Coastal Engineering最新文献

Tropical cyclones are one of the most destructive natural phenomena, causing tremendous coastal disasters worldwide. The maximum intensity of tropical cyclones is determined by momentum and heat transfer at the air-sea interface. Momentum transfer corresponds to the momentum loss of tropical cyclones and, consequently, to the underlying ocean's momentum gain causing extreme ocean waves and storm surges. Air-side observations of wind profiles and ocean-side observations of ocean subsurface currents show a slowdown of momentum transfer under high tropical cyclone wind speeds in the previous studies. However, there is still disagreement regarding the slowdown owing to lack of data. Here, we show momentum transfer under high wind speed conditions by observing ocean waves. Although ocean wave observations are highly spatially limited, we deployed a fleet of drifting ocean wave buoys covering the active area of tropical cyclones in the Western North Pacific. The buoy fleet captured extreme waves near the eye of the strongest category 5 tropical cyclone, indicating an ocean wave footprint of the momentum transfer saturation above surface wind speeds of 25 m/s. Our approach from ocean surface wave observation is a unique contribution to determination on air-sea momentum transfer slowdown under extreme wind speeds, which can compensate for the knowledge from conventional air and ocean-side observations. This finding advances tropical cyclones, extreme ocean waves, and storm surge modeling.

Foredunes provide many environmental and ecosystem services including protection from wave erosion and flooding hazards during storm events. While the impact of human interventions on the short-term evolution of coastal dunes is reasonably well understood, less is known about their contemporary influence on current wind and sediment dynamics several decades after implementation. The coastal dunes in Leucate (SE, France) have been anthropogenically constructed and are dominated by offshore wind conditions. Since their construction 20 years ago, a distinct variation in their longshore morphology has developed that is inherited from its original construction. The northern part of the dune has a symmetrical profile with a 28° degree stoss slope, 30° lee slope and a single crest. The southern part is asymmetric, with a gentler stoss slope (12°), 26° lee slope, and a double crest. To explore the potential geomorphic impacts of this distinct difference in morphology, several numerical simulations with varying wind speeds and direction were conducted. We used Computational Fluid Dynamics (CFD) to explore the spatial variations of the near surface wind flow, shear stress and aeolian sediment transport.

Results

show that for each scenario, near surface wind speed accelerated toward the dune crest on the windward slope of the dune. The maximum wind speed varied with incident wind direction, the highest speeds occurring when incident wind flow was perpendicular to the dune crest. The double crest in the southern section of the dune affected the wind flow by inducing two consecutive speeds-up zones, with a greater maximum wind speed than on the single crested dune. Wind flow separation was observed where a steep lee slope was present (single crested dune), and only during perpendicular winds. This suggests that the shape of the dune and the direction of the wind are key parameters rather than wind speed. The area affected by reversed separated flow was spatially limited and did not extend beyond the dune toe but was below the threshold for aeolian sediment transport. Elsewhere in the lee of the dune, the wind was only deflected by an order of 15° for the oblique winds (310 and 330°), and less than 10° for the perpendicular wind (290°) on the southern part. In these locations, the shear velocity exceeded the threshold, notably on the southern dune, which coincided with the formation of undulating aeolian deposits in the lee of vegetation on the dune crest. The spatial differences observed in wind flow and aeolian sediment transport processes on this human-made dune were directly inherited from differences in their construction two decades ago. These results demonstrate the importance of the constructed dune profile, due to its potential impact on the long-term evolution of the landscape and the sediment budget of the system.

Determining the friction threshold velocity (FTV) of wind-induced erosion is crucial to understanding and predicting the morphodynamics and management of foreshores and dunes. However, the FTV is influenced by multiple factors, including particle size, mineralogy, surface roughness, and moisture content. Although existing models account for these parameters, they suffer from limited precision, are not generalized and developed for specific sediment types, and rely on expensive and time-consuming testing procedures. Furthermore, no predictive equations for FTV currently consider the combined effects of bed inclination and moisture common to coastal dunes. This study presents a comprehensive closed-form model for predicting the FTV in the onset of wind erosion for different types of sands. The model considers various geometric and material properties, including cohesion, moisture, soil packing, slope, and grain size distribution. A soil water retention curve (SWRC) is incorporated into the formulation to establish a relationship between water content and sediment shear strength. This simple SWRC approach enables simplified calculations of the onset of wind erosion under various conditions, requiring only a few inexpensive inputs. Extensive parametric wind tunnel experiments were conducted to measure the FTV in combinations of bed slope, sand particle size, moisture, and density. The findings indicate that the combined influence of slope and moisture increases the FTV. Furthermore, compared to the FTV for dry sediments on a horizontal bed, the amplification factor exhibits a nonlinear combination of the effects of inclination and moisture. The proposed FTV predictive model demonstrates adequate agreement with published results when applied to scenarios such as dry sand on a horizontal surface, dry sand on an inclined bed, and moist sand on a horizontal surface.

There is a lack of research in the existing literature regarding the scour around foundations for offshore wind turbines under tidal currents, which primarily relies on laboratory experiments with simplified flow velocity hydrographs like square tidal currents. To improve the prediction accuracy of scour development under tidal currents, a series of experiments were conducted to investigate the local scour process around a pile foundation under two typical tidal velocity hydrographs (sinusoidal and square tidal currents) in a specially designed fluid-structure-soil coupling flume. The results demonstrate that reciprocating tidal currents lead to a continuously evolving process of sediment erosion and backfilling around the pile. Although the shapes of the scour holes are similar between sinusoidal and square tidal currents, there are significant differences in the evolving process of the scour depth, presenting a short-platform shape and serrated shape, respectively. A consistent relationship is found between the dimensionless scour depth and the dimensionless effective flow work (DFW) under both tidal and unidirectional currents. An equivalent velocity expression for sinusoidal and square tidal currents is proposed and verified using existing experimental data. Furthermore, an empirical expression for the scour depth reduction coefficient between square tidal currents and unidirectional currents is proposed. These outcomes not only establish a theoretical approach for simplifying tidal currents hydrographs in laboratory experiments, but also provide practical guidance for assessing the tidal currents-induced scour development around pile foundations for in-situ offshore wind turbines.

Pressure and aeration measurements obtained under storm conditions on the steep-fronted masonry wall of a rubble-mound breakwater are analysed in detail, and the results compared with those obtained using a 1:4 scale freshwater model of the field test site. New insights are gained into the complex behaviour of the most violent impacts, with particular attention given to aeration and scale effects.

The existence in the field of both low-aeration (LA) and high-aeration (HA) impacts is confirmed and new parameters introduced to facilitate further analysis. Maximum pressures (P_max) up to 771 kPa are categorised and the magnitudes of the resultant impulses found to depend mainly on their durations. The alternate expansion and recompression (ERC) of air following a HA impact is shown to apply significant oscillatory pressures and forces to the wall. Information on the magnitude, period and damping of these oscillations is presented.

The model results are initially scaled in accordance with the Froude law. In conditions comparable to those in the field, the highest pressure on the sloping wall is again found to occur in HA impacts with P_max ≤ 3.17 MPa followed by ERC oscillations. Like those in the field, the oscillations at different elevations tend to come into phase with each other and can subject the wall to oscillatory forces of significant vertical extent. Both the initial excursion and the damping of the oscillations tend be greater in the model than in the field. The maximum forces on the wall also tend to be greater than those on the field breakwater, but the durations of the impulses tend to be shorter. This apparent trade-off between force and duration may indicate that the model is responding differently to the momentum flux of the incoming waves. P_max ≤ 5.42 MPa are obtained when the model wall is vertical.

Because the Froude law does not scale aeration effects correctly, model data are also scaled in accordance with the Bagnold-Mitsuyasu (B-M) law which increases the highest P_max for the vertical wall to 20.97 MPa. An alternative assessment of the ERC oscillations is also made on the assumption that the trapped-air pockets are geometrically similar to ones that could occur in the field.

Likely generic characteristics of violent wave-impacts are identified as are probable model scale-effects. Impact-pressure reduction curves derived from a numerical model are presented to emphasise the influence of entrained air on wave loading. Further work is recommended.

Physics simulation results of natural processes usually do not fully capture the real world. This is caused for instance by limits in what physical processes are simulated and to what accuracy. In this work we propose and analyze the use of an LSTM-based deep learning network machine learning (ML) architecture for capturing and predicting the behavior of the systemic error for storm tide forecast models with respect to real-world water elevation observations from gauge stations during hurricane events. The overall goal of this work is to predict the systemic error of the physics model and use it to improve the accuracy of the simulation results post factum (i.e., to correct the model bias). We trained our proposed ML model on a dataset of 61 historical storms in the coastal regions of the south and southeastern U.S. and we tested its performance in bias correcting modeled water level data predictions from Hurricane Ian (2022). We show that our model can consistently improve the forecasting accuracy for Hurricane Ian – unknown to the ML model – at the majority of gauge station coordinates. Moreover, by examining the impact of using different subsets of the initial training dataset, containing a number of relatively similar or different hurricanes in terms of hurricane track, we found that we can obtain similar quality of bias correction by only using a subset of six hurricanes. This is an important result that implies the possibility to apply a pre-trained ML model to real-time hurricane forecasting results with the goal of bias correcting and improving the forecast accuracy. The presented work is an important first step in creating a bias correction system for real-time storm tide forecasting applicable to the full simulation area. It also presents a highly transferable and operationally applicable methodology for improving the accuracy in a wide range of physics simulation scenarios beyond storm tide forecasting.

This study employs the large-eddy simulation (LES) method to investigate the interaction of submarine sediment flows with extensive shear behavior and ambient water. This method is validated with good accuracy by simulating the head velocity and evolution geometries of a submarine mud flow with non-Newtonian fluid characteristics and a submarine turbidity current with Newtonian fluid characteristics in inclined and regular lock-exchange flume experiments. This study finds that the violent mass transfer at the interface of the submarine sediment flow and seawater is caused by numerous eddies, which significantly alter the submarine sediment flow's geometry, resulting in varying degrees of undulation, including the deposition pattern of the submarine sediment flow tail. The acceleration zone, where the velocity of the submarine sediment flow increases significantly at this undulation, propels the sediment flow forward, supporting its long-distance transport. Furthermore, the turbulence and mass transport characteristics of submarine turbidity currents with low dynamic viscosity Newtonian fluid characteristics are stronger than those of submarine mud flows with high dynamic viscosity non-Newtonian fluid characteristics. Therefore, when submarine landslides develop into later stages, such as submarine turbidity currents with high velocity, large volume, and long run-out distance characteristics, more attention must be given to the mass transport process.

Embryonic dunes, continuous dunes and classical beach nourishment are tested as soft coastal protection measures in the vulnerable Trabucador barrier beach located in the NW Mediterranean Sea against different storm conditions. The beach was impacted by severe breaching events during past storms. Evaluation of the performance of the dunes and nourishment as coastal protection measures for the barrier beach is carried out using XBeach model for three different storm events: Storm Isaak being a mid-tier double peak storm, Storm Filomena a typical larger storm of the region and Storm Gloria the largest ever storm to hit the region, with 7, 12 and 60 years of return period respectively. The model showed embryonic dunes and shoreface nourishment systems greatly protect the beach against Storm Isaak and Storm Filomena but did not withstand Storm Gloria considering it being almost 1.5 times larger than the second-highest storm in terms of significant wave height. The study aids in assessing the effectiveness of various mitigation actions for barrier beaches, with the aim of implementing them in practical field applications.

The weakly-compressible smoothed particle hydrodynamics (WCSPH) models offer distinct advantages in simulating free-surface flow. Within the rapidly evolving WCSPH field, Classical WCSPH model, based on the artificial viscous term, and its derived models, which additionally introduce numerical diffusive terms into the continuity equations - including the δ-SPH, δ-SPH^C, δ-SPH^C+, δ-LES-SPH, and δ-SPH^F models have gained prominence recently. The numerical diffusive term is found to alter the particle distributions in the free-surface region, leading to a change in the mean water level that reflects the volume conservation, which might result in inaccuracies in some simulations. This study evaluates the volume conservations of the aforementioned WCSPH models for flows at quasi-hydrostatic states evolved from varying levels of flow violence under prolonged simulations, through a series of numerical tests involving hydrostatic, standing-wave, and dam-break cases. For the hydrostatic and standing-wave cases, the performance of different types of WCSPH models remains consistent overall. The Classical WCSPH and δ-LES-SPH models exhibit minimal changes in volume, with almost no decrease in the mean water level occurring. The δ-SPH, δ-SPH^C, δ-SPH^C + models demonstrate decreases in the mean water level converging to around 0.2 times the SPH particle diameter (Δx), indicating favorable volume conservation. Conversely, the δ-SPH^F model consistently exhibits a decrease in the mean water level exceeding 1 Δx at t = 2000s in a linear fashion, resulting in a noticeable reduction in volume. Under the dam-break case, most of the mean water levels simulated by different models experience a small increase, which is close to the decrease observed under the hydrostatic and standing-wave cases with corresponding models. Only the δ-SPH^F model continues to show a continuous decreasing tendency. In summary, considering volume conservation, the δ-LES-SPH model demonstrates the best performance (excluding the Classical WCSPH model as it cannot simulate violent flow), followed by the δ-SPH^C, δ-SPH^C+, δ-SPH and δ-SPH^F models.

The abundant spectral data provided by satellite technology are crucial for interpreting the complex marine environment, and the effective and accurate analysis of these data is particularly important for coastal engineering. In this regard, this study proposes a Physically Informed ViT-GAN (PI-ViT-GAN) automatic partitioning method, based on CFOSAT satellite wave spectrum data. Specifically, the model consists of a generator and discriminator. The generator utilizes a contrastive learning strategy as pretraining and through the self-attention mechanism of the ViT model, it focuses on key parts of the spectrum to extract wave group features and wave element parameters. Partitioning-head joint training realizes the output of wave group partition element indices. Subsequently, the discriminator uses the wave group features and a parametric model for spectrum reconstruction and computes the error with the original observed spectrum to evaluate the partition and reconstruction effects. Additionally, this model incorporates two physically corrected functions, wave system classification loss and merging loss, based on the wave age criterion, thereby guiding the training process, and enhancing model efficiency. The results indicate that the reconstructed theoretical spectrum, obtained through the utilization of this method, aligns well with the original sea wave spectrum, demonstrating a precision superior to the spectral partitioning product of CFOSAT's own SWIM. Combining the robust learning capability of the transformer and the regularization of physical prior knowledge, this model can achieve precise, low-cost automated analysis of satellite wave spectra, providing a new scalable method for big data analysis in marine and coastal engineering.