At present, iFEM (inverse finite element method) is one of the most promising methods to construct a structural strain field. The purpose of this method is to obtain a structural strain field that meets the precision requirement with the least number of real measuring points in the process of discrete strain acquisition. However, when it is difficult to collect strain data in some local areas, discrete strain data can be collected by combining virtual and actual measuring points. In this paper, the stiffened plate of a typical ship structure was taken as an example, according to the measured data, combined with the simulation model and the measurement point regression method of Xgboost, the strain field reconstruction accuracies of the three methods of measurement, simulation and virtual and real combination were calculated based on the iFEM technology, and the causes of error were analyzed. The prediction results showed that the average error of 47 physical measurement points was the lowest, which was 1.92%.When 15 points and 21 points were input through the virtual-real combination path, the errors between the results and the verification points were all less than 3%, which verified that the strain field reconstruction method of virtual-real combination with a quick supplement of the missing data has strong operability and high accuracy.

Ship roll damping estimation based on roll decay curves is very common in engineering. There are many methods to estimate damping from roll decay curves, which lead to difference in damping estimation results. In order to achieve the purpose of obtaining high-precision damping prediction methods, the principle of estimation of roll damping based on roll decay curves in recent years was analyzed in detail first in this paper and then its scope of application was expanded. The methods were divided into two categories according to the principle, namely, one based on piecewise linear assumption and the other based on parameter identification. The data of standard model (DTC) were used to verify and compare the characteristics of different methods, and the error sources of damping coefficient estimation were analyzed. The results show the accuracy of estimation is strongly related to the used method. The Froude energy method with clear physical meaning, few error sources, and insensitivity to measurement noise and error is recommended as the preliminary estimation method. If a damping model with sufficient accuracy can be found, estimation based on the Prony-SS method, which has an inherent noise suppression mechanism and a unique solution, can be further done to improve the accuracy.

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.

The Arctic region is rich in oil and gas resources. The exploitation and utilization of oil and gas resources in this area have great prospects, but are also very challenging. Arctic areas have ice-free and ice-covered seasons. As current design specifications for offshore platforms do not fully consider the impact of sea ice, the effect of wave loads and ice loads should be considered together to enable the platform to operate all year round. In this paper, the dynamic response of a semi-submersible offshore platform under different conditions was studied, such as wave, level ice, and ice floes. Potential flow theory and Morrison equation were used to calculate wave loads while the discrete element method was used to solve the ice loads. The slender body finite element method was used for analysis of the slender system. The motion of the platform and the force of the slender system were solved by nonlinear time-domain calculation. The results show that compared with other environmental loads, the tension of the mooring line is the highest under level ice. In a broken ice field with smaller ice thickness, ice concentration, and ice floe size, the platform motion conforms to current safety specifications. The research of this paper will provide a reference for the safe development of oil and gas resources in the Arctic region.

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.

For high speed ships, impact produced by cavitation is the source of abnormal noise and even cavitation erosion. However, cavitation is actually a complex process containing multi-scale structures coupled with many influencing factors such as cavitation shedding, cavity breaking, local merging and collapse, it is still a tough work to make clear the mechanism for the impact in full-scale cavitating flow and to control its effects. In this paper, cavitation around a twisted hydrofoil was selected to clarify the relation between the cavitating impact and instantaneous cavitation behavior, using a synchronized system composed of a high speed camera and a hydrophone to make the measurements synchronously in time domain, and a soft paint layer to show the cavitation impacted region. The results indicate that for a typical sheet-to-cloud cavitating flow, the high magnitude impulse composed of high frequency component is related to the local collapse and rebound of cloud cavitation shedding from sheet cavity. The study provides the physical understanding and control of cavitation impact in the industrial field.

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.