In the evolving landscape of nuclear energy, ensuring the safety and efficiency of nuclear reactors remains paramount, particularly with the increasing demands for energy and a concurrent rise in global temperatures. A significant aspect of nuclear safety involves maintaining the integrity of the fuel rods, which are susceptible to Turbulence Induced Vibrations (TIV) resulting from axial flows of the coolant liquid. TIV can instigate severe repercussions including structural damage such as fatigue, wear, and stress corrosion cracking, posing substantial threats to reactor safety. Despite the historical attention this phenomenon has garnered since the 1950s, conventional semi-empirical methods offer limited predictive accuracy and do not facilitate extrapolations for multi-rod scenarios effectively.  Recent developments have turned to Fluid-Structure Interaction (FSI) simulations as a powerful tool to study fuel rods’ behavior under TIV effects, capitalizing on the increase of computational power available today. While Direct Numerical Simulation (DNS) and Large Eddy Simulation (LES) offer more accurate predictions, their computational demands make them unsuitable for complex FSI simulations. This has led to a preference for Unsteady Reynolds-Averaged Navier-Stokes (URANS) simulations, despite them underpredicting the displacement amplitudes of the vibrations.  Evolving from this shortfall, the current study directs its focus on a recently developed Anisotropic Pressure Fluctuation Model (AniPFM). This model generates a synthetic velocity fluctuations field, which is used to solve for the pressure fluctuations. The use of this model together with URANS poses as a possible way to inexpensively simulate the excitation mechanisms of TIV of fuel rods. While previous research has highlighted the potential of this model, it is important to note the considerable level of uncertainty still associated with it. Additionally, there are parameters, definitions and constants whose impacts on the model are not yet fully understood or even explored. This calls for a comprehensive research to fine-tune the model, optimize its performance and further validate it. This is precisely the goal of this study, carried out through the analysis of two pure flow and two FSI cases. Hypotheses were formulated and tested in pure flow scenarios before being further validated in FSI cases. Key advancements were made by optimizing the time correlation method used on the generated velocity fluctuations, which significantly reduced the model’s uncertainty. This method was then calibrated using DNS data of turbulent channel flow. Further calibration was undertaken, this time in the parameters part of the modelling of the turbulent kinetic energy spectrum, to address the overprediction of pressure fluctuations near the wall observed in the baseline model. Moreover, the turbulent annular flow was used as the second flow only case, providing more complexity compared to channel flow, by adding curvature, as well as another opportunity to test the hypothesis made.  Furthermore, the hypotheses underwent additional validation via FSI simulations, through a brass beam in turbulent axial flow, showing a substantial decrease in the average difference from the experimental data to 19% from a previous 68%, over the range of inflow velocities considered. Notably, the calibrated AniPFM surpassed LES in accuracy while requiring fewer computational resources. The results obtained are promising, but further validation is needed. This thesis also outlines and lays the foundation for further validation work, through the setup and initial simulations of a flexible cantilever rod in turbulent axial water flow.

Due to the complicated design of nuclear reactors, many complex phenomena can cause points of failure. In the case of nuclear fuel rods, the axial flow that cools the rods can induce vibrations due to the turbulent nature of the flow. Turbulence-induced pressure fluctuations create small but significant vibration amplitudes, which in turn can cause structural effects such as material fatigue and fretting wear. For this reason, turbulence-induced vibrations have been the subject of many studies, with a recent focus on the development of computational methods, so called Fluid-Structure Interaction (FSI) simulations. While scale-resolving methods can predict pressure fluctuations directly, they are typically too expensive for industrial nuclear applications in FSI. Instead, an Unsteady Reynolds-Averaged Navier-Stokes (URANS) approach coupled with a pressure fluctuation model can be used, to reduce the computational cost. While showing promising results, this approach generally underestimated the vibration amplitudes. For this reason, an improved pressure fluctuation model, called AniPFM (Anisotropic Pressure Fluctuation Model), was developed. It models velocity fluctuations based on existing methods for synthetic turbulence. In turn, these velocity fluctuations are used to obtain the pressure fluctuations. AniPFM improves the prediction of the pressure fluctuations in three ways. First, whereas previous iterations could only represent the turbulence as isotropic, in the current model anisotropic Reynolds stresses can be embodied. Second, only the scales that can be resolved on the grid are represented by the velocity fluctuations, causing a more realistic distribution of energy along the different wavelengths. Finally, time correlation is introduced based on the transport and decorrelation of turbulence. From simulating decaying homogeneous isotropic turbulence, it was found that this time correlation method gives a significant improvement over previous methods. From turbulent channel flow simulations, the results show that for anisotropic turbulence, the pressure fluctuations are overestimated, but they are still within a reasonable range of 10% compared to high-resolution data. AniPFM doubles the cost of simulation, compared to a URANS simulation. Even though that is a steep increase, the cost is still much lower than scale-resolving methods. Finally, the fluid-structure interaction of a brass beam in turbulent water is simulated, which showed the ability of the AniPFM to predict turbulence-induced vibrations. The AniPFM showed errors w.r.t. the replicated experiment that were in a similar range as LES calculations, while using less computational resources. The AniPFM simulations gave an error range of 15-60% w.r.t. experimental data over the full range of simulated flow velocities, whereas a previously used pressure fluctuation model underestimated the RMS amplitude by a factor of six. While further validation is ongoing, the AniPFM has demonstrated its potential for cheaper simulations of turbulence-induced vibrations in industrial nuclear applications.

The advent of global warming has brought an increased interest in non-conventional sources of energy, one of which is nuclear energy. Threatening the almost year-round functioning of nuclear power plants are Flow-Induced Vibrations (FIV). One such mechanism, Vortex-Induced Vibration (VIV), holds importance in areas of cross flow in nuclear power plants. To make fail-safe designs, computational analysis in the domain of Fluid Structure Interactions (FSI) has been increasing over the past two decades. The thesis work aims to add to the body of knowledge by making predictions for an in-line two-cylinder configuration, set up as part of a benchmark proposed by the Organization for Economic Co-operation and Development (OECD), using the commercial code Simcenter STARCCM+ (v2020.3.1). The main objective of this study is to test the efficacy of the URANS framework in predicting VIV which is strongly correlated with the objective of the OECD to propose recommendations for the Best Practice Guidelines. To do so, it is desired to shortlist the most appropriate turbulence model for the final application and point out gaps in the prediction of the same. The thesis work is thus carried out in three phases: code validation, turbulence model selection and final application. Key results from this study reveal the ‘Standard K-Epsilon Low Re: Cubic’ model to be the most apt for the final application. Furthermore, gaps are also identified in the application of URANS to predict VIV resonance conditions, the primary of which is the overprediction of the vortex shedding frequency.