Packed spherical pebble beds are widely used in several engineering applications, including Generation-IV Pebble Bed Reactors (PBRs), where the randomly packed core geometry produces highly complex flow structures within the inter-sphere void regions. Accurate characterization of turbulence structure and coherent flow dynamics in such configurations remains limited due to experimental accessibility constraints. The present experimental investigation examines the spatial correlation characteristics, spectral behavior of velocity fluctuations, and vortex structure dynamics in a randomly packed pebble bed using high-resolution Time-Resolved Particle Image Velocimetry (TR-PIV) measurements. A Matched Index of Refraction (MIR) facility enabled non-intrusive optical access to the void regions between spheres, allowing detailed measurements of turbulence structure within the packed geometry. Experiments were performed under isothermal conditions at two modified Reynolds numbers (Re1 = 306 and Re2 = 1473), representing transition and fully turbulent flow regimes. Two-point spatial cross-correlation analysis of spanwise and streamwise velocity fluctuations at representative near-wall and center-region locations quantified the spatial extents of coherent turbulence structures across the measurement domain. Persistence power spectral density analysis further identified the dominant frequency content of velocity fluctuations and revealed the spectral distribution of turbulent interactions within the inter-sphere flow regions. Vortex identification analysis was performed to characterize the spatial occurrence, circulation strength, and size distribution of coherent vortex structures in both near-wall and central regions of the randomly packed bed. The results provide detailed insight into the evolution of turbulence structures and coherent flow dynamics in randomly packed pebble beds and establish a high-fidelity experimental dataset for validation of computational fluid dynamics models relevant to thermal-hydraulic analysis and performance assessment of pebble bed reactor core geometries.

Packed spherical pebble beds are widely used due to their applications in a wide variety of engineering applications. Pebble Bed Reactors (PBR) are a Generation-IV nuclear reactor design which are a subject of extensive research, utilizing packed spherical bed arrangements. These packed beds have intricate yet randomized geometry with vacant spaces, increasing the flow complexity in PBR cores which require detailed characterizations. The presented experimental research on a facility of randomly packed pebble bed spheres investigates the complex flow phenomena to evaluate fluid dynamics within a PBR core. By utilizing Particle Image Velocimetry (PIV) among the spheres, high-fidelity velocity measurements were carried out. In this facility, Matched Index of Refraction (MIR) method provides a clear non-intrusive view of the sphere void regions to analyze the flow with precise resolution. The flow was investigated for two modified Reynolds numbers (Re1 = 306 and Re2 = 1473) to provide a comprehensive profile of the flow. The experiments investigated isothermal conditions to examine the differences in flow dynamic patterns within packed spheres. The results characterize first- and second-order flow statistics including mean spanwise and streamwise velocity components, velocity magnitude, velocity fluctuation components, Reynolds shear stress, vorticity, and turbulence kinetic energy. Line profile analyses were performed at three spanwise locations along the near-wall and center regions to assess the downstream development of these flow parameters. The experimental results provide unique high-fidelity data sets for computational fluid dynamics model development and validation important for the design and developmental optimization of PBR core geometries.

Helical cruciform fuel (HCF) rod bundles provide a spacer-grid-free lattice while inducing geometry-driven sweep and crossflow that can enhance inter-subchannel exchange. In this work, time-resolved, two-component particle image velocimetry (TR-PIV) is performed in an optically accessible 9 & times; 9 acrylic HCF bundle using a matched-index-of-refraction (MIR) facility. Velocity fields are acquired in an interior subchannel over laminar, transitional, and turbulent conditions (Reb= 350-20,000), with 10,000 snapshots per case. Mean velocities, spanwise vorticity, RMS fluctuations, Reynolds shear stress, and two-component turbulent kinetic energy (TKE) are reported with uncertainty-aware convergence assessment, together with Welch-averaged spectra and two-point spatial correlations. The flow is strongly streamwise-dominant, but the helical geometry imposes repeatable secondary motion and phase-locked modulation as the inter-subchannel gap periodically opens and closes. Gap-conditioned statistics reveal a contraction-like closed-gap throat where mean streamwise velocity increases while fluctuation levels and turbulent momentum exchange are reduced; the opposite trend occurs during open-gap conditions, consistent with intermittent cross-gap jetting and enhanced mixing. Correlation maps indicate near-isotropic lateral fluctuations within interior regions, supporting the use of lateral RMS velocity as a representative mixing-velocity scale. Using this surrogate, PIV-inferred local effective turbulent mixing coefficient is obtained (3 ti 0.05-0.07) with weak Reynolds-number dependence trending toward a geometry-limited regime (3 ti 0.198Reb-0.1235 for 7000 <= Reb <= 20,000). The dataset provides a benchmark for CFD validation and a physically grounded basis for assessing and improving mixing models for HCF assemblies.

This paper discusses the key features of integral Pressurized Water Reactors (iPWRs) including Helical Coil Steam Generators (HCSGs) and associated correlations. The objective is to highlight design challenges and system level modeling strategies.A RELAP5-3D ver. 4.4.2 nodalization of a NuScale-like iPWR was created based on publicly available literature and, where necessary, design assumptions. The model was qualified under steady-state conditions against the NuScale Final Safety Analysis Report approved as part of the Design Certification Application (DCA) in 2020.Because HCSGs are prone to instabilities, a start-up procedure was simulated to test the model response across a range of operating parameters. Primary flow and temperature results have been found to be consistent with DCA data at reduced power. However, at power levels below 60%, Type-II Density Wave Oscillations (DWOs) occurred in the HCSGs tubes. Analysis of subcooling and phase change numbers informed of potential mitigation strategies; however, stable performance at low power could not be obtained together with steam superheat and constant primary average temperature.The main outcome of the present paper is the presentation of a collaborative benchmark internal to the Texas A&M University in which a station blackout scenario for a NuScale-like iPWR was simulated. Results obtained from RELAP5-3D were compared with those from TRACE, the NuScale Simulator, and DCA data, demonstrating strong qualitative agreement but highlighting quantitative discrepancies primarily due to geometric and correlation differences among the different models. RELAP5-3D simulations have specifically highlighted the occurrence of Type-I DWO if the ECCS is not timely activated.

This study investigates the buoyancy-opposed turbulent flow over a heated hollow sphere placed inside a circular pipe by performing Large Eddy Simulation (LES). The Reynolds number (Re), based on the sphere diameter, and inlet velocity, was fixed at 16,000, while the Richardson number (Ri) was varied from 0 to 2.21 to include both forced and mixed convection conditions. Argon was selected as the working fluid at an operating pressure of 3 MPa to reflect conditions relevant to the experimental data used for comparison. LES predictions were compared with available experimental and Numerical data. Detailed analysis was conducted on key flow and thermal characteristics, including the non-dimensional reattachment length (Lr/D), separation angle (Bs), measured from the upstream stagnation point, turbulent kinetic energy (TKE/U2 infinity), Nusselt number (Nu), and Strouhal number (St). Moreover, Power Spectral Density (PSD) was performed on the co-efficient of lift (Cl) to determine the vortex shedding frequency (fvs). The results demonstrated that, as Ri increased, buoyancy effects increasingly opposed the main flow, resulting in longer reattachment lengths, shorter separation angles, and slightly smaller St. This indicated that buoyancy caused the wake region to expand both in length and width. Furthermore, Proper Orthogonal Decomposition (POD) was performed on streamwise and cross-stream velocity components and it was found that the first 159 modes contained 90% of the total energy for Ri = 1.84. Further analysis suggested that variation in Ri has little effect on the system's dimensionality.

Commercial nuclear plants face several financial challenges due to extended downtimes, often caused by delays in maintaining or replacing reactor vessels. These vessels degrade over time as a result of thermo-mechanical fatigue, embrittlement, and corrosion, leading to cracks that compromise structural integrity and necessitate costly replacements. This economic hurdle inevitably diminishes the attractiveness of adopting nuclear energy. Implementing a real-time health monitoring system can enable proactive maintenance scheduling, minimizing unplanned outages and significantly improving plant efficiency and economic viability.The feasibility of using off-the-shelf sensors such as high-temperature strain gauges and thermocouples for real-time monitoring from outside the reactor vessel is explored in this study. Preliminary bench-top tests are performed on a smaller rectangular specimen made of 304-series stainless steel (SS-304). For validation of strain gauge measurements, various mechanical and thermal loads were systematically applied to the specimen, resulting in consistent and anticipated outcomes. To assess defect detection capability, grooves of varying depths were machined on the face opposing the gauge to simulate interior surface cracks. Surface grooves as shallow as 0.5 mm produced a detectable 15.2% reduction in strain, while deeper defects yielded proportionally greater changes, confirming the sensitivity of exterior-mounted gauges to interior structural anomalies.To simulate the vessel environment and evaluate sensor performance under representative operating conditions, an experimental facility was constructed featuring a 1:23 scaled down section of a High Temperature Gas-cooled Reactor vessel, made from the same SS-304. An array of 32 thermocouples and 11 weldable high-temperature strain gauges, provided by Hi-tech Products Inc., are mounted on the vessel's outer surface for the monitoring application. Several normal and off-normal thermal cases are simulated to characterize the resulting strain and temperature fields and evaluate the sensors' measuring standard deviations and sensitivity. Average strain measurement standard deviations of 1.860 × 10−5, 2.562 × 10−5, and 12.33 × 10−5 m/m were recorded at 200 °C, 400 °C, and 600 °C setpoints, respectively. The sensor array successfully detected and triangulated localized hotspots, with an average sensitivity of 1.81 με/°C recorded across the 11 gauges. Finally, a Residual Monitoring Algorithm is proposed for real-time anomaly detection, demonstrating reliable event localization with minimal false positives and reasonable response times.

High-temperature heat pipes are promising devices for advanced microreactor technologies in terrestrial and space applications. However, off-design conditions such as transient power spikes exceeding the capillary limit can induce dryout, undermining performance and safety. This study experimentally investigates the transient dryout and subsequent rewetting behavior of a stainless-steel, water-filled screen-wick heat pipe subjected to pulsed heat loads beyond its nominal operating limit. A high-resolution optical fiber temperature sensor captured detailed internal vapor temperature distributions, while a miniature pressure transducer captured saturation conditions to identify periods of vapor superheating. Pulse lengths were varied to control the duration and severity of the pulsed dryout conditions and study rewetting and the long-term effects on heat transfer performance. The results reveal that transient dryout elevates thermal resistance, induces significant vapor superheating, and leads to persistent post-transient hysteresis in operating temperatures. The internal measurements highlight the complexity of dryout onset, delayed temperature spikes driven by thermal inertia, and the sensitivity of rewetting behavior to design parameters such as filling ratio and inactive regions. These insights challenge the assumption of saturated vapor conditions near operating limits and underscore the need for refined numerical models. The experimental data set presented here offers critical benchmarks for validating advanced two-phase computational tools and guiding design strategies to enhance the resilience, safety, and performance of heat pipes in next-generation microreactor systems.

This study experimentally investigates the frictional pressure loss and flow regime behavior of a 9 x 9 Helical Cruciform Fuel (HCF) rod bundle, a novel design proposed for Small Modular Reactors (SMRs). The unique cruciform cross-section, featuring four twisted petals, eliminates the need for conventional spacer grids, offering higher fuel packing fraction and enhanced coolant mixing. To assess these advantages, a high-precision differential pressure measurement system was employed over a Reynolds number range of 200-22,000, covering the laminar, transition, and turbulent flow regimes. The experimentally determined friction factors showed statistically similar trends between the "one pitch" and "bundle-averaged" axial segments, confirming fully developed flow in both regions. Empirical correlations for friction factor and differential pressure per unit length were then developed for each flow regime and validated by comparison with previous HCF and wire-wrapped fuel bundle studies. Results identified flow regime boundaries at approximately Re approximate to 1000 for laminar-to-transition and Re approximate to 8274 for transition-to-turbulent, highlighting distinctly different hydraulic behavior in the three regimes. The findings significantly broaden the limited experimental database on HCF rod bundles, providing new insights into regime-dependent pressure drop characteristics. By refining existing correlations and offering high-fidelity benchmark data, this work advances the development of more efficient and accurate reactor core designs that leverage HCF technology for enhanced thermal performance.

Molten Salt Accelerator-Driven Systems (MoSTADS) have been attracting a lot of research interest lately due to their unique characteristics and advantages, including reduced radiation damage of the fuel, and stable operation achieved through online fuel feeding process. Simulations of an experimental molten salt test facility being developed in the Thermal Hydraulic Research Laboratory (THRL) at Texas A&M &M University, were conducted using Monte Carlo radiation transport methods, to design and optimize selected components of the system. The system consists of a proton beam generated by an accelerator, impinging on a target to generate neutrons, which can be used induce fission reactions within a thorium fueled, high-temperature molten salt forced convection test loop. Parametric studies were performed to optimize several key components of the system including target material, proton beam energy, target thickness and location, and reflector thickness. Furthermore, in order to ensure the safe operation of the facility, parametric studies were also performed to identify the composition and thickness of the system shielding that would be needed to satisfy acceptable exposure limits.

Microreactors could play a crucial role in decarbonizing our energy portfolio. However, their development and implementation come with specific challenges, particularly regarding cost. Due to their compact size and the harsh operational environment, collecting real-time data on reactor operation can be challenging. Many probe designs are unable to withstand extreme conditions (e.g., temperature, radiation) in the reactor. In this context, using convolutional neural networks (CNNs) can pave the way for developing a nonintrusive approach that relies solely on ex-core sensors. A well-trained physics-informed CNN can reconstruct the distribution of a given physical quantity over a domain using only a few sensors, allowing us to reconstruct the desired field distribution even in a limited space or complex geometries where a large array of sensors is impractical. In this work, we present the initial steps toward developing a real-time tool for monitoring the thermal behavior of nuclear reactor pressure vessels. Based on an experimental setup, a computational model using the Multiphysics Object-Oriented Simulation Environment (moose) framework was built, where the Ray Tracing and Heat Conduction modules were used to evaluate the temperature distribution over a convex metal surface heated through radiative heat transfer. This metal surface represents a section of a heated nuclear reactor vessel wall. The model also accounts for solid mechanics physics through the moose Solid Mechanics module. In situ experimental data, acquired from a Texas A&M facility, were used to validate the computational model. Part of the data generated by the moose model was used to train the convolutional neural network to reconstruct the vessel wall's outer surface temperature. The CNN generalization was then compared against the experimental and computational data

This paper explores the intricate interplay of three-dimensional effects on the operational dynamics of nuclear reactors employing natural circulation (NC). A review of thermal-hydraulic phenomena (THP), with insights into three-dimensional THP and NC, as well as of their role in deterministic safety assessment has been performed. Moreover, some ongoing research directions relevant to NC reactors have been summarized, showing that they do not address the concerns highlighted in the present work. In this work, attention is directed towards reactors featuring a long chimney, also called riser, in which upward movement of hot fluid happens, together with a downflow with lower temperature in the surrounding downcomer. The study delves into the potential occurrence of buoyancy driven recirculation phenomena within the chimney and the consequential risk of cold fluid ingress into the core region. Such occurrences may precipitate in instabilities including the neutronic-thermal hydraulic feedback. In this work, we consider single phase flow including the presence of subcooled void and two-phase flow in the core region which are typical respectively of NC iPWRs and NC BWRs. Conceptually simplified RELAP5-3D nodalizations have been adopted, in which the chimney region has been divided into a peripheral annular part and a central cylindrical region. Recirculation in the chimney is affected by core power, which also determines NC flow inside the vessel. The performed study is preliminary considering that no experimental data is available, and the system code RELAP5-3D is used instead of a more powerful CFD code, perhaps more suited in case of single-phase conditions.

Medium-temperature heat pipes, operating in the 200-600 degrees C range, find widespread application in sectors such as nuclear microreactors, solar energy collectors, thermal energy storage, and space. Efficient, passive heat transfer devices, like heat pipes, are essential for power systems operating in this temperature range. Despite such a broad range, traditional working fluids for heat pipes in the medium-temperature regime frequently underperform, prompting the need for more research into these working fluids. Dowtherm A is attractive for its chemical compatibility with heat pipe materials, low toxicity, low flammability, and adequate thermal-hydraulic properties, things that cannot be said for most medium-temperature heat pipe working fluids. This experimental study investigates the performance of Dowtherm A as a medium-temperature heat pipe working fluid, using internal and external measurements to quantify the heat transport in the heat pipe. A 25.4 mm outer diameter, 316 stainless steel tube was used for the heat pipe testing. Ten wraps of 100 x 100 (100 openings per inch) 316 stainless steel screen mesh were used as the wick, with a sliding fit and no annular gap. A fill ratio of 103 % of the total wick void volume was used. An air jacket was attached to the condenser of the heat pipe for cooling. Internal and external temperature measurement was performed, utilizing optical fiber distributed temperature sensing and conventional thermocouples, respectively. All tests conducted were in the horizontal orientation. The test matrix consisted of three different cooling conditions, controlled by changing the flow rate of air in the jacket over the condenser, with multiple power levels for each cooling condition. It was found that the thermal resistance of the heat pipe is not influenced directly by the cooling flow rate but is instead linked to the operating temperature. A minimum thermal resistance of 0.58 degrees C/W was achieved at the highest operating temperature tested of 274 degrees C. This corresponds to a maximum effective thermal conductivity of 2300 W/m & sdot;K. This finding agrees with values from previous studies. Internal vapor temperature measurements determined the active condenser length, where vapor condenses-a useful tool in heat pipe design. The capillary limit, which governs power transport in heat pipes, was exceeded in all tests without dryout, suggesting Dowtherm A outperformed expectations. This finding questions the soundness of the commonly used theoretical capillary limit, as applied for organic fluids such as Dowtherm A. Collectively, these findings highlight Dowtherm A's viability for use in medium-temperature heat pipes, offering improved efficiency and operational safety in diverse energy systems.

Mixing in large enclosures and thermal stratification play critical roles in advanced reactor designs, including liquid metal-cooled and high-temperature gas reactors. Lessons from a recent international benchmark (IAEA, 2017), using system-level codes for Sodium-Cooled Fast Reactors (SFRs) highlight the need for improved models to accurately capture mixing and thermal stratification in the reactor hot pool upper plenum. These improvements are essential for predicting the propagation of stratification fronts and the effects on natural circulation and heat transfer between primary and intermediate loops. Current computational dynamics (CFD) codes, particularly those relying on Reynolds-averaged Navier-Stokes (RANS)-based turbulence models and the Simple Gradient-Diffusion Hypothesis (SGDH), underperform in simulating buoyancy-driven flows, leading to inaccurate predictions of stratified fronts. The NEAMS IRP Challenge Problem 3 (CP3) aims to develop multi-fidelity, multi-scale models for mixing and stratification in large enclosures. This includes models ranging from high-fidelity Large Eddy Simulations / Direct Numerical Simulations (DNS/LES) to system-level code models. High-resolution experiments and LES/DNS inform the development of these models, providing accurate and computationally affordable predictions. This paper provides an overview of ongoing experimental and modeling activities within CP3, showcasing advancements in understanding and predicting mixing and stratification in large enclosures for advanced reactor applications.

The helical-cruciform fuel (HCF) design features helically twisted rods with a four-lobed cross-section, increasing the surface-to-volume ratio compared to conventional cylindrical rods. This geometry enhances heat transfer and coolant mixing while reducing peak fuel temperatures. The self-supporting rod arrangement eliminates spacer grids, reducing flow obstruction and pressure losses. These characteristics enable higher reactor power density and lower operating temperatures in current and next-generation reactors. This study numerically investigates pressure drop and flow characteristics in a 9 x 9 HCF assembly using Reynolds-Averaged Navier-Stokes (RANS) simulations with the k-omega Shear Stress Transport (SST) turbulence model. Preliminary analyses of 3 x 3 to 11 x 11 assemblies demonstrated that the 9 x 9 configuration is the minimum bundle size required to accurately represent essential flow behavior in larger assemblies. Entrance length analysis at Re = 21,121 shows fully developed flow after one helical pitch. The CFD model is validated against experimental pressure drop data. Flow regime boundaries are estimated at Reynolds numbers of approximately 861 (laminar-to-transitional) and 9,755 (transitional-to-turbulent). A friction factor correlation covering Re = 119 to 21,958 is developed and compared with existing correlations. The flow characteristics at Re = 21,121 were analyzed within subchannels and intersubchannel gaps.

This experimental study investigates the effects of buoyancy on wake dynamics in buoyancy opposed-flow mixed convection by analyzing time-resolved particle image velocimetry data collected at an elevated pressure (3 MPa), which spans a range of Reynolds numbers (14 000 ≤ Re ≤ 28 500) and Richardson numbers (0.47 ≤ Ri ≤ 1.84). Changes in recirculation characteristics, turbulent kinetic energy (TKE) distribution, separation angle, and large-scale coherent structures are reported. Spectral proper orthogonal decomposition (SPOD) is applied to identify dominant flow structures and their spectral energy distribution across varying Ri. Results indicate that increasing buoyancy effects expands the recirculation zone, suggesting enhanced lateral mixing due to buoyancy-driven instabilities. The separation point shifts upstream with increased heating. Spanwise TKE distribution broadens with increasing Ri, highlighting a transition from shear-driven Kelvin–Helmholtz instability to buoyancy-driven Rayleigh–Taylor instability, fundamentally altering turbulence production. SPOD analysis reveals that in the unheated case, mode 1 energy is concentrated in a narrow frequency range, whereas heating redistributes spectral energy, broadening the bandwidth and stabilizing shear layer structures over a wider frequency range. Mode 2 captures lateral velocity fluctuations at the recirculation zone edges, with different frequencies corresponding to distinct shedding behaviors. The persistence of shear-layer mode shapes at higher Ri suggests an increase in coherent structure stability. These findings provide insight into the competition between opposing buoyancy and inertial forces in mixed convection flows, with implications for engineering applications such as thermal management in buoyancy-opposed configurations. Understanding the stabilization and redistribution of turbulent structures can aid in optimizing heat transfer and flow control strategies in high-temperature environments.

Randomly packed pebble-bed reactors are integral components in various engineering applications, in nuclear reactors where they offer inherent safety advantages through the use of tristructural isotropic coated fuel particles embedded in a graphite matrix. Predicting coolant flow and heat transfer within these packed beds presents significant challenges due to the complex, non-uniform arrangement of pebbles, resulting in intricate flow patterns and thermal fields. High-fidelity simulations like large Eddy simulation (LES) provide detailed insight but are computationally expensive, necessitating efficient alternatives for practical applications. This study introduces a machine learning-based approach for high-to-low flow field learning using deep convolutional encoder–decoder networks applied to randomly packed pebble-bed geometry. An end-to-end field-to-field regression framework is employed, utilizing a fully convolutional encoder–decoder architecture with DenseNet feature extraction. The model is trained on velocity fields derived from both coarse and fine mesh simulations across multiple Reynolds numbers. The proposed method significantly reduces computational cost while maintaining high accuracy in predicting detailed velocity flow fields. The model's performance is validated across different Reynolds numbers and flow configurations, demonstrating a strong ability to capture dominant flow structures and localized turbulence, especially near pebble surfaces. The results confirm that this deep learning model can effectively upscale coarse mesh flow fields to high-resolution outputs, offering a promising solution for efficient and accurate simulation of packed bed reactors in thermal-hydraulic applications. Furthermore, the model's robustness is validated through tests on different pebble bed configurations, ensuring its generalizability and potential for real-world applications.

This study investigates the startup behavior of sodium heat pipes, focusing on how different startup methods, the presence of non-condensable gases (NCGs), and flow instabilities near the mixing layer affect thermal performance and operational stability. Four startup methods were evaluated, ranging from slow, incremental power increases to rapid, one-step power applications. Thermal instabilities were observed to emerge at a critical power of 50.43 W, corresponding to an operating temperature of 340 °C. Slow startups initiated below this threshold enabled a gradual displacement of NCGs toward the condenser, resulting in a uniform temperature distribution and extended effective heat transfer lengths. At 200 W, the effective length exceeded 800 mm in slow startups, whereas rapid startups showed shorter lengths due to mixing at the vapor-NCG interface. At 1000 W, rapid startups exhibit significant portions of the heat pipe remaining below the sodium melting point of 97.8 °C, particularly near the condenser. This occurs due to incomplete displacement of NCGs during the initial phase of startup, leading to uneven temperature distributions and inactive regions. The abrupt vaporization of sodium causes unstable flow patterns that prevent the vapor from fully engaging the condenser region. Slow startups, by contrast, gradually transition the entire pipe into operation, minimizing inactive regions and maintaining a more uniform temperature profile. These results underscore the need to manage startup rates carefully, especially at higher power levels, to ensure complete activation of the heat pipe. The results validate a theoretical model treating the flow near the mixing layer as compressible in time and incompressible in space. This approach successfully modeled the interface dynamics and instability mechanisms caused by rapid interactions between sodium vapor and NCGs. The findings demonstrate that gradual power increases are shown to maximize thermal performance and operational stability. Future research should refine startup methodologies, develop strategies to mitigate instabilities, and improve the interaction between sodium vapor and NCGs for high-temperature applications. This study provides critical insights into optimizing sodium heat pipe performance in high-temperature applications, particularly for advanced nuclear reactors and other demanding thermal management systems.

GPU-based supercomputing enables a significant advancement in Computational Fluid Dynamics (CFD) capabilities for nuclear reactors. Pre-exascale GPU-based supercomputers such as ORNL’s Summit allow for the first time to perform full core CFD calculations with URANS and LES approaches. Key to this has been the development of NekRS, a novel GPU-oriented variant of Nek5000, an open-source spectral element code in development at Argonne National Laboratory. NekRS delivers peak performance for key kernels on the GPUs and good scaling performance even on CPU architectures. Recent performance measurements showed that NekRS, when running on GPUs, outperforms the CPUs by 40x. This manuscript focuses on how these calculations and novel high-resolution experimental data improve the fidelity of traditional approaches such as systems analysis codes, subchannel codes, and Reynolds-Averaged Navier-Stokes. Supercomputing simulation alone cannot impact design and safety analysis without a suitable multiscale framework. An ongoing IRP project led by Penn State is pursuing novel methods for scale bridging. We discuss details of the project, and, in particular, we review some recent progress centered on four industry-driven challenge problems.

System code modeling is the primary tool used for design and licensing and operator training of advanced reactor technologies. While system codes have been well validated for existing reactor technologies, caution should be taken with respect to system code modeling capabilities in advanced reactors which have significant phenomenological differences in their designs. Within the scope of advanced reactors, NuScale Power is the first vendor to have their reactor design approved by the U.S. Nuclear Regulatory Commission. NuScale has developed a plant simulator which models a 12-unit NuScale plant capable of running operational or accident transients of each of the units. In an effort to assess the capabilities of the TRACE system code and perform a code benchmark, a NuScale-like reactor model was developed based on the Design Certificate Application. A Station-Blackout (SBO) accident scenario was modelled and compared with data obtained from the NuScale simulator. The SBO transient was run for a total of 8000 s and characteristics of the primary and secondary side systems were compared. Despite some differences attributed to the realistic approach of the simulator, the study found that the primary and secondary system characteristics over the course of the SBO transient showed reasonable agreement for trends and values observed in the NuScale simulator data and the TRACE model.

An in-depth understanding of the flow physics in packed beds is critical for developing simulation tools for pebble bed reactors. Advances in computing power have now made the full-core pebble-resolved computational fluid dynamics simulation of these systems possible. This work presents validation of the velocity and pressure predictions made by the spectral element code NekRS followed by a study of the turbulent kinetic energy and turbulent heat flux budgets. Two cases with corresponding experiments are considered: a bed of 67 pebbles with Re = 1460 and a bed of 789 pebbles with 324 < Re < 1024. Velocity and pressure drop comparisons are performed with the two cases, respectively. Good agreement is found between the experiments and their respective NekRS simulations.The 67-pebble case was then used to perform a direct numerical simulation to extract the turbulent kinetic energy and turbulent heat flux budget terms. Analysis of the turbulent kinetic energy production revealed large areas of negative production near the bottom surfaces of the pebbles. Further investigation revealed a trend between the average amount of negative turbulent kinetic energy production and the local porosity. These results continue to suggest that inertial effects play a large role in differentiating near-wall flow from bed-interior flow.