SMR have emerged as next-generation nuclear power system, offering enhanced safety, efficiency, and economic advantages. Among their critical components, HCSGs have been extensively studied for their effective heat exchange capabilities. However, primary-side cross flow within HCSG could induce vortices and turbulent structures between tubes, resulting in flow instabilities that negatively impact overall system stability. Large eddy simulation based CFD can accurately capture this complex behavior but requires fine meshes and short time-steps, leading to high computational costs. In this study, a deep-learning-based reduced-order modeling strategy is proposed to maintain both accuracy and computational efficiency in analyzing local flow regions between HCSG tube layers. POD, DMD, and nonlinear autoencoder are employed to reduce data dimensionality, followed by a Long Short-Term Memory network for predicting flow evolution. These ROM frameworks are compared to reduce simulation overhead while preserving CFD-level predictive accuracy. The results indicate that linear methods effectively capture dominant features such as vortex formation and dissipation, whereas the nonlinear autoencoder tends to preserve finer-scale fluctuations. Notably, the POD-LSTM model demonstrates superior performance in predicting flow field dynamics, achieving on the test set (AE = 0.9477, DMD = 0.9409).

Real-time thermal-hydraulic simulation is essential for digital twin (DT) technology that supports the safe and efficient operation of small modular reactors (SMRs). Computational fluid dynamics (CFD) provides high-fidelity flow analysis, but its computational cost prevents direct use in DT applications. AI-based surrogate modeling has been actively investigated to address this limitation, yet neural operator–based surrogates for CFD-level transient analysis of SMR-specific geometries have not been reported. This study presents an integrated framework that combines a reduced-order model (ROM) with neural operators, applied to the helical coil steam generator (HCSG) of the System-integrated Modular Advanced Reactor (SMART). Two ROM strategies tailored to each CFD data type were compared, an MLP-based autoencoder (AE) for unstructured mesh data and a convolutional autoencoder (CAE) for structured mesh data, and each was coupled with the deep operator network (DeepONet) to construct the latent DeepONet (L-DeepONet). The Fourier neural operator (FNO) was additionally adopted for comparison. A multi-scale technique was incorporated into both frameworks to mitigate spectral bias and improve the prediction of Kármán vortex streets developing inside the HCSG. The multi-scale L-DeepONet captured the instantaneous periodic vortex dynamics in both velocity and pressure fields, while the FNO and its multi-scale variant predicted the time-averaged mean flow and provided reliable pressure drop estimates. These complementary characteristics provide a practical model-selection guideline that links each architecture to specific DT objectives based on CFD data type and the required level of flow resolution.

A new molten salt reactor (MSR) design has been developed aiming for long‐term operation and high safety. In order to enhance the integrity and economy of the system during the long‐term operation, pumps were removed from the primary system, and the fuel salt flow was developed by natural circulation. In terms of thermal–fluidic, the natural circulation operation without a pump increases the reactor safety and resistance to accidents. The normal operation feasibility of the reactor was evaluated with the multiphysics analysis conducted with the Generalized Nuclear Foam (GeN‐Foam) code. It was shown that the reactor can maintain stable power under a fixed heat exchanger outlet temperature condition. To increase the natural circulation, the active core region was designed to have a simple cylindrical shape, which induced a stagnation zone with slow velocity near the side wall. Due to the slow velocity, the stagnation zone has a substantially high temperature, and a flow guide was introduced to mitigate the stagnation effect. The impact of the flow guide was evaluated, including the reactivity feedback and delayed neutron precursor drift effect. The results highlight the importance of analyzing the flow distribution within the core in an MSR and demonstrate the effectiveness of the guide structure in ensuring stable core flow.

This study presents a conduction-based heat pipe modeling approach to simulate the transient thermal response of liquid metal heat pipes (LMHPs) during frozen startup. By formulating the model solely on the heat conduction equation, the approach offers a simplified yet physically grounded framework that avoids the complexities associated with detailed multiphase flow modeling. The model incorporates effective thermal conductivity of the metal vapor to represent evolving vapor flow regimes and employs a loosely coupled numerical scheme to address the disparity in time scales between vapor dynamics and wall conduction. Implemented in commercial computational fluid dynamics (CFD) software, the model was validated against experimental data from sodium heat-pipe startup tests. The results demonstrate good agreement across different heat pipe configurations and heat inputs, confirming the model's capability to capture key thermal transient behaviors during frozen startup. Owing to its simplicity, robustness, and ease of implementation, the proposed model offers practical value for both academic research and engineering applications involving LMHP technologies.

A high-fidelity numerical analysis methodology was proposed for evaluating the fuel rod cladding integrity of a Prototype Gen IV Sodium Fast Reactor (PGSFR) during normal operation and Design basis events (DBEs). The MARS-LMR code, system transient safety analysis code, was applied to analyze the DBEs. The results of the MARS-LMR code were used as boundary condition for a 3D computational fluid dynamics (CFD) analysis. The peak temperatures considering HCFs satisfied the cladding temperature limit. The temperature and pressure distributions were calculated by ANSYS CFX code, and applied to structural analysis. Structural analysis was performed using ANSYS Mechanical code. The seismic reactivity insertion SSE accident among DBEs had the highest peak cladding temperature and the maximum stress, as the value of 87 MPa. The fuel cladding had over 40 % safety margin, and the strain was below the strain limit. Deformation behavior was elucidated for providing relative coordinate data on each active fuel rod center. Bending deformation resulted in a flower shape, and bowing bundle did not interact with the duct of fuel assemblies. Fuel rod maximum expansion was generated with highest stress. Therefore, it was concluded that the fuel rod cladding of the PGSFR has sufficient structural safety margin during DBEs.

A high-fidelity numerical analysis methodology was proposed for evaluating the fuel rod cladding integrity of a Prototype Gen IV Sodium Fast Reactor (PGSFR) during normal operation and Design basis events (DBEs). The MARS-LMR code, system transient safety analysis code, was applied to analyze the DBEs. The results of the MARS-LMR code were used as boundary condition for a 3D computational fluid dynamics (CFD) analysis. The peak temperatures considering HCFs satisfied the cladding temperature limit. The temperature and pressure distributions were calculated by ANSYS CFX code, and applied to structural analysis. Structural analysis was performed using ANSYS Mechanical code. The seismic reactivity insertion SSE accident among DBEs had the highest peak cladding temperature and the maximum stress, as the value of 87 MPa. The fuel cladding had over 40% safety margin, and the strain was below the strain limit. Deformation behavior was elucidated for providing relative coordinate data on each active fuel rod center. Bending deformation resulted in a flower shape, and bowing bundle did not interact with the duct of fuel assemblies. Fuel rod maximum expansion was generated with highest stress. Therefore, it was concluded that the fuel rod cladding of the PGSFR has sufficient structural safety margin during DBEs.

This study involved a Reynolds-averaged Navier-Stokes- (RANS-) based computational fluid dynamics (CFD) analysis of the 37-pin wire-wrapped fuel bundle of the PNC Plant dynamics test loop (PLANDTL) facility. Previously, mainly the hydrodynamic phenomena of the wire-wrapped fuel bundle were analyzed, but the present study additionally included heat transfer analysis through conjugate heat transfer. The main purpose of the study was to benchmark the experimental data of the PLANDTL 37-pin wire-wrapped fuel bundle to investigate the heat transfer phenomena. In addition, the aim was to verify the accuracy of the RANS-based CFD analysis method using the STAR-CCM+ simulation software in comparison with the experimental data. The grid used for verification was an innovative grid system consisting of hexahedra using Fortran-based code. The development of the RANS-based CFD methodology included grid sensitivity analysis, turbulence model sensitivity analysis, and turbulent Prandtl number sensitivity analysis. Information on the temperature, mass flow rate, and area of the CFD results for each subchannel was provided for the top of the heated section and is expected to serve as a reference for future studies aiming to perform the validation and verification of a PLANDTL facility. In addition, the dependence of the peak temperature on the azimuth angle of each pin was analyzed.

A high-fidelity computational fluid dynamics (CFD) analysis was performed using the Large Eddy Simulation (LES) model for the lower plenum of the High–Temperature Test Facility (HTTF), a ¼ scale test facility of the modular high temperature gas-cooled reactor (MHTGR) managed by Oregon State University. In most next–generation nuclear reactors, thermal stress due to thermal striping is one of the risks to be curiously considered. This is also true for HTGRs, especially since the exhaust helium gas temperature is high. In order to evaluate these risks and performance, organizations in the United States led by the OECD NEA are conducting a thermal hydraulic code benchmark for HTGR, and the test facility used for this benchmark is HTTF. HTTF can perform experiments in both normal and accident situations and provide high-quality experimental data. However, it is difficult to provide sufficient data for benchmarking through experiments, and there is a problem with the reliability of CFD analysis results based on Reynolds–averaged Navier–Stokes to analyze thermal hydraulic behavior without verification. To solve this problem, high-fidelity 3-D CFD analysis was performed using the LES model for HTTF. It was also verified that the LES model can properly simulate this jet mixing phenomenon via a unit cell test that provides experimental information. As a result of CFD analysis, the lower the dependency of the sub-grid scale model, the closer to the actual analysis result. In the case of unit cell test CFD analysis and HTTF CFD analysis, the volume-averaged sub-grid scale model dependency was calculated to be 13.0% and 9.16%, respectively. As a result of HTTF analysis, quantitative data of the fluid inside the HTTF lower plenum was provided in this paper. As a result of qualitative analysis, the temperature was highest at the center of the lower plenum, while the temperature fluctuation was highest near the edge of the lower plenum wall. The power spectral density of temperature was analyzed via fast Fourier transform (FFT) for specific points on the center and side of the lower plenum. FFT results did not reveal specific frequency-dominant temperature fluctuations in the center part. It was confirmed that the temperature power spectral density (PSD) at the top increased from the center to the wake. The vortex was visualized using the well-known scalar Q-criterion, and as a result, the closer to the outlet duct, the greater the influence of the mainstream, so that the inflow jet vortex was dissipated and mixed at the top of the lower plenum. Additionally, FFT analysis was performed on the support structure near the corner of the lower plenum with large temperature fluctuations, and as a result, it was confirmed that the temperature fluctuation of the flow did not have a significant effect near the corner wall. In addition, the vortices generated from the lower plenum to the outlet duct were identified in this paper. It is considered that the quantitative and qualitative results presented in this paper will serve as reference data for the benchmark.

This work provides a summary of selected experimental capabilities being developed to support nonnuclear testing and demonstration of technology in support of microreactors under the U.S. Department of Energy's (DOE's) Microreactor Program. Major capabilities include the Single Primary Heat Extraction and Removal Emulator (SPHERE) and the Microreactor Agile Non-nuclear Experimental Test Bed (MAGNET). The SPHERE facility allows for controlled testing of the steady-state and transient heat rejection capabilities of a single heat pipe using electrical heaters that simulate nuclear heating. The facility is capable of monitoring axial temperature profiles along the heat pipe and surrounding test articles during startup, steady-state operation, and transients. Instrumentation includes noncontact infrared thermal imaging, surface thermocouples, spatially distributed fiber optic temperature and strain sensors, electrical power meters, and a water-cooled, gas-gap calorimeter for quantifying heat rejection from the heat pipe. The facility can be operated under both vacuum and inert-gas conditions. The MAGNET facility is a large-scale, 250-kW electrically heated microreactor test bed to enable nonnuclear experimental evaluation of a variety of microreactor concepts. It can be supplied to electrically heat a scaled section of a microreactor and further test the capabilities of heat rejection systems. The initial MAGNET experiments will support technology maturation and reduce uncertainty and risk associated with the design, operation, and deployment of monolithic heat pipe-based reactors. However, this test bed can broadly be applied to multiple microreactor concepts to evaluate a wide range of thermal-hydraulic and structural phenomena such as interface coupling with power conversion units and other collocated systems. MAGNET can evaluate integral thermomechanical effects during electrical heating of an array of heat pipes in a larger test article. Examples of initial testing will include thermal stresses in the monolith and the impact of debonding of a heat pipe from the core block and how that failure could impact surrounding heat pipes, i.e., understanding the potential for cascading failure. This work also discusses some modeling capabilities that can support experiment design, analysis, and interpretation, including the heat pipe code Sockeye and a comparison of thermal-structural simulations performed using ABAQUS and STAR-CCM+.

This paper presents a numerical investigation of two-phase natural circulation flows established when external reactor vessel cooling is applied to a severe accident of the APR1400 reactor for the in-vessel retention of the core melt. The coolability limit due to external reactor vessel cooling is associated with the natural circulation flow rate around the lower head of the reactor vessel. For an elaborate prediction of the natural circulation flow rate using a thermal-hydraulic system code, MARS-KS1.5, a three-dimensional computational fluid dynamics (CFD) simulation is conducted to estimate the flow rate and pressure distribution of a liquid-state coolant at the brink of significant void generation. The CFD calculation results are used to determine the loss coefficient at major flow junctions, where substantial pressure losses are expected, in the nodalization scheme of the MARS-KS code such that the single-phase flow rate is the same as that predicted via CFD simulations. Subsequently, the MARS-KS analysis is performed for the two-phase natural circulation regime, and the transient behavior of the main thermal-hydraulic variables is investigated.