Search Results (65)

This study investigates the response of laterally loaded pile foundations embedded in sloping beds under scour conditions, which is vital for the design and stability of coastal and offshore infrastructure like sea-crossing bridges, offshore wind turbines, and wharves. While previous studies have focused on scour-affected pile performance in horizontal beds, this research expands the scope by incorporating sloped beds and corresponding scour effect, which are common in coastal and offshore environments. A three-dimensional finite element model was established to evaluate the pile foundation’s lateral load-bearing capacity under different slope and scour conditions, according to preceding flume tests on the mechanism of local scour around a pile in sloping bed. The results indicate that the lateral response of the pile is significantly influenced by the seabed slope and scour depth. A negatively inclined seabed weakens the interaction between the pile and the surrounding sediment, thereby reducing the lateral bearing capacity and bending moment. As the scour depth increases, the support provided by the soil further weakens, intensifying the reduction in lateral resistance. This effect is particularly pronounced for steep negative slopes, where the combined impact of slope and scour has a more significant detrimental effect. Full article

Extreme events such as tropical cyclones frequently occur in coastal areas in China. With high wind speeds and rainfall during such extreme events, the vehicles on sea-crossing bridges may face severe instability problems. In this study, the dynamics of vehicles on a cross-sea bridge under the wind–rain coupling effect were analyzed based on field measurement data using computational fluid dynamics (CFD). Wind field parameters of the coastal area in China were obtained using wind speed data from measurement towers. Based on CFD, the sliding grid method was applied to establish an aerodynamic analysis model of a container truck moving on a bridge under wind and rain conditions. The discrete phase model based on the Euler–Lagrange method was used to investigate the influence of rain and obtain the aerodynamic characteristics of the truck under the coupled wind and rain effects. Based on the computational analysis results, considering the turbulence intensity, the yaw angle peaks of the tractor and trailer increased by 5.2% and 3.8%, respectively, and the lateral displacement of the truck’s center of mass increased by 9.8%. Rainfall may cause the vehicle to have a higher response, resulting in a high risk of skidding. The results show that skidding occurs for the considered container truck when rainfall is at 9.8%. These results can provide parameters for traffic control strategies under such extreme climate events in coastal areas. Full article

Local scour is a phenomenon of sediment erosion and transport caused by the dynamic interaction between water flow and seabed sediment, posing a serious threat to the safety of marine engineering structures such as cross-sea bridges and offshore wind turbines. To improve scour prediction and prevention capabilities, this review systematically analyzes the influence mechanisms of factors such as hydrodynamic conditions, sediment characteristics, and structural geometry, and discusses scour protection measures. Based on this, a comprehensive evaluation of the applicability of different prediction methods, including traditional empirical formulas, numerical simulations, probabilistic prediction models, and machine learning (ML) methods, was conducted. The study focuses on analyzing the limitations of existing methods: empirical formulas lack adaptability under complex field conditions, numerical simulation still faces challenges in validating real marine environments, and data-driven models suffer from “black box” issues and insufficient generalization capabilities. Based on the current research progress, this review presents prospects for future development, emphasizing the need to deepen the study of scouring mechanisms in complex real marine environments, develop efficient numerical models for engineering applications, and explore intelligent prediction methods that integrate data-driven approaches with physical mechanisms. This aims to provide more reliable theoretical support for the safe design, risk prevention, and scouring mitigation measures in marine engineering. Full article

Despite the existence of standardized collision regulations such as the International Regulations for Preventing Collisions at Sea (COLREGs), ship collisions continue to occur, indicating persistent gaps in how navigators interpret and apply these rules. The COLREGs are globally adopted rules that govern vessel conduct to avoid collisions. Borderline encounter situations—such as those between head-on and crossing, or overtaking and crossing—pose particular challenges, often resulting in inconsistent or ambiguous interpretations. This study models navigator awareness as a probabilistic function of encounter angle, aiming to identify interpretive transition zones and cognitive uncertainty in rule application. A structured survey was conducted with 101 licensed navigators, each evaluating simulated ship encounter scenarios with varying relative bearings. Responses were collected using a Likert scale and analyzed in angular sectors known for interpretational ambiguity: 006–012° for head on to crossing (HC) and 100–160° for overtaking to crossing (OC). Gaussian curve fitting was applied to the response distributions, with the awareness center (μ) and standard deviation (σ) serving as indicators of consensus and ambiguity. The results reveal sharp shifts in awareness near 008° and 160°, suggesting cognitively unstable zones. Risk-averse interpretation patterns were also observed, where navigators tended to classify borderline situations more conservatively under uncertainty. These findings suggest that navigator awareness is not deterministic but probabilistically structured and context sensitive. The proposed awareness modeling framework helps bridge the gap between regulatory prescriptions and real world navigator behavior, offering practical implications for MASS algorithm design and COLREGs refinement. Full article

Abnormal ship navigation behaviors in cross-sea bridge waters pose significant threats to maritime safety, creating a critical need for accurate anomaly detection methods. Ship AIS trajectory data contain complex temporal features but often lack explicit labels. Most existing anomaly detection methods heavily rely on labeled or semi-supervised data, thus limiting their applicability in scenarios involving completely unlabeled ship trajectory data. Furthermore, these methods struggle to capture long-term temporal dependencies inherent in trajectory data. To address these limitations, this study proposes an unsupervised trajectory anomaly detection model combining a transformer architecture with a variational autoencoder (transformer–VAE). By training on large volumes of unlabeled normal trajectory data, the transformer–VAE employs a multi-head self-attention mechanism to model both local and global temporal relationships within the latent feature space. This approach significantly enhances the model’s ability to learn and reconstruct normal trajectory patterns, with reconstruction errors serving as the criterion for anomaly detection. Experimental results show that the transformer–VAE outperforms conventional VAE and LSTM–VAE in reconstruction accuracy and achieves better detection balance and robustness compared to LSTM–-VAE and transformer–GAN in anomaly detection. The model effectively identifies abnormal behaviors such as sudden changes in speed, heading, and trajectory deviation under fully unsupervised conditions. Preliminary experiments using the POT method validate the feasibility of dynamic thresholding, enhancing the model’s adaptability in complex maritime environments. Overall, the proposed approach enables early identification and proactive warning of potential risks, contributing to improved maritime traffic safety. Full article

Climate-induced migration has emerged as a major concern in India and Bangladesh, due to their geographical vulnerability and socioeconomic conditions. Coastal areas, such as the Sundarbans and the Ganges–Brahmaputra Delta, face relentless threats due to rising sea levels, cyclones, and floods. These factors force millions to relocate, resulting in rural–urban transitions and cross-border movements that worsen urban challenges and socioeconomic vulnerabilities. For this, a systematic literature review of the Scopus database was undertaken using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A detailed review analysis of 65 papers was carried out. The study highlighted key climatic and non-climatic drivers of migration, including natural disasters, resource depletion, poverty, and poor governance. Despite existing adaptation strategies, such as early warning systems, micro-insurance, and climate-resilient practices, gaps remain in addressing long-term resilience and legal recognition for climate migrants. The research emphasizes the need for a holistic, multi-stakeholder approach, integrating adaptive infrastructure, sustainable livelihoods, and international cooperation. Recommendations include bridging research gaps, increasing community participation, and implementing global frameworks, like the Fund for Responding to Loss and Damage. Addressing climate migration through fair, inclusive measures is essential for building resilience and ensuring long-term development in the region. Full article

Coastal areas have been the target of interdisciplinary research aiming to support studies related to their socio-economic and ecological value and their role in protecting backshore ecosystems and assets from coastal erosion and flooding. Some of these studies focus on either onshore or inshore areas using sensors and collecting valuable information that remains unknown and untapped by other researchers. This research demonstrates how satellite, aerial, terrestrial and marine remote sensing techniques can be integrated and inter-validated to produce accurate information, bridging methodologies with different scope. High-resolution data from Unmanned Aerial Vehicle (UAV) data and multispectral satellite imagery, capturing the onshore environment, were utilized to extract underwater information in Coral Bay (Cyprus). These data were systematically integrated with hydroacoustic including bathymetric and side scan sonar measurements as well as ground-truthing methods such as drop camera surveys and sample collection. Onshore, digital elevation models derived from UAV observations revealed significant elevation and shoreline changes over a one-year period, demonstrating clear evidence of beach modifications and highlighting coastal zone dynamics. Temporal comparisons and cross-section analyses displayed elevation variations reaching up to 0.60 m. Terrestrial laser scanning along a restricted sea cliff at the edge of the beach captured fine-scale geomorphological changes that arise considerations for the stability of residential properties at the top of the cliff. Bathymetric estimations derived from PlanetScope and Sentinel 2 imagery returned accuracies ranging from 0.92 to 1.52 m, whilst UAV reached 1.02 m. Habitat classification revealed diverse substrates, providing detailed geoinformation on the existing sediment type distribution. UAV data achieved 89% accuracy in habitat mapping, outperforming the 83% accuracy of satellite imagery and underscoring the value of high-resolution remote sensing for fine-scale assessments. This study emphasizes the necessity of extracting and integrating information from all available sensors for a complete geomorphological and marine habitat mapping that would support sustainable coastal management strategies. Full article

The span of a double-deck cross-sea bridge that can be used for both highway and railway purposes is usually 1 to 16 km. Compared with small-span bridges and single-layer main girder forms, its lightweight design and low damping characteristics make it more prone to vortex-induced vibration (VIV). To predict the VIV performance of a double-deck steel truss (DDST) girder with additional aerodynamic measures, the VIV response of a DDST bridge was investigated using wind tunnel tests and numerical simulation, a learning sample database was established with numerical simulation results, and a prediction model for the amplitude of the DDST girder and VIV parameters was established based on three machine learning algorithms. The optimization algorithm was selected using root mean square error (RMSE) and the coefficient of determination (R²) as evaluation indices and further improved with a genetic algorithm and particle swarm optimization. The results show that for the amplitude prediction of the main girder, the backpropagation neural network model is the most effective. The most improved algorithm yields an RMSE of 0.150 and an R² of 0.9898. For the prediction of VIV parameters, the Random Forest model is the most effective. The RMSE values of the improved optimal algorithm are 0.017, 0.026, and 0.295, and the R² values are 0.9421, 0.8875, and 0.9462. The prediction model is more efficient in terms of computational efficiency compared to the numerical simulation method. Full article

The response of large temporary working platforms for cross-sea bridges under the action of strong wind and waves with large tidal ranges is one of the key issues in offshore engineering. Based on a grand offshore bridge project in Fujian Province of China, on-site monitoring tests were carried out on a temporary working platform. A high-precision and fully automatic monitoring system was adopted to conduct the all-weather and high-frequency monitoring on vibrations, responses, and sea conditions of the platform, enabling us to grasp its structural mechanical characteristic and ensuring the platform safety. The results show that, under the severe sea conditions of typhoons, the stress of the platform structure increases significantly with the increase in the tidal range and reaches its maximum value at the high tide level. The inclination angle changes violently at the high tide level, while the amplitude of inclination angle change is relatively small at the low tide level. The effective value of the platform displacement under the severe sea conditions of typhoon meteorology is much larger than that under normal sea conditions. Compared with the low tide level, the acceleration of the offshore temporary work platform changes more drastically at the high tide level under severe sea conditions. Under severe sea conditions, the tidal level has a significant impact on the frequency corresponding to the peak value of the acceleration power spectrum of the offshore temporary platform. Full article

Large-span precast prestressed concrete box girders have been widely used in bridge construction near or across the sea. However, this would easily lead to a hydration heat problem, including large initial tensile stress and concrete cracks during the stage of concrete pouring. A 5 m long segment of the prestressed concrete box girder for the Hangzhou Bay Cross-Sea Railway Bridge was continuously monitored to investigate the hydration heat effect on the long-span concrete box girder during the pouring stage of construction. The initial temperature variation and stress distribution of the concrete in the segment were analyzed through finite element analysis based on the experimental data and temperature monitoring results. A suitable concrete pouring and maintenance plan for the box girder was proposed after the comparison of several construction schemes. The results indicate that the primary cause of initial tensile stress is the temperature difference between the inner and outer surfaces of the long-span precast concrete box girder. By adding some ventilation inside the box girder with suitable maintenance measures, the initial tensile stress in the concrete can be effectively reduced, thus mitigating the risk of early cracking. Full article

High-rise pile cap structures, such as sea-crossing bridges, suffer from long-term degradation due to continuous corrosion and scour, which seriously endangers structural safety. However, there is a lack of research on this topic. This study focused on the long-term performance and dynamic response of bridge pile foundations, considering scour and corrosion effects. A refined modeling method for bridge pile foundations, considering scour-induced damage and corrosion-induced degradation, was developed by adjusting nonlinear soil springs and material properties. Furthermore, hydrodynamic characteristics and long-term performance, including hydrodynamic phenomena, wave force, energy, displacement, stress, and acceleration responses, were investigated through fluid–structure coupling analysis and pile–soil interactions. The results show that the horizontal wave forces acting on the high-rise pile cap are greater than the vertical wave forces, with the most severe wave-induced damage occurring in the wave splash zone. Steel and concrete degradation in the wave splash zone typically occurs sooner than in the atmospheric zone. The total energy of the structure at each moment under load is equal to the sum of internal energy and kinetic energy. Increased corrosion time and scour depth result in increased displacement and stress at the pile cap connection. The long-term dynamic response is mainly influenced by the second-order frequency (62 Hz). Full article

The Global Navigation Satellite System (GNSS), renowned for its high precision and automation, has shone brightly in the deformation monitoring of offshore facilities and sea-crossing bridges. However, antennas placed in these locations are often subject to signal interference from various reflective surfaces, such as rivers and oceans, which significantly compromises observation accuracy and reliability. Synthesizing previous research, we first propose a method for multipath dataset construction, which involves GNSS observation linear combinations, detailed mapping of the near-field reflector, and employed static solution residuals as reference. Subsequently, we construct and train a corresponding para-TCN (parametric Temporal Convolution Network) to enable real-time prediction of multipath prediction. Through time domain and frequency domain analysis, it has been demonstrated that the trained network can capture the main features of multipath models and suppress those components in both the data distribution and frequency band, effectively mitigating the interference of multipath errors in observations. Full article

This study examines the in-situ lateral static load behavior of a closed-diaphragm wall foundation, aiming to better understand its load–displacement response, structural behavior, and soil interaction under horizontal loading. An in-situ static load test was conducted with a maximum applied load of 70 MN, revealing that the diaphragm wall initially exhibits a linear load–displacement response, which becomes increasingly nonlinear as the load increases. The horizontal displacement of the lateral walls is nearly identical to the overall displacement of the diaphragm wall, making it a reliable indicator of the wall’s load state, particularly when it is challenging to measure total displacement. The wall behaves as a rigid body with minimal relative displacement between sections, and overturning failure is identified as the primary failure mode. Earth pressure distribution varies around the wall: passive earth pressure is observed at the front edge, while active and passive pressures alternate at the rear edge. These findings provide valuable insights into the design of diaphragm wall foundations, emphasizing the importance of lateral displacements. Full article

Vortex-induced vibration is a type of wind-induced vibration occurring frequently in large-span sea-crossing bridges under relatively low wind speeds, posing a threat to the structural fatigue performance and driving comfort. Identifying the instantaneous occurrence moments of vortex-induced vibration is a prerequisite for establishing a data-driven prediction model for vortex-induced vibration, and it is of great significance for the monitoring and early warning of vortex-induced vibration performance in bridges. To automatically detect the occurrence moments of vortex-induced vibration and establish a correlation model between vortex-induced vibration amplitude and environmental factors, this study proposes a fuzzy C-means clustering-based classification method. In order to detect the occurrence moments of vortex-induced vibration more finely, only short-term or even instantaneous structural vibration indicators were selected and transformed for distribution as clustering features. The entire detection process could be carried out unsupervised, reducing the manual cost of obtaining vortex-induced vibration information from massive monitoring data. Finally, actual vortex-induced vibration test data from a certain overseas bridge was utilized to verify the feasibility of this method. Based on the classification results, the correlation between vortex-induced vibration amplitude and environmental variables was determined, providing valuable guidance for predicting vortex-induced vibration amplitudes. Full article

In order to study the collision of sea ice on bridge piers of a sea-crossing bridge, this study establishes a finite element model of the impact of sea ice on bridge piers in aqueous media based on explicit dynamics analysis software and programming software using the arbitrary Lagrangian Eulerian (ALE) method. The results show that, when the sea-ice spacing is larger than the sea-ice edge length, the increase in sea-ice spacing leads to a decrease in the collision force and a significant increase in the probability of climbing and overturning. The increase in sea-ice mass significantly increases the impact force on the bridge abutment, and the peak value increases linearly with the increase in mass, and the sea-ice climbing and overturning phenomena are obvious. Different shapes of sea ice are obtained by cutting the sea-ice field with the two-dimensional Voronoi method, and the maximum impact force increases significantly with the increase in the average area. Irregularly shaped sea ice leads to a larger impact force and triggers the accumulation climbing phenomenon, which is verified by experiments, and the experimental values are in good agreement with the simulated values. In conclusion, this study reveals the significant effects of the spacing, mass, and shape of sea ice on the impact force of bridge piers, which provides an important reference for the design of bridge structures. Full article