast Data Processing and Autonomous Detector Control for High-Energy Nuclear Experiments

The aim of this project is to develop software and hardware for fast real-time data processing and autonomous detector control and calibration for the sPHENIX and the future EIC experiments. Below summarizes Georgia Tech team efforts in the past year: 1. We developed a real-time clustering algorithm and FPGA-based pipeline architecture for processing fired pixel data from ALPIDE sensors in sPHENIX experiments. Our Columnar Clustering Co-Design introduces a hardware-aware, stream-friendly approach that segments pixel data by column pairs using a Column Pair Clustering (CPC) strategy, followed by Cluster Stitching to merge adjacent subclusters. Implemented in Vitis HLS, the pipeline comprises five stages—read-in, subclustering, stitching, analysis, and write-out—connected by tagged HLS streams with custom end-of-event signaling for robust synchronization. We designed a pipelined dataflow model optimized for throughput, low latency, and minimal buffering, enabling scalable clustering across events of arbitrary size. Our system maintains spatial precision via center-of-mass and shape key extraction and efficiently handles edge cases such as fragmented or nested clusters. Compared against DBSCAN in both software and hardware, our approach demonstrates competitive performance under FPGA constraints. 2. We also conducted a comprehensive algorithm-to-hardware co-design of connected component analysis tailored for sPHENIX experiments, focusing on real-time, low-latency processing using FPGAs and High-Level Synthesis (HLS). Starting from a Python-based particle tracking pipeline, the team translated the core logic—graph traversal via DFS and Union-Find—into an HLS-compatible C++ model, replacing dynamic memory and recursion with static arrays and pipelined control flow. The final design includes a fully streamed and dataflow-compatible Union-Find kernel optimized across five iterations, incorporating loop pipelining, array partitioning, AXI/FIFO interface tuning, and function flattening. Experimental results show up to 14.8× speedup over the CPU baseline, reducing per-graph latency to 1.58 μs and demonstrating strong resource efficiency with only ~7k LUTs and zero BRAM usage. The design maintains functional correctness against the Python reference using a Python-based C-simulation framework and Mean Squared Error metrics. This work validates the potential of HLS-driven FPGA designs for edge-level HEP data acquisition, laying a scalable foundation for future integration with real-time detector pipelines and multi-graph processing systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS

Data-Efficient Methods for Determining Flory–Huggins χ Parameters in Multicomponent Polymer Formulations

Polymer formulations are essential in diverse applications including personal care products, coatings, paints, adhesives, and plastic materials. Designing these formulations requires navigating large, complex design spaces, where phase and self-assembly behavior critically impact performance. The Flory–Huggins χ parameter, which quantifies segmental miscibility, is widely used to parametrize the excess free energy of mixing in formulation models. In this work, we introduce two data-efficient, top-down methods for estimating χ parameters using the Random Phase Approximation (RPA): (i) Boundary Nonlinear Regression (Boundary-NLR), which fits theoretical spinodal boundaries to experimental phase boundaries, and (ii) Surrogate Model Inverse Parameter Estimation (SMIPE), which uses a Gaussian Process Classifier to fit sparse phase maps via a surrogate model. Both methods allow rapid parametrization of polymer field-theoretic models without the need for additional experiments. We evaluate these approaches on data sets involving polymer–solvent–nonsolvent ternary mixtures and block copolymer–solvent systems, demonstrating their robustness to experimental noise and their relevance for real-world formulation design.

copolymers

The System for Classification of Low-Pressure Systems (SyCLoPS): An All-In-One Objective Framework for Large-Scale Data Sets

We propose the first unified objective framework (SyCLoPS) for detecting and classifying all types of low-pressure systems (LPSs) in a given data set. We use the state-of-the-art automated feature tracking software TempestExtremes (TE) to detect and track LPS features globally in ERA5 and compute 16 parameters from commonly found atmospheric variables for classification. A Python classifier is implemented to classify all LPSs at once. The framework assigns 16 different labels (classes) to each LPS data point and designates four different types of high-impact LPS tracks, including tracks of tropical cyclone (TC), monsoonal system, subtropical storm and polar low. The classification process involves disentangling high-altitude and drier LPSs, differentiating tropical and non-tropical LPSs using novel criteria, and optimizing for the detection of the four types of high-impact LPS. A comparison of our labels with those in the International Best Track Archive for Climate Stewardship (IBTrACS) revealed an overall accuracy of 95% in distinguishing between tropical systems, extratropical cyclones, and disturbances. SyCLoPS produces a better TC detection skill compared to the previous algorithms, highlighted by an approximately 6% reduction in the false alarm rate compared to the previous TE algorithm. The vertical cross section composite of the four types of high-impact LPS we detect each shows distinct structural characteristics. Finally, we demonstrate that SyCLoPS is valuable for investigating various aspects of LPSs in climate data, such as the evolution of a single LPS track, patterns of LPS frequencies, and precipitation or wind influence associated with a particular LPS class.

54 ENVIRONMENTAL SCIENCES

Compact X-band split electron linac for cabinet-size small-sample irradiators

Many small-scale industrial radiation facilities rely on hazardous radioisotope-based gamma ray irradiators, which are being gradually replaced by alternative technologies, such as particle accelerators. RadiaBeam has developed a compact, cabinet-size, 3 MeV electron-linac-based irradiator to match the penetration of Co-60 and provide high irradiation throughput. Here the linac utilizes X-band RF power to reduce size, employs an innovative split-linac approach to lower costs, and features a novel X-ray conversion target geometry that spreads the beam out across the target, providing a low dose uniformity ratio. In this paper, we discuss the accelerator design, fabrication, and test results.

43 PARTICLE ACCELERATORS

Chapter 12 - Flight Envelope

The term "flight envelope" is used to refer to the boundaries of aircraft loading and flight conditions within which operation of the aircraft is satisfactory, and beyond which some aspect becomes unacceptable. This flight envelope represents, in fact, the limiting conditions arising from a matrix of inter-related flight envelopes covering the appropriate variables. Thus, for each loading (i.e., external stores configuration and its associated range of weight and center of gravity (c.g.) position) and aircraft configuration (i.e., position of undercarriage (u/c), flaps, slats, etc.), the envelopes of airspeed versus altitude, airspeed versus load factor, angle of attack versus angle of sideslip, etc., must be investigated to establish the limits within which all aspects such as handling qualities, engine behavior, structural loads, etc., remain acceptable. Flight testing of new or derivative aircraft models is carried out with the initial purpose of defining a flight envelope which is, first and foremost, safe and secondarily, which enables the effective use of the vehicle for its intended purpose. Flight testing occurs only after numerous reviews of the design and review of results from ground tests and predictions of flight characteristics in such areas as structures, aerodynamics, stability and control, flight controls (particularly fly-by-wire control systems, propulsion, etc.). Accordingly, opening and expanding the envelope is a task that must be approached cautiously, systematically, and with coordination and cooperation of the many disciplines involved in the design and test of an airplane. (Sections 8 and 10 cover test planning and safety of flight considerations, respectively). The fundamental tenet in establishing a flight envelope via flight test is risk reduction. This is reflected in the typical sequence of events leading to initial flight test - design reviews (both hardware and software), then ground test involving singular disciplines (windtunnel tests for aerodynamics, structurally loading the wing/fuselage/nacelle on a ground test article with loads anticipated to occur in flight, flight control system control law checkout, propulsion test cell runs and/or flying test bed tests, etc.), and then ground tests involving multi-disciplines (See Section 9). Only after these have been accomplished will an initial, limited, low-risk, flight envelope be established. The limited envelope will typically be in the middle of the projected final flight envelope. Subsequent flight tests will then be devoted to expanding the initial envelope by operating the airplane at increasing ranges - representing increasing risk - of engine operation, airspeeds both fast and slow, altitude, load factor both above and below 1g, centers of gravity (fore and aft), and with system/subsystem failures. Whether flight tests are to define a flight envelope on a new model airplane with the attendant new airframe, new engine(s), and new subsystems (hydraulics, pressurization, etc.), or on an airplane involving only a few of these areas such as new engines in an old airframe, the fundamental approach to establishing an envelope is the same.

H Walgemoed

ReSpike: A Co-Design Framework for Evaluating SNNs on ReRAM-Based Neuromorphic Processors

With Moore’s law approaching its end, traditional von Neumann architectures are struggling to keep up with the exceeding performance and memory requirements of artificial intelligence and machine learning algorithms. Unconventional computing approaches such as neuromorphic computing that leverage spiking neural networks (SNNs) to perform computation are gaining traction and seek the paradigm shift necessary to sustain the increasing demands of modern applications. Novel memory technologies, such as resistive RAM (ReRAM), employ a crossbar architecture that possesses the inherent capability of efficiently computing vector-matrix multiplication—a dominant operation in SNNs. The prospect of naturally mapping SNNs to the crossbar structures provides a unique opportunity for achieving a high-performance, power-efficient neuromorphic system. In this work, we present ReSpike, which is a new framework, behavioral simulator, and architectural design based on ReRAM crossbar architectures, enabling modeling and co-design to achieve efficient execution of SNNs. We drive this co-design forward by quantifying the impact that ReRAM cell nonidealities have on the corresponding accuracy of an SNN application.

Asifuzzaman, Kazi [ORNL] (ORCID:0000000240044791)

Interwoven magnetic kagome metal overcomes geometric frustration

Magnetic kagome materials provide a platform for exploring magneto-transport phenomena, symmetry breaking and charge ordering driven by the intricate interplay among electronic structure, topology and magnetism. Yet geometric frustration in conventional kagome magnets limits their tunability. Here we propose a design strategy for interweaving quasi-one-dimensional magnetic Tb zigzag chains with non-magnetic Ti-based kagome bilayers in TbTi 3 Bi 4 . Comprehensive spectroscopic analyses reveal coexisting elliptical-spiral magnetic and spin-density-wave orders accompanied by a large ~90 meV band-folding gap. The combined magnetic and electronic state leads to a giant anomalous Hall conductivity of 10 5 Ω −1 cm −1 , which exceeds that observed in frustrated kagome analogues. These results establish TbTi 3 Bi 4 as a model system of magnetic kagome metals with strong electron–magnetism interactions and underscore the necessity of interweaving designed magnetic and charge layers separately to achieve tunable transport properties. This design strategy will enable the discovery of emergent quantum states and next-generation electronic materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

Development for Integrated System-Level Analysis Capabilities in SAM for Molten Salt Reactors

In recent years, there has been renewed interest in Molten Salt Reactors (MSRs) for their potential advantages compared to reactors that rely on solid fuel. In response to such interest, many methods and codes have been developed to capture the unique features of MSRs. Among them, the System Analysis Module (SAM) is a modern system analysis tool that provides fast-running, modest-fidelity, whole-plant transient analysis capabilities, essential for fast-turnaround design scoping and engineering analyses of advanced reactor concepts. For liquid-fuel MSRs, the complex physics and chemistry involved in MSR operation—such as reactor kinetics, fluid flow, heat transfer, and salt composition dynamics—pose significant challenges for system-level modeling. Specific modeling capabilities are needed for system-level transient simulation. This paper presents recent advancements in SAM capability enhancements for system-level modeling of MSRs, focusing on improved simulation fidelity, computational efficiency, and multi-physics integration. Key enhancements include the development of species transport, Delayed Neutron Precursor (DNP) drift, modified Point Kinetics Equations (PKE), decay heat modeling, key fission product behavior, salt corrosion, and thermal-hydraulic coupling, as well as code robustness and performance enhancements for MSR applications. The code enhancement allows for better predictive accuracy in safety analysis, transient behavior, and operational optimization, thus supporting the design and licensing of next-generation MSRs. Results from case studies are presented to demonstrate the benefits of these enhancements in accurately capturing key reactor transient behaviors.

Hu, Rui (ORCID:0000000237712920)

Performance of a Regenerative Fuel Cell System for the Lunar Surface

Regenerative fuel cells (RFCs) are an attractive energy storage solution for lunar missions as a technology capable of providing a higher specific energy (i.e., W∙h/kg) than state-of-the-art packaged Li-ion battery systems. An RFC consists of the (1 & 2) electrochemical stacks (chemical to electrical energy conversion to supply electricity to an external load, i.e. the fuel cell reaction, and electrical to chemical energy conversion of supplied electrical power to dissociate water into hydrogen and oxygen gases, i.e. water electrolysis), (3) fluidic conditioning, (4) reactant storage, (5) avionics, (6) power management and distribution (PMAD), and (7) thermal management. NASA’s Glenn Research Center has designed, assembled, and tested a breadboard RFC sys-tem capable of operating autonomously for multiple simulated lunar day/night cycles in a laboratory environment. The system is comprised of a non-flow through proton exchange membrane (PEM) fuel cell stack and a liquid-anode feed PEM electrolyzer (EZ) stack designed to electrochemically compress the reactants at balanced pressures up to 12.4 MPa (1800 psia). The fluidic conditioning, avionics, PMAD, and thermal management sub-systems are largely comprised of commercial-off-the-shelf components for this system-level development effort. The hardware is controlled by a CubeSat space processor running an operational program based on core flight architecture that can control the RFC hardware autonomously through a state machine with fault monitoring. The testing results highlighted here were completed with the system in an open-loop configuration such that reactants generated through water electrolysis were vented while gas cylinders supplied fuel cell operation. The breadboard operated autonomously, but there were five unplanned transitions to a safe state that required a manual restart after reviewing the data, determining a root cause, and implementing a solution. Four of the transitions were caused by the thermal management subsystem and the fifth was caused by a water management control issue in the EZ sub-system. The RFC system operated for over 550 hours with the final cycle being slightly abbreviated due to reasons unrelated to system performance.

Kerrigan Cain