International Journal of Naval Architecture and Ocean Engineering最新文献

The present study concerns validation of data-driven modeling for ship dynamics from free-running model test results, in terms of estimation of hydrodynamic force and moment, maneuvering coefficients, and maneuver simulation results. An estimation method for the hydrodynamic force and moment from the acceleration of a surface combatant model ship is suggested and compared with the conventional ship dynamics modeling. The hull dynamics modeling relates the motion and hydrodynamic force and moment is developed by optimizing maneuvering coefficients which leads to minimum loss function of hydrodynamic force and moment and maneuvering criteria. The maneuvering coefficients of the dynamics model is compared with a conventional system-based dynamics model. Lastly, the maneuvering simulation results are compared to the free-running model test results. The suggested model adequately predicts hydrodynamic force and moment in highly coupled sway and yaw motion.

Real-time acquisition of wave-induced hull girder loads of a sailing ship will help the captain make reasonable decisions, which is of great significance for improving the safety of the ship's navigation. This paper investigates the real-time prediction method of hull girder loads based on the Recurrent Neural Network (RNN) model and error correction strategy. Firstly, taking the vertical bending moment, horizontal bending moment, and torsional moment at the mid-ship position of a large container ship as examples, corresponding neural network prediction models are established through parameter influence analysis. Secondly, various sea state conditions are used to verify the feasibility of established network prediction models to predict the hull girder loads in real-time. The VBM prediction model performs better than the TM prediction model and HBM prediction model, and the errors of the TM prediction model and HBM prediction model are slightly larger in some cases. Lastly, an improved prediction model based on an error correction strategy is proposed to improve the prediction accuracy of the neural network prediction model, and the adequate performance of the error correction strategy is discussed.

Corrosion damage to submarine pressure hulls is a crucial consideration during the structural design phase because it diminishes the structural strength of a submarine, reducing its operational depth and posing a severe risk to the life of the crew. This necessitates using a validated analytical method to estimate the residual strength and assess the safety of corrosion-affected pressure hulls. This paper presents an experimental and numerical investigation of the residual strength of corroded ring-stiffened cylinders, which are typical components of submarine pressure hulls, the main legs of semi-submersibles, and Floating Offshore Wind Turbine (FOWT) foundations. Four steel ring-stiffened cylinder models were fabricated: two remained intact, whereas the other two were artificially corroded by machining. Hydrostatic collapse tests were conducted in a pressure chamber. To evaluate the effect of initial shape imperfections caused by welding fabrication on the strength of the structure, the initial shape imperfections were measured using a three-dimensional coordinate measuring machine. The experimental results illustrate a significant reduction in the residual strengths of the two damaged models compared with those of the intact models. The collapse processes simulated using the Abaqus software package are presented, demonstrating a close agreement between the experimental results and numerical predictions.

As international maritime trade among countries increases, great efforts are being made to reduce the amount of greenhouse gases emitted from ships using conventional fossil fuels. A variety of environment-friendly power sources for ships are being considered, and nuclear energy is one of them. The research described in this paper focuses on elemental technologies related to nuclear-powered ships rather than the nuclear reactor technology itself. Among those technologies, the Passive Residual Heat Removal System (PRHRS) of a nuclear-powered ship is studied to remove residual heat by using seawater as an alternative heat sink. New concept of PRHRS is proposed and it is named as SWC-PRHRS. SWC-PRHRS has two heat exchangers: one is for driving force and another is for dumping the most of residual heat to the sea. Numerical analysis and experimental studies are conducted to improve the performance of SWC-PRHRS. The numerical results show that most of the residual heat comes from a reactor core is eliminated by sea water cooling proving the concept of SWC-PRHRS is working properly without any operator intervention and additional water supply. Experimental studies are conducted based on the numerical analysis results. From the experimental results, it is found that the mass flow rate of SWC-PRHRS is very sensitive to the filling ratio of SWC-PRHRS and there are three distinctive filling ratio ranges. Through the experiment, it is confirmed that SWC-PRHRS is working efficiently with the lower mass flow rate and the smaller upper heat exchanger without any operator intervention. SWC-PRHRS could remove a large amount of residual decay heat from the ship's reactor and release it to the sea. Considering the size, weight, and exceptional heat removal capability of SWC-PRHRS, it is clear that SWC-PRHRS is well suited for marine application usage.

To solve the problem of full-process path planning that includes multi-target path planning and automatic mooring, this paper proposes a hybrid D*Lite algorithm for an unmanned surface vessel with pose constraints (position and attitude) in an unknown environment. First, to solve the problem of multi-target path planning under the pose constraints, the D*Lite algorithm is combined with the Dubins search tree algorithm, and the corner at the sampling point is eliminated so that the path is smoothly connected. Second, to achieve the automatic mooring under the pose constraints and the avoidance of unknown obstacles, the D*Lite algorithm is combined with Reeds-Shepp curves to introduce the heading angle into the traditional two-dimensional search. This paper has conducted three groups of simulation experiments. In simulation experiment 1 and 2, compared with other algorithms in the multi-target points and automatic mooring environment for simulation experiments respectively, the D*Lite (Dubins) and D*Lite (RS) algorithm outperformed other algorithms in terms of planning time, planning distance, and smoothness. In simulation experiment 3, the effectiveness and superiority of the proposed method were verified on the grid map and compared with the traditional D*Lite algorithm. A visualization simulation was conducted, and the results revealed that the hybrid D*Lite algorithm enabled the unmanned surface vessel to efficiently achieve smooth movement with full-process throughout unknown environment.

Efforts to improve the hydrodynamic performance of high-speed ships have been underway for a long time. There are different approaches, one of which is to take advantage of an interceptor. Conventionally, the interceptor blades are mounted vertically on the ship's bottom transom, oriented at a zero-degree angle of attack (AoA). This study comprehensively explores high-speed ships' hulls with and without interceptor configurations, encompassing both negative and positive AoA of the interceptor, conducted through experimental and numerical methods using a fully captive model. The interceptors are strategically positioned and configured. Each configuration was examined under varying AoA settings, with uniform interceptor depths and systematic trim angle adjustments. The Computational Fluid Dynamics (CFD) approach simulates the local flow dynamics around the hull, thoroughly analyzing resistance, pressure distribution, lift force, wave profile, and trim moment. The results indicate that interceptor placement near the keel with AoA adjustments significantly reduces hydrodynamic resistance, while AoA changes have limited impact in other positions. Lift force analysis shows interceptors improve lift compared to the bare hull, but this improvement is not linear across positions. Furthermore, it is observed that adjustments in AoA influence lift, with a negative AoA generally being considered favorable. In summary, carefully considering placement, AoA, and height-to-length ratio is necessary to maximize interceptor advantages.

The presence of twin hulls of a catamaran has a strong impact on wave pattern in the whole inner region due to interference between waves generated by each demi-hull. Consequently, wave profiles as well as wave height become complicated and unpredictable in the inner region not only in still water, but also in the presence of waves. Determining wave characteristics between demi-hulls of the catamaran is essential for predicting the operation of an autonomous underwater vehicle (AUV) throughout the launch and recovery (LAR) process. This study performed an experiment to investigate wave characteristics between demi-hulls of the catamaran under regular and irregular waves at various wave directions and speeds. The experiment was designed to measure wave elevation in the inner region between demi-hulls in waves using ultrasonic sensors and capacitance wave probes. The experimental method and setting were verified exacting by comparing the motion response of the catamaran measured by the Qualisys system with numerical simulation using the 3D panel method. Then, wave elevation in the inner region was measured and analyzed to wave height which is a representative parameter of regular waves and to wave spectral density and significant wave height which are representative parameters for irregular waves. These parameters were compared to those of the ocean waves to understand influences of wavelengths, sea states, wave directions, and speeds on wave characteristics between demi-hulls of the catamaran. Plotting of difference from ocean waves indicated the discrepancy in wave characteristics among positions in the inner region, wavelengths, wave directions, sea states, and speeds compared to ocean waves. Results of wave characteristics in the inner region are valuable to analyze motion response and behavior of AUV during LAR process of unmanned surface vehicle (USV).

Reinforcement learning has shown promise in enabling autonomous ship navigation, allowing vessels to adapt and make informed decisions in complex marine environments. However, the integration of soft constraints and their impact on performance in RL-based autonomous vessel navigation research remain understudied. This research addresses this gap by investigating the implications of soft constraints in the context of the risk-averse ship navigation problem. Four distinct soft constraint functions are proposed, which are integrated with two widely used RL algorithms, resulting in the creation of eight risk-averse autonomous vessel navigation models. To ensure a comprehensive evaluation of their performance, comparative analyses are conducted across seven virtual digital channel environments. Additionally, a novel metric, known as Large Helm Momentum (LHM), is introduced to quantify the smoothness of autonomous vessel navigation. Through thorough experimentation, key considerations for the design of soft constraint functions in the domain of autonomous ship navigation are identified. A comprehensive understanding of how different soft constraint functions influence autonomous driving behavior has been achieved. Key considerations for designing soft constraint functions in the domain of autonomous ship navigation have also been identified. Five principles, namely the constraint association principle, dominance of hard constraints, reward-balance principle, mapping requirement principle, and iterative improvement principle, are proposed to optimize the design of soft constraint functions for autonomous ship navigation, providing valuable guidance and insights.