Actual Sea Research Articles

A coupled wave-hydrodynamical model to assess the effect of Mediterranean storms under climate change: The Calabaia case study

Climate change will have an undeniable influence on coastal areas, resulting in increased rates of both sea level rise and storm-related impacts. In this context, it is crucial to estimate the local probable extreme sea wave conditions, to properly reproduce the sea state and the coastal hydrodynamic, and to investigate the effectiveness of sea defenses under sea level rise. This work describes the first steps towards an innovative fully coupled modeling system composed of a wind-sea wave (SWAN) and hydrodynamic model (2DEF). Numerical simulations, focusing on the shoreline of Calabaia, Cosenza, Italy, have been compared to the MIKE model outcomes in the same area. The simulations have been performed to investigate the inshore sea wave characteristics, to assess the effectiveness of the actual sea defense interventions, and to identify the impact of extreme storms, by combining sea level rise and extreme sea wave scenarios with the most recent georeferenced territorial data. The models are two-way coupled at half-hourly intervals exchanging the following fields: 2D sea level, surface currents and bottom elevation are transferred from 2DEF to SWAN; sea wave characteristics computed by SWAN is then passed to 2DEF by modifying the radiation stress.

Establishment and program development of failure criterion of hollow glass microspheres/epoxy resin composites based on tension/compression discrepancy

A failure criterion was established for hollow glass microspheres/epoxy resin (HGM/ER) composites, based on the experimental results. Compared with the traditional failure criterion, the new failure criterion innovatively takes into account the tension/compression discrepancy. Next, the subroutine of Finite Element Method (FEM) software was programmed to realize the secondary development, which enables the proposed failure criterion to be applied to numerical calculations. The results of this paper are beneficial to the accurate prediction of the ultimate load capacity of solid buoyancy materials under actual sea conditions, which can meet the design requirements of deep-sea buoyancy materials in engineering practice.

Sequential learning navigation method and general correction model for Autonomous Underwater Vehicle

The errors introduced in the modeling and state estimation by conventional navigation methods will affect the AUV navigation accuracy. Therefore, this paper proposes a sequential learning method for AUV navigation. Firstly, a Temporal Convolutional Network (TCN) module is used to learn the temporal relationships from raw sensor data. After the feature representation, a Self-Attention (SA) mechanism is implemented to weigh the data at different time steps. Finally, the Fully Connected (FC) layers are adopted to regress the AUV displacements. Since the sequential learning navigation method does not require state estimation computation and can calculate the AUV position by displacement accumulation, it can avoid introducing related errors. Meanwhile, this paper proposes a general correction model based on the sequential learning method to correct the errors of various state estimation techniques. The experimental results based on actual sea trial data from Sailfish 210 AUV show that the average AUV navigation accuracy of the presented sequential learning method is improved by 56.78% compared to EKF, 57.64% compared to UKF, and 47.85% compared to CKF. Meanwhile, the navigation accuracy of the proposed general correction model is improved by 62.88% compared to EKF, 49.45% compared to UKF, and 42.86% compared to CKF.

Validation of short-term prediction of added resistance in head seas considering wave steepness nonlinearity with probability density function method

The added resistance in waves, which is an important component in the estimation of actual sea performance of ships, has been evaluated as the average value by short-term prediction methods. In this paper, a novel probabilistic method to account for non-linearities of added resistance with respect to wave height in short-term sea conditions is proposed using the joint occurrence probability distribution of wave height and period and non-linear added resistance response in the frequency region. It is a method of averaging the combination of crest and trough that ships encounter in irregular waves, which is considered as one wave of the regular waves, and the resulting added resistance is combined stochastically. The non-linearity with respect to wave height is empirically expressed as a “correction coefficient” obtained from the comparison of CFD data and potential-based linear calculation results in regular waves. The results of the proposed method have a reasonable agreement in the acceptable range of accuracy with results of RANSE based CFD numerical simulations in long crested irregular waves and the experimental model tests. As a result, the proposed method is applicable for obtaining added resistance in irregular head waves having the non-linearity with respect to wave height with a scope of further improvement in the method.

Multi-GNSS Combination Multipath Reflectometry Based on IVMD Method for Sea Level Retrieval

Sea level monitoring is particularly important in coastal areas that are vulnerable to marine disasters. It was recently demonstrated that the global navigation satellite system multipath reflectometry (GNSS-MR) technique, which uses multipath signals reflected from the sea, can be applied to determine the sea level. However, this approach does not provide sufficient accuracy or equally spaced sampling to meet the actual sea level monitoring requirements for certain stations. To solve the deficiency of the traditional GNSS-MR technique, the least squares method, which is based on sliding time windows, was applied. Using the sliding windows to combine the quad-constellation multi-GNSS retrieval can effectively improve the accuracy and time resolution of sea level retrieval, but insufficient data or a lack of data in some time ranges and missing overflights in some timeframes can lead to the calculation of faults in these time windows, causing the estimated loss of corresponding sampling points. In this study, we used a robust regression solution strategy based on multi-GNSS sea level retrieval and an improved variational mode decomposition (IVMD) algorithm to process sea level retrieval after robust regression. BRST and HKQT stations are located on the western coast of France and the northern coast of Hong Kong. The two stations can both receive satellite observation data from the four satellite systems. Through the experiment, using data retrieved from the BRST and HKQT stations, the results of this study demonstrate that the IVMD method based on multi-GNSS sea level retrieval can further improve the accuracy to <10 cm and can achieve 10 min equal interval sampling. This is significant for using GNSS-MR technology to detect sea level height and monitor sea level change and could be applied to other sites.

The Energy Recovery Effect of Wave Energy Utilization System under the Rolling Motion of Ships

In order to realize the utilization of wave energy on ships, this study proposes a wave energy utilization system mounted on ships. The wave energy utilization system can transform wave energy into electric energy. The working principle and installation mode of the system are introduced in detail, and the motion model of the system on the ship is established. The motion equation of the system is solved by the Newmark-β method, and the influence of different slider masses (150–500 kg) and different radius of sliding rail (7–15 m) on the energy recovery performance of the system is studied. The data simulation shows that under a certain radius of the sliding rail, there is a slider mass that makes the system achieve the best energy collection effect. With the increase of the radius of the sliding rail, the slider mass corresponding to the best energy recovery performance of the system also increases. In addition, the energy recovery performance of the system under actual sea conditions is simulated, and the research shows that the system can continuously output power.

An Integrated Navigation Method for Small-Sized AUV in Shallow-Sea Applications

The navigation and localization of Autonomous Underwater Vehicle (AUV) face many challenges. In surface missions, AUV typically relies only on Global Positioning System (GPS) to perform navigation. However, the GPS data output frequency is low, usually only 1 Hz. Meanwhile, the navigation system is susceptible to interference from GPS measurement outliers. For underwater missions, without the assistance of additional underwater absolute positioning measurements, the unknown errors introduced by the navigation system modeling process and state estimation process will affect the navigation accuracy. Therefore, in this paper, we propose an integrated navigation method for small-sized AUV in shallow-sea applications. Firstly, a robust GPS/Attitude and Heading Reference System (AHRS)/Doppler Velocity Log (DVL) navigation method for surface missions is proposed to maintain high-frequency output and robustness. Secondly, a Multiple Model (MM) integrated navigation method is proposed for AUV underwater missions. An AHRS/DVL/NavNet sub-model is proposed to perform measurement correction to correct the unknown errors. At the same time, an adaptive AHRS/DVL sub-model based on Variational Bayesian (VB) is presented to estimate the time-varying measurement noise covariance to improve the state estimation accuracy without the extra external observations. Two sub-models run parallel based on the Interacting Multiple Model (IMM). The effectiveness of the proposed integrated navigation method is verified by actual sea trial data from Sailfish 210 AUV.

Analysis of wave added resistance and motion response of fishing boat sailing against waves

In order to accurately predict the on-wave resistance and responses to hull motions of ships in actual sea conditions, the k-ε method of the RNG model is adopted on the basis of the unsteady RANS method. The twoformula turbulence model deals with the viscous flow, the VOF method captures the free surface, the velocity boundary method makes waves, the artificial damping method is used to eliminate waves, and the nested grid technology is used to deal with the motion response of ships on waves. Combined with the 6-DOF motion formula, a three-dimensional numerical wave cell for regular waves is established. For one example, taking a KCS Container ship and fishing boat sailing at a mid-high-speed, the increase of wave resistance and motion response at different wavelengths are analyzed, and the simulation results are compared with the experimental value, the content of strip theory in potential flow theory and the panel method to prove the reliability of CFD method in predicting ship motion.

Unmanned Surface Vehicle Using a Leader–Follower Swarm Control Algorithm

To overcome the limitations of a single unmanned surface vehicle (USV), this study investigated the swarm control algorithms of USVs. Among various swarm control methods, a leader–follower swarm control method was selected and studied. The performance of the swarm algorithm proposed in this study was verified through an actual sea area test. A USV was designed and manufactured by dividing the power and communication parts. The power system was equipped with a coulometer to monitor the battery state in real time to protect the system through a switch linked to the coulometer in the case of abnormalities in the battery and to prevent accidents. In addition, a communication system was established to process the sensor data and camera image data of the USV in real time. Consequently, the desired swarm formation was achieved through the separately constructed swarm control algorithm. Before the actual sea area test, individual performance tests of each sensor were conducted. Finally, the performance of the swarm algorithm was verified by conducting a sea area test. The performance of the controllers was confirmed to be good, and the swarm formation was confirmed to be successful.

Applications of Polyaniline–Alkaline Copper Carbonate Composites for Anti-Bio-Attachment of Concrete in Marine Environments

This study proposed the use of polyaniline–alkaline copper carbonate composites as anti-corrosion and anti-biofouling concrete additives and established a set of high-dispersion preparation methods for this composite additive. The effects of polyaniline–alkaline copper carbonate composites in concrete were investigated in marine environments via the preparation of concrete specimens, actual sea suspension experiments, concrete mechanical property tests, and biological attachment avoidance tests. The experimental results showed that (1) the yield of the chemical reactions leading to the preparation of the composite was above 96.46% with a good output. The composite was hydrophilic. The addition of ethylene carbonate as a surfactant and the mixing of the composite into the concrete in a suspension form enabled uniform dispersion of the composite. (2) In the sea waters of Zhoushan, China, bio-attachment was mainly dominated by barnacles and sea anemones. Polyaniline–alkaline copper carbonate composites had good anti-bio-attachment properties and could significantly reduce the amount of bio-attachment in concrete. (3) When the additive content was less than 0.20% of the concrete mass, it did not negatively affect the mechanical properties of the concrete specimens and exerted anti-corrosion and anti-biofouling effects. This reduced the strength loss of concrete and increased the service life of the concrete specimens in the ocean. To ensure the best application effect of the compound in concrete, the recommended content of the compound is 0.05–0.15% of the concrete mass.

An autonomous cooperative system of multi-AUV for underwater targets detection and localization

This paper proposes a cooperative online target detection methodology by multiple autonomous underwater vehicles (Multi-AUV) equipped with the side-scan sonar (SSS) sensor for real-time, accurate, and efficient underwater target detection and positioning in unknown environments. Due to the existence of unfavorable factors such as severe noises and geometric deformation of SSS images, this study incorporates the prior-based threshold segmentation with multi-scale cascaded networks (MSCNet) to reduce the high false alarm rate significantly. Specifically, to the real-time requirements of the AUVs computational platform, this study proposes the sequentially dual-branch lightweight block (LWBlock) as a baseline to obtain dense feature maps, which provide a good trade-off between accuracy and speed. Meanwhile, this study establishes the comprehensive correction model, which obtains the accurate target positioning information fusing with the predicted results. Furthermore, according to the target information provided by the automatic target recognition (ATR) system, the data-driven behavior-based (DDBB) path re-planning algorithm is performed that endows each AUV to scan above the interest target autonomously and in detail by designed maneuver behavior. Simulation and actual sea trial experimental results show that the proposed method outperforms other state-of-the-art algorithms, and achieves the recognition accuracy of 92.16%, inference speed of 2.45 s, and obtained the best FPR indicator in three SSS targets of 2.54% (metal ball),1.96% (seabed rock) and 1.03% (metal rod), respectively. At the same time, the proposed algorithm can improve detection efficiency by at least 40% compared with a single AUV, which can be widely used in marine mission exploration and resource deployment.

Automatic Docking Trajectory Design-Based Time-Varying-Radius Dubins for Unmanned Surface Vessel

Facing the demand of efficient automatic docking for USV, this paper proposes a new kind of iterative varying-radius Dubins curve design. Due to the special mobility of dockyards, one novel trajectory optimization problem considering time optimum is modeled first. Then, we use the ant colony optimization (ACO) algorithm to solve such a complex problem. In addition to the global exhaustive search algorithm and ACO-based solution, a novel distributed local path planning algorithm named ADTA-TRD is proposed to obtain the solution of the above optimization problem restricted by the local perception of the USV. In essence, this paper draws lessons from the idea of the circular arc segment and straight line segment in the traditional Dubins curve, and consequently, the smoothness of the derived automatic docking trajectory can be guaranteed. Finally, the performance of proposed automatic docking path planning method is verified through simulation results and an actual sea trial.

Polarization Transmission of Visible Light in Inhomogeneous Sea Fog Particle Environment

Sea fog is a weather phenomenon suspended in the ocean-atmosphere boundary layer. This phenomenon makes the horizontal visibility of the sea atmosphere less than 1 km. Sea fog reduces sea surface visibility. Moreover, the inhomogeneous sea fog particles in the transmission channel result in the absorption and scattering of photons, which seriously affect the performance of optical detection instruments. Polarization imaging detection can solve this problem. However, the evolution law of transmission characteristics between polarized light and inhomogeneous sea fog particles remains unclear. Therefore, we use the equivalent analysis method to improve Monte Carlo, and finally construct the inhomogeneous particle scattering model. The influence of wavelength and relative humidity on DOP (Degree of Polarization) was calculated by the model. The simulated sea fog was created using brine with a preset concentration, and then established an experimental system close to the actual sea fog environment. Indoor polarized light transmission experiments verified the inhomogeneous particle scattering model. Results showed that the accuracy of the inhomogeneous particle scattering model can reach more than 75%. In the visible band, the DOP decreases with the wavelength increase. DOP450 (Degree of Polarization at 450nm wavelength) is approximately 3–10% higher than DOP532, and DOP532 is approximately 5% higher than DOP671. The relative humidity increases from 45% to 85%, and DOP increases by 10–15%. Therefore, in the visible band, the wavelength and relative humidity are inversely proportional to DOP.

Application of Reinforcement Learning to Generate Non-linear Optimal Feedback Controller for Ship's Automatic Berthing System

In this paper, we present an application of reinforcement learning for automatic ship's berthing system. In the proposed method, the model-based reinforcement learning is used to generate non-linear feedback controller. The proposed system is composed of an Actor-Critic algorithm suitable for continuous state and a function approximator by Radial Basis Function networks. To evaluate the performance of the proposed system, extensive computer simulations and actual sea tests are carried out using small training ship Shioji-Maru III under various conditions. As a result, we can see that the proposed non-linear optimal feedback controller by reinforcement learning is useful for designing automatic berthing system for the ship.

Quantitative evaluation on the suitable flow region inside the shielding device of submersible aquaculture facility

The primary purpose of the aquaculture facility is to provide a comfortable living environment and achieve welfare aquaculture for cultured fish in the open sea. Nevertheless, it has been a challenge to accurately assess the suitable flow region of the cultured fish inside the aquaculture facility for the severe ocean environment, which is a pressing concern for aquaculture farmers. First, the maximum domed swimming speed (MDSS) is used as an indicator to assess the swimming ability of Sciaenops ocellatus in this study, which can be measured through a vertical circulation water channel. Subsequently, the porous media theory is adopted and applied to predict the flow field inside the shielding device of the submersible aquaculture facility based on the shear stress transport k-omega turbulence model using the computational fluid dynamics (CFD) approach. In addition, combining the swimming ability of Sciaenops ocellatus and current speed distribution inside the shielding device of a submersible aquaculture facility, the suitable flow region is quantitatively assessed. The results indicate that when middle height, the inclined angle and net solidity are 0.4 m, 3π/12 and 0.65, respectively, the current speed inside the shielding device attenuates below the maximum domed swimming speed of Sciaenops ocellatus - 0.76 m/s and meets the survival of Sciaenops ocellatus for the actual sea condition with an incident current speed of 1.5 m/s. In addition, a suitable flow region for Sciaenops ocellatus, which is 204.512 m3 and accounts for 17.76% of the total aquaculture volume, is formed and located inside the shielding device, close to the downstream sides, and gradually extends towards the middle of the shielding device. Based on the swimming ability of Sciaenops ocellatus, using numerical means to describe the suitable flow region in detail is to provide clear and macroscopic guidance for aquaculture farmers.

Modeling and simulation analysis of active heave compensation control system for electric-driven marine winch under excitation of irregular waves

The six-degree-of-freedom (6 DOF) motion of the mother-ship, which is caused by wave fluctuation, makes offshore operations difficult. To solve this problem, various heave compensation systems were proposed, as well as the law of wave motion. These heave compensation systems included passive heave compensation system, semi-active heave compensation system, and active heave compensation (AHC) system. However, the empirical formula of wave motion is not suitable for practical offshore operations, and rare AHC systems take the characteristic of compensation into consideration. To study the compensation characteristic of the AHC system based on electric-driven marine winch in the actual sea condition and improve the accuracy of compensation, this work uses the measured data of wave motion, and deduces the motion equations of multi-axial driving system. By substituting the above elements into the AHC system and designing the sliding mode controller (SMC), the simulation results show the ideal compensation effect of the system. By comparing with experimental results, it is concluded that the driving system operates in according with the specified states, and the compensation performance of system is effective. The overall work is conductive to the research on AHC system, as well as the exploitation of marine resources.

Numerical Simulation of the Maneuvering Motion Wake of an Underwater Vehicle in Stratified Fluid

When a vehicle moves underwater, disturbance is generated and a wake remains that destroys the original free surface and produces a new wake. In order to study the mechanism and characteristics of the wave-making wake generated by the maneuvering motion of an underwater vehicle in density-stratified fluid, the k-ε model and the VOF method that is based on the RANS equation were used in this paper to analyze the SUBOFF model in stratified fluid at different drift angles. Numerical simulation of the maneuvering motion was carried out under these angles, and the corresponding changes in flow field caused by this motion were analyzed. The results from the comparison and analysis of the surface wave wakes under different drift angles in stratified fluid show that with the increasing drift angle, the motion wake of the vehicle still exhibits obvious Kelvin wave system characteristics. However, there are significant changes in hydrodynamic performance. The asymmetry of the surrounding flow field will increase with the increase in the drift angle. The pressure of the underwater vehicle is inversely proportional to the velocity of the surrounding flow field, and the amplitude of the peak and trough of the free surface wave is linearly related to the change in the drift angle. The numerical simulation can serve as a reference for the non-acoustic detection of the motion heading of an underwater vehicle and the motion trajectory of anti-reconnaissance underwater vehicles under actual sea conditions.

Uncertainty-informed ship voyage optimization approach for exploiting safety, energy saving and low carbon routes

Voyage optimization has been an effective way to find safe, energy-saving and low carbon routes, but it strongly depends on the accuracy of the weather forecast data that exists the uncertainties which has been influencing the effectiveness and capability of the voyage optimization. In this paper, an uncertainty-informed multi-objective voyage optimization approach is presented. The uncertainty of weather forecast is first explored and modeled by using the historic weather forecast data and the corresponding observations. Then a novel multi-objective voyage optimization model is proposed based on the uncertainty of weather forecast. To solve this uncertainty-informed voyage optimization problem, an uncertainty-based risk penalty function is presented to guide the fitness assessment of the evolutionary algorithm. Finally, the weather forecast uncertainty model was evaluated by using the actual voyage record data, and the superiority and effectiveness of the proposed method were confirmed by comparing it with the conventional state-of-the-art optimization method on the North Atlantic where there were adverse sea conditions. Experimental results show that the optimized route obtained by the proposed method can effectively avoid some underestimated areas where the actual sea states far exceed the forecast data, which is significant for ships to enhance the safety and the energy efficiency.

Mid-XIX Century Estuary SST Time Series Recorded in the Venice Lagoon

Sea surface temperature (SST) is of paramount importance for comprehending ocean dynamics and hence the Earth’s climate system. Accordingly, it is also the most measured oceanographic parameter. However, until the end of the XIX century, no continuous time series of SST seems to exist, with most of the available data deriving from measurements on ships. Here, we present a continuous digitalized record of surface water measurements originally written in a book published in 1853. The measurements were retrieved thrice daily in the Venice lagoon, in the northeastern part of the Italian peninsula, from June to August 1851 and 1852. To the best of our knowledge, these data constitute the oldest time series of the entire world ocean. The measurements were performed by immersing a Réaumur thermometer a few meters deep in the lagoon water at 8 a.m., 12 p.m., and 8 p.m. Despite several limitations affecting these data (e.g., lacking information regarding the exact water depth where measurements were performed and instrumental metadata), they are of utmost significance, as they put many decades backward the date of the development of a fundamental aspect of oceanographic observations. Moreover, the data were collected close to the Punta della Salute site, where actual sea water temperature measurements have been performed since 2002. Therefore, a unique comparison between surface water temperatures within the Lagoon of Venice across three centuries is possible.

Evaluation of ship operational effect based on long-term encountered sea states using wave hindcast combined with storm avoidance model

Ships avoid severe sea states for the safety of lives and property and to save energy. Therefore, the actual sea states encountered by ships differ from nature and are affected by human operational effects that we refer to as the “ship operational effect”. The evaluation of the ship operational effect is crucial for the rational design of structural strength of the hull. In this study, we derived the sea states encountered over 25 years in the North Atlantic, by considering storm avoidance by merchant ships. We then performed long-term predictions of the ship motions and wave loads of 75 merchant ships. Existing pioneering studies used automatic identification system (AIS)-based ship locations and timestamps to subsample wave hindcast data along ship tracks for a limited duration. Unlike existing studies, we used a statistical storm avoidance model of merchant ships to reconstruct the sea states, encountered over 25 years, in the North Atlantic. Owing to the ship operational effect, the long-term prediction values of roll motion, pitch motion, vertical bending moment amidships, and hydrodynamic pressure on bottom centerline amidships of merchant ships, at the probability level 10−8, were reduced by approximately 10–20%, and the coefficient of the ship operational effect was 0.8–0.9. Furthermore, we evaluated the uncertainties in the ship operational effect. The values deviated by as much as 6%, depending on the choice of wave hindcast products (TodaiWW3-NK, IOWAGA, and ERA5). The variation based on the parameter settings of the storm avoidance model (severity of the storm, radius of influence of the storm, and number of ship locations) was up to approximately 1 m at a probability level of 10−5 of the encountered sea states for 25 years.