In order to improve the efficiency of multi-parameter, high dimensional and high nonlinear optimization of ship structure reliability optimization design and make up the lack of uncertainty factors affecting structural safety in traditional deterministic optimization design, a river-sea-going ship was taken as the research object. BP (Back Propagation) neural network agent model technique and SMOTE (Synthetic Minority Oversampling Technique) algorithm were used to increase the number of sample points near the failure surface, in order to obtain a high-precision limit state agent model of ship structure with fewer sample points. Combined with Monte Carlo simulation method, the reliability calculation program of hull structure was developed. Structural reliability optimization analysis was performed adopting the simulated annealing optimization algorithm in order to reduce the structural weight. A set of complete and effective reliability optimization design system based on agent model technology was established to improve the efficiency of reliability optimization design, which has guiding significance to the reliability optimization design of river-sea-going ship structures.

Mobile floating offshore wind turbines (MFOWTs) can store the generated wind energy onboard, and navigate to preset working areas due to their mobility. Compared to fixed and moored floating offshore wind turbines, MFOWT can not only harness the abundant far-offshore wind resource but also supply power to offshore energy consumers, because of its superior working ability in deep sea. In this paper, key technical problems in the development of MFOWT are summarized and discussed in several aspects based on a literature review and our research: (1) floating substructure selection; (2) conceptual design and approval; (3) dynamic response analysis for the integrated system; (4) operational strategy decision; (5) safety assessment; (6) model test in ocean wave basin; (7) construction and installation.

An acoustic black hole stiffened plate was designed based on acoustic black hole and stiffener structures. Acoustic radiation characteristics, vibration energy distribution and transmission characteristics were studied by establishing the finite element model of the acoustic black hole stiffened plate. The simulation results show that the radiated sound power of the acoustic black hole stiffened plate is 8~20 dB lower than that of ordinary stiffened plates above the cut-off frequency. Because of the local damping layer, the vibration gathered in the acoustic black hole’s region is effectively dissipated. Therefore, the vibration level is significantly lowered and the acoustic black hole stiffened plate is weakly coupled to the sound field. It is verified that most of the kinetic energy of the acoustic black hole stiffened plate is concentrated in the acoustic black hole region while analysis of the vibration energy distribution characteristics shows that the vibration level of the overall structure is reduced. It is revealed that the acoustic black hole stiffened plate is affected by the superposition effects which include acoustic black hole’s concentrating energy effect and stiffened plate’s blocking vibration effect. Compared with ordinary stiffened plates, acoustic black hole stiffened plates have better vibration and noise’s reduction performance.

Based on the immersed boundary-multiple relaxation-lattice Boltzmann method, a numerical simulation of the flow around three cylinders in equilateral triangle arrangement was conducted at Re=100, the influence of two key parameters, the spacing ratio (K_d) and incoming flow angle (α), on fluid force coefficient and flow field characteristics was analyzed, and several flow mechanisms were revealed. The calculation results show that the wake pattern in different flow fields is divided into single vortex, single vortex to double vortex, irregular double vortex, regular double vortex, double vortex to triple vortex, irregular triple vortex and regular triple vortex pattern, and that the downstream vortex street is more regular and the wake pattern changes faster at α=30°. The time-averaged fluid force coefficient of three cylinders is greatly affected by the gap flow velocity, and the changing trend with the spacing ratio (except for the small spacing ratio) at each incoming flow angle is nearly identical. The transition of the wake pattern will change the root mean square value of three cylinders’ fluid force coefficient significantly. When K_d≥3.5, the root mean square value of upstream cylinder’s fluid force coefficient fluctuates greatly. Except for α=0°, the vortex shedding frequency of the midstream cylinder is less affected by α and K_d when K_d≥2.5, which is relatively stable.

As the application of composite materials can improve the cavitation performance and vibration characteristics of propellers, it has been widely concerned in the field of advanced marine propulsion equipment. In this paper, the flow field of a composite material propeller was calculated based on URANS, the dynamic response of the blade structure was solved by FEM, and the hydrodynamic load and structural deformation were transmitted in real time bi-directionally. The simulation of the evolution of tip cavitation in the high wake region shows that the maximum tip deformation increases with the initiation and development of tip cavitation, reaches the maximum at the stage of tip vortex cavitation formation, and then decreases with the collapse of bubbles. The mechanism of the improvement of propeller propulsive efficiency and the suppression of tip cavitation due to the application of composite materials was revealed, indicating that the composite material propeller produces bending torsion coupling deformation under cavitation hydrodynamic load, and adaptively adjusts the angle of attack to suppress cavitation development. Comparison of the cavitation performance between the composite material propeller and the rigid propeller under typical cavitation condition reveals that the composite material propeller has a mild peak pressure fluctuation and a better adaptability to the non-uniform wake.

High-resolution flow field data are of great significance to the study of fluid mechanics. Limited by measurement methods and calculation efficiency, it is still difficult to obtain high-resolution flow fields directly in some circumstances. A low-dimensional representation model for flow time history data was poposed, and a deep learning method for reconstruction of unsteady flow time history data was developed. The proposed method extracted the time-history features contained in the samples using one-dimensional convolution directly; then, the mapping from the physical space and the encoding space was built; and finally, the decoder in the representation model was utilized to generate flow time history data at unknown positions. Unsteady laminar flow with Re_D=200 was studied, and the accuracy of the method was verified. The method proposed in this paper, a new flow field data reconstruction method in an unsupervised training manner in the time dimension, can be widely used in point-based sensor data analysis.

Small- and medium-sized ships have a shallow draft, but their propellers are fast in speed, small in diameter and light in weight. Once the span of the front and after stern tube bearings is large, the position of the after stern tube bearing fulcrum will exceed the range given by the standard. Based on the finite element method, the shafting was simplified into Timoshenko beam element to establish a finite element model. Considering the actual installation clearance of the ship shafting and the load stiffness curve calculated based on Hertz contact theory, the shafting alignment calculation of large span propeller shaft, which was based on different support positions and various support models, indicates that for the shafting with a large span of propeller shaft, the value of the fulcrum position of stern tube rear bearing in CB/Z 338-2005 is not suitable. If the bearing fulcrum exactitude is correct, the calculated bearing loads of single point rigid support, single point elastic support and multi-point nonlinear elastic support will have a similar result.

Particle image velocimetry (PIV) technology is a non-contact global velocity field measurement technology. In the field of shipbuilding and ocean engineering, the particle images taken in the PIV experiment often contain interference such as structure occlusion and free liquid surface, which needs to be masked before the liquid phase velocity field is calculated. Therefore, it is of great significance to realize the automatic masking of the interference area in the PIV image and the high-precision calculation of the velocity field in the liquid phase area. In this paper, based on the optical flow convolutional neural network LiteFlowNet, a deep learning model Mask-PIV-LiteFlowNet that can realize automatic mask and velocity field calculation was designed. Furthermore, based on the PIV mask dataset of the object entering the water and on the PIV velocity field calculation data set, a data set was made to train and test. The test results show that the model can effectively reduce the calculation errors of the velocity field near the boundary of the mask and can extract small-scaled flow information of the flow field finely. Compared with the current advanced particle image velocimetry deep learning model, the calculation accuracy was improved by more than 20%, and the calculation speed was improved by 5.7%. Finally, the proposed model was tested with the actual images of the wedge-shaped body entering the water and the carp swimming PIV, verifying that the model has a strong generalization ability.

In order to investigate the microbubble drag reduction (MBDR) of ships, numerical studies of MBDR on a low-speed bulk carrier model were conducted based on the two-phase Euler model in OpenFOAM. The governing equations were established for the gas and liquid phases, respectively, considering five kinds of interfacial forces and bubble coalescence and breakup. The modified k-ε turbulence model considering the effects of bubbles was also used, and the superimposed model was adopted to ignore the influence of free surface. The effects of air flow rate, bubble size, ship speed and draft on MBDR of the ship were investigated while the distributions of air volume fraction, turbulent viscosity and bubble size around the ship were analyzed. The numerical results show that: micro bubbles can simultaneously reduce the frictional drag, viscous pressure drag and total drag of the ship; air flow rate can directly influence the drag reduction and more air flow rate can lead to more drag reduction; smaller micro bubbles can lead to higher average volume fraction, more uniform gas distribution and smaller turbulent viscosity, resulting in drag reduction more effectively;bubble coalescence will occur along the direction of the flow and the coalescence effects are more intense for smaller bubbles; higher ship speed and lower draft are more conducive to drag reduction.

In this paper, to study the evolution pattern of wake vortices past two crossing cylinders in 60 degrees arrangement at the gap ratio of G=4 and the Reynolds number of Re=200, proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD) were employed to analyze the magnitude vorticity data. The analysis results indicate that the spatial scale of wake vortices decreases with the frequency increasing. The large-scale flow phenomena in the wake can be approximately reconstructed by a few low-frequency modes, while high-frequency modes mainly enrich the small-scale turbulence details. Wake vortices shed from upstream and downstream cylinders at a frequency of 0.19 Hz and propagate toward downstream in parallel morphology with the same frequency. The interaction of the vortex shedding from upstream cylinder on the downstream cylinder causes a significant vortex-induced vibration(VIV) on the downstream cylinder and results in multiple peaks in its lift coefficient spectrum.