Rui Hu

Accurate and computationally efficient representation of key thermal-fluid phenomena is essential for improving the transient simulation capabilities of liquid-metal fast reactors (LMFRs). This report addresses an important modeling gap associated with thermal mixing and stratification in large plena through the development and integration of advanced data-driven turbulence models in the System Analysis Module (SAM). The proposed approach retains the conventional numerical solution of the mass, momentum, and energy equations while using neural networks to provide the turbulent-viscosity closure required by the multidimensional fluid solver. Artificial intelligence (AI) and machine learning (ML) thereby offer a means to improve the fidelity of reactor system simulations while retaining the computational efficiency required for engineering-scale transient analysis. Two neural network architectures, Convolutional Neural Networks (CNNs) and transformers, are investigated and compared using CFD-generated training data. The results demonstrate that the data-driven model can reproduce the turbulent-viscosity field with substantially improved accuracy compared with the simplified Prandtl mixing-length model currently used in SAM. The transformer architecture provides further improvement over CNNs, achieving a 32% lower RMSE than the CNN for the same benchmark problem. To address the computational and memory requirements associated with the quadratic scaling of conventional self-attention, a compressed-attention transformer is subsequently developed. The approach compresses the full mesh representation into a fixed number of latent tokens, reducing the attention complexity from O(N 2 ) to O(NL + L 2 ), where L ≪ N. The resulting model enables application to mesh sizes that are compatible with the typical requirements of coarse-mesh reactor simulations. Finally, the AI-driven turbulence model is integrated into a system-level simulation of an advanced sodium fast reactor. For comparison, a protected loss-of-flow transient is simulated using three different modeling approaches for the sodium hot pool: a 0D perfectly mixed volume, a 1D mixing and stratification model, and a 2D axisymmetric multi-dimensional model with AI-driven turbulence closure. The results demonstrate that the spatial distribution of temperature within the hot pool can produce non-negligible differences in natural circulation and reactor temperatures, highlighting the need for detailed simulation capabilities for thermal mixing and stratification, such as those developed in this work. Overall, the work demonstrates the feasibility of integrating AI-based physical models into SAM and combining system-level and multi-dimensional simulations to enable AI-enhanced multiscale modeling of nuclear reactor systems.

This report details the FY26 Computational Fluid Dynamics (CFD) modeling activities conducted for the water-based testing phase of the Natural convection Shutdown heat removal Test Facility (NSTF). Focusing on the reconfigured lower tank inlet piping configuration, the primary objectives of this study are twofold: (1) to evaluate the high-fidelity predictive capability of 3-D CFD for single-phase natural circulation and thermal mixing to complement 1-D system codes, and (2) to assess the current modeling capabilities and numerical stability of CFD codes for two-phase hydrostatic head reduction flashing in passive safety systems. For single-phase natural circulation, transient simulations were performed for the deep-pool baseline (Run089, 80% initial inventory fill) and the shallow-pool accident limit (Run093, 20% depleted inventory fill). The RANS-based models demonstrated outstanding numerical robustness, near-linear parallel scaling on High-Performance Computing (HPC) clusters, and excellent quantitative agreement with transient and spatial experimental thermocouple measurements. High-resolution flow fields illuminated the decisive influence of pool depth on buoyant jet trajectories, demonstrating unconstrained vertical thermal stratification in deep pools and revealing the potential for horizontal flow recirculation and thermal short-circuiting in shallow pools. For two-phase operations, demonstration simulations encompassing prescribed boundary conditions (Case 1), internally resolved Eulerian Multiphase (EMP) flashing models (Case 2), and scoping Mixture Multiphase (MMP) models successfully captured high-level complex multi-dimensional phenomena, including severe upper-pipe phase stratification, liquid acceleration beneath vapor blankets, and buoyant vapor plume venting in the primary tank. Despite these successes, modeling two-phase flash boiling presented severe numerical challenges driven by stiff interphase coupling and explosive volumetric expansion. Robust numerical stability was successfully achieved across the full integrated geometry in collaboration with Siemens engineering support—leveraging user-defined NIST REFPROP equation-of-state tables, non-reflecting boundaries, and under-relaxation scheduling. However, current stabilized two-phase predictions have notable limitations, as the modeled phase-change patterns deviate from test data and fail to capture the experimental downward propagation of the flashing front from the tank inlet into the vertical chimney. This study lays a solid foundation and provides recommendations to guide future research. Near-term priorities include systematically restoring higher-order spatial discretization schemes, calibrating interfacial drag and dispersion closures, tuning dynamic bubble interaction length scales, and extending computational domains to simulate full-duration inventory boil-off transients. Ultimately, integrating these multi-dimensional CFD insights with 1-D system-level codes (such as SAM and RELAP5-3D) will advance multiscale predictive capabilities for reactor passive decay heat removal systems.

The Natural convection Shutdown heat removal Test Facility (NSTF) at Argonne National Laboratory completed its eighth and final year of water-based testing in 2026, marking the conclusion of a multi-configuration experimental campaign that first began in 2018. This report documents results from the past year of testing activities, detailing nine tests across pressure and loss coefficient parametric conditions, beyond design basis accident scenarios, and studies at full dryout conditions. Over this past year, the NSTF logged 370 hours of heated operation, producing data sets from four scoping and five accepted DataQuality tests under the NQA-1 quality assurance program. The pressure parametric testing finalized a multi-year comparison between mid-tank and lower-tank inlet configurations across a range of system pressures. The effects of pressure primarily influence the local parameters such as liquid temperatures and oscillation damping behavior, with relatively minor influences on the fundamental instability mechanism. Tank inlet elevation, however, was found to strongly affect system behavior, with significant influences on flashing instability propagation, duration of large amplitude flow oscillation, and quasi-steady-state heat removal performance. The lower tank inlet configuration consistently produced lower loop flow, higher riser and panel temperatures, and stronger persistence of flow oscillations than the mid-tank inlet configuration, reflecting the reduced chimney height and resulting in higher hydrostatic head. A full-inventory depletion test, the first to combine a near-full initial inventory level with continuous accelerated drain to complete depletion, successfully characterized the system response across the entire usable inventory range in a single continuous transient. Comparison with prior discrete inventory parametric cases showed that thermal structure conditions at boiling incipience, not inventory level alone, is a primary driver for determining startup and initial transient flow oscillation behavior, especially below 30% fill levels. This test concluded in flow stagnation and geysering, after which cold inventory replenishment via the primary water tank was initiated to allow loop recovery and re-establishment of natural circulation flow. Two throttling tests examined variations in loss coefficient along the network piping for loss factor coefficients (Kvalve) up to 423 at the inlet header and up to 522 in the upper chimney. Expanding on previous testing, results from the throttle parametric series showed that heat removal performance remains effective across a wide range of throttling conditions, with only minor degradation observed even when the loop experienced significant flow instabilities. The testing indicates that upper chimney throttling can create destabilization conditions at loss coefficients lower than header throttling, but did not progress to full geysering, instead producing irregular non-stagnant oscillations. Reduced power scoping tests were performed to evaluate the potential of developing natural air circulation cooling within the empty water pipes under dry out conditions. Measurements indicate that minor amounts of heat removal by air circulation do, in fact, develop within the channels of the empty loop. A single-phase repeatability and rapid evacuation test then showed excellent reproducibility with prior baseline data (differences under 3% across key parameters) and resulted in the first direct measurement of NSTF thermal response to a nearly instantaneous, nearly total inventory loss. With the completion of this test matrix, the experimental campaign using the current water-based NSTF configuration is concluded. Across eight years of water-based testing, NSTF performed 94 tests over 1,978 hours of operation, generating a robust dataset that has been shared with multiple U.S. based organizations. These data sets have directly supported code validation, licensing-relevant dat

This report summarizes FY26 progress under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program's high-temperature gas-cooled reactor (HTGR) application driver work, covering a wide range of activities such as code validation and multi-physics code assessment. 1) A detailed SAM model of the High-Temperature Engineering Test Reactor (HTTR) was developed using a unique-block grouping approach, with an extended parallel thermal network method to capture block-to-block conduction and radiation heat transfer, and applied to steady-state simulations of the HTTR 30~MW and 9~MW cases. 2) In another activity, SAM's newly implemented multi-component gas flow model was validated against the Natural convection Shutdown heat removal Test Facility (NSTF) argon ingress experiment, correctly capturing the density-driven suppression and thermal recovery of natural circulation observed when argon is introduced into the air-cooled Reactor Cavity Cooling System (RCCS) loop. 3) For the OECD/NEA High Temperature Test Facility (HTTF) benchmark, we co-led the international benchmark activities as well as the OECD/NEA final benchmark report to be released at the end of this year. 4) Finally, the coupled Griffin-SAM modeling capability for pebble-bed HTGRs was advanced by verifying the Griffin neutronics solution against Serpent Monte Carlo for a realistic non-uniform temperature distribution, resolving several deficiencies in the SAM-to-Griffin temperature transfer scheme, and enabling distinct fuel kernel, moderator, and coolant temperatures for cross section feedback. These new features were demonstrated in a PBR load-following transient.

This report documents fiscal year 2026 enhancements to the System Analysis Module (SAM) for modeling fission product transport in liquid-fueled molten salt reactors (MSRs). The work advances three principal areas: noble gas transport, noble metal deposition, and user interface improvements. The noble gas transport capability integrates drift-flux gas transport, Henry’s law two-film interphase mass transfer with pressure-based nucleation suppression, Knudsen-regime pore diffusion into porous graphite with a conjugate salt-graphite interface constraint, built-in material properties, five Sherwood-number mass transfer correlations including three derived from high-fidelity NekRS simulations, and xenon-135 reactivity feedback through SAM’s point-kinetics model. This work also presents a comprehensive verification test suite, including new analytically verified cases for pressure-dependent onset of interphase gas transfer in a stagnant vertical pipe, a postulated FLiBe-graphite Xe extraction permeator, a gravity riser with a fission-product source, and a descending pipe with gas redissolution driven by hydrostatic pressure. A machine learning framework for bubble rise velocity prediction in molten salt systems is developed and benchmarked on molten-salt and diverse aqueous bubble datasets. The best-performing fine-tuned transfer-learning networks achieve an 82% reduction in RMSE relative to the Clift correlation, and is implemented directly in SAM. The noble metal transport capability is developed, including a liquid-wall deposition model and a gas-surface flotation mechanism that transfers insoluble particles entrained by sparging gas to wetted structures. Verification tests and demonstration cases cover the surface deposition, flotation efflux, and flotation shedding. Finally, a new [SpeciesTransport] input structure replaces positional global vectors with selfcontained, order-independent, named species blocks, simplifies the specification of multiphase species and decay chains, and remains fully compatible with existing SAM input files. Together, these developments improve the physical fidelity, verification basis, and usability of SAM for system-level analyses of fissionproduct behavior in MSRs.

The System Analysis Module (SAM) is being developed as a modern system analysis code for advanced non-light-water-reactor safety analysis under the U.S. DOE NEAMS program. Previous feasibility studies have demonstrated that a staggered-grid finite volume method (SG-FVM), implemented under the MOOSE framework, can deliver more than an order of magnitude speedup over the existing continuous Galerkin finite element method (CG-FEM) solver for liquid-cooled, incompressible but thermally expandable flow systems. This work extends the previous effort to compressible, gas-cooled reactor applications, where pressure couples directly into the mass equation adding additional nonlinearity into the equation system. New code capabilities are implemented for pebble bed high-temperature gas-cooled reactor (PB-HTGR) analysis, including a pebble bed CoreChannel component, built-in pebble bed effective thermal conductivity model and channel-to-channel crossflow model. The capabilities are tested, benchmarked, and demonstrated for problems with increased level of model and physical complexities, including the HTTU effective thermal conductivity test, the SANA passive cooling test, and a demonstration case using the GPBR200 reactor design covering steady-state operation, DLOFC and PLOFC transients. Across all cases, the SG-FVM solver demonstrated strong robustness and efficiency, and the solutions agree well with reference results and data. The finding of this work proves that SG-FVM is a viable and efficient solver pathway for compressible, gas-cooled reactor system analysis in SAM. In addition, work has been done to successfully support SAM-FVM recover/restart code feature that is essential to reactor safety analysis applications, and MultiApp code feature that is essential to multi-scale and multi-physics simulations. In summary, this work continued from previous feasibility studies, and further demonstrated that the SG-FVM will serve as a strong foundation for SAM’s advanced solver algorithm for future deployment.

Air-ingress following a depressurized loss-of-forced-cooling (DLOFC) event is a challenging, multiphysics safety scenario for High-Temperature Gas-Cooled Reactors (HTGRs), involving coupled gas composition transport, buoyancy-driven flow redistribution, graphite oxidation, and structural heat-up. Despite its importance — air ingress is a key scenario identified in the PIRT process for the HTGRs — existing system-level safety codes have lacked the integrated capability to simulate the complete event sequence with high confidence. This report documents the development, validation, and demonstration of three new capabilities in the SAM code to address this gap: (1) a multi-component gas mixture flow model with binary diffusion to track the helium-air composition and its effect on system density and flow; (2) a 0-D graphite oxidation model based on the Roes correlation, including oxygen consumption and exothermic heat release; and (3) an isentropic critical flow model for accurate representation of primary system depressurization through a break. These capabilities are validated against two benchmark experiments. The NSTF heavy-gas ingress experiment validates the multi-component flow model: SAM correctly reproduces the rapid buoyancydriven flow stagnation and subsequent natural circulation recovery driven by composition-dependent density changes. The NACOK graphite oxidation experiment validates the oxidation model: SAM predicts a bottom-level graphite weight loss of 25%, in close agreement with the measured 24%, and reproduces the strong axial nonuniformity and block-geometry dependence of oxidation, at a level comparable to the SPECTRA and TINTE codes. The validated capabilities are then exercised together in an integrated, reactor-scale simulation of a DLOFC air-ingress transient in a simplified HTR-PM pebble-bed reactor. In a single calculation spanning approximately 8 days, SAM reproduces the complete accident sequence: rapid depressurization, densityand diffusion-driven air ingress over ˜15 hours, onset of buoyancy-driven natural circulation, exothermic graphite oxidation with a peak fuel temperature at ˜62 hours, and eventual passive cooldown. These results demonstrate that SAM now provides the nuclear community with a preliminarily validated, modern systemlevel tool for HTGR air-ingress safety analysis, filling a recognized capability gap. Future extensions to broaden species tracking, improve oxidation chemistry, and refine the reactor model are discussed.

I. Molten salt reactors (MSRs) are a class of nuclear reactors in which molten salt serves as fuel and coolant, depending on the specific design. Benefiting from the unique properties of molten sal...

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.