Non-linear time domain analysis of cross-flow vortex-induced vibrations

Thorsen, Mats Jørgen; Sævik, Svein; Larsen, Carl M.

doi:10.1016/j.marstruc.2016.10.007

Cited by 50 publications

(22 citation statements)

References 25 publications

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“…Recently, heave induced VIV of an SCR with non-linear bottom contact was simulated. The response was in good agreement with measurements (Thorsen et al, 2017). The fundamental idea of the model is the way synchronization between hydrodynamic force and response is handled.…”

Section: Introductionsupporting

confidence: 70%

“…The relative velocity is found as v = u −ẋ. Figure 1: A cylinder segment with local coordinate system and velocity vectors (Thorsen et al, 2017).…”

Section: Deterministic Hydrodynamic Force Modelmentioning

confidence: 99%

“…The vortex shedding forcing term is added to Morison's equation to cause excitation under what commonly is referred to as "lockin"-conditons. Thorsen et al (2017) acknowledged that Morison's drag force might be inaccurate as damping model in case of VIV. However, it is the total energy balance between damping and excitation which is of main concern.…”

Section: Deterministic Hydrodynamic Force Modelmentioning

confidence: 99%

“…Thorsen et al (2017) proposed a method based on a phase portrait (see figure 2). Structural velocity in the instantaneous cross-flow direction is normalized by its r.m.s.…”

Section: Deterministic Hydrodynamic Force Modelmentioning

confidence: 99%

“…Figure 2: The phase diagram illustrates how the instantaneous phase of the relative cross-flow velocity is found (Thorsen et al, 2017).…”

Section: Deterministic Hydrodynamic Force Modelmentioning

confidence: 99%

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Stochastic modelling of cross-flow vortex-induced vibrations

et al. 2017

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Semi-empirical models are commonly used to predict vortex-induced vibrations (VIV). Empirical parameters are often based on forced harmonic motion tests of short rigid cylinders in one degree of freedom, which is a significant simplification of the three dimensional VIV experienced by flexible cylinders. Still, the models may provide satisfactory estimates of the response of slender marine structures exposed to current. At least in terms of root mean square (r.m.s.) of displacements and strains, dominating frequency and dominating mode. However, VIV of long slender beams, especially in sheared current, show large response variability in time and space, which appears to be of a random nature. Semi-empirical models that predict steady-state VIV are hence unable to reflect the non-stationary response observed in experiments, even though the time and space averaged result might be well represented.In this work, a previously published semi-empirical time domain model for cross-flow vortex-induced vibrations is modified to describe the stochastic nature of the response of long slender beams subjected to stationary current. The mean non-dimensional frequency of the synchronization model (previously constant) is taken to be a simplified Gaussian process, where standard deviation and spectral frequencies are input. The stochastic synchronization model allows the response to jump between different eigenfrequencies and corresponding modes, and still predict mean and r.m.s. values close to the deterministic model. Its performance is verified through simulation of an experiment with a long riser in sheared flow. The response sensitivity of standard deviation and spectral frequencies is investigated. It indicates that for a proper choice of empirical coefficients, the chaotic response of the riser can be quite realistically simulated in terms of frequency variation and, to some extent, amplitude modulation.

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Section: Introductionsupporting

confidence: 70%

“…The relative velocity is found as v = u −ẋ. Figure 1: A cylinder segment with local coordinate system and velocity vectors (Thorsen et al, 2017).…”

Section: Deterministic Hydrodynamic Force Modelmentioning

confidence: 99%

Section: Deterministic Hydrodynamic Force Modelmentioning

confidence: 99%

“…Thorsen et al (2017) proposed a method based on a phase portrait (see figure 2). Structural velocity in the instantaneous cross-flow direction is normalized by its r.m.s.…”

Section: Deterministic Hydrodynamic Force Modelmentioning

confidence: 99%

“…Figure 2: The phase diagram illustrates how the instantaneous phase of the relative cross-flow velocity is found (Thorsen et al, 2017).…”

Section: Deterministic Hydrodynamic Force Modelmentioning

confidence: 99%

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Stochastic modelling of cross-flow vortex-induced vibrations

et al. 2017

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Data-Driven Prediction of Vortex-Induced Vibration Response of Marine Risers Subjected to Three-Dimensional Current

Riemer-Sørensen

Lie

et al. 2019

Communications in Computer and Information Science

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Slender marine structures such as deep-water marine risers are subjected to currents and will normally experience Vortex Induced Vibrations (VIV), which can cause fast accumulation of fatigue damage. The ocean current is often three-dimensional (3D), i.e., the direction and magnitude of the current vary throughout the water column. Today, semi-empirical tools are used by the industry to predict VIV induced fatigue on risers. The load model and hydrodynamic parameters in present VIV prediction tools are developed based on two-dimensional (2D) flow conditions, as it is challenging to consider the effect of 3D flow along the risers. Accordingly, the current profiles must be purposely made 2D during the design process, which leads to significant uncertainty in the prediction results. Further, due to the limitations in the laboratory, VIV model tests are mostly carried out under 2D flow conditions and thus little experimental data exist to document VIV response of riser subjected to varying directions of the current. However, a few experiments have been conducted with 3D current. We have used results from one of these experiments to investigate how well 1) traditional and 2) an alternative method based on a data driven prediction can describe VIV in 3D currents. Data driven modelling is particularly suited for complicated problems with many parameters and non-linear relationships. We have applied a data clustering algorithm to the experimental 3D flow data in order to identify measurable parameters that can influence responses. The riser responses are grouped based on their statistical characteristics, which relate to the direction of the flow. Furthermore we fit a random forest regression model to the measured VIV response and compare its performance with the predictions of existing VIV prediction tools (VIVANA-FD).

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