This study develops a physics-informed reduced-order framework that combines proper orthogonal decomposition (POD) with a physics-informed neural network (PINN) to reconstruct pressure and velocity fields in an axial-flow main coolant pump (MCP) of lead-cooled fast reactor (LFR). The model is evaluated using 25 steady-state computational fluid dynamics (CFD) cases covering rotational speeds of 375–675 r/min and volume flow rates of 0.05–0.48 m3/s, where 20 cases were used for training and five for testing. It is found that the proposed physics-informed training model reduces the testing loss from 2.25 to 1.82, corresponding to a 19 % improvement compared with a purely data-driven model. The relative errors for the two dominant velocity components and pressure are 10.5 % and 8.3 % respectively. The proposed method reconstructed a flow field within 8 ms, substantially less than the minutes or longer typically required by conventional numerical simulations. The model’s capability for rapid reconstruction of flow-fields under different operating conditions can accelerate further analysis of hydraulic performance, structural safety, and corrosion which is a velocity-related factor that affects the design of pumps with lead based coolants. Such responsiveness also reduces the dependence of time-consuming, conventional computational fluid dynamics methods during the design workflow that requires iterative flow-field solution, resulting in acceptable computational costs when applying optimization algorithms. These results demonstrate the proposed framework is a practical and efficient screening tool for rapid reconstruction of complex flow field and design space exploration of LFR- MCPs.

During severe accidents in a nuclear power plant, the core melt (corium) may relocate to the lower head of the reactor pressure vessel (RPV). To prevent further progression of corium and massive release of radioactive materials out of RPV failure, the in-vessel melt retention (IVR) has been proposed in some advanced reactor designs, where a melt pool will be formed in the lower head and cooled by external flooding. Accurate estimation of the thermal loading over the lower head plays an essential role in the qualification of the IVR strategy. For this purpose, the present study investigates the temperature profile and heat transfer characteristics of a homogeneous melt pool and naturally stratified melt pools in the SAMPO test facility. Thermal oil and molten binary nitrates are employed as simulation materials of the upper and lower layer of the stratified melt pools, respectively. The results show that the maximum temperature and sidewall heat flux of the homogeneous melt pool may be overestimated. In addition, the stratified morphology of the melt pool also affects the crust formation: the sidewall crust range is larger in a stratified melt pool. A thinner upper layer yields a higher heat flux peak in the stratified melt pool.

This study develops a continuous-parameter creep model for reactor pressure vessel (RPV) steel SA533B1 based on the Liu–Murakami continuum damage mechanics (CDM) framework to overcome the limitations of conventional creep models in capturing temperature-dependent creep behavior and tertiary creep over broad temperature ranges. Globally continuous functions are established for the material constants, allowing the model parameters to vary continuously over the severe-accident temperature range of 900–1623 K. This formulation avoids unphysical parameter discontinuities and rigid regime-switching in transient thermo-mechanical simulations. The model was calibrated using INEL and JAEA datasets and validated against OECD lower head failure (OLHF) tests. Compared with conventional creep models, the proposed model more accurately reproduces the transient displacement history and spatial damage localization up to rupture, improving the prediction of RPV lower-head failure under severe accident conditions of light water reactors.

A simplified neutron-kinetics model for recriticality calculations has been developed and implemented within the severe accident code MELCOR. The model partitions the core into active and inactive regions and determines neutron flux using factorization with adiabatic and prompt-jump approximations. Homogenization of pre-calculated core cell multiplication factors, together with Doppler and xenon reactivity defects calculated by perturbation theory, avoids explicit treatment of cross-sections. This approach allows recriticality analysis to be performed seamlessly within MELCOR at standard time-steps and computational cost. Comparisons with SARA project simulations show reasonable agreement. Integrated with MELCOR, the model extends its capabilities to predict reactivity, recriticality timing, fission power, fuel temperatures, and xenon transients. The model was applied to station blackout scenarios in a Nordic BWR with varying low-pressure safety injection timing and two decay-heat curves. Simulations suggest that the time window for recriticality may be substantial if the core periphery remains intact and coolant flow through a breached vessel is limited. In cases where recriticality occurred, fission power evolution was irregular, and even relatively low fission power accelerated containment heat-up and pressurization. These results demonstrate that the simplified model provides an efficient tool for investigating recriticality phenomena, their impact on severe accident progression, and the effectiveness of mitigation strategies under uncertainty and sensitivity analyses.

The characteristics of interactions between melt and below-vessel structures are of great importance to the accident progression in boiling water reactors. This paper presents an experimental investigation on the influence of below-vessel structures on melt spreading behavior. The study was conducted in the new COSIN facility, focusing on melt spreading over a radiation shield penetrated by structures. A scaled-down (1/6) configuration was employed, using zinc as a simulant for corium, with prototypical structures represented by an array of cylindrical rods. Two key tests were performed: one on a plain surface (S1) and one with structures (S2). The results demonstrate that structures fundamentally affect the spreading dynamics. The plain surface case (S1) led to non-uniform, directionally accelerated spreading, while the presence of structures (S2) resulted in a crossshaped, channeled flow pattern. This directional effect restricted the overall spreading length (28% reduction in average melt layer thickness of S2) but promoted extensive lateral spreading to the plate periphery, leading to a significantly higher mass fraction (50% in S2) bypassing the plate edge. Consequently, melt poses a markedly higher possibility of breaching the side walls of radiation plate. Furthermore, the final melt layer morphology differed substantially, with S2 exhibiting localized melt accumulation and greater average thickness (15% increase) within the structural zone, contrasting with the radially increasing profile in S1. These findings underscore the critical role of below-vessel structures in determining melt distribution and the resultant threats to containment integrity.

The influence of particle surface wettability on melt infiltration in porous media is investigated by combining both experiments and simulations. Melt infiltration experiments are conducted by introducing molten tin-bismuth eutectic alloy (Sn-Bi) into preheated particle beds composed of 1.5 mm spherical particles of either copper (Cu) or tin-coated Cu (Sn-coated Cu). After solidification, the distribution of Sn-Bi within the particle beds is analyzed using scanning electron microscopy (SEM). To complement the experimental findings, three-dimensional (3D) pore-scale numerical simulations are carried out, allowing a direct comparison between the simulated melt distribution and SEM observations. The SEM analysis of the composite of the particle bed infiltrated by Sn-Bi reveals that at temperatures below 150 °C, the Cu particles exhibit poor wettability by Sn-Bi melt, characterized by a local contact angle of around 145°, whereas Sn-coated particles demonstrate enhanced wettability with a contact angle of approximately 65°. These observations are also supported by the 3D simulations, which show that higher wettability leads to smoother melt fronts and more pervasive infiltration, while lower wettability results in restricted melt infiltration. The findings highlight the critical role of particle surface wettability in governing melt infiltration, which is crucial for understanding the melt relocation behaviors in safety-critical systems and optimizing materials processing.

The vibration responses and bubble behaviors are simultaneously measured when subcooled pool boiling occurs on a vertical heated surface. The vibration velocity of the heated surface is collected with a non-contact laser system while the bubble behaviors are captured by a high-speed camera. Experiments with different heat flux and subcooling are carried out, and the vibration responses correlated with the bubble behaviors are analyzed. The results show that with the increase of heat flux, more nucleation sites on the heated surface are activated, and bubble interactions occur. Four typical modes are extracted from the experimental data with isolated bubbles from a single site, continuous bubbles from a single site, bubbles from two sites and bubbles from multiple sites. The main excitation mechanism for all the cases is the pressure fluctuations caused by the rapid growth of the bubble at the initial stage, and other bubble behaviors such as departure, collapse and bubble interactions show insignificant influence. Moreover, the vibration responses in time and frequency domain are strongly related to the temperature distribution before bubble initiation and the position of the nucleation site for isolated boiling bubbles. The generation behaviors of the bubbles also affect the vibration responses especially in frequency domain.

The stratified molten pool, consisting of an upper metal layer and a lower oxide layer, may form in the lower head of the reactor pressure vessels (RPV) during severe accidents of a pressurized water reactor (PWR) with in-vessel melt retention (IVR) strategy. It is therefore of paramount importance to quantify the thermal load distribution of the stratified structure on the RPV lower head. Motivated by such interest, the test facility SAMPO (StrAtified Molten Pool) is developed at CNPE to investigate the convection and heat transfer in stratified pools in a slice of semispherical vessel with the inner diameter in 1100 mm. In the present study two naturally stratified material pairs, i.e. water/thermal oil and nitrate salt (50 %NaNO3-50 %KNO3)/thermal oil, are used as the simulant materials of two types of stratified molten pool denoted by W-O and S-O, respectively. The upper layer has a free surface and the lower layer has an isothermal boundary due to the intensive cooling of water flowing through the external channel. The test results indicate that the profiles of central temperature and heat flux in the lower layers of molten pools are similar to those of a homogenous molten pool with a radiation upper boundary condition. The focusing effect is observed only in the S-O pool of nitrate salt/thermal oil, and the peak heat flux is strongly affected by heating power of the lower layer, thickness of the upper layer and the interlayer crust next the sidewall.

In the context of severe nuclear accidents, the migration of corium into the reactor pressure vessel (RPV) poses significant hazards, prompting the proposal of the in-vessel melt retention (IVR) strategy, particularly the external reactor vessel cooling (ERVC) approach. Evaluating the accuracy of turbulence models within the melt pool is crucial for assessing the feasibility of IVR. However, previous studies have yet to reach a consensus about the most suitable model due to the lack of data comparison. We aim to conduct a comprehensive comparative analysis of turbulence models to evaluate their performance across a range of Rayleigh numbers, particularly under conditions relevant to IVR scenarios. Therefore, this study employs six commonly used turbulence models in computational fluid dynamics (CFD) software, ANSYS Fluent, to simulate three natural convection experiments (Kulacki-Goldstein, BALI, and LIVE-3D). The results demonstrate that the choice of turbulence model significantly impacts the accuracy of temperature and heat flux predictions within the melt pool. Although the relative temperature deviation is less than 0.1% in all the simulations of the Kulacki-Goldstein experiment, the differences among turbulence models become increasingly pronounced with rising Rayleigh numbers. Among the models tested, wall-modeled large eddy simulation (WMLES) proved the most reliable for complex geometries and high Rayleigh numbers, while the realizable k-epsilon and generalized k-omega (GEKO) models also showed consistent performance. However, the Reynolds stress model (RSM)-baseline (BSL) and detached eddy simulation (DES) models exhibited notable limitations, particularly in scenarios involving solidification and melting. These findings provide valuable guidance for selecting appropriate turbulence models in IVR-related natural convection simulations and highlight the need for further refinement to improve model accuracy across varying melt pool conditions.

The MELCOR code as a severe accident simulation tool does not have the capability to capture the quench process of a debris bed which may form in the wet cavity during a severe accident of light water reactors (LWRs). Although the coupled MELCOR/COCOMO simulation could overcome the limitation (Chen et al., 2022), the calculation time was explosively escalated due to mechanistic modeling of debris bed thermal-hydraulics in COCOMO. To suppress the computational cost, a surrogate model (SM) was developed in our previous study (Wang et al., 2023), and its coupling with MELCOR could realize a quick estimation of the quench process of one-dimensional debris beds. The present study is an extension of the previous work, aiming at the development of a new surrogate model for the quench process of two-dimensional conical debris beds. The new surrogate model (SM) was based on artificial neural networks (ANNs) and trained by the database from COCOMO calculations of various conical debris beds quenched in the reactor cavity of a Nordic boiling water reactor (BWR). The MELCOR was then coupled with the new SM to simulate a postulated station blackout (SBO) scenario in the BWR. The results show that the coupled MELCOR/SM simulation could provide similar ex-vessel debris bed quench period and containment pressure/temperature trends as the coupled MELCOR/COCOMO. Compared with the MELCOR standalone calculation, the coupled calculations predicted earlier points of time for water pool saturation and containment venting, since the heat transfer from conical debris bed to water pool is faster in the coupled simulations.