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AbstractReflood thermal hydraulics remains a difficult and complex subject, and understanding the physical phenomena that occur during a reflood transient is important to nuclear safety. The Organisation for Economic Co-operation and Development/Nuclear Energy Agency (OECD/NEA) Rod Bundle Heat Transfer (RBHT) project was designed to provide unique experimental data for code assessment and model development. Participants, which came from 21 international organizations, used analysis codes including APROS, ATHLET, CATHARE, CTF, MARS, RELAP5, TRACE, and SPACE to simulate the tests performed in the RBHT facility.The experimental campaign carried out within the OECD/NEA RBHT project produced data for a total of 16 reflood tests conducted in two test series. An “open” test series consisted of 11 experiments, and a “blind” test series consisted of 5 experiments. In the blind tests, only the initial and boundary conditions were provided to participants prior to simulation of those experiments. Reflood rates ranged from 0.5 to 15 cm/s, thus producing data applicable to dispersed flow film boiling and inverted annular flow film boiling. Inlet subcooling ranged from 2.8 to 80 K. Tests with variable reflood rates and oscillatory reflood rates were included in the test matrix. This paper describes the project and presents a summary of major experimental and analytical findings. [ABSTRACT FROM AUTHOR]

The accurate prediction of the fluid flow mass and the heat transfer process as well as the system response during reflood transients has long been a critical and challenging issue for reactor system safety analyses. Accurate characterization of the flow and energy transport can also significantly facilitate the various system/component design and optimization tasks. In the current study based on the U.S. Nuclear Regulatory Commission/Pennsylvania State University Rod Bundle Heat Transfer (RBHT) reflood experimental data, a comprehensive uncertainty analysis framework is developed using DAKOTA. The developed framework is used to perform an in-depth reflood model validation and verification for the subchannel analysis code COBRA-TF. In the meantime, the artificial intelligence (AI)–based machine learning (ML) model for rod cladding temperature prediction during reflood is also developed and evaluated using the current framework. Key input parametric effects for reflood thermal-hydraulic prediction include the system pressure, inlet liquid temperature/enthalpy, inlet mass flow rate, and average bundle power input. The figure of merit under consideration is the peak cladding temperature variations. It is found in the current study that, while further model improvement is needed, COBRA-TF can predict the correct parametric trends when compared with the RBHT data. On the other hand, it is challenging for the pure AI-based ML models to correctly reflect the parametric trends. Suggestions for future ML model development are provided in the end. [ABSTRACT FROM AUTHOR]

The U.S. Nuclear Regulatory Commission has been conducting thermal-hydraulic research using the Rod Bundle Heat Transfer (RBHT) facility at the Pennsylvania State University since 2001. The facility has been used for five individual test programs: forced reflood, steam cooling, mixture level swell, dispersed droplet injection, and oscillatory reflood test series. While rod bundle thermal hydraulics has been extensively studied in the past, the RBHT data have provided new insights into rod bundle phenomena especially on the effects of spacer grids. This paper provides a summary of the RBHT test program and discusses some of the major findings from this research with the emphasis on reflood thermal hydraulics and the effect of spacer grids. Of particular interest are data that enable model and correlation development. Recent efforts have focused on the evaluation of RBHT data and development of improved models and correlations suitable for systems thermal-hydraulic codes such as TRACE and RELAP. Because of detailed instrumentation on and about spacer grids, RBHT data have enabled improved models for convective heat transfer enhancement and droplet breakup. New correlations for the inverted annular and the inverted slug film boiling regimes have also been developed as an initial step toward an improved model for dispersed droplet film boiling. [ABSTRACT FROM AUTHOR]

Film boiling is an important phenomenon in the evaluation of an emergency core cooling system following a hypothetical loss of coolant accident in a nuclear reactor. This study investigates the effects of liquid subcooling, surface oxidation, and surface materials on the minimum film-boiling temperature . Quenching experiments were performed using stainless steel and zirconium (Zr) test samples. The samples were heated to a temperature well above then plunged vertically in various degrees of liquid subcooling pools. A visualization study using a high-speed camera was conducted to capture the quenching behavior. Additionally, surface characterization analyses including X-ray diffraction, scanning electron microscopy, and energy dispersive X-ray spectroscopy were performed to quantify the surface conditions. Results indicate that liquid subcooling has a strong influence on . The visualization study shows a very thin vapor formation around the test sample for higher subcooling pools which explains the enhancement in the heat transfer. It is observed from the surface characterization analyses that the variations in the surface condition of the stainless steel and Zr causes the vapor bubbles to depart differently in the nucleate boiling regime. Furthermore, the effect of surface oxidation is clearly noticeable in the Zr test sample compared to the stainless steel test sample due to the oxidation kinematic of each substrate material. It is found that the substrate thermophysical properties have a significant impact on . Comparing the bare substrates shows that for the same degrees of liquid subcooling pool, the value of for the Zr sample is ∼30°C to 60°C higher compared to the stainless steel sample. Moreover, increasing the degrees of liquid subcooling contributes to a significant increase in that varies between ∼50°C and 70°C for both samples. [ABSTRACT FROM AUTHOR]