Flow-induced vibrations (FIV) in tube bundles subjected to cross-flow pose significant risks to the safety and performance of nuclear reactor components. These vibrations, driven by mechanisms such as vortex shedding, turbulence fluctuations, and fluid-elastic instabilities, can lead to structural fatigue and failure. Accurately predicting FIV remains a challenge due to the complex interaction between fluid dynamics and structural response. This study investigates the effectiveness of hybrid turbulence models within commercial Computational Fluid Dynamics (CFD) tools to improve the accuracy and computational efficiency of FIV simulations.

Hybrid turbulence models, including Scale-Adaptive Simulation (SAS) and Delayed Detached
Eddy Simulation (DDES), were explored for their ability to balance computational efficiency with the accuracy required for FIV predictions. Simulations were conducted in ANSYS Fluent and STAR-CCM+ across various mesh configurations and flow conditions. The results indicate that DDES, particularly with fine polyhedral meshes and wall y+ < 1, provides improved predictions of flow-induced forces and vibrations. ANSYS Fluent exhibited greater robustness and reliability in this study, particularly for strongly coupled FSI problems in FIV simulations.

This research contributes to the ongoing efforts in refining FIV simulation methodologies by proposing a standardized workflow and offering insights into the applicability of hybrid turbulence modeling. The findings enhance the understanding of FIV phenomena and support the development of improved numerical approaches for the safer design of nuclear reactor components.