Flow-induced Vibration Research Articles

Numerical investigation on the effect of an orifice plate on the flow-induced and acoustically induced vibration of a gas transmission pipe

In this paper, a numerical method is proposed for investigating the flow-induced vibration (FIV) and acoustically induced vibration (AIV) of a straight pipe with an orifice plate. First, the turbulent pressure (TP) and acoustic pressure (AP) signals on the pipe wall were obtained through the simulation of an unsteady flow field and the application of Mohring's analogy, respectively. Subsequently, the FIV and AIV of the pipe were calculated by means of one-way fluid-structure interaction and acoustic-structure interaction, respectively. The calculated pressures, flow velocities, and sound powers at the monitoring point were in good agreement with the experimental results reported in the literature. The numerical results revealed that the power spectral densities of the AP were significantly higher than those of the TP on the surface of the tested end pipe, particularly at the natural frequencies of the acoustic modes. In the low-frequency regime, FIV was the dominant factor, whereas in the medium-high frequency regime, particularly above the cutoff frequency of the plane wave, AIV was the dominant factor. The findings of the parametric studies demonstrated that the AP and AIV of the pipe exhibited a considerable increase with the Mach number. Conversely, the TP and FIV demonstrated a more pronounced rise when the Mach number increased from 0.1 to 0.2, followed by a less pronounced increase when the Mach number increased from 0.2 to 0.3. A reduction in the orifice diameter resulted in an increase in the AP and AIV. In contrast, the TP and FIV exhibited a comparatively minor increase.

Characteristics of flow structure of lateral inlet/outlet in pumped storage power stations

Investigating the complex separated flows in lateral inlet/outlets of pumped-storage power stations(PSPS) is crucial for optimizing their design to ensure safe and efficient operation. In this study, Large Eddy Simulations (LES) are employed to reveal the relationship between turbulence intensity and the distribution of coherent structures in separated flows, as well as the evolution characteristics of hairpin vortices. The flow separation is notably influenced by the vertical diffusion angles α, which causes recirculation zones at the top of the inlet/outlet, leading to significant local flow velocities at the trash racks and increasing the risk of flow-induced vibration damage. Areas of high turbulence intensity exist at the top and bottom of the core flow, caused by the propagation of corresponding streams of vortical flow, which is identified as the primary cause of head loss in the inlet/outlet. Based on the average turbulence intensity, the inlet/outlet can be divided into zones of sharp turbulence increase, high turbulence intensity, and decreasing turbulence intensity. The vortical flow mainly includes three types of coherent structures: attached vortices, hairpin vortices, and quasi-streamwise vortices. Among these, the frequency of top hairpin vortices and the growth angle of hairpin vortex packets are highly susceptible to α. The growth direction of hairpin vortex packets closely aligns with the direction of turbulence intensity propagation. These findings contribute to optimizing the design of inlet/outlet of PSPS.

Parametric Optimization For Power Generation Of Flow Induced Vibration Energy Harvester

Flow-induced vibration occurs when the motion of fluids through a structure induces oscillations or vibrations in the structure. An effective flow-induced vibration energy harvester has substantial challenges due to the river's irregular velocity flows. It is not practicable to use one parameter for all velocities. This work presents the testing of a flow-induced vibrational energy harvester in laminar flow using two circular cylinders positioned in tandem within an open-channel flow. A CFD simulation using COMSOL Multiphysics was performed for the proposed parameter. A comprehensive simulation run at multiple Reynolds numbers with varying gap lengths between the bluff bodies is studied to determine the maximum power generated. Simulation results show that the optimal gap lengths for Re 60, 80, 100, 120, 140, and 160 are 8.5, 6.0, 3.0, 3.0, 3.5, and 4.5, respectively. These gap lengths result in power outputs of 0.0315 W, 2.616 W, 1.899 W, 0.6552 W, 0.5018 W, and 0.3782 W. By demonstrating the relationship between Reynolds number and gap length, this study provides important information for maximising the energy harvesting from flow-induced vibration (FIV).

Method and Application of Spillway Radial Gate Vibration Signal Denoising on Multiverse Optimization Algorithm-Optimized Variational Mode Decomposition Combined with Wavelet Threshold Denoising

To address the noise issue in the measured vibration signals of spillway radial gate discharge, this paper utilizes the Multiverse Optimization Algorithm (MVO) to optimize the number of decomposition modes (K) and the penalty factor (α) in Variational Mode Decomposition (VMD). This approach ensures improved efficiency of VMD decomposition while maintaining accuracy. Subsequently, the obtained Intrinsic Mode Functions (IMFs) from VMD decomposition are classified based on Multi-scale Permutation Entropy (MPE). IMFs are divided into pure components and noisy components; the noisy components are processed with Wavelet Threshold Denoising (WTD), while the pure components are overlaid and reconstructed to obtain the denoised vibration signal of the gate. Comprehensive comparisons involving artificial signal simulations, gate flow-induced vibration model tests, and numerical simulations lead to the following conclusions: compared to other algorithms, the proposed combined denoising method (MVO-VMD-MPE-WTD) achieves the highest signal-to-noise ratio (SNR) in both the frequency and time domains for artificial signals, while yielding the lowest mean square error (MSE). In the gate flow-induced vibration model tests, the method significantly reduces noise in the vibration signals and effectively preserves characteristic information. The error in preserving characteristic information across model tests and numerical simulations is kept below 1%. Furthermore, compared to other optimization algorithms, the MVO demonstrates higher computational efficiency. The parameter-optimized combined denoising method proposed in this study provides insights into denoising measured vibration signals of hydraulic spillway radial gates and other drainage structures, and it opens possibilities for exploring more efficient optimization algorithms for achieving online monitoring in the future.

Flow-induced vibration of a flexible tube with squeeze film in an otherwise rigid tube array subjected to cross-flow

Flow-induced vibration of a flexible tube with squeeze film in an otherwise rigid tube array subjected to cross-flow

Harvesting multidirectional wind energy based on flow-induced vibration triboelectric nanogenerator with directional tuning mechanism

Wind-induced vibration (WIV), as low-velocity wind energy utilization technology in agricultural environment, has significant advantages. Nevertheless, there is a mismatch between the variability of wind direction and the work mode of triboelectric nanogenerator (TENG), which leads to a sharp decline in the performance of triboelectric power generation. This work proposes a TENG based on multidirectional WIV (TENG-WIV), which mainly contains triboelectric power generation unit, guide-wing and triboelectric direction sensor. By introducing the directional tuning mechanism based on guide-wing, the TENG-WIV aims to break the constraints of single wind direction response and effectively respond to the wind direction within 360° range, thereby realizing multidirectional wind energy harvesting and sensor power supply. The empirical findings indicate that the output voltage and current of triboelectric power generation unit are in the ranges of 62–241 V and 0.25–1.21 μA, respectively, at the wind velocities of 1.23–5.13 m/s. At a wind velocity of 3.18 m/s, the unit achieves an out-power peak of 0.09 mW. Furthermore, the triboelectric direction sensor can respond to changes in 8 directions and has wind direction monitoring potentiality. The directional tuning mechanism endows flow-induced vibration energy harvesters with an all-around multidirectional sensitivity.

A vibration-based method to estimate the low-wavenumber wall pressure field in a turbulent boundary layer

When an elastic structure is excited by a low-speed turbulent flow, it generates flow-induced vibration which is primarily due to the low-wavenumber components of the wall pressure field (WPF) beneath the turbulent boundary layer (TBL). Therefore, to accurately predict the vibration response of the structure, an accurate estimation of the low-wavenumber WPF is needed. While existing TBL models for WPF well predict the convective region, they exhibit significant discrepancies in predicting the low-wavenumber levels. This numerical study aims to explore the feasibility of estimation of the low-wavenumber WPF by analysing vibration data obtained from a structure excited by a TBL. An inverse method is proposed based on the relationship between the TBL forcing function and structural vibrations in the wavenumber domain. The random TBL force is simulated with deterministic loading using the uncorrelated wall plane wave technique. A model of a simply supported plate under a TBL excitation is developed to demonstrate the proposed method. The plate's acceleration data is then used to estimate the WPF in the low-wavenumber range. It is shown how using multiple discrete frequencies in the analysis can reduce the required snapshots for accurate estimation of the WPF.

Acoustic characterization of porous windscreens for sound pressure and particle velocity sensors

Acoustic measurements of ground vehicles, wind turbines or aircrafts are often performed outdoors in presence of wind. Air movement around an acoustic sensor may significantly disturb the measured signals due to flow-induced vibrations and turbulence. This is specially relevant for pressure-gradient and particle-velocity based acoustic transducers which are more sensitive to these perturbations. To attenuate this effect and improve measurement quality, the sensors are typically covered with windscreens made of porous materials. However, designing an appropriate windscreen poses a challenging task, demanding a deep understanding of sound transmission characteristics. This study works towards quantifying acoustic properties of rigid-frame porous materials through in-situ measurements and fitting a parametric fluid-equivalent model to find optimal model parameters. The parameters are subsequently investigated by comparing windscreen insertion loss through finite-element numerical simulations and measurements on a sound intensity PU probe.

Investigating the impact of system parameters on flow-induced vibration hard galloping based on deep neural network

Abstract In this paper, a classification model is established for the flow-induced vibration response based on the numerical and experimental data, using a deep neural network-based machine learning approach. The model effectively distinguishes between hard galloping and soft galloping in flow-induced vibrations by identifying the corresponding range of system parameters. Moreover, a regression model is established to determine the relationship between the critical reduced velocity of hard galloping and system parameters, then an exploratory function strategy is utilized to establish the functional relationship between the critical reduced velocity of the hard galloping and the system parameters. The results reveal that the system parameter range with the occurrence of hard galloping is fn<0.85Uζ>-0.1fn+0.19. Additionally, the functional relationship between the critical reduced velocity and system parameters facilitates the adjustment of vibration states in flow-induced vibrations and enables deeper investigation into the phenomenon of hard galloping.

Asymmetric instability of flow-induced vibration for elastically mounted cube at moderate Reynolds numbers

The asymmetric instability in two streamwise orthogonal planes for three-dimensional flow-induced vibration (FIV) of an elastically mounted cube at a moderate Reynolds number of 300 is numerically investigated in this paper. The full-order computational fluid dynamics method, data-driven stability analysis via the eigensystem realization algorithm and the selective frequency damping method and total dynamic mode decomposition (TDMD) are applied here to explore this problem. Due to the unsteady non-axisymmetric wakefield formed for flow passing a stationary cube, the FIV response was found to exhibit separate structural stability and oscillations (including lock-in and galloping behaviour) in the two different streamwise orthogonal planes while the body is released. The initial kinetic energy accompanying the release of the cube could destabilize the above-mentioned structural stability. The observed FIV asymmetric instability is verified by the root trajectory of the structural mode obtained via data-driven stability analysis. The stability of the structural modes dominates regardless of whether the structural response oscillates significantly in various (reduced) velocity ranges. Further TDMD analysis on the wake structure, accompanied by the time–frequency spectrum of time-history structural displacements, suggested that the present FIV unit with galloping behaviour is dominated by the combination of the shifted base-flow mode, structure modes and several harmonics of the wake mode.

Enhancing stability and performance of flexible membrane structures in wake flows through jet flow control

This study investigates jet flow control on flexible membrane structures placed in the wake of a stationary cylinder to enhance performance and stability. Flexible membranes, found in both nature and engineering, often face nonlinear disturbances where passive deformation is insufficient. Inspired by adaptive fish fins, we explore active flow control strategies using a high-fidelity fluid–structure interaction solver to simulate the dynamics of a flexible membrane downstream of a cylinder. High-momentum jet flows with different momentum coefficients are applied at membrane leading edge to modulate the boundary layer flow features. Numerical simulation results reveal that jet flow control can weaken the wake interference effect on the membrane dynamics, resulting in lift improvement and flow-induced vibration suppression. The flow separation within the boundary layer is suppressed by high-momentum jet flows, thereby enhancing lift performance and stability. The reason of the flow-induced vibration suppression is attributed to the redistribution of the vibration energy in high-order structure modes excited by jet flows. Our results demonstrate that jet control has great potential for optimizing the performance and stability of flexible membrane structures in complex flow environments, providing valuable insights into the design of next-generation intelligent underwater vehicles and ships with flexible membrane propulsion systems.

A semi-analytical prediction model for fluid elastic instability in the streamwise direction of a normal triangular tube array

Fluid elastic instability (FEI) is widely regarded as the most destructive mechanism of flow-induced vibration. Numerous failures of heat exchanger tubes have been attributed to this phenomenon. This paper focuses on a normal triangular tube array and develops a semi-analytical time-domain solving model to address FEI in the streamwise direction. Utilizing computational fluid dynamics simulations and image processing techniques, a comprehensive set of tube-in-channel model parameters is derived, including the area perturbation amplitude, phase difference, mean area along the flow channel, and steady-state term of flow velocity. Tube motion in the streamwise direction generates a disturbance distinct from that caused by transverse flow, leading to revisions in the expressions of relevant model parameters. Furthermore, variations in these parameters across different positions and velocities are quantitatively analyzed through function fitting, yielding specific mathematical formulas. Ultimately, the derived tube-in-channel model parameters applicable to streamwise FEI are validated against experimental data, affirming the model's accuracy.

Mitigation of flow-induced vibrations in high-speed flows using triply periodic minimal surface structures

Mitigation of flow-induced vibrations in high-speed flows using triply periodic minimal surface structures

A Comprehensive Deep Learning–Based Approach to Field Reconstruction in Reactor Cores

The aging process or flow-induced vibration of reactor cores may lead to increased mechanical vibrations, affecting the reliability of in-core sensors and necessitating a robust solution for robust field reconstruction. This work tackles the challenges of reconstructing multiphysics fields from sparse and movable measurements by introducing an advanced framework that integrates various machine learning models with Voronoi tessellation. Our approach, building upon the Voronoi tessellation-assisted Convolutional Neural Network (VCNN), expands the capabilities to include a wider array of neural network architectures such as Convolutional Neural Networks (CNNs), Fourier Neural Operator (FNO), Dilated ResNet Encode-Process-Decode (DilResNet), Dilated Convolution Neural Operator (DCNO), Galerkin Transformer (GT), U-shaped Neural Operator (UNO), and Multiwavelet-based Operator (MWT). The effectiveness of these models is evaluated and validated through numerical tests based on the International Atomic Energy Agency benchmark, particularly noting average relative errors below 5% and 10% in the L 2 norm and L ∞ norm, respectively, within a 5-cm amplitude around sensor nominal locations. The developed software toolkit encapsulates these architectures, providing a versatile option for nuclear engineers to reconstruct different types of physical fields efficiently.

The Effect of Reynolds Numbers on Flow-Induced Vibrations: A Numerical Study of a Cylinder on Elastic Supports

In the field of fluid dynamics, the Reynolds number is a key parameter that influences the flow characteristics around bluff bodies. While its impact on flow around stationary cylinders has been extensively studied, systematic research into flow-induced vibrations (FIVs) under these conditions remains limited. This study utilizes numerical simulations to explore the FIV characteristics of smooth cylinders and passive turbulence control (PTC) cylinders supported elastically within a Reynolds number range from 0.8 × 104 to 1.1 × 105. By comparing the vibration responses, lift coefficients, and wake structures of these cylinders across various Reynolds numbers, this paper aims to elucidate how Reynolds numbers affect the flow and vibration characteristics of these structures. The research employs images of instantaneous lift changes and vortex shedding across multiple sections to visually demonstrate the dynamic changes in flow states. The findings are expected to provide theoretical support for optimizing structural design and vibration control strategies in high-Reynolds-number environments, emphasizing the importance of considering Reynolds numbers in structural safety and design optimization.

The influence of the self-issuing jet on the flow-induced vibration suppression

In order to weaken the vibration response of the cylinder, the self-issuing jet method based on an internal pipe is investigated. The ocean current is modeled by Reynolds Average Navier-Stokes (RANS) method and the Shear Stress Transport (SST) k-ω transient model in order to fit the actual engineering. The motion is transformed into a mass-spring-damped oscillator model, and it will be solved by the Newmark-β method. A two-way fluid-structure interaction (FSI) numerical simulation channel is established by using embedded user-defined functions. The numerical method is demonstrated with relevant experimental results. It is found that the scheme to increase the velocity of the jet by reducing the outlet width is feasible. The self-issuing jet significantly reduces the amplitude ratio, and the amplitude ratio is reduced by 92.70% in Desynchronization region. Meanwhile, the self-issuing jet decreases the locking region of vortex resonance.

Underwater blade-free triboelectric nanogenerator for harvesting current energy in low-speed current

Ocean current energy bears the characteristics of wide distribution and high energy density. Harvesting current energy as the in-situ power for distributed ocean sensors will greatly enhance the sustainability of ocean sensing. In many parts of the ocean, the current speed is not desirable (low or unstable) for conventional current energy harvesting devices. Here, an underwater blade-free triboelectric nanogenerator (UBF-TENG) is developed to effectively utilize the low-speed currents through the flow-induced vibration (FIV). The power generation unit is fully enclosed inside the shell, effectively reducing the direct impact and underwater corrosion. The study demonstrates that within the established experimental parameters space, the optimized UBF-TENG can facilitate a start-up speed as low as 0.14 m/s. The UBF-TENG has achieved a maximum open-circuit voltage output of 250 V and a maximum short-circuit current output of 2.2μA at 0.76 m/s. The charging capacity of the UBF-TENG is tested with various capacitors, demonstrating the application potential of the UBF-TENG as an in-situ power supply underwater.

Modeling of high-pressure transient gas-liquid flow in M-shaped jumpers of subsea gas production systems

Two-phase flow with low liquid loads is common in high-pressure natural gas offshore gathering and transmission pipelines. During gas production slowdowns or shutdowns, an accumulation of liquid in the lower sections of subsea pipelines may occur. This phenomenon is observed in jumpers that connect different units in deep-water subsea gas production facilities. The displacement of the accumulated liquid during production ramp-up induces temporal variations in pressure drop across the jumper and forces on its elbows, resulting in flow-induced vibrations (FIV) that pose potential risks to the structural integrity of the jumper. To bridge the gap between laboratory experiments and field conditions, transient 3D numerical simulations were conducted using the OpenFOAM software. These simulations facilitated the development of a mechanistic model to elucidate the factors contributing to increased pressure and forces during the liquid purging process. The study examined the influence of gas pressure level, pipe diameter, initially accumulated liquid amount, liquid properties, and gas mass flow rate on the transient pressure drop and the forces acting on the jumper's elbows. The critical gas production rate required for complete liquid removal of the accumulated liquid was determined, and scaling rules were proposed to predict the effects of gas pressure and pipe diameter on this critical value. The dominant frequencies of pressure and force fluctuations were identified, with low-pressure systems exhibiting frequencies associated with two-phase flow phenomena and high-pressure systems showing frequencies attributed to acoustic waves.

Experimental and Simulation Study on Flow-Induced Vibration of Underwater Vehicle

At high speeds, flow-induced vibration noise is the main component of underwater vehicle noise. The turbulent fluctuating pressure is the main excitation source of this noise. It can cause vibration of the underwater vehicle’s shell and eventually radiate noise outward. Therefore, by reducing the turbulent pressure fluctuation or controlling the vibration of the underwater vehicle’s shell, the radiation noise of the underwater vehicle can be effectively reduced. This study designs a cone–column–sphere composite structure. Firstly, the effect of fluid–structure coupling on pulsating pressure is studied. Next, a machine learning method is used to predict the turbulent pressure fluctuations and the fluid-induced vibration response of the structure at different speeds. The results were compared with experimental and numerical simulation results. The results show that the deformation of the structure will affect the flow field distribution and pulsating pressure of the cylindrical section. The machine learning method based on the BP (back propagation) neural network model can quickly predict the pulsating pressure and vibration response of the cone–cylinder–sphere composite structure under different Reynolds numbers. Compared with the experimental results, the error of the machine learning prediction results is less than 7%. The research method proposed in this paper provides a new solution for the rapid prediction and control of hydrodynamic vibration noise of underwater vehicles.

Development and experimental evaluation of an acoustic flow meter prototype for measuring air flow

This study outlines the development and testing of a flow meter prototype specifically designed for use in nuclear reactor environments. The meter uses flow-induced vibration to measure flow rates and is designed for remote monitoring in harsh environments where radiation can damage electronics. The device generates a vibration signal produced by a feedback system when fluid flows out of an orifice and interacts with a downstream wedge. The frequency of the vibration signal corresponds directly to flow rate and velocity. The study investigates geometric parameters intrinsic to the prototype, such as orifice height, width, edge distance, and chamber length. Different configurations were also tested, including a bypass loop with variable cross-sections around the device. The investigation results reveal the impact of these geometric parameters on the vibration signal output, providing valuable insights for future design improvements and enhancing the effectiveness of flow metering systems used in nuclear reactor applications.