Pitch and Pattern Effects On Streamwise Fluidelastic Instability in Tube Arrays

Fluidelastic instability (FEI) is well known to be a critical flow-induced vibration concern for the integrity of the tubes in nuclear steam generators. Traditionally, this has been assumed to occur in the direction transverse to the direction of flow but the tube failures at San Onofre Nuclear Generating Station (SONGS) in Los Angeles proved that this assumption is not generally valid. A simple tube-in-channel theoretical model was previously developed to predict streamwise as well as transverse FEI in a parallel triangular tube array. This predicted that this array geometry was particularly sensitive to streamwise FEI for high mass-damping parameters and small pitch ratios, the conditions in which the SONGS failures occurred. The advantage of this simple modelling approach is that no new empirical data are required for parametric studies of the effects of tube pattern and pitch ratio on FEI. The tube-in-channel model has been extended to in-line square, normal triangular and rotated square tube arrays and the stability of these geometric patterns are analyzed for the effects of varying pitch ratio and the mass-damping parameter. The results are compared with the available experimental data and conclusions are drawn regarding the relative vulnerability of these different tube array geometries to streamwise FEI.

Numerical Prediction of the Phase Difference in Tube Bundles Experiencing Streamwise Fluidelastic Instability

Recent experimental investigations have shown that tube arrays can become unstable in the streamwise direction. This is contrary to the long-held notion that fluidelastic instability is only a concern in the direction transverse to the flow. The possibility of streamwise fluidelastic instability (FEI) as a potential threat to the integrity of tube bundles was confirmed by the recent failures of newly installed replacement steam generators. A number of investigations were conducted to uncover the nature of this mechanism. A theoretical framework was developed by Hassan and Weaver [1] to model streamwise fluidelastic instability in a bundle of flexible tubes. The model utilized a simple time lag expression for the flow channel area perturbation. The current work aims at developing a numerical model to precisely predict the flow perturbation characteristics in a tube bundle due to streamwise tube motion. Flow simulations were carried out for single phase fluid flow in a parallel triangle tube bundle array with 1.2, 1.5 and 1.7 pitch to diameter ratios. The numerical model was benchmarked against numerical and experimental results available in the FEI literature. Simulations were carried out for a range of reduced flow velocities. The model results showed that the upstream flow perturbation magnitude and phase are different from those obtained in the downstream of the moving tube. The obtained flow perturbation characteristics were implemented in the Hassan and Weaver [1] model and the streamwise FEI threshold was predicted.

Implementation of Machine Learning Algorithms for Prediction of Fluidelastic Instability in Tube Arrays

Fluidelastic instability (FEI) in tube arrays has been studied extensively experimentally and theoretically for the last 50 years, due to its potential to cause significant damage in short periods. Incidents similar to those observed at San Onofre Nuclear Generating Station indicate that the problem is not yet fully understood, probably due to the large number of factors affecting the phenomenon. In this study, a new approach for the analysis and interpretation of FEI data using machine learning (ML) algorithms is explored. FEI data for both single and two-phase flows have been collected from the literature and utilized for training a machine learning algorithm in order to either provide estimates of the reduced velocity (single and two-phase) or indicate if the bundle is stable or unstable under certain conditions (two-phase). The analysis included the use of logistic regression as a classification algorithm for two-phase flow problems to determine if specific conditions produce a stable or unstable response. The results of this study provide some insight into the capability and potential of logistic regression models to analyze FEI if appropriate quantities of experimental data are available.

In-Plane Fluidelastic Instability Evaluation of Triangular Array Tube Bundle Using Fluid Force Measured Under Steam–Water Two-Phase Flow Condition

Recently, tube-to-tube wear indications of triangular tube bundle steam generators (SGs) caused by fluidelastic instability (FEI) in the in-plane direction of U-bend region (in-plane FEI) have been reported. Several experiments were conducted to investigate the characteristics of in-plane FEI by our research groups. In a series of experiments, particular characteristics of in-plane FEI were found. For example, there are the critical velocity difference between the in-plane and the out-of-plane directions, the difference between straight tube bundle tests and U-bend tube bundle tests, etc. To explain these characteristics, unsteady fluid force acting on tubes were measured. The experimental investigation was conducted under high temperature and high-pressure steam–water flow conditions close to the SGs. Stability analyses were conducted using the measured unsteady fluid forces as inputs. First, stability analyses were done to simulate straight tube bundle tests. Analysis results agreed well with experiments and it could explain the effect on critical velocity trend by number of flexible tubes and directions of vibration. Second, U-tube stability analyses were performed by applying unsteady fluid force coefficients for each location of U-bend tube finite element method (FEM) model. From the results, mechanisms of in-plane FEI were understood.