Numerical Study of Turbulence Induced Vibrations Using Synthetic Fluctuation Field Modeling in Nuclear Reactor Applications

Abstract

The nuclear technology is changing at a rapid pace driven by the quest for more powerful and safer nuclear power plants, as a consequence several structural components in a reactor are becoming larger and slender while working fluids have higher densities and velocities. These changes can often alter the dynamics of the interaction between the coolant and the structural components and cause Flow Induced Vibrations (FIV) to become more prominent. As analytical methods are often insufficient to predict FIV in complex geometries, numerical approaches are commonly used to predict such phenomena.
Of all the possible modes of excitation in a nuclear reactor, simulating Turbulence Induced Vibrations (TIV) is a particularly challenging problem due to the wide range of scales involves, and is the main focus of this thesis work. Ideally high fidelity fluid solvers using DNS or LES can be used to resolve all the scales involved, but such methods are computationally expensive for complex domains with high Reynolds numbers. In this work, an alternative method to using high fidelity solvers is presented, which involves synthetically modeling the turbulent fluctuations using the known turbulence parameters from U-RANS simulations. These fluctuation fields are then superimposed on top of the average fields and act as the required excitement at the fluid structure interface. The numerical framework in which this method is implemented is first validated with known benchmark cases and it is found that the solver produces accurate results which are in good agreement with the reference data. The capabilities of the synthetic fluctuation modeling in simulating TIV are then assessed by performing simulations of a configuration adopted from an experimental set-up. It is observed that this model is able to reproduce the dynamics of the vibrations observed in the experiments while classical U-RANS model fails to predict physical oscillations.