Search Results (62)

Extreme surface winds and wave heights of tropical cyclones (TCs)—pose serious threats to coastal community, infrastructure and environments. In recent decades, progress in numerical wave modeling has significantly enhanced the ability to reconstruct and predict wave behavior. This review offers an in-depth overview of TC-related wave modeling utilizing different computational schemes, with a special attention to WAVEWATCH III (WW3) and Simulating Waves Nearshore (SWAN). Due to the complex air–sea interactions during TCs, it is challenging to obtain accurate wind input data and optimize the parameterizations. Substantial spatial and temporal variations in water levels and current patterns occurs when coastal circulation is modulated by varying underwater topography. To explore their influence on waves, this study employs a coupled SWAN and Finite-Volume Community Ocean Model (FVCOM) modeling approach. Additionally, the interplay between wave and sea surface temperature (SST) is investigated by incorporating four key wave-induced forcing through breaking and non-breaking waves, radiation stress, and Stokes drift from WW3 into the Stony Brook Parallel Ocean Model (sbPOM). 20 TC events were analyzed to evaluate the performance of the selected parameterizations of external forcings in WW3 and SWAN. Among different nonlinear wave interaction schemes, Generalized Multiple Discrete Interaction Approximation (GMD) Discrete Interaction Approximation (DIA) and the computationally expensive Wave-Ray Tracing (WRT) A refined drag coefficient (C_d) equation, applied within an upgraded ST6 configuration, reduce significant wave height (SWH) prediction errors and the root mean square error (RMSE) for both SWAN and WW3 wave models. Surface currents and sea level variations notably altered the wave energy and wave height distributions, especially in the area with strong TC-induced oceanic current. Finally, coupling four wave-induced forcings into sbPOM enhanced SST simulation by refining heat flux estimates and promoting vertical mixing. Validation against Argo data showed that the updated sbPOM model achieved an RMSE as low as 1.39 m, with correlation coefficients nearing 0.9881. Full article

Currently, the RANS (Reynolds-Averaged Navier–Stokes) method is widely recognized as a prevalent approach for computing ship maneuvering forces and moments. Obtaining hydrodynamic derivatives using pure RANS is time-consuming, especially with rotating propellers. A reasonable simplification of the propeller is usually necessary to improve simulation efficiency. The ITTC suggests both the discretized propeller model (DPM) and the body-force model (BFM) for RANS simulations. While BFM offers computational efficiency, it may not accurately represent large-amplitude ship maneuvers. It is quite significant to figure out how BFM affects numerical accuracy. This study compares the DPM and a very simple BFM in RANS simulations of the KCS (KRISO Container Ship), focusing on static rudder, drift, and circle motion tests. The main purpose is to check the differences between the simulated results by using the BFM and DPM. While side forces and yaw moments from both models are similar, discrepancies in longitudinal forces increase with higher rudder angles, drift angles, or turning rates. Errors in side forces and yaw moments are under 10% for both models, compared with experimental data. But BFM’s longitudinal force errors exceed 20% at large motion amplitudes, indicating reduced accuracy compared to DPM. The results of the BFM method are subject to two main sources of error. First, the lack of physical shape representation for the propeller blades leads to the absence of lather force during rotation. This in turn results in an inaccurate prediction of the interaction between the propeller blade root or blade tip leakage vortices and the rudder. Second, the limitations of the adopted model prevent it from accurately providing the thrust and torque generated by the propeller under actual operating conditions. Full article

This paper presents an experimental and numerical investigation of submerged vegetation flow, with a particular focus on vegetation-related terms, especially in the vicinity of the free end. Experimental results indicate that substantial shear stress is observed near the top of vegetation, where the drag coefficient increases significantly due to the disturbance caused by the free end. Furthermore, wake generation is notably suppressed, particularly at heights where wake-generated turbulence dominates, leading to a reduction in turbulent kinetic energy (TKE). A numerical model based on the volume-averaged Reynolds-averaged Navier–Stokes (VARANS) equations was developed, incorporating a vertically varying drag coefficient. The two-scale $⟨k⟩-⟨\epsilon ⟩$ turbulence model is further modified with the inclusion of a new damping function to capture the suppression of wake generation. The model accurately simulates both unidirectional and oscillatory flows, as well as the associated turbulence structures, with good agreement with experimental measurements. The influence of the tips on wave-induced currents, mass transport and TKE distribution is also investigated. It was found that the tip effects play a significant role in strengthening wave-induced currents at the top of loosely arranged, short, and sparse vegetation, with shear kinetic energy (SKE) serving as a critical component of TKE, contributing to the nonuniform distribution. Both Eulerian currents and Stokes drift contribute to streaming in the direction of wave propagation near the vegetation top, which intensifies with increasing solid volume fraction, while tip effects further enhance the onshore mass transport. Within the vegetation, mass transport is more sensitive to wave period and wave height, shifting from onshore to offshore as wavelength increases under constant water depth. Full article

The Fokker–Planck (FP) equation represents the drift and diffusive processes in kinetic models. It can also be regarded as a model for the collision integral of the Boltzmann-type equation to represent thermo-hydrodynamic processes in fluids. The lattice Boltzmann method (LBM) is a drastically simplified discretization of the Boltzmann equation for simulating complex fluid motions and beyond. We construct new two FP-based LBMs, one for recovering the Navier–Stokes equations for fluid dynamics and the other for simulating the energy equation, where, in each case, the effect of collisions is represented as relaxations of different central moments to their respective attractors. Such attractors are obtained by matching the changes in various discrete central moments due to collision with the continuous central moments prescribed by the FP model. As such, the resulting central moment attractors depend on the lower-order moments and the diffusion tensor parameters, and significantly differ from those based on the Maxwell distribution. The diffusion tensor parameters for evolving higher moments in simulating fluid motions at relatively low viscosities are chosen based on a renormalization principle. Moreover, since the number of collision invariants of the FP-based LBMs for fluid motions and energy transport are different, the forms of the respective attractors are quite distinct. The use of such central moment formulations in modeling the collision step offers significant improvements in numerical stability, especially for simulations of thermal convective flows under a wide range of variations in the transport coefficients of the fluid. We develop new FP central moment LBMs for thermo-hydrodynamics in both two and three dimensions, and demonstrate the ability of our approach to simulate various cases involving thermal convective buoyancy-driven flows especially at high Rayleigh numbers with good quantitative accuracy. Moreover, we show significant improvements in the numerical stability of our FP central moment LBMs when compared to other existing central moment LBMs using the Maxwell distribution in achieving high Peclet numbers for mixed convection flows involving shear effects. Full article

Stokes drift refers to the net horizontal displacement of water particles under the influence of wave action, playing a crucial role in the transport of heat, salt, nutrients, and pollutants in the ocean. Accurate estimation of Stokes drift is essential for understanding ocean dynamics and material transport. This study utilizes two deep learning models (Earthformer and ConvLSTM) to predict surface Stokes drift, using wind and water depth as input variables. We designed three control experiments to evaluate the impact of different training objectives on the experimental results. In Exp. 1, the model used the two Stokes drift components (u^s, v^s) as the training objectives. In Exp. 2, the objectives were the two components (u^s, v^s) plus the direction θ. In Exp. 3, the model employed the magnitude $\left|{\mathbf{u}}^{\mathrm{s}}\right|$ and the direction $\theta$ of the Stokes drift as the training objectives. The results indicate that using the magnitude and direction (Exp. 3) significantly reduces the RMSE for magnitude, direction, and each component (u^s, v^s) by up to 33.3%, compared to the other two strategies. Moreover, the approach of choosing magnitude and direction as the training objectives can also be applied to the prediction of other vector variables, such as ocean currents and winds. Full article

Storm surge is one of the most significant marine hazards in coastal regions of Fujian, China. Previous studies show that surface waves can exacerbate storm surge by providing additional momentum and mass flux. In fact, surface wave effects on currents can be divided into conservative and non-conservative parts. However, it is unclear whether or not both kinds of wave effects are important to storm surge. In this study, we utilize an ocean circulation model coupled with surface wave forcing to investigate wave effects on the storm surge caused by Typhoon Doksuri (2305). The results indicate that both Stokes drift and wave breaking significantly contribute to the storm surge in the region located in the northeast quadrant of the typhoon’s trajectory. Wave breaking enhances the onshore current during the passage of the typhoon. This effect, combined with the onshore Stokes drift, leads to a rapid accumulation of nearshore water, thereby exacerbating storm surge. This study compares the contribution of conservative and non-conservative wave effects to the storm surge induced by Doksuri and underscores the necessity for numerical models to incorporate wave breaking and Stokes drift in order to accurately simulate and forecast storm surge. Full article

This study examines the influence of drift angle on the wave and flow field generated by a submarine navigating through a density-stratified fluid. Employing a numerical methodology, this research computed the viscous flow field around the SUBOFF bare hull under conditions of oblique shipping maneuvers. The analytical framework relies on the Reynolds-Averaged Navier–Stokes (RANS) equations, supplemented by the Re-Normalization Group (RNG) k-ε turbulence model and the Volume of Fluid (VOF) method. The initial phases of this study involved verifying grid convergence and the accuracy of the numerical methods used. Subsequently, numerical simulations were performed across a spectrum of drift angles while maintaining a fixed Froude number of F_n = 0.5, with submergence depths set at 1.1 D and 2.0 D. The analysis focused on the wave profiles at both the free surface and the internal surface. The results indicate that the presence of a drift angle produces significant alterations in the characteristics of the free surface and internal surface when compared with straight-ahead motion. Specifically, the asymmetry in the flow field is enhanced, and the variability in the roughness of the free surface is pronounced. Full article

This article studies the general properties of the Stokes drift field. This name is commonly used for the correction added to the mean Eulerian velocity for describing the averaged transport of the material particles by the oscillating fluid flows. Stokes drift is widely known mainly in connection with another feature of oscillating flows known as steady streaming, which has been and remains the focus of a multitude of studies. However, almost nothing is known about Stokes drift in general, e.g., about its energy or helicity (Hopf’s invariant). We address these quantities for acoustic drift driven by simple sound waves with finite discrete Fourier spectra. The results discover that the mean drift energy is partly localized on a certain resonant set, which we have described explicitly. Moreover, the mean drift helicity turns out to be completely localized on the same set. We also present several simple examples to discover the effect of the power spectrum and positioning of the spectral atoms. It is revealed that tuning them can drastically change both resonant and non-resonant energies, zero the helicity, or even increase it unboundedly. Full article

We present a new formulation of the central moment lattice Boltzmann (LB) method based on a minimal continuous Fokker-Planck (FP) kinetic model, originally proposed for stochastic diffusive-drift processes (e.g., Brownian dynamics), by adapting it as a collision model for the continuous Boltzmann equation (CBE) for fluid dynamics. The FP collision model has several desirable properties, including its ability to preserve the quadratic nonlinearity of the CBE, unlike that based on the common Bhatnagar-Gross-Krook model. Rather than using an equivalent Langevin equation as a proxy, we construct our approach by directly matching the changes in different discrete central moments independently supported by the lattice under collision to those given by the CBE under the FP-guided collision model. This can be interpreted as a new path for the collision process in terms of the relaxation of the various central moments to “equilibria”, which we term as the Markovian central moment attractors that depend on the products of the adjacent lower order moments and a diffusion coefficient tensor, thereby involving of a chain of attractors; effectively, the latter are nonlinear functions of not only the hydrodynamic variables, but also the non-conserved moments; the relaxation rates are based on scaling the drift coefficient by the order of the moment involved. The construction of the method in terms of the relevant central moments rather than via the drift and diffusion of the distribution functions directly in the velocity space facilitates its numerical implementation and analysis. We show its consistency to the Navier-Stokes equations via a Chapman-Enskog analysis and elucidate the choice of the diffusion coefficient based on the second order moments in accurately representing flows at relatively low viscosities or high Reynolds numbers. We will demonstrate the accuracy and robustness of our new central moment FP-LB formulation, termed as the FPC-LBM, using the D3Q27 lattice for simulations of a variety of flows, including wall-bounded turbulent flows. We show that the FPC-LBM is more stable than other existing LB schemes based on central moments, while avoiding numerical hyperviscosity effects in flow simulations at relatively very low physical fluid viscosities through a refinement to a model founded on kinetic theory. Full article

In this study, a novel algorithm to retrieve the current speed along the range direction under extreme sea states is developed from C-band synthetic aperture radar imagery. To this aim, a Sentinel-1 (S-1) dual-polarized synthetic aperture radar (SAR) dataset consisting of 2300 images is collected during 200 tropical cyclones (TCs). The dataset is complemented with collocated wave simulations from the Wavewatch-III (WW3) model and reanalysis currents from the HYbrid Coordinate Ocean Model (HYCOM). The corresponding TC winds are officially released by IFRMER, while the Stokes drift following the wave propagation direction is estimated from the waves simulated by WW3. In this study, first the dependence of wind, Stokes drift, and range current on the Doppler centroid anomaly is investigated, and then the extreme gradient boosting (XGBoost) machine learning model is trained on 87% of the S-1 dataset for range current retrieval purposes. The rest of the dataset is used for testing the retrieval algorithm, showing a root mean square error (RMSE) and a correlation coefficient (r) of 0.11 m/s and 0.97, respectively, with the HYCOM outputs. A validation against measurements collected from two high-frequency (HF) phased-array radars is also performed, resulting in an RMSE and r of 0.12 m/s and 0.75, respectively. Those validation results are better than the 0.22 m/s RMSE and 0.28 r achieved by the empirical CDOP model. Hence, the experimental results confirm the soundness of the XGBoost, exhibiting a certain improvement over the empirical model. Full article

In order to address the issue of limited common coverage and high cost in mapping ocean surface vector current by two (or more) high-frequency surface wave radars, this paper proposes a single-station surface wave radar vector current inversion algorithm. The feasibility of this algorithm has been validated in the Taiwan Strait. Based on the ocean dynamic characteristics of the Taiwan Strait, the algorithm utilizes the radial current obtained from a high-frequency surface wave radar (HFSWR) in Fujian Province to invert the ocean surface vector current. The surface vector current can be decomposed into three primary dynamic components: tidal currents, wind-driven currents, and geostrophic currents. Firstly, tidal current forecasting models and Ekman and Stokes theories are used to calculate the tidal and wind-driven currents in the Taiwan Strait, respectively. Subsequently, the directions of geostrophic currents in the Taiwan Strait are determined with sea surface height data, and the magnitudes of the geostrophic currents are constrained using the radial current from the single HFSWR. Finally, the three components are added together to obtain the vector current. Comparative results demonstrate that the efficacy of the algorithm has been validated through field experiments (with two HFSWRs and two drifting buoys) conducted in the southwestern of the Taiwan Strait. Further research is needed on the applicability of this algorithm to other sea areas and monitoring systems. Full article

Drifting fish aggregating devices (DFADs) can significantly enhance fishing efficiency and capability. Conventional drifting devices are prone to degradation in harsh marine environments, leading to marine waste or pollution. In this study, we develop a biodegradable DFAD (Bio-DFAD) to minimise negative impacts on marine ecology. To investigate the hydrodynamic performance of the proposed device, numerical modelling involving the unsteady Reynolds-averaged Navier–Stokes equation has been conducted, in which a realisable k–ε model is applied to consider the turbulence effect. The response amplitude operators, which are key parameters for design, are obtained for heave and pitch motions. The hydrodynamic performance is found to be sensitive to the relative length, relative diameter, and wave steepness, but they are less sensitive to the relative current velocity. This work provides some scientific insights for practical applications. Full article

Fish Aggregating Devices (FADs) are essential supplementary structures used in tropical tuna purse-seine fishing. They are strategically placed to attract tuna species and enhance fishing productivity. The hydrodynamic performance of FADs has a direct effect on their structural and environmental safety in the harsh marine environment. Conventional FADs are composed of materials that do not break down naturally, leading to the accumulation of waste in the ocean and potential negative effects on marine ecosystems. Therefore, this work aimed to examine the hydrodynamic performance of biodegradable drifting FADs (Bio-DFADs) in oceanic currents by numerical modelling. The Reynolds-averaged Navier–Stokes equation was used to solve the flow field and discretized based on the realizable k-ε turbulence model, employing the finite volume method. A set of Bio-DFADs was developed to assess the hydrodynamic performance under varying current velocities and attack angles, as well as different balsa wood diameters and sinker weights. The results indicated that the relative current velocity significantly affected the relative velocity of Bio-DFADs. The relative length of the raft significantly affected both the relative velocity and the relative wetted area in a pure stream. Finally, the diameter of the balsa wood affected the drift velocity, and the sinker’s relative weight affected the hydrodynamic performance of the Bio-DFADs. Full article

With the continuous increase in ship size combined with the generally slower increase in the sizes of waterways, the need for the prediction of ship maneuvering in shallow waterways continues to attract attention from the international scientific community. Ship behavior in shallow water is relevant in seabed effects that result in changing the hydrodynamic forces acting on a ship. In this study, the maneuvering characteristics of a container ship with four degrees of freedom in shallow water are analyzed. The Reynolds-Averaged Navier Stokes approach in Ansys Fluent code is used to produce the maneuvering coefficients through the simulations of forward running, static drift, static heel, circular motion, the combined motions, and the pure roll motion of the KRISO container ship. The maneuvering characteristics of the ship are estimated for evaluating the ship behaviors in shallow-water conditions. The obtained results show that the roll has a significant decrease and the ship’s turning diameter has a significant increase when the ship operates in a shallow waterway. The predicted maneuvering characteristics of the ship are in good agreement with those of free-running model tests, indicating that the numerical simulation based on the Computational Fluid Dynamics method has good capability to predict the maneuvering derivatives and the four-DOF ship maneuvering motion in shallow water as well. Full article

This study explores the near-surface dispersion mechanisms of contaminants in coastal waters, leveraging a comprehensive method that includes using dye and drifters as tracers, coupled with diverse observational platforms like drones, satellites, in situ sampling, and HF radar. The aim is to deepen our understanding of surface currents’ impact on contaminant dispersion, thereby improving predictive models for managing environmental incidents such as pollutant releases. Rhodamine WT dye, chosen for its significant fluorescent properties and detectability, along with drifter data, allowed us to investigate the dynamics of near-surface physical phenomena such as the Ekman current, Stokes drift, and wind-driven currents. Our research emphasizes the importance of integrating scalar tracers and Lagrangian markers in experimental designs, revealing differential dispersion behaviors due to near-surface vertical shear caused by the Ekman current and Stokes drift. During slow-current conditions, the elongation direction of the dye patch aligned well with the direction of a depth-averaged Ekman spiral, or Ekman transport. Analytical calculations of vertical shear, based on the Ekman current and Stokes drift, closely matched those derived from tracer observations. Over a 7 h experiment, the vertical diffusivity near the surface was first observed at the early stages of scalar mixing, with a value of $1.9\times {10}^{-4} {\mathrm{m}}^2/\mathrm{s}$, and the horizontal eddy diffusivity of the dye patch and drifters reached the order of 1 ${\mathrm{m}}^2/\mathrm{s}$ at a 1000 $\mathrm{m}$ length scale. Particle tracking models demonstrate that while HF radar currents can effectively predict the trajectories of tracers near the surface, incorporating near-surface currents, including the Ekman current, Stokes drift, and windage, is essential for a more accurate prediction of the fate of surface floats. Full article