Search

The increased application of Information and Communications Technology in automation and digitization is the driving concept towards the actualization of the Industrial Revolution 4.0. Many aspects of industrial design and operations including offshore engineering have been automated. However, the selection procedure of mooring design parameters including azimuth angle, pretension, diameter, fairlead slope, and mooring radius, which is a critical aspect of mooring system design has remained heavily based on a manual approach despite the availability of sophisticated hydrodynamic analysis software. Up to date, there is no proper review on optimisation techniques that have the potential of automating these procedures. In the past, some of the few available mooring optimisation procedures consider only the mooring lines for the prediction of optimal platform offset without due consideration to the integrity of the risers. Thus, the significance of adopting an integrated riser-mooring design methodology in the optimisation of mooring design variables is discussed in this paper where the integrity of the riser is adequately represented using a Safe Operation (SAFOP) zone polar diagram. We also review the developmental transition from the use of classical to Evolutionary Algorithms (EA) in the optimisation procedure. EA has been acknowledged as a practical alternative for solving mooring optimisation problems. Hence, some of the EA techniques are presented and their computational capabilities explored. In the last part, a concise review of the application of optimisation techniques for mooring optimisation of the different offshore floating platforms is presented based on their capabilities in minimizing platform offset and efficiency in terms of simulation time. So far, EA techniques like the Differential Evolution (DE), variants of Genetic Algorithms (GA) and Particle Swarm Optimisation (PSO) have been used to optimize mooring line design variables. Based on the discussions, the potentials of DE, RegPSO and other variants of PSO can be further explored for better efficiency. • Previous studies addressing differential evolution (DE), genetic algorithm (GE) and particle swarm optimisation (PSO) techniques used for optimisation of mooring parameters have been critically reviewed. • The integrated riser -mooring design methodology is effective in accounting for integrity of riser and mooring systems. • The application of evolutionary algorithms, particularly the variants and hybrids of DE ,PSO and GA, have proven to be efficient optimisation of mooring systems. • Some variants of PSO like the RegPSO have demonstrated improved capability in terms of escaping premature convergence , thereby resulting in better computational efficiency. [ABSTRACT FROM AUTHOR]

Hydraulic drive is one of the main driving methods of traditional bionic fish, which has the disadvantages of high driving pressure and significant radial expansion of the fishtail. In this research, two innovative structures are introduced in the fishtail design to overcome these drawbacks. Firstly, high-flexible origami technology is applied to the fishtail, significantly reducing the unwanted radial expansion of the fishtail and improving energy efficiency. Based on the experiments, the origami-structured fishtail can save up to 92.3% energy compared with the traditional fishtail. Secondly, according to the bionic principles, the hybrid neutral layer of the fishtail which is sandwich-structured with knitting methods was designed. The test results show that this novel hybrid neutral layer could save up to 56.7% energy compared to the fishtail with a rigid neutral layer. A bionic fish in BCF model (Body and/or Caudal Fin propulsion) is fabricated and tested in a water tank. The results prove that the new bionic fish with the innovative fishtail obtain a good straight-line swimming direction and turning ability. This study could provide an important reference for the bionic design to mimic real fish. • A new type of fishtail is designed with an origami-style driven structure and a neutral layer that mimics a real fish's bone. • The structure of the elastic fluid driver adopts the folding paper structure to expand and contract efficiently. • Inspired by traditional Chinese knot structure, the neutral layer of the original rigid body structure was scattered first and then connected by knot structure to form a whole structure. • The novel fishtail shows excellent energy efficiency in experiments. [ABSTRACT FROM AUTHOR]

Aiming at the problem that the distribution of explosion load in the cabin and the propagation law of structural impact response was unclear, this paper established the numerical calculation model of explosion in a closed cabin by ALE (Arbitrary Lagrangian Eulerian) method. There was an apparent convergence of shock waves at the cabin's corners, and the pressure relief hole's area and its position significantly affected the peak of quasi-static pressure. The peak acceleration of the deck structure decreased exponentially as the distance from the location of charge increased. Peak acceleration decreased by approximately 50% for each bulkhead crossing. There was a "paper window effect" during the cabin interior explosion on the whole ship. It meant there was a limit to the value for the energy generated by the explosion to be transmitted along the frame structure. When the charge was 150 kg, it reached the limit of the energy transferred by the structure in this paper. The response of the distant structure did not change significantly with the increase in the charge quality. The research revealed the impact response propagation mechanism in the structure and provided a reference for designing protective structures. • The shock wave shows noticeable convergence in the cabin corner, where the area and position of the pressure relief hole significantly affect the peak quasi-static pressure. • The existence of a bulkhead greatly affects the maximum acceleration, each additional bulkhead results in approximately a 50% reduction. • The investigation reveals a remarkable "paper window effect" during the localized explosion of the entire vessel. [ABSTRACT FROM AUTHOR]

Autonomous ships are vulnerable to a spectrum of potential faults, including propeller damage, shaft-line failures, and electrical supply disruptions. Swift fault detection is critical to minimize the potentially catastrophic consequences of these issues. In this paper, we introduce an innovative digital twin-based method for diagnosing faults in autonomous ships. Our digital twin system collects data from the ship's sensor array, conducts comprehensive analysis, computes fault parameters, and provides real-time visualizations of the findings. To achieve this, we utilize the ship's dynamical model and employ a novel adaptive extended Kalman filter (AEKF) algorithm to estimate the severity of these faults. We evaluate the effectiveness of this approach through numerical simulations and practical implementation in an autonomous surface vehicle called the Otter, developed by Maritime Robotics. The experimental results, which consider both normal and faulty ship propulsion systems, underscore the significant potential of this novel approach to improve ship condition monitoring during operational activities. • This paper presents digital twin-based fault diagnosis architecture. • The fault diagnosis algorithm is based on a novel AEKF method. • The approach is demonstrated in a real-world scenario using a small autonomous vessel. [ABSTRACT FROM AUTHOR]

Research on fishing vessels worldwide began in the 1850s and continues to increase to this day. In Turkey, academic studies on fishing vessels commenced with the establishment of the Ata Nutku Ship Model Experiment Laboratory in 1953. Academic studies on fishing vessels in Turkey can be divided into three periods: the early period studies, the İTU fishing vessel series studies, and the Black Sea type fishing vessels studies. The early period studies started in the 1950s and continued until the 1970s, focusing on Taka, Çektirme, and Alametro type fishing vessels. The İTU fishing vessel series studies began in 1979 under the leadership of Prof. Dr. Kemal KAFALI, in collaboration with İTU and TÜBİTAK, based on fishing vessel forms developed through model experiments, and have continued to the present day. The third period, the Black Sea type fishing vessels studies, started in the 1990s and research on these forms is still ongoing. These fishing vessels, generally built in the Black Sea region, are now used in all seas and oceans. This study examined master's and doctoral theses, articles, and conference papers from these three periods. The subjects were analyzed in a cause-and-effect relationship, and the information contained was summarized. • Academic studies on fishing vessels in Turkey. • Doctoral and master's theses, articles and conference papers from 1950 to the present. • Studies on Taka, Çektirme, Alametro. • Studies on ITU fishing boats series. • Studies on the Black Sea type fishing vessel. [ABSTRACT FROM AUTHOR]

This paper aims at the identification and assessment of High-Impact Research Papers (HIRPs) on the Berth Allocation Problem (BAP) research at marine terminals. The BAP objective is to optimally assign and schedule ships at berthing positions along a quay, as well as to determine the berthing times and positions of ships at a port. The purpose of this study is to facilitate the work of the relevant research community and ultimately promote the research quality in this area. In meeting this objective, the paper utilizes a systematic and fair method to determine HIRPs of the BAP, which is based on the h -index and the g -index. An in-depth bibliometric analysis of the identified studies reveals their key features and characteristics. The analysis was conducted using the VOSviewer and bibliometrix R-package software programs. The main findings provide many useful insights on the BAP research development. The adopted approach and associated analysis results present an up-to-date detailed picture of the BAP research and constitute a valuable tool for its applications into other relevant research areas. The common trends in the reviewed HIRPs and important future research needs are discussed in a comprehensive manner. This survey study can be viewed as the first attempt for a comprehensive bibliometric survey of the high-impact BAP literature, which will be of a great value to researchers and industry practitioners. Furthermore, the proposed methodology for the identification of HIRPs can be used not only for the BAP research but for the literature surveys in other domains as well. [Display omitted] • A comprehensive analysis is conducted for the Berth Allocation Problem (BAP) research. • High Impact Research Papers (HIRPs) in the BAP research are identified and analyzed. • The co-authorship relations among countries, institutes, and authors are investigated. • Trending models of HIRPs and their solution techniques are discussed. • The statistical techniques for mapping and network analysis of HIRPs are presented. [ABSTRACT FROM AUTHOR]

Welding automation has witnessed significant advancements with the integration of control systems and artificial intelligence (AI) in welding robots. This review paper explores the significance of control systems in various welding methods, including arc, laser, spot, and friction stir welding. It highlights their role in achieving precise, efficient weld quality, reducing human errors, and executing complex tasks with high accuracy and repeatability. Sensor technologies play a crucial role in control systems, enabling real-time monitoring of welding parameters and ensuring optimal process control. Thus, various sensor technologies utilized in welding robots are examined, such as vision systems, force sensors, and temperature sensors, emphasizing their contribution to enhancing weld quality and overall system performance. Additionally, the application of welding robots in challenging environments, such as ocean pipeline welding, is discussed, highlighting the importance of robust control systems and sensor technologies in these contexts. Lastly, the paper delves into applying machine learning methods to welding robots, enabling the development of intelligent systems capable of adapting and optimizing the welding processes. The utilization of machine learning algorithms for weld defect detection, process parameter optimization, and predictive maintenance is discussed, representing the potential of integrating AI in welding robots to enhance their performance and efficiency. • Study of the significance of control systems in various welding methods. • Review and comparison of different control systems applied in Welding Robots. • Review of application and limitations of various Sensors used in welding robots. • Review of the state-of-the-art artificial intelligence use in Welding Robots. [ABSTRACT FROM AUTHOR]

An extensive review on the numerical modelling of various flow-induced vibration (FIV) phenomenon and energy harvesting is systematically carried out in this paper. Apart from the experimental endeavours by several researchers, various modelling approaches have become crux in the study of flow-induced vibration (FIV) response of the bluff bodies with different geometries. Here, we have exclusively limited the complex FIV studies to vortex-induced vibration (VIV) and galloping. Primarily, the various computational methods adopted in the numerical modelling of FIV, particularly Reynolds averaged Navier-Stokes (RANS) modelling, direct numerical simulation (DNS) etc. are elucidated in detail while other approaches like detached eddy simulation (DES) and large eddy simulation (LES) are briefly discussed, followed by a concise review of experimental studies on this phenomenon. Secondly, the working principle and practical applications of these methodologies in harnessing energy from VIV and galloping are elaborately described. Furthermore, thriving technologies including vortex bladeless turbine and vortex-induced vibration aquatic clean energy (VIVACE) are succinctly summarized in this paper. The paper concludes with a note on the future prospects and research challenges in the area of modelling and energy capture of FIV. [Display omitted] • This paper extensively reviews the modelling techniques and the practical applications of FIV energy harvesters based on galloping and VIV in particular. • The experimental studies on the various flow-induced vibration phenomena is also studied in detail. • The widely used strategy to improve harvesting efficiency is the use of non-linear magnetic force, which changes the natural frequency of the structure to attain resonance. • Multi-directional harvesters overcome the difficulty of fluctuating power output arising due to time-varying wind speed to a certain extent and it is observed that hybrid harvesters achieve improved energy efficiency. [ABSTRACT FROM AUTHOR]

The high-precision localization module is an essential component of unmanned underwater vehicles (UUVs), providing critical parameter information for motion control, decision-making, and environmental sensing. To efficiently recognize the environment and give accurate location and scene information for vehicle motion, the simultaneous localization and mapping (SLAM) approach is employed for underwater visual applications. Robust visual-based localization and mapping algorithms have generated a lot of interest recently because of the harsh and unpredictable underwater environment. This paper provides an extensive overview of the latest developments in underwater SLAM technology based on optical vision. Special emphasis is placed on different underwater image processing, sensor parameter calibration, odometry, state estimation, loop closure, and mapping methods. Biomimetic SLAM, active SLAM, cooperative SLAM, multi-session SLAM, and other new visual-based types of underwater SLAM are described, along with techniques for multi-sensor fusion. In addition, the paper provides an introduction to ground truth and dataset collection methods for visual underwater SLAM, as well as insightful observations and inspiring future research prospects. • The basic modules of visual-based underwater SLAM are reviewed. • Robust multi-sensor fusion SLAM based on underwater optical vision is surveyed. • Novel visual-based underwater SLAM methods are reviewed. • Analyzed visual-based ground truth collection techniques for underwater datasets. [ABSTRACT FROM AUTHOR]

Path planning of multiple autonomous underwater vehicles (AUVs) is the premise to complete large-scale marine geophysical exploration, military reconnaissance and so on. However, the disturbance of ocean currents has an important effect on the performance of the multi-AUVs path planning and cannot be ignored in practice. Path travel time, smoothness and safety factor are set as the objective functions of multi-AUVs path planning in this paper. An improved 'min–max' multiple traveling salesmen problem (MTSP) robust path planning model is proposed for multiple AUVs under ocean currents, which is designed to obtain the best solution with the worst case. The cooperative genetic algorithm is proposed to obtain a cluster of optimal paths for multiple AUVs. The results show that the proposed algorithm makes the path planning with strong robustness for the multi-AUVs in the environment with ocean currents. The proposed algorithm in this paper has better performance than existing methods for the multi-AUVs path planning with ocean currents. • Considering the effect of ocean currents, a 'min–max' robust optimization problem is proposed for multi-AUVs path planning. • A cooperative genetic algorithm is presented to solve the formed uncertain multi-AUVs path planning problem. • The best solution for the worst case has strong robustness for the planning path of multiple AUVs. [ABSTRACT FROM AUTHOR]

This paper delves into the trajectory tracking problem of networked autonomous surface vehicles (NASV) facing model uncertainty and disturbances. A novel event-triggered strategy, featuring a time-varying threshold and alternative parameters, is devised to optimize the utilization of network resources between the plant and the controller. To succinctly describe the tracking error, the autonomous vehicle system is simplified to a second-order dynamic model. A new event-triggered fixed-time sliding mode control (EFSMC) strategy is formulated to stabilize the sliding system at the origin within a fixed time. This strategy not only diminishes high-frequency chattering but also fulfills convergence performance. The fixed-time stability of the vehicle is validated using the Lyapunov theory. Finally, numerical simulations are conducted to showcase the superiority of the constructed EFSMC in this paper. The simulations illustrate that the control unit reduces the frequency of control protocol transmissions while ensuring stable performance. • To reduce communication burden, a time-varying event-triggeredstrategy with alternative parameters is constructed. • To overcome the limitation of initial values, a fixed time protocol is designed. • To mitigate input chattering, the saturation function is employed to achieve fixed-time robust stability and attenuate chattering phenomena. • A novel event-triggered fixed-time control protocol is constructed, which exhibits better convergence accuracy in a complicated and changeable environment. [ABSTRACT FROM AUTHOR]

The potential flow theory is a reliable tool widely-used in ocean engineering to solve the fluid hydrodynamic problems such as the wave hydrodynamic problems. The Rankine source and its image about the seabed is often chosen as the Green's function to solve the potential flow problems for its simple form, easy singular-integral treatment and few boundary conditions in the boundary integral equations. However, traditionally, the boundary element method based on it is only executed in the time domain by time stepping technique which requires lots of computation due to the time domain form of the damping zone's boundary condition. To apply this Green's function in frequency domain, this paper derived a parameterized frequency-domain formula for the boundary condition of the damping zone, and successfully applied the Rankine source and its image about the seabed in frequency domain. This paper's work possesses a great potential to promote the efficiency in solving the potential flow problems. • Derived a parameterized frequency-domain formula for the boundary condition of the damping zone. • With the formula, the boundary element method using the Rankine source and its image about the seabed as the Green's function can be implemented rapidly and effectively in the frequency domain rather than traditionally in the time domain. • Applicability, accuracy and efficiency of this new method to solve the potential flow problems were presented. [ABSTRACT FROM AUTHOR]

The smoothed particle hydrodynamics (SPH) method has been widely used to simulate fluid–solid interaction (FSI) problems. The solid boundary treatment under complex geometric configurations has always been a hot topic in the SPH numerical simulation. An improved single-layer particle technique combined with an effective anti-penetration boundary improvement algorithm is proposed in this paper, which allows for multi-resolution single-layer particle distribution and effectively prevents particle penetration under complex geometric configurations. Four engineering problems are simulated with the improved technique: dam-break flows with a rectangular prism, water entry of a revolution body, oscillations of a floating body, and gearbox operation. The simulation results of four engineering problems are in good agreement with the reference results, which demonstrates that the improved single-layer particle boundary technique proposed in this paper can accurately simulate the FSI problem of complex geometric configurations. • An improved single-layer particle technique combined with an anti-penetration algorithm is proposed, which allows for multi-resolution single-layer particle distribution. • Four numerical cases from basic to complex applications are selected to verify the accuracy of the improved single-layer particle technique. [ABSTRACT FROM AUTHOR]

In this paper, a formation control problem with collision avoidance is investigated for underactuated surface vessels with position–heading measurements. Each vessels is subject to actuator magnitude and rate saturations. At first, an anti-saturation nonlinear extended state observer is developed to recover the linear velocity and yaw rate as well as unknown uncertainty and disturbances. Then, observer-based formation control laws are designed based on an artificial potential functions, obstacle avoidance yaw references and a backstepping technique. The stability of closed-loop formation control system is proved. The salient features of this paper are as follows. First, formation control with the capability of collision avoidance is achieved by using artificial potential functions and obstacle avoidance yaw references, which is more aggressive. Second, the proposed controller is able to deal with the magnitude and rate constraints of the actuator. Third, the proposed anti-saturation nonlinear extended state observer can achieve better estimation results for rapidly changing signals. Simulation results are given to substantiate the proposed formation control laws. • Formation control with collision avoidance is achieved by using artificial potential functions and obstacle avoidance yaw references. • The proposed controller is able to deal with the magnitude and rate constraints of the actuator. • The proposed anti-saturation nonlinear extended state observer can achieve better estimation results can be achieved for rapidly changing signals. [ABSTRACT FROM AUTHOR]

The underwater glider, which relies on buoyancy and attitude adjustments to achieve spatial motion, is an energy-saving observation platform for ocean phenomenon. Accurate dynamic models have important guiding significance for performance evaluation and controller design of the glider. This paper takes the Petrel glider as the research object, and establishes four types of dynamic models considering different ranges of attack angle, which has never been reported before. The model difference is mainly reflected in the viscous hydrodynamic equations obtained by using polynomials to fit computational fluid dynamics (CFD) simulation results. Then, some numerical cases are given to study the dynamics response difference of these models considering the ideal working condition and complex water current environments, respectively. The results indicate that there is not obvious dynamics response difference under the steady-state gliding condition, and the difference mainly occurs during the glider motion transition stage. Under the complex water current conditions, the dynamics response difference will be very significant, and the traditional dynamic models may exhibit the non-convergence issues. The comprehensive model established in this paper, which fully considers the ranges of attack angle, can better simulate the dynamics behavior of the glider and can provide certain theoretical guidance for actual application. • Four types of dynamic models of underwater gliders considering different ranges of attack angle. • Comparative study of these models considering ideal working condition and complex water current environments. • The comprehensive model of the glider, which fully considers the ranges of attack angle, is proposed. [ABSTRACT FROM AUTHOR]

Freak waves have posed a serious threat to the safety of marine structures. Thus, the accurate simulation and prediction of freak waves are crucial for maritime safety. This paper proposes a nonlinear numerical method based on phase modulation. This method achieves precise time and location simulation of two-dimensional freak waves, while preserving the key statistical characteristics of the wave sequence, thereby obtaining more accurate two-dimensional wave height information. Additionally, this paper constructs a Long Short-Term Memory (LSTM) deep neural network integrated with a Sequence-to-Sequence (seq2seq) framework for predicting sequences of freak wave heights. In this study, we conduct an in-depth predictive analysis of the experimental data for sequences of freak wave heights. And this paper provides a comprehensive assessment of the performance of Recurrent Neural Networks (RNNs), Gated Recurrent Units (GRUs), and Long Short-Term Memory (LSTM) networks in the task of freak wave prediction. The experimental results indicate that the seq2seq-LSTM model demonstrates significant performance advantages in predicting the wave heights of freak waves, particularly for long-term predictions. In summary, the numerical simulation method based on phase modulation and the improved seq2seq-LSTM deep learning model are of significant practical value for enhancing the safety of offshore platforms and ships. • Simulate 2D freak waves based on the improved Longuet-Higgins model. • Enhance an LSTM deep neural network model integrated with a seq2seq framework. • Effectively improve the predictive accuracy of freak wave height sequences. • Evaluate the performance of RNN, GRU, and LSTM in the task of predicting. • Improve the prediction method of freak wave height based on deep learning. [ABSTRACT FROM AUTHOR]

Accurate and trustworthy wave height forecast is essential for the efficient exploitation of wave energy. However, the non-linearity and non-stationarity of waves present a challenge task when using the conventional statistical models in the ocean wave forecasting. Aiming at these problems, this paper proposes a short-term wave height prediction method based on the Variational Mode Decomposition (VMD), Deep Extreme Learning Machine (DELM) and Sparrow Search Algorithm (SSA). Specifically, the original wave height data is initially decomposed into numerous sub-series from high to low frequency by VMD technique. Subsequently, the SSA method is employed to optimize the DELM parameters to enhance the functionality of the basic DELM model. Three wave height datasets located in the North Pacific Ocean are employed as cases in this paper. In comparison with other benchmark models, the RMSE parameters of VMD-SSA-DELM model are reduced by 35.59%–73.33% even at 10-h lead time by analyzing different forecast durations, which demonstrate the proposed model's superiority in short-term wave height prediction. • A novel hybrid VMD-SSA-DELM approach is proposed for significant wave height prediction. • The VMD algorithm is employed for preprocessing, and the original sequence is decomposed into multiple sub-modes. • The validity and accuracy of the model are verified by the measured data in three regions of the North Pacific Ocean. • Through comparison with other benchmark models, the impacts of wave non-stationary properties and advance forecast duration on forecast performance are examined. [ABSTRACT FROM AUTHOR]

Aiming at the problems of slow error convergence rate and external unknown disturbances in trajectory tracking control of underactuated ships, an adaptive fast non-singular integral terminal sliding mode (AFNITSM) trajectory tracking control scheme is designed. By designing fast non-singular integral terminal sliding mode surface, the error convergence rate is accelerated and singularities are avoided. In the paper, the controller will be designed using the sliding mode control method, the "differential explosion" problem will be solved using the dynamic surface technique, and adaptive laws will be used to approximate the upper bound of the unknown disturbances in order to improve the control accuracy. Finally, rigorous theoretical analysis will be carried out by Lyapunov's method to obtain all signals of the closed-loop system are bounded and the tracking errors are made to converge to the bounded interval. Simulation results show that the control scheme proposed in this paper can enable the underactuated ship to track the desired trajectory, and errors converge faster compared with the traditional control scheme, and also has satisfactory robustness in the face of external unknown time-varying disturbances. The study can provide an effective reference for the trajectory tracking control of ships, which is of certain theoretical significance. • An adaptive fast non-singular integral terminal sliding mode control scheme is designed for the slow convergence rate of sliding mode control and the singularity problem. With this scheme, ship can realize the fast tracking of the desired trajectory. The scheme can effectively accelerate the convergence rate of the error and avoid the appearance of singular points. • In the design of the controller, the DSC technique will be combined to solve the "differential explosion" problem. • The adaptive technique will be used to estimate the upper bound of the unknown external disturbances, and the hyperbolic tangent function will be used to eliminate the chattering instead of the traditional sign function. [ABSTRACT FROM AUTHOR]

In the field of offshore oil exploitation, the compact multi-riser arrangement increases the risk of collision and has an adverse impact on production and the marine environment. The solution to this problem involves accurate motion prediction and collision prevention control under the effect of flow field superposition between risers, but there is little research on this related theory. This paper improves the traditional wake shielding effect model and further proposes a wake shielding superposition effect model for the mutual influence between risers, in order to establish a comprehensive accurate motion control model for tri-riser array system. A solution method is introduced for this model, both vibration and collision analysis are conducted for the system. The study revealed that solely augmenting the spacing inadequately mitigates system collisions, and active control is an inevitable choice. Based on this, this paper further designs an active boundary controller that is easy to implement in engineering, to achieve collaborative collision prevention control for three risers, and verifies its stability. Compared with traditional PD control, the proposed control method exhibits significant superiority, which can effectively reduce vibration amplitude, significantly increase dynamic spacing, and thus effectively prevent collisions between risers. • Propose a wake shielding superposition effect model and establish a comprehensive accurate motion control model for the tri-riser array system. • Dynamic response analysis of the tri-riser array system is presented. • Propose a group of collision prevention controller that considers the wake shielding superposition effect. • The proposed collision prevention control method is compared with the traditional PD control method to highlight its superiority. [ABSTRACT FROM AUTHOR]

Maritime transportation is a critical component of global trade and commerce. To ensure maritime safety, fixed shipping routing has been established in many complex waters. However, there is currently a lack of comprehensive digital shipping networks in wide-range maritime areas. To better understand the navigational patterns, this paper proposes a data-driven extraction framework for multi-scale shipping networks, including port-, node-, and route-level shipping networks. It is essentially a hierarchical approach, which progresses from port to route. In particular, for the extraction of port-level shipping networks, the clustering in quest (CLIQUE) and alpha-shapes algorithms are employed to accurately extract the boundaries and spatial extents of individual ports. For the node-level shipping network extraction, an adaptive Douglas-Peucker algorithm is developed to identify crucial feature points, and CLIQUE clustering is further exploited to extract the network waypoints. A novel slice-based traffic flow fitting algorithm is finally introduced to extract the route-level shipping network. To verify the performance of shipping network extraction methods, comprehensive experiments are conducted using the massive Automatic Identification System (AIS) data in different water areas. The experimental results have demonstrated that our method was capable of extracting multi-scale shipping networks, revealing traffic characteristics and vessel behaviours. Overall, the method proposed herein is useful for shipping logistic analysis and provides a foundation for several potential maritime applications, including route planning, trajectory prediction, and others. • This paper introduces a novel framework for extracting multi-scale maritime shipping networks. • Clustering techniques and geometric methods are used to determine the individual ports and their boundaries. • An adaptive Douglas-Peucker algorithm is developed for identifying feature points. • A slice-based traffic flow fitting algorithm is designed to extract the vessel customary routes and their boundaries. [ABSTRACT FROM AUTHOR]

The reliability assessment of the Subsea Horizontal Clamp Connector (SHCC) sealing performance faces a challenge due to the lack of characteristic dimension evaluation methods. Hence, this paper develops the Comprehensive Sealing Reliability Evaluation (CSRE) method. This approach allows for the simultaneous analysis of failure in two dimensions: structural sealing and structural strength, incorporating the uncertainty of fuzzy stress in the evaluation. The CSRE method is based on Bayesian networks, using contact stress as a critical parameter to establish structural sealing failure nodes with gasket coefficients combined with the API standards for acceptance. Simultaneously, it establishes structural strength failure nodes using an improved stress interference model. When applying the CSRE method, this paper, through Monte Carlo simulations combined with torque transmission mechanics and finite element contact models, analyzes the reliability variations of the developed SHCC under different torque levels. The results indicate that the sealing reliability of SHCC is related to sealing pressure and structural strength, with excessively high or low torque affecting its sealing reliability. At an input torque of 2400 N·m, its reliability reaches the maximum value, which is 0.9912. The presented CSRE approach, validated through experimentation and method comparison, demonstrates greater alignment with engineering practicality. • This article proposes the Comprehensive Sealing Reliability Evaluation (CSRE) method, based on Bayesian networks, with contact stress as a key parameter. It establishes structural sealing and strength failure nodes using gasket coefficients and API standards, and incorporates fuzzy stress uncertainties. Experimental verification shows this method's practicality. • This paper employs the Monte Carlo method, torque transmission mechanics models, and finite element contact models to analyze SHCC's contact stress distribution. The process considers friction coefficient variability, aligning it with engineering reality. • This paper uses the CSRE method to assess the sealing reliability of the Deep-Sea Horizontal Clamp Connector (SHCC) and addresses the torque range challenge by analyzing reliability variations under different torque conditions. [ABSTRACT FROM AUTHOR]

Accurate position information of an underwater target is the premise of successfully executing underwater missions, and this paper focuses on underwater target motion analysis (TMA) using delayed azimuth angles. Considering that the underwater sound speed (around 1500 m/s) is much smaller than the speed of light (3 × 108 m/s), the underwater TMA needs to adopt the non-stop model considering the effect of the target movement during signal propagation on state estimation, instead of the traditional go-stop model ignoring the target movement during signal propagation. The existing non-stop model is based on a constant-velocity target, and the model mismatch will make the estimated results biased when it is applied to a maneuvering target. In this paper, we focus on the constant-acceleration (CA) target and propose two methods to solve this problem. One is to extend the non-stop model to the case of a constant-acceleration target. We build the corresponding least squares (LS) estimator and derive the expression of the root mean square error (RMSE) of the LS solution. The other is to directly offset the estimation bias of the CA go-stop model and a bias-compensated algorithm is proposed to improve the performance. Simulations prove that the proposed methods can result in a smaller RMSE than the traditional CA go-stop model. Their RMSEs decrease with the number of measurements and observers and increase with random angle errors. When the number of measurements is small, the RMSE of the established CA non-stop model is smaller than that of the bias-compensated algorithm. As the number of measurements increases, their estimation precisions become gradually equal. The running time of the proposed methods increases with the number of measurements and observers. When the number of observers is small, the bias-compensated algorithm has the advantage of needing less running time. In addition, the running time of the bias-compensated algorithm does not approximately change with the random angle errors, while that of the CA non-stop model increases with the random angle errors. • The effect of delayed azimuth angles on state estimation is analyzed when the traditional CA go-stop model is used to achieve the underwater target motion analysis. • The CA non-stop model is established, and the RMSE analysis of the corresponding LS estimator is conducted. • A bias-compensated algorithm is proposed to improve the performance of the LS solution of the traditional CA go-stop model. [ABSTRACT FROM AUTHOR]

This paper presents an innovative dual autonomous underwater vehicle (AUV) system with a flexible cable connection, exhibiting superior endurance, stability, and deformability compared to traditional towed systems. This advancement significantly enhances performance. The research analyzed the interactions between AUVs, fluids, and linear arrays, and based on this, constructed a system model. Faced with the system's strong nonlinearity and high-dimensional characteristics, as well as the resulting challenges in control system design, this paper introduced a novel Multivariate Extension Dynamic Mode Decomposition (MEDMD) method to establish a reduced-order model. This method integrates the k-means algorithm and system state determination rules, innovatively devising a data segmentation framework that efficiently achieves multi-cluster division of the dual-AUV system's input data, markedly enhancing the predictive accuracy of the reduced-order model. Physical and simulation experiments demonstrate that compared to the full-order model, the reduced-order model exhibits lower dimensions and complete linear characteristics, markedly reducing computation time and rendering it more suitable for control system development. Relative to the conventional Extension Dynamic Mode Decomposition (EDMD) method, this study also achieved substantial enhancements in model accuracy. • The proposal of a flexible connection dual-AUV system with a cable, addressing the issue of limited payload capacity in long cable deployments in towed systems. • Develop a method for constructing reduced-order models, adeptly projecting high- dimensional state data into a low-dimensional subspace, thereby enhancing the applicability of control system development. • The MEDMD reduced-order modeling method introduced in this paper by executing precise clustering of the input data from the flexible linked dual AUV system, markedly enhancing the predictive accuracy of the reduced-order model. [ABSTRACT FROM AUTHOR]

The inconsistencies in the optimization data presented in the original paper by Hua et al. (2024) (hereafter identified as "the original paper", or, "the original authors") will be thoroughly examined in this study. The necessary parameters in the optimization model will be identified from a data consistency standpoint, and any insufficiencies in the original conclusions will be highlighted. An optimization model with consistently reliable data will be developed, based on the available information in the original paper. An illustrated example is solved by a rigorous meta-heuristic method. The original paper could potentially enhance its clarity by providing a more detailed explanation of the optimization model's parameters to further reinforce its findings and conclusions. This not only adds credibility to the study but also enables readers to replicate the analysis and validate the outcomes. [ABSTRACT FROM AUTHOR]

Due to tiny edge and texture details of harmful algae blooms(HABs), existing segmentation networks are not effective for HABs segmentation. In order to solve the above problems, this paper proposes a Multi-scale Feature extraction and TrasMLP Encoder Fusion-based network (MFTS). To tackle the complex morphological characteristics and the complex backgrounds of HABs, a TrasMlp module which can effectively identify long-range patterns and adapt network parameters is introduced, enabling accurately parsing of complex algae images. Secondly, the deep convolution module is constructed by combining deep separable convolution with a two-channel attention mechanism to separate the target region from the background. In addition, this paper proposes a Weighted Feature Fusion of Deep Convolution and INRS Encoder Module classification network(FDIR) is proposed to quantify the performance of the image segmentation network. The segmentation results on HABs dataset from AICO Lab show that our proposed MFTS model achieves a miou of 90.02%, outperforming the performance of classical segmentation networks such as U-Net and Mask R-CNN. Compared to original HABs dataset, the segmented result shows a 5.1% improvement in the classification accuracy of the FDIR model. • Proposes a novel method for automatic detection of harmful algal blooms. • Development of a novel network architecture for harmful algal blooms segmentation and classification. • Achieves the best performance on the AICO labs dataset. • Shows the effectiveness of using multi-scale feature methods. • Demonstrates that the TrasMLP Encoder is helpful for improving model accuracy. [ABSTRACT FROM AUTHOR]

Safe execution of a Marine operation (MO) depends on accurate values of operational limits and forecasting quality of environmental parameters, especially wave spectral parameters (significant wave height, peak period, and peak direction). Since offshore sites are generally characterized by the presence of more than one wave system e.g. wind seas and swells, it becomes challenging to assess accurate multimodal spectral parameters. Apart from forecasts, buoy or vessel motions can be used to estimate wave spectral parameters. This paper deals with an assessment of trimodal wave spectral parameters using three machine learning (ML) methods, i.e. Random forest, Extra trees, and Convolutional neural networks, for an offshore site in the Norwegian Sea. The methods use synthetic statistics of vessel responses as features and spectral parameters computed from a spectrum partitioning method, for training the ML algorithms. It is found that the Extra trees method has the best performance and is very accurate for predicting spectral parameters of three wave systems. Findings from this paper can be used to further develop efficient on-board safety systems and help superintendents make more informed decisions. • Multi-output machine learning algorithms are used to assess trimodal wave spectral parameters. • Vessel response statistics and spectral parameters from wave partitioning are used for training algorithms. • The Extra trees method can accurately predict trimodal wave spectral parameters. • Predicted wave spectral parameters can be used to support on-board decision-making. [ABSTRACT FROM AUTHOR]

Most of the studies on multimode vibration reduction of floating raft systems remain at the stage of theoretical analysis, while relevant experimental studies are rare. In this paper, an experimental setup for a scaled-down floating raft system is constructed. The vertical track nonlinear energy sink (TNES) cells are experimentally applied for the first time to suppress the multimode vibration of the floating raft system. To ensure the damping effect is not affected by additional mass, the TNES cells are always installed on the floating raft system. The TNES is able to achieve vibration suppression by allowing unrestricted movement of its vibrator. Two damping systems with different TNESs placement are proposed. Experimental modal analysis is performed on the floating raft structure to determine its response characteristics. Based on the results, different magnitudes of excitation force are applied to each order mode to effectively suppress the multimode vibration of the system. Meanwhile, the nonlinear system coupled with TNES cells is analyzed using the harmonic balance method (HBM) to obtain the approximate analytical solution. The system responses obtained from the analytical solution are compared with the experimental data results. The particle swarm optimization (PSO) algorithm is used to obtain the optimal parameters of the TNESs for vibration suppression. The results show that the multimodal vibration of the floating raft structure is effectively suppressed by the TNES cells in both experimental and theoretical analyses. The vibration suppression effect for all modes is significantly improved by the PSO algorithm. In conclusion, the research content of this paper provides a practical and feasible vibration suppression solution for the design of floating raft systems. [Display omitted] • A scaled-down experimental setup for the floating raft system is constructed. • The vertical track nonlinear energy sink cells are experimentally applied to the floating raft system. • The particle swarm optimization algorithm is used to obtain the optimal parameters of the TNESs. [ABSTRACT FROM AUTHOR]

The initial alignment of the inertial navigation system of unmanned offshore platforms is interfered with the swaying motion induced by wave action. Departing from the traditional alignment model based on gravitational apparent motion, this paper derives the models of gravitational apparent acceleration and velocity in order to overcome the theoretical insufficiency of directly employing accelerometers to approximate gravity. Parameter identification and reconstruction of gravitational apparent motion are performed by recursive least squares algorithm (RLS) to determine the attitude of the strapdown inertial navigation system (SINS). Concurrently, a comparison is made between the calculated and reconstructed gravitational apparent motion for the separation of the platform's linear acceleration or velocity. Simulation and mooring experiment indicate that the method studied in this paper demonstrates superior convergence and accuracy compared to traditional anti-rocking coarse alignment methods. In particular, the parameter identification alignment method based on gravitational apparent velocity is capable of achieving the extreme accuracy of the inertial measurement unit (IMU). The error in separated linear motion does not diverge over time, which meets engineering requirements. This method has important implications for application scenarios such as the initialization of inertial navigation systems on unmanned platforms. • The proposed method significantly improves the accuracy and convergence of attitude angles compared with the traditional method. • The method addresses the theoretical limitations for alignment and allows the separation of linear acceleration or velocity. [ABSTRACT FROM AUTHOR]

This paper delves into the distributed formation control of unmanned surface vehicles (USVs) under conditions of simultaneous input and state quantization. The primary objective is to ensure that USVs in the formation can effectively follow the specified trajectory in a bandwidth-limited communication environment. A distributed extended state observer (ESO) is proposed to observe the state information of the virtual leader in the USV formation. Furthermore, another ESO is introduced to address the impact of uncertainty terms in the ship model and quantized state variables during communication on the formation control system. Subsequently, the USVs formation guidance laws are formulated in the kinematics subsystem. In addition, the quantized control laws are described linearly in the kinetics subsystem so that the USVs distributed formation controller does not need to anticipate specific information about the quantization parameters. Meanwhile, the USVs formation tracking underlying control laws are designed in the quantized environment to achieve the tracking of the desired kinematic guidance signal. Then, the stability of the designed distributed formation tracking control system for USVs is proved using Lyapunov stability theory. Finally, the effectiveness of the proposed strategy is validated through two sets of simulation experiments, providing empirical evidence of its practical applicability. • Compared to the existing formation tracking control methods for USVs, this paper investigates distributed formation tracking control of USVs with input and state quantization in complex marine communication environments, which reduces the actuator execution frequency without significantly sacrificing the control quality. • Compared with the prior research addressing state quantization in control systems, this paper introduces a distributed ESO to indirectly address the effect of quantized state variables on the designed control system during the transmission of communication signals between USVs. • Unlike current quantized control methods, which setting parameters in quantizers as constant or adjustable within specific constraints, this paper utilizes a linear model to describe the input quantization process, eliminating the need for a priori parameter information of the quantizer. [ABSTRACT FROM AUTHOR]

Sea ice constitutes one of the primary risks in Arctic navigation. Currently, how to maneuver a ship within a sea ice environment relies predominantly on the experience of the pilot. In this paper, based on satellite image data and an improved sea ice target matching approach, a dynamic ship navigation environment within the sea ice zone is established. Subsequently, we developed a sea ice collision risk index (ICRI), which takes into account the relative motion relationship between the sea ice and the ship as well as the sea ice area parameter. Finally, a flexible velocity obstacle (FVO) algorithm is proposed by the Arctic ice navigation proposal, enabling the optimization of ship routes and preventing ships from passing through the central region of large floating ice. The results show that the method proposed in this paper successfully constructs the navigation environment model in the drifting ice region, and can provide real-time maneuvering guidance for ships, effectively reduce the risk of sea ice collision, and optimize the navigation path planning in the ice region. It can improve the safety and pre-planning efficiency of ship navigation in the ice region. • Use satellite remote sensing images to simulate a navigating environment in a floating ice area in the Arctic. • The visual early warning method is implemented to warn the sea ice of collision risk. • Develop a decision support model for ship navigation in the Arctic floating ice region based on a flexibility velocity obstacle algorithm. • The model can help ships reduce collisions with floating ice. [ABSTRACT FROM AUTHOR]

This paper presents an in-depth analysis of population-based structural health monitoring applied to offshore wind farms, with a specific focus on a real wind farm. The study quantifies the heterogeneity within the wind turbine population utilising advanced numerical methods. The Fréchet distance is introduced as a key metric to assess the similarity in terms of structural integrity among the turbines considering factors, such as geometry, material properties, topology, and operational conditions. The results revealed a predominant homogeneity with respect across the wind turbines, despite variations in environmental exposure and operational states. Furthermore, the scope of the study is extended to explore the implications of environmental influences, such as corrosion, scour, and marine growth, which are typically unmonitored yet crucial for comprehensive structural assessment. The present paper contributes to the field by demonstrating the feasibility of knowledge transfer in homogeneous wind turbine populations and highlighting the need for detailed similarity assessments in heterogeneous settings. The findings of this study pave the way for better-targeted, smart, and efficient structural health monitoring strategies in renewable energy systems. • The heterogeneity in a real offshore wind farm is quantified. • The Fréchet distance is introduced to assess similarity in OWTs. • The analysis of the wind farm showed homogeneity in structural integrity. • Unmonitored environmental impacts on OWTs are explored. • Advanced PBSHM strategies for renewable energy systems are presented. [ABSTRACT FROM AUTHOR]

Deep-sea submersibles are subjected to trapezoidal wave loading during operation, which can cause creep–fatigue failure of pressure hull structures. To ensure structural safety, it is necessary to develop accurate and efficient creep–fatigue life prediction methods. This paper proposes a continuum damage mechanics-informed BPNN approach for predicting the creep–fatigue life of titanium alloy submersibles. To obtain a reliable sample set, the creep–fatigue life is calculated based on the titanium alloy room-temperature creep–fatigue damage model and numerical analysis methods proposed by the authors. The operating duration, operating pressure, axial stress, and circumferential stress were selected as the input variables, whereas the number of cycles and actual operating duration were chosen as the output variables. The proposed model fills the current gap of a lack of research on the creep‒fatigue life prediction of titanium alloy deep-sea submersibles via machine learning methods. The research results show that the neural network model established in this paper can quickly and accurately predict the creep–fatigue life of titanium alloy deep-sea submersibles. A sensitivity analysis of the input parameters revealed that the creep–fatigue life is more sensitive to the operational pressure than to the dwell time. • A creep–fatigue life prediction method based on a CDM-informed BPNN was proposed. • The sample data were obtained using the newly proposed creep–fatigue damage model. • A trained neural network can predict the creep–fatigue life of deep-sea pressure hulls well. • The creep–fatigue life is more sensitive to the operating depth than to the dwell time. [ABSTRACT FROM AUTHOR]

In the study of ship direct stability assessment and nonlinear motion prediction, a fast and accurate numerical simulation method is needed to consider the nonlinear effect of ship's large roll motion and improve the calculation accuracy for high wave frequency conditions. In this paper, a potential flow and viscous flow hybrid method is proposed for the nonlinear motion prediction of ship. Based on the assumption of ship periodically steady motion, the nonlinear instantaneous radiation force caused by the change of the ship motion attitude is calculated by using a pre-calculated database in a relatively short time. The instantaneous nonlinear restoring force is obtained by the pressure integration on instantaneous wetted surfaces. In order to solve the problem that the radiation potential calculation error is large based on the potential flow theory in the high wave condition, the instantaneous wave exciting force is modified by adding correction coefficient based on the viscous flow theory. In addition, the feasibility and effectiveness of the proposed method are verified by the comparative study of four theoretical approaches for nonlinear motion prediction of shallow draft ships. The results show that the prediction error of wave exciting force in roll direction based on potential flow theory is an important reason for the prediction error of ship roll motion. The hybrid method proposed in this paper can improve the prediction accuracy of ship nonlinear roll motion. Compared with the model test results, the calculation error of roll response amplitude operator is within 5% under most wave conditions. For high wave frequency conditions, the calculation error is reduced from 51.66% to 8.94%. • A hybrid method is proposed for the nonlinear motion prediction of ship. • The nonlinear radiation force caused by the change of the ship motion attitude is considered. • A comparative study for nonlinear motion of shallow draft ships is performed. [ABSTRACT FROM AUTHOR]

This review paper presents a comprehensive analysis of the mechanical design and analysis of dynamic power cables for marine renewable energy applications, focusing on research from the last two decades. The review covers key aspects such as mechanical properties, failure mechanisms, fatigue analysis, experimental studies, local cable analysis, and global load analysis. The study aims to provide a concise summary of the state-of-the-art, identifying recent advancements and research gaps in the field. The methodology involves a systematic review of relevant literature, including journal articles, conference papers, and industry reports. The findings are synthesised to provide insights into the current understanding of power cable design and analysis, as well as to highlight areas requiring further research and development. The review is intended to serve as a valuable resource for researchers, engineers, and stakeholders in the marine renewable energy sector, contributing to the development of more reliable and cost-effective dynamic power cable solutions. • Comprehensive review of dynamic power cable mechanical analysis for floating offshore wind turbines. • Identification of research gaps in testing, validation, and deep-water cable behaviour. • Recommendations for future research: multi-physics simulations, analysis methods, and test standardisation. [ABSTRACT FROM AUTHOR]

USVs have emerged as effective instruments in a wide range of maritime applications, including environmental monitoring and search-and-rescue missions. The surge in their application is attributed to their operational flexibility and cost efficiency, making them a focal point of research interest in recent years. One of the research angles related to the USV is the path planning algorithm, which is the core technology in USV deployment. Among various path planning algorithms, Ant Colony Optimization (ACO) has garnered considerable attention for its capability to discover near-optimal solutions in complex search spaces inspired by the foraging behavior of ants. Therefore, this paper discusses the application of ACO in the path planning of USVs, including the development of the ACO algorithms and the challenges faced in designing the path planning algorithm. This work also proposes research priorities and future works for USV path planning based on existing research works. Specifically, future research works aim to address the existing challenges and enhance the practical deployment of ACO-based path planning techniques for USVs. In summary, this paper is a valuable resource for researchers and engineers interested in optimizing the navigation of USVs through effective path planning strategies using ACO algorithms. • Implementing ACO-based path planning in the dynamic environment is the main challenge. • There has been limited research on multi-objective path planning for USVs. • Collaboration mission between multiple USVs and UUVs can be explored in the future. • Only 14.7% of the ACO-based path planning in USVs works include the hardware validation. [ABSTRACT FROM AUTHOR]

With the development of polar shipping, invisible bulbous bows are increasingly utilized in the design of polar transport vessels. However, there is a paucity of literature addressing their performance in ice conditions. To bridge this gap, this paper establishes a Computational Fluid Dynamics method combined with the Discrete Element Method (CFD-DEM) model to simulate ship–ice–fluid interaction for ships with invisible bulbous bows. The accuracy of the CFD-DEM model is validated through a model test conducted at the Hamburg Ship Model Basin. Furthermore, recognizing the significant errors in predicting ice resistance for this ship type using traditional formulas, this paper proposes a correction to the Riska formula for predicting brash ice resistance in ships with invisible bulbous bows. Based on data from CFD-DEM numerical calculations, an exponential correction and coefficient adjustment method is employed to modify the Riska brash ice resistance formula. The corrected empirical formula aligns closely with the numerical results. To further validate the feasibility of the corrected formula, ice resistance forecasts for two additional ships with invisible bulbous bows were performed using both the original and corrected Riska formulas. The results demonstrate that the original formula's calculations significantly deviate from actual values, whereas the corrected formula closely aligns with actual values, affirming the reliability of the correction. This study provides valuable reference material for researchers studying the brash ice performance of ships with invisible bulbous bows and for those revising brash ice resistance formulas. • A CFD-DEM method calculates brash ice resistance for invisible bulbous bow ships. • Interaction analysis between ship and ice compared to HSVA model tests verifies CFD-DEM. • The corrected Riska formula for invisible bulbous bow ships shows improved accuracy. [ABSTRACT FROM AUTHOR]

The identification and tracking of ships can be achieved by analyzing laser echo signals from their wakes. A new method for the laser detection of bubble wakes based on multi-timescale hierarchical processing is presented in this paper. It contributes to amplifying the strength of the wake echo while mitigating its nonstationary characteristics. The applicability of the algorithm for bubble wake detection under strong and weak shading effects is verified through combining the bubble cluster distribution with a Monte Carlo simulation. Additionally, the method is tested in a real wake crossing and following detection experiments. The experimental results demonstrate that the signal-to-backscatter ratio and detection rate trends are consistent with the simulation findings. Specifically, the algorithm improves the signal-to-backscatter ratio by an average of 17.35%, and increases the detection rate to an impressive 90.74%. Applying this algorithm enhances the system's effectiveness in detecting bubble wakes. • A new laser detection method for ship bubble wakes based on multi-timescale hierarchical processing is presented in this paper. • The applicability of the method to both single- and multi-cycle echoes is demonstrated by simulations and experiments on the lake. • It contributes to amplifying the strength of the wake echo while mitigating its nonstationary characteristics. • The method can effectively improve the signal-to-backscatter ratio and detection rate under strong and weak shading effects. [ABSTRACT FROM AUTHOR]

Long wave equations are an important class of equations in oceanographic engineering. Engineers could have insight in to the behavior of complex systems by fractional generalized long wave equations which are used to describe various physical phenomena in ocean engineering, including wave propagation, wave-structure interaction, sediment transport, and coastal erosion. However, fractional-order long wave equations are generally difficult to solve. In this paper, we present a method for solving approximate analytical solutions, which is called Laplace residual power series method. Firstly, the equation is Laplace transform on both sides; Secondly, the general solution of the equation is obtained by Laplace inverse transformation; Thirdly, the analytical solution of the equation is expanded into a fractional power series function in the form of variable separation, in the general solution, the coefficients of the unknown power series are obtained according to the initial conditions, thus each term of the approximate analytic solution is obtained one by one, the approximate analytical solution of the original equation is obtained. Compared with numerical methods, the approximate analytical solution obtained by this method has a clear functional expression, which can facilitate theoretical analysis of the system; Secondly, the method proposed in this article does not require fractional derivatives, making it convenient for computer program simulation calculations. The numerical results indicate that the algorithm proposed in this paper is a simple and effective approach. • Calculating of fractional derivatives is unnecessary when used proposed method. • Compared to numerical methods, expressions will be obtained by this method. • New solution is more precise than solution from using residual power series method. [ABSTRACT FROM AUTHOR]

With the continuous increase in maritime traffic and navigation tasks, the demand for mission execution in complex maritime environments, such as islands and reefs, has grown. Path planning for Unmanned Surface Vehicles (USVs) in these areas requires overcoming challenges posed by sea wind interference, island topography, and other complex geographical factors, ensuring safe and efficient navigation. This paper aims to delve into the impact of factors such as water currents and wind speed on ship navigation paths and proposes a comprehensive path planning compensation strategy that considers these factors. Firstly, regarding the planned potential field space, directional and dilation factors are introduced to alter the distribution of potential risks, enhancing the safety and reducing potential risks in the planned routes of USV. Secondly, a detailed analysis of different environmental factors is conducted, exploring their impact mechanisms on the performance of USV navigation and planned routes. Based on the analysis, this paper establishes a mathematical model for environmental interference factors, considering the parameters of USV, laying the foundation for modeling environmental issues in global path planning. In terms of path evaluation metrics, this paper defines path length and time, as well as safety indicators for avoiding dangerous areas in the environment, as evaluation criteria. To address the interference of waves and currents in complex water areas with the planned navigation route, this paper proposes a navigation point compensation optimization strategy based on the Fast Sweeping Method (FSM). Combining the calculated estimated drift distance with the planned route comprehensively, a corrective strategy model is proposed by integrating it with the B-spline method. Finally, simulation and emulation were conducted. • An improved path planning algorithm is proposed in this study. • In response to complex navigational water environments and narrow navigation channels, this paper proposes a directional factor. • A novel heading point path compensation is introduced for enhancing the path planning of USVs under the influence of real-world conditions and disturbances like wind and currents. [ABSTRACT FROM AUTHOR]

A mode-dependent supervisory switching fault-tolerant controller is proposed for dynamic positioning (DP) ships. First, the input-to-state stability (ISS) of nonlinear switched systems with a larger class of mode-dependent switching signals is studied, which requires fewer constraints on the subsystems. By appropriately constraining the switching signals, a class of mode-dependent exponentially weighted integral ISS for the switched system is achieved. Furthermore, a mode-dependent scale-independent hysteresis (MDSIH) switching logic is designed, which takes into account both model estimation errors and time scales. This logic avoids the stagnation issues inherent in traditional scale-independent hysteresis switching, which are often caused by improper hysteresis constant selection. It enables more proactive switching, which is crucial for effective fault-tolerant control (FTC). Lastly, the design principles of the multi-estimator and multi-controller are given for DP ships. By employing the designed MDSIH switching logic, the DP system can tolerate sudden actuator faults while ensuring the boundedness of all signals in the closed-loop switched system. • This paper proposes a less conservative assumption condition for the ISS of switched systems. • This paper introduces a novel mode-dependent exponentially weighted integral ISS. • A new MDSIH switching logic is proposed, which, unlike traditional scale-independent hysteresis switching logic that only considers estimation error, takes into account both estimator performance and time scales. • A novel mode-dependent supervisory switching fault-tolerant controller is designed for DP ships. [ABSTRACT FROM AUTHOR]

The paper introduces a semi-analytical approach for predicting the pile-soil response under cyclic lateral loads in sands, incorporating the cavity expansion/contraction theory with an anisotropy and non-associated constitutive model, Simple ANIsotropic SAND (SANISAND). The pile hole is regarded as a cylindrical cavity, and the cyclic loading process is reasonably treated as a cavity expansion/contraction problem. A superposition principle is introduced to determine the superimposed stress states around the cavity. The geometric relationship, quasi-static equation, and boundary conditions are integrated into a standardized solving procedure to obtain the stress-strain distribution surrounding the pile. Subsequently, the derived cyclic p-y curve is used in conjunction with the deflection equilibrium differential equation and finite-difference method to determine the pile-soil response under lateral cyclic load. The method's validity and capacity are further demonstrated through two well-examined centrifuge tests, which shows a good agreement with the experimental data. The cumulative deformation, hardening and ratcheting behaviors of pile-soil system can be captured in this study, which provides a novel approach to figure out the pile-soil response in sands under cyclic lateral loads. • This paper presents a semi-analytical approach for predicting cyclic laterally loaded pile-soil interaction in sands. • The soil deformation mechanism around the pile is determined using the constitutive model, SANISAND. • The hardening and ratcheting behaviors of pile-soil system during cyclic lateral loading process can be captured. [ABSTRACT FROM AUTHOR]

Traditional deep-sea landers lack maneuverability during the diving process, making it difficult to effectively regulate the diving trajectory and velocity. In this paper, a novel deep-sea lander with flapping hydrofoils is proposed, and the simplified geometric model and typical flapping modes are introduced. Through computational fluid dynamics (CFD) simulation, the effectiveness of the flapping hydrofoils in regulating the diving trajectory and velocity of the lander is verified, and the influence of the amplitude of flapping angle and flapping frequency of the hydrofoils on the maneuverability of the lander and the propulsion efficiency and deceleration ratio of the flapping hydrofoil is explored. The relationship between the thrust generated by flapping hydrofoils and the maneuverability of the lander, as well as the relationship between the vortex topology and the propulsion efficiency and deceleration ratio of the hydrofoil are explained, respectively. And the diving trajectory of the lander is predicted based on Gaussian process (GP). The results show that the lander can have a certain degree of maneuverability through flapping hydrofoils, and the prediction error of the diving trajectory is within 4%. This paper provides reference for the design and application of the novel deep-sea lander with flapping hydrofoils. • A novel deep-sea lander with flapping hydrofoils is proposed in this paper, and the lander can have a certain degree of maneuverability through the flapping hydrofoils. • The maneuverability of the lander and the propulsion efficiency and deceleration ratio of the flapping hydrofoil are closely related to the amplitude of flapping angle θ 0 and flapping frequency f of the hydrofoil, and high maneuverability conflicts with high propulsion efficiency and high deceleration ratio. • The hydrodynamic mechanism of the flapping hydrofoil is revealed and the relationship between the vortex topology and the propulsion efficiency and deceleration ratio of the hydrofoil is explained. • A diving trajectory predictive method is proposed and verified based on the GP prediction model, with high prediction accuracy and strong generalizability. [ABSTRACT FROM AUTHOR]

Trajectory-based fishing vessel behavior recognition is currently a vibrant and dynamic area of investigation within transportation and maritime research. It can provide crucial technical support for combating illegal, unreported, and unregulated (IUU) fishing. Nevertheless, existing studies typically rely on extensive datasets of pre-labeled data to train machine learning models. The acquisition of these labeled datasets is frequently a time-consuming and complicated endeavor, which presents challenges in the practical application. Hence, this paper develops a semi-supervised approach for fishing vessel behavior identification using a small amount of manually labeled trajectory samples. Besides, given that the common vessel behavioral feature parameters provide limited insight into fishing activities, this paper innovatively proposes a set of descriptive trajectory feature parameters. Based on the morphological characteristics of fishing activities and domain knowledge, the proposed trajectory features excel in discerning the intricate pattern of fishing vessel trajectories. Combined with a set of Long Short-Term Memory (LSTM)-based encoding trajectory features, a composed feature engineering scheme that leverages both human intelligence and machine intelligence is proposed. The clustering experiment result confirms that our trajectory feature scheme can successfully recognize different fishing vessel behaviors while the conventional trajectory features can't. In the consequently classification tests, the 90% accuracy achieved by the composed feature scheme exhibits a 10% increase compared to solely using deep learning-based encoding features. This novel trajectory feature engineering method together with the semi-supervised machine learning structure, not reliant on extensive labeled datasets, can be tailored and applied to mobility pattern identification across various domains. • Develop a semi-supervised approach for fishing vessel behavior identification. • Propose a set of descriptive trajectory feature parameters based on domain knowledge. • Combine both human and machine intelligence to compose the feature engineering. • The developed approach identifies fishing vessel behavior with over 90% accuracy. [ABSTRACT FROM AUTHOR]

Corrosion is one of the important components that cause failure of submarine pipelines, and accurate assessment of the impact of corrosion on the failure pressure of submarine pipelines is important for assessing the integrity of submarine pipelines. This paper first verifies the accuracy of finite element modeling of submarine pipelines containing corrosion defects using existing experimental results. On this basis, the influence of corrosion location, shape, and width on the collapse pressure of submarine pipelines under different corrosion lengths and depths is explored. It is found that the effect of corrosion length on the collapse pressure of submarine pipeline is weakened with the increase of corrosion length. The corrosion depth, shape and width will directly affect the collapse pressure of submarine pipeline. The change in corrosion location changes the failure pattern of submarine pipelines. Based on the extensive numerical analysis, this paper establishes a collapse pressure prediction model of the submarine pipelines relating to corrosion length, corrosion depth and corrosion width. Furthermore, the shape coefficient is introduced to establish the prediction model of corrosion shape and submarine pipeline collapse pressure. Compared with the Netto's collapse model evaluation results, the predicted results of the prediction model have higher reliability. • The influence of corrosion characteristic parameters on collapse pressure as well as buckling instability mode is revealed. • The collapse pressure prediction model of submarine pipeline is established, including corrosion length, corrosion depth and corrosion width. • A corrosion characterization parameter and submarine pipeline collapse pressure prediction model is established under different corrosion shapes. • It is compared with the results of the Netto's collapse model, the prediction model shows good reliability. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive approach for the linearized frequency-domain analysis of hydrodynamic loading and structural responses on a deformable body. The structural and hydrodynamic analyses are integrated by employing the mode superposition method. Commencing with an eigenvalue analysis on the structural model, the shapes of selected modes, mass, and structural stiffness matrices are extracted as input to the subsequent hydrodynamic analysis, where the global response is solved in the modal space. The resulting hydrodynamic and inertial loads are then transferred to the same finite element model for stress assessment. To exemplify the proposed methodology, a bottom-fixed flexible cylindrical monopile and a long box-shaped barge model are investigated. For the barge model, the sectional loads are obtained from the integral of stresses in the cuts along the structure model, which are found to be consistent with those from the hydrodynamic analysis, demonstrating the consistency of the entire workflow. In particular, this paper introduces a straightforward formulation for evaluating the generalized restoring matrices, eliminating the need for spatial derivatives of the mode shape function and thereby significantly reducing numerical uncertainties in using the flexible modes derived from finite element model for hydrodynamic analysis. • An integrated hydrodynamic-structural analysis workflow is proposed to account for the deformable motions of large volume floating structures. • Mode shapes FE model is taken as input to hydrodynamic analysis, with the resulting loads applied to the same model for stress evaluation. • Straightforward formulations proposed for restoring matrices, eliminating the need to operate with the spatial derivatives. • Mode superposition approach is validated against discrete module method to evaluate sectional loads and stresses for a flexible barge model. [ABSTRACT FROM AUTHOR]