Journal of Marine Science and Technology最新文献

This paper examines the acquisition of the measurement data of the spatial distribution of unsteady pressure on a ship advancing in waves. The purpose of the study is to investigate the reliability of the pressure data obtained by the unprecedented experiment and to provide experimental data of unsteady pressure which can be used for validation of arbitrary computation methods. The optical fiber sensing technology, so-called FBG (fiber Bragg gratings) sensing, is employed as the pressure sensors. In the experiment, 379 FBG pressure sensors (version 7; the latest version) in total are attached to the port side surface of ship model and also ordinary strain-type pressure sensors are embedded in the starboard side for validating reliability of FBG pressure sensors by comparing both results. In addition to the pressure distribution, measurement is made for unsteady hydrodynamic forces such as added mass, damping coefficients, and wave exciting forces, and also for ship motions and added resistance. Most of the measurement is repeated at least five times for each condition, and results of measured pressures are evaluated with mean value and standard deviation. Regarding the added resistance, the distribution for estimating added resistance is also extracted from obtained pressure distribution and its pressure contour is illustrated to show visually which hull region affects the added resistance significantly. Validation of the measured pressure with FBG pressure sensors is carried out also by integrating measured pressures over the ship model surface and comparing it with forces directly measured with load cells. The measured pressure distribution is compared with typical calculation results with the Rankine panel method in frequency domain to demonstrate usefulness of the spatial pressure data for validating the calculation method. Through these studies, it is confirmed that the measured unsteady pressures with FBG pressure sensors are accurate enough and valuable as the validation data for any calculation method.

The recent global trend toward decarbonization is also occurring in the maritime industry and there is an urgent need to improve the fuel efficiency of ships. Various energy-saving devices (ESDs) are adopted for this purpose. However, because of the difference in the boundary layer thickness between full-scale and model-scale, it is difficult to estimate the actual performance of ESDs in a tank test. As a solution to overcome this difficulty, the Boundary Layer Similarity model (BLS model) is proposed in which only the stern part of the hull is extracted to shorten the model length and to make its boundary layer thickness equivalent to that of a full-scale ship. By using this BLS model, the performance of ESDs on a full-scale can be estimated in a model test. In the present paper, the applicability of the BLS model is investigated by CFD (Computational Fluid Dynamics) simulations of performance estimation of an energy-saving fin in different locations for a bulk carrier. It is found that the BLS model is capable of predicting the full-scale performance of the fins by the model-scale simulations. Moreover, the flow fields affected by the fins with the BLS model are similar to those of full-scale. It is expected that the use of the BLS model enables the prediction of the full-scale performance of ESDs in a model test.

Heave plate is one of the most commonly used plates for controlling the movement of floating structures that are used for offshore deep water operations. Heave plates, in fact, move in both directions simultaneously. Therefore, the primary goal of this work is to examine the coupling motion’s effects on hydrodynamic coefficients caused by the heave and pitch motion of a heave plate. Numerical simulations are used to first simulate coupling motion in phase, and then out of phase which varies from (0^circ) to (90^circ). The effects of added mass and moment, as well as pitching and heaving damping are investigated. Based on the results of the coupling oscillation of the heaving plate at different Keulegan–Carpenter (KC), the results indicate that added mass and pitching damping have more influence than added moment and heave damping coefficient.

Ocean wave spectrum is the key to the response estimation of seagoing vessel whose structural integrity is of utmost importance. Efforts have been made by researchers to correctly estimate the ocean wave spectrum using so called ‘wave-buoy analogy’ concept, where the vessel is considered to behave as a wave buoy. The aim of this study is to develop a methodology through which the directional wave spectrum can be estimated using the concept of ‘wave-buoy analogy’. To achieve the objective, ocean wave was modeled with 10-parameter bimodal wave spectrum combining long- and short-wave component. These 10 parameters of bimodal wave spectrum were targeted by solving non-linear least square problem, which is formulated by error function quantifying the difference between model prediction and onboard measurement data. Model prediction is based on the linear relationship between the wave spectrum and response spectra and measurement data are directly from the sensors installed on the vessel. To solve the non-linear least square problem, Bayesian statistics-based probabilistic approaches, Markov-Chain Monte Carlo simulation (MCMC), were utilized. Well-known adaptive Metropolis–Hastings algorithm which is one of the most popularly used MCMC techniques was utilized to derive the spectrum parameters that best describe the directional wave spectrum. To validate the proposed methodology, pseudo measurement data generated by numerical analysis with different loading conditions were used. The application of the proposed methodology to the numerical analysis data confirmed that it accurately estimates the response at locations where sensors are not installed.

This study proposes a method for estimating river plume length from water levels and river discharge rates. A numerical model for coastal ocean dynamics was refined by comparing thermohaline fields calculated using the model with those measured off the mouth of the Sakawa River in Sagami Bay, Japan. The model successfully captured the reduction in salinity within the surface 1.0-m layer caused by riverine water transport. The simulated surface salinity maps revealed that the dynamic motions of the river plumes were primarily driven by one of the two diurnal occurrences of tidal current intensification. Regression analyses of the simulated results demonstrated that the river plume lengths were closely correlated with the water levels and river discharge rates, and that they could be accurately estimated from preceding river discharge rates under weak wind condition.

Abstract

Many efforts have been dedicated to examining the flow characteristics around a pair of cylinders. Despite the straightforward geometry, the flow dynamics around a cylinder prove to be intricate. The practical applications of this phenomenon extend across various engineering domains, including oil and gas transmission lines, heat exchangers, pipelines, and the construction of successive skyscrapers. The current investigation delves into the examination of the critical distance ratio, fluctuating velocity, flow pattern, and drag surrounding two sequential circular and square cylinders. The governing equations are solved using the finite volume method (FVM). For momentum, turbulent kinetic energy, and turbulent dissipation rate equations, the upwind second-order discretization is used. The findings, acquired at a Reynolds number of 32,000 for distance ratios ranging from 0.25 to 10, are then compared with those from single-cylinder cases. The results highlight the significant influence of both geometry and the distance between cylinders on the observed flow patterns. The critical distance ratio is obtained as (s_{c})  = 2 and 2.5 for the case of two sequential circular and square cylinders, respectively, while for the case of combined circular and square cylinders, it is calculated as (s_{c})  = 3. The non-dimensional fluctuating velocity decreases by 7%, 26%, and 38% in the case of two sequential circular cylinders with distance ratios of S* = 1, 2, and 3 at the first station, respectively, compared to a single circular cylinder. The drag coefficient is 50% lower in the two sequential circular and square cylinders case compared to the single square cylinder.

This study aims to develop a practical path following controller and examine its control effects for large-sized ships in shallow water. First, a new controller is designed and implemented in a ship manoeuvring simulator, and the controller’s tracking capacity is evaluated via controlling a 6 DOF math model following a prescribed path at various speeds and water depths. Then, towing tank tests are conducted with the corresponding physical model to validate the simulation results. Based on experimental results, comparisons are executed between the proposed controller and the traditional controllers (e.g. fuzzy controller). Finally, the applicability of the controller is investigated through simulations of the ship transiting the Panama Canal, meanwhile, the bank effects on the controller’s performance are discussed. The results show that the designed controller offers satisfactory tracking performance. Simulation results match well with the experimental results despite slight discrepancies. Additionally, satisfactory path following performance is obtained by the simulations in the canal. To conclude, the proposed controller is able to fulfill path following missions in shallow water with high precision and can be applied in the manoeuvring simulator.

With the development of artificial intelligence (AI) technology, the autonomous navigation and behavior decision-making capabilities of MASS (marine autonomous surface ship) are constantly being innovated, thereby ensuring their safe navigation. However, the recent algorithms exhibit limited efficacy in navigating in unknown and complex environments, while also lacking the capability to effectively handle the encounters resulting from the uncertain behavior of other ships. Consequently, this study proposes an intelligent navigation methodology utilizing the PRM (Probabilistic Roadmap) and PPO (Proximal Policy Optimization) algorithm to facilitate autonomous navigation and collision avoidance decision-making for MASS. Moreover, the MASS disciplined behaviors prescribed by COLREGs are taken into the consideration of the reward function design. Particularly, in extreme encounter situation, it becomes necessary for MASS to depart from COLREGs, thus requiring a corresponding definition of the reward function. Finally, the autonomous navigation and decision-making capability of the MASS is evaluated using real-time ship traffic in a voyage scenario, while various extreme encounter situations are also simulated to demonstrate the generality and practicality of the proposed PRM-PPO method.

Abstract

Container ships encounter large roll angles and high acceleration, and container loss remains a problem. This study proposes a method for calculating the probability density function (PDF) of roll angular and cargo lateral accelerations. First, the moment values of these accelerations are derived using the linearity of expectation, and the validity of this method is examined. Second, the PDF shapes of these accelerations are proposed and their coefficients are determined using the obtained moment values. Our proposed method can be used to derive the PDFs of roll angular and cargo lateral accelerations.

This paper proposes an positional encoding-based attention mechanism model which can quantify the temporal correlation of ship maneuvering motion to predict the future ship motion in real sea state. To represent the temporal information of the sequential motion status, the positional encoding consisted by sine and cosine functions of different frequencies is chosen as the input of the model. First, the reasonableness of the improved architecture of the model is validated on the standard turning test datasets of an unmanned surface vehicle. Then, the absolute positional encoding based-scaled-dot product attention mechanism model is compared with other two attention mechanism models with different positional encoding and attention calculation methods and its superiority is verified. As demonstrated by exhaustive experiments, the model has the highest prediction accuracy when the input sequence length equals the output sequence length and the accuracy defined in this paper of the model will drop to less than 90% when the predicted length exceeds 45. Finally, the attention mechanism model is compared with the LSTM model with different lengths of input sequences to demonstrate that the attention mechanism model has a faster training speed when dealing with long sequences.