There is an increasing trend towards using numerical wave simulations for the design of offshore structures, especially for the stochastic prediction of nonlinear wave loads like those related to air-gap and wave impact. Unlike experimental facilities, where the complex nonlinear physics of wave propagation is simply enforced by the laws of nature, numerical wave tanks (NWTs) rely on assumptions and simplifications to solve the propagation equations in a reasonable amount of time. It is therefore important to verify the quality of the waves generated by NWTs in terms of realistic physical properties. As part of the effort to develop reliable numerical wave modeling practices in the framework of the “Reproducible Offshore CFD JIP”, qualification criteria are formulated for the wave solutions generated from either potential-flow based or CFD-based codes. The criteria have been developed based on experiences from physical wave tank tests and theoretical/numerical studies. They are being evaluated using results from several numerical models and available benchmark data. This paper presents the proposed qualification criteria and on-going evaluation efforts by comparing results from different codes.

In this work, we compare the wave and loads statistics for two different sea states with a T P = 15.0[s] on a h = 33.0[m] depth, one with a 10-year return period (H S = 7.5[m]) and one with a 100-year (H S = 9.5[m]). For each sea state, a unidirectional and a multi-directional wave realization was measured experimentally and then reproduced numerically via a fully-nonlinear potential solver. The computed wave kinematics were used to calculate loads on a stiff cylinder with a diameter of D = 7.0[m], and compared with experiments. To perform a quantitative analysis, we extracted 30-minute maxima of the free surface elevation and in-line force, and fitted a Gumbel distribution via a Bayesian methodology. The analysis of the experiments showed that the extreme forcing on a stiff cylinder was larger in the 2D sea state than in the 3D sea state. As for the crest statistics, the 2D were higher than the 3D for the milder storm, while they were quite similar for the stronger storm, likely a consequence of the increased wave breaking, limiting the maximum achievable wave crests. The reproduction of the sea states and associated loads via a fully-nonlinear potential solver was overall able to predict the main trends. However, the 3D wave crests were overestimated for the milder sea state, probably due to a too soft breaking filter. The 2D forces for the larger sea state were on the other hand underestimated, likely due to the lack of a slamming load model. The analysis of the average wave shape leading to the extreme load events showed that in the experiments the extreme events are dominated by physics linked with the particle velocity, and hence in phase with the wave elevation signal, as drag loads, slamming loads and velocity-dependent free-surface intersection loads. On the other hand, in the simulations they are more inertia dominated, hence in phase with the kinematic acceleration signal.

Ocean surface is complex and difficult to predict accurately due to its random nature. Ocean surface waves in strong wind conditions have been widely studied for last few decades. Almost half of world’s winds are below 7.5 m/s and the physics of such winds contains a lot of uncertainties. The simulation of ocean waves is largely dependent on the driving winds force accuracy and source term parameterizations. However, low winds are often ignored on the perception of their lesser effect on overall results of existing models. It is important to understand the relative strength/ weaknesses of wave forecast models under low wind conditions from scientific perspective which should lead to improved wave forecast and wave-ocean-weather coupling capabilities. There are many critical thresholds involved in the initial generation and growth of wind waves whereas current parameterizations of wave models are mostly based on moderate – high wind conditions. Wave model’s performance, although not very prominent, contains bias under low winds conditions and these thresholds need to be embedded in current physics of wave forecast models for more accurate simulations. In this study, WAVEWATCH III (v6.07) wave forecast model with observation based source terms parameterizations (ST6 package) is used to simulate waves on a global scale. The model’s output is analyzed with a globally calibrated and cross validated global dataset of 13 altimeters to analyze its performance under low wind conditions. A relative error of −1 to 6 is observed in global significant wave heights simulated by WAVEWATCH III model compared to altimeter’s measured wave heights for wind speeds less than 5ms −1 .

I consider nonlinear wave motion in shallow water as governed by the KP equation plus perturbations. I have previously shown that broad band, multiply periodic solutions of the KP equation are governed by quasiperiodic Fourier series [Osborne, OMAE 2020]. In the present paper I give a new procedure for extending this analysis to the KP equation plus shallow water Hamiltonian perturbations. We therefore have the remarkable result that a complex class of nonlinear shallow water wave equations has solutions governed by quasiperiodic Fourier series that are a linear superposition of sine waves. Such a formulation is important because it was previously thought that solving nonlinear wave equations by a linear superposition principle was impossible. The construction of these linear superpositions in shallow water in an engineering context is the goal of this paper. Furthermore, I address the nonlinear Fourier analysis of experimental data described by shallow water physics. The wave fields dealt with here are fully two-dimensional and essentially consist of the linear superposition of generalized cnoidal waves , which nonlinearly interact with one another. This includes the class of soliton solutions and their associated Mach stems, both of which are important for engineering applications. The newly discovered phenomenon of “fossil breathers” is also characterized in the formulation. I also discuss the exact construction of Morison equation forces on cylindrical piles in terms of quasiperiodic Fourier series.

The design of structures at sea requires knowledge on how large and steep waves can be. Although extreme waves are very rare, their consequences in terms of structural loads, such as wave impact or ringing, are critical. However, modelling the physical properties of steep waves along with their probability of occurrence in given sea states has remained a challenge. On the one hand, standard linear and weakly nonlinear wave theories are computationally efficient, but since they assume that the steepness parameter is small, they are unable to capture extreme waves. On the other hand, recent simulation methods based on CFD or fully nonlinear potential solvers are able to capture the physics of steep waves up to the onset on breaking, but their large computational cost makes it difficult to investigate rare events. Between these two extremes, the High-Order Spectral (HOS) method, which solves surface equations, is both efficient and able to capture highly nonlinear effects. It may then represent a good compromise for long simulations of steep waves. Unfortunately, it is based on a perturbation expansion where the small parameter is the wave steepness, and consequently, simulations tend to become unstable when steep wave events occur. In this work, we investigate the properties of irregular waves simulated with a modified HOS method, in which the sea surface is described with a Lagrangian representation, i.e. by computing the position and the velocity potential of individual surface particles. By doing so, nonlinear properties of the surface elevation are simply captured by the modulation of the horizontal and vertical particle motion. The same steep wave is then described more linearly with a Lagrangian representation, which reduces the instabilities of the HOS method. The paper focuses on bi-chromatic waves and irregular waves simulated from a JONSWAP spectrum. We compare simulations performed with the standard HOS and the modified Lagrangian methods for various HOS-orders.

In this study, the forces and moments acting on the KCS ship model as a result of oblique towing at 10 and 20 degrees drift angles are evaluated experimentally and numerically via a commercial Reynolds averaged Navier-Stokes solver. For the purposes of this work, the KCS hull is modelled both experimentally and numerically at a scale factor of 1:75. The adopted case-studies feature both horizontal and vertical restrictions. Thus, the subject of this work is the oblique motion of a ship in a narrow canal with a depth of h/T = 2.2. The relative impact of turbulence modelling is assessed by comparing the computed integral quantities via several eddy-viscosity closure strategies. These include significant variants of the k-ϵ and k-ω models as well as a widely used one-equation closure. Multiphase numerical simulations are performed at several of the experimentally investigated depth Froude numbers for each drift angle condition in order to fully capture the physics of the problem at hand. The present study aims to provide a quantitative evaluation of the performance of the adopted turbulence models and recommended the best closure strategy for the class of investigated problems.

The purpose of this study is to numerically investigate the bed shear stress and near-bed mixing due to coherent vortex structures in the vicinity of a vertically wall-mounted circular cylinder subject to an imposed finite-depth oscillatory sinusoidal flow. Previous studies reveal that the Keulegan–Carpenter (KC) number influences the formation of lee-side wake vortex structures as well as the horseshoe vortex in front of a cylinder. Therefore, parametric studies in a moderately wide range of KC from 5 to 20 are numerically performed. In the present study, Direct Numerical Simulation (DNS) is conducted using the open-source software, OpenFOAM, that solves the three-dimensional unsteady incompressible Navier-Stokes equations using finite volume method. Nondimensional parameters used in the simulations are carefully chosen to represent the real physics. The numerical solutions are first validated using an analytical solution for the oscillating Stokes flow and the results are then systematically and quantitatively compared with the experimental measurements. The results show that the lee-side wake is significantly influenced by KC, and distinctive types of the lee-side wake are generated and classified based on KC. It is also found that both KC and the ratio of the thickness of the Stokes boundary layer to the water depth are heavily associated with the stability of the lee-side wake. In addition, the simulated size and lifespan of the horseshoe vortex agree well with the experimental data.

Fluid drag is an integrated force that depends on the velocity of the fluid flow relative to the motion of a structure. In previous OMAE papers, we used nonlinear physics-based time-domain simulations to show how fluid drag evolves geometric changes in slender (long and thin) structures. We then showed how these changes physically determine the specific dynamic nature of the vibrations that the fluid can induce in the structure. Induced vibrations are four-dimensional oscillations in a marine riser, suspended pipe or other slender structure, whereby the maximum amplitude of deflection is generally perpendicular to the sustained action. The sustained action is often fluid drag. In this paper, we study the physical relationship between fluid drag and induced vibrations. By focusing on the nonlinear interaction between fluid and structure, we revisit a longstanding belief that vortex-induced vibrations amplify fluid drag. Using nonlinear physics-based simulations of a slender structure interacting with flowing fluid, we show how amplification depends on the type of vibration (imposed or free). In other words, drag amplification can occur when we impose a vibration on the structure, but does not occur when we allow sufficient geometric freedom so that the fluid merely induces the structure to vibrate. Using simple visual experiments, we confirm that Vortex-Induced Vibrations (VIV) do not amplify fluid drag. This result is consistent with basic energy conservation principles.

The study on flow around a hydrofoil has been performed using various methods experimentally and numerically. Here we use a purely data-driven model using deep neural networks (DNNs) to reconstruct the flow fields. Its results are also compared with that obtained by traditional methods. The datasets of flow fields around a static hydrofoil obtained from computational fluid dynamics (CFD) are used for training the DNNs and then the trained data-driven model is utilized to make reconstructions and predictions. 9 different physics informed loss functions, which contain the prediction error and the error measuring the violation of the conservation law, are proposed to train the parameters of DNNs. Effects of the proposed loss functions on reconstruction of velocity field and pressure field are analyzed. Lift and drag forces predicted during the training time are also analyzed. However, the data-driven model based on DNNs with the optimum loss function works well in the interpolation but fails in the extrapolation. The reasons causing the errors are discussed.

The paper addresses the flow-induced response of a rigid spool/jumper. It mainly focuses on its mechanical response resulting from internal intermittent slug flows but also addresses potential coupling with an external excitation due to vortex shedding. These works provide quantitative experimental data that match quite well with existing empirical correlations in terms of slug flow properties. The repeatability of the measurement system has been experienced and underlines promising capabilities. The tests provide exhaustive complementary data regarding the slug flow properties (e.g. pocket length) which will be reused for numerical modelling purpose. The mechanical response of the spool is exhaustively addressed for different regular slug flows. Some correlations are proposed aiming at describing the mechanical responses. The coupling with an additional external current solicitation and Vortex Induced Vibrations (VIV) is discussed and characterized for some conditions. Finally, a discussion on the current Industry Best Practices is introduced in order to challenge the capability of the proposed approaches to described and recover such complex phenomenon. The comparisons underline the weak agreement between experiments and numerical models, opening discussion on the best way to address this physics and the next developments.

In-service integrity management (IM) of steel lazy wave risers (SLWRs) can benefit significantly from quantitative assessment of the overall risk of system failure as it can provide an effective tool for decision making. SLWRs are prone to fatigue failure within their touchdown zone (TDZ). This failure mode needs to be evaluated rigorously in riser IM processes because fatigue is an ongoing degradation mechanism threatening the structural integrity of risers throughout their service life. However, accurately evaluating the probability of fatigue failure for riser systems within a useful time frame is challenging due to the need to run a large number of nonlinear, dynamic numerical time domain simulations. Applying the Bayesian framework for machine learning, through the use of Gaussian Processes (GP) for regression, offers an attractive solution to overcome the burden of prohibitive simulation run times. GPs are stochastic, data-driven predictive models which incorporate the underlying physics of the problem in the learning process, and facilitate rapid probabilistic assessments with limited loss in accuracy. This paper proposes an efficient framework for practical implementation of a GP to create predictive models for the estimation of fatigue responses at SLWR hotspots. Such models are able to perform stochastic response prediction within a few milliseconds, thus enabling rapid prediction of the probability of SLWR fatigue failure. A realistic North West Shelf (NWS) case study is used to demonstrate the framework, comprising a 20” SLWR connected to a representative floating facility located in 950 m water depth. A full hindcast metocean dataset with associated statistical distributions are used for the riser long-term fatigue loading conditions. Numerical simulation and sampling techniques are adopted to generate a simulation-based dataset for training the data-driven model. In addition, a recently developed dimensionality reduction technique is employed to improve efficiency and reduce complexity of the learning process. The results show that the stochastic predictive models developed by the suggested framework can predict the long-term TDZ fatigue damage of SLWRs due to vessel motions with an acceptable level of accuracy for practical purposes.

A successful primary cementing job requires an efficient fluid displacement process in order to place cement in the annulus between a casing or liner and the formation around the wellbore. This operation is a critical part of the well construction and due to the hardening properties of cement there will be no second chance with this operation. Once hardened, the cement should provide zonal isolation and pressure containment and should do so through the lifetime of the well. Furthermore, the cement shall anchor and support the casing string and protect it against corrosion due to formation fluids. A good quality cement job is important both from an environmental and from an economical perspective. In order to improve recommended cementing practices, and thus also the quality of cementing process, it is necessary to develop cementing simulation software for proper engineering. Detailed data on the displacement efficiency from practical operations are difficult or impossible to obtain. Furthermore, field operations do not allow for a systematic change in fluid properties. To be able to validate the engineering tools it is therefore necessary to perform laboratory measurements with fluids with relevant properties. It is also important to perform these experiments in laboratory equipment of sufficient diameter dimensions to facilitate scale up of the results. The purpose of the present article is to give an overview of cement displacement experiments which were conducted using a large diameter annular flow loop using model fluids with relevant rheological properties. While some results from these experiments have been presented in previous articles, this article is intended to give an overview of all the experiments, including the setup and experimental approach, and provides in more detail results not presented previously. In particular we show results from video recordings which confirm previous conclusions based on conductivity measurements. It is found that eccentricity affects the displacement physics significantly. In washout sections the effects of eccentricity are different and generally smaller since the eccentricity is also reduced. Drill string rotation improves displacement efficiency in all tested cases both within and outside the washout cavity. Since the amount of publicly available experimental data of this type is very limited, the detailed information presented here should be of great interest and relevance for the development and validation of industrial cementing simulation software.

Underwater Gliders are unique buoyancy propelled oceanographic profiling vehicles. Their speed and endurance in longitudinal motion are affected by the symmetry, sweep dihedral angle and span of the control surfaces. In the low-velocity regime, these parameters can be varied to examine the flow around the glider. They also affect the lift-to-drag ratio (L/D) essential for the manoeuvring path in longitudinal and transverse motions. In this paper, the sweep angle of the main wing of a blended wing autonomous underwater glider configuration is varied as 10°, 15°, 30°, 45° and 60° and the resulting hull forms are numerically simulated in the commercial software, STARCCM+. The main wing is a tapered NACA0018 section (taken as per the general arrangement requirement) with 1.5m chord at the root and 0. 1m at the tip. The numerical model is validated using the CFD results of NACA0012 airfoil from Sun.C et al, 2015 [1]. The hydrodynamic forces are obtained by varying the angle of attack (α) of the body from −15° to 15°, for flow velocity of 0.4m/s. The hydrodynamic coefficients (lift-to-drag ratios) and flow physics around the wing are analyzed to arrive at an optimum Lift-to-drag ratio for increased endurance.

The sound of waves breaking on shore, or against an obstruction or jetty, is an immediately recognizable sound pattern which could potentially be employed by a sensor system to identify obstructions. If frequency patterns produced by breaking waves can be reproduced and mapped in a laboratory setting, a foundational understanding of the physics behind this process could be established, which could then be employed in sensor development for navigation. This study explores whether wave-breaking frequencies correlate with the physics behind the collapsing of the wave, and whether frequencies of breaking waves recorded in a laboratory tank will follow the same pattern as frequencies produced by ocean waves breaking on a beach. An artificial “beach” was engineered to replicate breaking waves inside a laboratory wave tank. Video and audio recordings of waves breaking in the tank were obtained, and audio of ocean waves breaking on the shoreline was recorded. The audio data was analysed in frequency charts. The video data was evaluated to correlate bubble sizes to frequencies produced by the waves. The results supported the hypothesis that frequencies produced by breaking waves in the wave tank followed the same pattern as those produced by ocean waves. Analysis utilizing a solution to the Rayleigh-Plesset equation showed that the bubble sizes produced by breaking waves were inversely related to the pattern of frequencies. This pattern can be reproduced in a controlled laboratory environment and extrapolated for use in developing navigational sensors for potential applications in marine navigation such as for use with autonomous ocean vehicles.

When free-surface waves are generated using wave paddles to produce the desired waves, higher order effects might be inevitable for some cases. These can be due to the mismatch in the wave paddle displacement and non-linear free-surface wave kinematics, as well as the moving boundary of wave paddles. Such higher order effects are often manifested as higher harmonic waves, which can propagate independently (or free waves). The presence of such waves will contaminate the quality of the tank test, and together with effects due to scaling and finite size of tank, it is important to reduce or mitigate such effects as much as possible in a wave tank in order to simulate a more realistic scenario. This study investigates the above problem in a systematic manner by using a fully-nonlinear numerical wave tank based on the three-dimensional time-domain Harmonic Polynomial Cell (HPC) method. Wave is generated by flap-type wave paddles on one end of the tank, and is damped on the other end. The paddle boundary conditions are satisfied on the instantaneous paddles surfaces, and the free surface is tracked by the generalized semi-Lagrangian scheme. In this study, first order paddle signal is used to generate regular waves, and the focus is on characterising the behaviour of the generated free higher harmonic waves. We first look into a rectangular wave tank where the paddles are distributed at one side of the tank. Upon the generation of an oblique regular wave (primary wave), it is observed that the generated free waves propagate at a different angle/direction. An explicit analytical expression is derived for the direction of the free waves, which agrees with the numerical observation. Besides propagating at a different direction, the free waves also interact with the primary waves resulting in additional bound waves of the first and third harmonics. Next, we consider a circular wave tank, where paddles along half of the circumference are used to generate planar regular wave, while paddles at the other half are assumed to be able to fully absorb the wave. The generated free waves are observed to focus at a particular region in the tank due to constructive interference. To eliminate or at least mitigate such undesired waves, correction to first order paddle signal is required. Second order correction scheme based on Schaffer (1996) is implemented for such purpose. Preliminary results seem to suggest that second order correction to the paddle signal can only mitigate but cannot completely eliminate the existence of free higher harmonic waves.

Sudden snap events on mooring lines and hanging cables can cause spikes in tension, resulting in reduced safety factors during extreme events. For example, the mooring system of a floating offshore wind turbine (FOWT) can be exposed to wave-induced motions making the former vulnerable to snap type impact. Suitable criteria to define snap events are still largely unclear, making current design practices overly conservative. To understand the underlying physics of snap loads on a mooring line system, this paper presents a theoretical development and an experimental parametric study of snap events. The effects of the nonlinearity of bilinear line stiffness and hydrodynamic drag force, as well as the weight of payload on snap events are investigated using the vertical hanging cable model. This cable model includes two springs in series and a payload. The bilinear spring model is designed to create nonlinear dynamic tension. A total of 108 tests were conducted in the wave tank of Tainan Hydraulic Laboratory. The excitation amplitude ranges from 0.01 to 0.04m; excitation time period ranges from 0.5 to 2s; the weight of payload ranges from 6.13 to 18.95N. The tests carried out in water are compared to those conducted in air. It is seen that the hydrodynamic drag force together with the small pretension could result in larger normalized tension ranges.

The increasing activities in arctic sea areas over the last years have led to a rising demand for numerical tools to design and evaluate ice-going ships. Numerical simulation of ship-ice interaction can be a suitable method for engineers to evaluate ship designs in early development phases. We present an efficient method to evaluate local and global loads on ships in level ice at moderate computational effort. The objective of this contribution is the holistic simulation of the icebreaking process along with the hydrodynamic interplay of the broken ice cups with the surrounding level ice and the hull. For this purpose, a free surface flow solver based upon the Lattice Boltzmann method is coupled to an icebreaking model and a contact-dynamic physics engine. Overall, the approach seeks to compute both local loads, acting on the ship hull, as well as the total resistance in ice. The direct simulation approach makes it possible to consider the load contributions of icebreaking and displacement separately and to analyze their contribution to the total resistance more precisely. Simulation results for a tanker in various ice conditions show significant differences in load distribution and can provide valuable information for the designer of ice-going ships.

Conventional kick detection methods mainly include monitoring pit gains, surface flow data (flow in and flow out), surface and down-hole pressure variations, and outputs from physics-based models. Kick detection times depend on a driller’s individual ability to interpret these drilling measurements, symptoms and model predictions. Furthermore, testing a novel data-driven solution in a full-scale operation may induce non-productive time, safety risks and crew fatigue adding to false alarms that inevitably occur during testing. Therefore, the development of better, faster and less human intervention-dependent kick detection on a laboratory scale system is a valuable step before full-scale testing. We have generated a dataset containing seven typical drilling measurements and a sequence of gas kicks from experiments conducted in the laboratory scale. First, we employ data analysis tools following data pre-processing steps, data scaling, outlier detection, and natural feature selection. Next, we consider additional “engineered features” and apply different feature combinations to logistic regression with an ensemble method (boosting) for developing kick detection algorithms. In our data analysis, ‘Delta flow’ (difference between flow in and flow out of the well) and ‘Rate of change of delta flow’ designed features, combined with logistic regression and boosting, give promising results in detecting kicks. Finally, we propose an intelligent algorithm and alarm architecture for a complete kick alarm system, which draws from both data analysis and machine learning models developed in this work.

An investigation into the computation of hydrodynamic loads on a suspended cylinder in regular waves is presented. The primary goal was to perform a three-way validation of the loads between experimental measurements and simulations from two computational methods. Experimental measurements of the longitudinal in-line force on a cylinder suspended at a fixed position were available from the Offshore Code Comparison Collaboration, Continued, with Correlation (OC5) project, Phase Ia. These measurements were compared to computational fluid dynamics (CFD) simulations based on the solution of Reynolds-averaged Navier-Stokes (RANS) equations, as implemented in STAR-CCM+. The study encompassed a sensitivity analysis of the loads computed in STAR-CCM+ based on wave modeling, boundary conditions, turbulence modeling, and spatial and temporal discretization. The analysis was supplemented by results generated with the offshore wind turbine engineering software OpenFAST, based on a hybrid combination of second-order potential flow and viscous drag from Morison’s equation. The focus of the investigation was on the assessment of the accuracy of the computation of first- and higher-order hydrodynamic loads. Substantial differences were observed in the numerical prediction of the second and third harmonic force contribution. Local flow field analysis with CFD was applied to study the physics of wave run-up and diffraction dynamics to identify the causes.

This work describes an automated condition monitoring framework to process and analyze vibration data measured on wind turbine gearboxes. The current state-of-the-art in signal processing often leads to a large quantity in health indicators thanks to the multiple potential pre-processing steps. Such large quantities of indicators become unfeasible to inspect manually when the data volume and the number of monitored turbines increases. Therefore, this paper proposes a hybrid analysis approach that combines advanced signal processing methods with machine learning and anomaly detection. This approach is investigated on an experimental wind turbine gearbox vibration data set. It is found that the combination of physics-based statistical indicators with machine learning is capable of detecting planetary gear stage damage and significantly simplifying the data analysis and inspection in the process.