Session: VVUQ for Fluid Dynamics and Heat Transfer 2

Paper Number: 151929

151929 - Experimental Analysis and Model Validation of Flow-Induced Vibrations in Helical Coil Steam Generators for Small Modular Reactors 

Abstract: 

Flow-Induced Vibrations (FIVs) present a significant and ongoing challenge within the nuclear engineering community due to their profound impact on the reliability and safety of nuclear reactor components. As the adoption of Small Modular Reactors (SMRs) increases, addressing FIVs becomes even more critical. SMRs often employ advanced heat exchangers to enhance heat transfer efficiencies while maintaining a compact design to limit overall footprint. One such advanced design is the Helical Coil Steam Generator (HCSG), which incorporates a large number of small-diameter tubes wound into a coil structure subjected to cross-flow conditions. These heat exchangers are increasingly featuring complex geometries, such as wrapping in both clockwise and counter-clockwise orientations, resulting in a constant axial pitch but variable lateral pitch. The complexity of these geometries, coupled with the structural interactions arising from vibrations, leads to a multitude of intricate flow phenomena, including turbulent buffeting and vortex shedding. Understanding the fluid-structure interactions (FSI) in these systems is essential for ensuring the safety and reliability of nuclear reactors. To address this challenge, we have conducted an experimental study utilizing non-intrusive measurement techniques to capture simultaneous flow-field and structural vibration data. A 5×5 cantilevered bundle section was constructed, featuring rods wrapped in opposite directions to investigate the coupling between rod motion and fluid-structure development. Particle Image Velocimetry (PIV) was employed to capture full-field velocity measurements, while the same image data were processed using an in-house developed code to track rod motion over time. First- and second-order statistical analyses were performed on the PIV results to gain physical insights into the turbulent buffeting and vortex-shedding phenomena. To further understand the complex flow structures and their interactions with the structural components, we applied Proper Orthogonal Decomposition (POD) techniques. The POD analysis allowed us to identify the dominant flow modes and to generate reduced-order datasets. These reduced-order datasets are crucial for the development and validation of reduced-order models (ROMs) in computational fluid dynamics (CFD). The ROMs are designed to accurately replicate the essential features of the flow and structural dynamics with significantly reduced computational cost compared to full-scale CFD simulations. This reduction in computational resources is vital for conducting extensive parametric studies and uncertainty quantification, which are necessary for the design and analysis of safe and efficient nuclear reactor components. In the context of Verification, Validation, and Uncertainty Quantification (VVUQ), our study contributes significantly by providing high-fidelity experimental data for the validation of computational models and uncertainty quantification of the model. The simultaneous measurement of flow fields and structural vibrations offers a comprehensive dataset that can be used to verify the accuracy of numerical simulations and to quantify uncertainties associated with model predictions. By comparing the reduced-order models against the experimental data, we can assess the models' predictive capabilities and identify areas where improvements are needed. Moreover, the use of non-intrusive measurement techniques minimizes experimental uncertainties and ensures that the data collected are representative of the actual physical phenomena without being influenced by the measurement process itself. This aspect is critical for achieving reliable validation and uncertainty quantification. Our research also explores the impact of geometric complexity on FIVs and the associated uncertainties in modeling such systems. By systematically studying the effects of variable lateral pitch and opposite wrapping directions, we aim to understand how these design parameters influence the flow-induced forces and vibrations. This knowledge is essential for developing robust design guidelines and for performing uncertainty quantification in the design of advanced heat exchangers. In conclusion, this work advances the understanding of fluid-structure interactions in complex geometry relevant to SMRs and contributes valuable data for the verification and validation of computational models. The methodologies and findings from this study are directly applicable to the VVUQ community, offering insights into experimental techniques, data analysis methods, and model development strategies that can enhance the reliability and safety of nuclear reactor designs.

Presenting Author: Joseph Seo Texas A&M University

Presenting Author Biography: Dr. Joseph Seo is a Senior Research Engineer at Texas A&M University, where he also completed his Ph.D. in Nuclear Engineering. Prior to his doctoral studies, he obtained an M.S. and a B.S. in Mechanical and Electrical Control Engineering from Handong University in South Korea. Dr. Seo's research expertise lies in the experimental domain of nuclear reactor thermal-hydraulics, with a particular focus on flow visualization, advanced measurement techniques, and computational analysis. Currently, his work is centered on pioneering instrumentation (sensors) for temperature measurement and visualization techniques tailored to nuclear engineering research applications. Furthermore, Dr. Seo is exploring thermal instrumentations for advanced reactors, including heat pipes, molten salt loops, and high-temperature thermal storage systems. With his vast experimental expertise, he plays a pivotal role in leading design, development, and testing endeavors at The Center for Advanced Small Modular and Micro Nuclear Reactors (CASMR).

Authors:

Noah Sutton Texas A&M University
Joseph Seo Texas A&M University
Hansol Kim Texas A&M University
Yassin Hassan Texas A&M University