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28 February 2024, Volume 58 Issue 2 Previous Issue   
Naval Architecture, Ocean and Civil Engineering
A Review of Numerical Studies of Wave Impacts on Marine Structures
ZHANG Nianfan, XIAO Longfei, CHEN Gang
2024, 58 (2):  127-140.  doi: 10.16183/j.cnki.jsjtu.2022.500
Abstract ( 1032 )   HTML ( 8 )   PDF (4659KB) ( 68 )  

Wave impact is a strongly nonlinear interaction between waves and structures, and its load usually has the characteristics of a large peak value and short duration. In recent years, the extreme environment has frequently led to severe wave impacts on marine structures, resulting in loss of life and property, thus making the issue of wave impact become a great concern. For the complicated impact process, the theoretical analysis and model experiments can only provide simplified analytical solution and limited information on the slamming flow field. Therefore, numerical simulation has gradually become an effective means to study the issue of wave impact. Scholars at home and abroad have conducted a large number of numerical investigations on the load characteristics of wave impact, impact process, and its influencing factors on marine structures, gaining numerous important research conclusions. In this paper, the current progress, existing methods, and important conclusions of the numerical study of wave impact on marine structures are reviewed, which can provide useful references for further research on the numerical simulation of wave impact.

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Inverse Reconstruction of Environmental Loads and Virtual Model Test
LI Xu, XIAO Longfei, WEI Handi, WU Wencheng, ZHU Ziyang, LI Yan
2024, 58 (2):  141-146.  doi: 10.16183/j.cnki.jsjtu.2022.398
Abstract ( 1002 )   HTML ( 4 )   PDF (3587KB) ( 55 )  

Novel methods of inverse reconstruction of environmental loads and virtual model test for hybrid model test are proposed. The environmental loads are extracted from the physical truncated model test, considering the nonlinear effects such as coupling effect among the six-degrees-of-freedom (6 DOF) motions and wave slamming, and viscous force of the fluid. The loads can be further applied to the numerical model in virtual wave basin to conduct virtual model test with truncated and full-depth mooring system. Wave basin tests under combined wave, wind, and current condition are conducted to validate the proposed methods, and the results show that the environmental loads can be accurately reconstructed from the physical model tests.

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Dynamic Response of a Vessel-Shaped Fish Cage Considering Coupling Effect Among Body Motion, Disturbed Velocity Field, and Net Loads
WANG Yihou, FU Shixiao, XU Yuwang, LI Shuai, FU Qiang, LIU Fuxiang
2024, 58 (2):  147-155.  doi: 10.16183/j.cnki.jsjtu.2022.404
Abstract ( 920 )   HTML ( 2 )   PDF (10409KB) ( 22 )  

Vessel-shaped fish cages are a new type of large aquaculture structure consisting of a floating body, steel frames, net system, and mooring system. The diffraction and radiation waves induced by the floating body can disturb the velocity field and induce additional changes to the hydrodynamic loads on the nets. In this paper, the velocity transfer functions around the nets induced by the diffraction and radiation waves are obtained and the effects of floating body on the forces of the nets are calculated by the Morison equation. By performing the iterations between the motion of floating body and loads on the nets, the fully coupled dynamic response of motion-disturbing velocity field-net loads is realized. Finally, the effects of diffraction and radiation waves on motion response, tension in the net twine, volume reduction, and connector loads are investigated. The results show that the influences of disturbing velocity field on cage motion response and volume reduction are not obvious, but they can lead to a significant increase in the tension in net twine and connector loads, which can provide helpful reference for the structural strength analysis and safety design of vessel-shaped fish cages.

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An Artificial Neural Network-Based Method for Prediction of Ice Resistance of Polar Ships
SUN Qianyang, ZHOU Li, DING Shifeng, LIU Renwei, DING Yi
2024, 58 (2):  156-165.  doi: 10.16183/j.cnki.jsjtu.2022.316
Abstract ( 952 )   HTML ( 3 )   PDF (1823KB) ( 31 )  

Accurate prediction of ice resistance plays an important role in ensuring the safety of ship sailing in polar navigation in ice areas. In recent years, machine learning has been widely used in the field of ships, among which artificial neural network (ANN) is a common method. The focus of this paper is to design an ANN model for predicting the ice resistance of polar ships. According to the traditional empirical and semi-empirical formula, appropriate input characteristic parameters are selected. The radial basis function (RBF) neural network model is built based on a large number of ship model test data, and the genetic algorithm (GA) is used to optimize the model. The research shows that the radial basis function neural network model optimized by genetic algorithm (RBF-GA) based on seven characteristic parameters input has good generalization effect. Compared with the model test and full-scale test data, the average error is about 8%, which shows that the RBF-GA model has a high accuracy, and can be used as a tool for ice resistance prediction.

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Calm Water Resistance Prediction and Navigation Posture Optimization of a New Unmanned Survey Catamaran
CAI Junlei, YAO Tiancheng, LIU Hong, WAN Lijian, WAN Jun, FAN Xiang, ZHAO Yongsheng
2024, 58 (2):  166-174.  doi: 10.16183/j.cnki.jsjtu.2022.452
Abstract ( 931 )   HTML ( 5 )   PDF (14650KB) ( 35 )  

In order to obtain the resistance performance and economic navigation posture of a new unmanned survey catamaran, a calm water resistance simulation of this catamaran is conducted by model tests, the empirical formula method, and the computational fluid dynamics (CFD) method. Further, the CFD method is used to explore the influence of different longitudinal positions of the center of gravity on the hull and perimeter waveform, and a suitable installation position is selected for the multi-beam acoustic equipment. The results show that the CFD method can accurately predict the navigation posture and resistance at all speeds, while the empirical formula method is mainly suitable when the speed is low (FrΔ<1.5). At the speed of 4 and 6 kn, the economic navigation posture is at a tail tilt of 1.4°. At this time, there is a relatively stable high water level area between the pieces of about 0.3 to 0.5 times of vessel length from the stern, which can be used as a suitable installation position for multi-beam acoustic equipment.

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Numerical Analysis of Hydrodynamic Performance of Propeller in Waves
ZHANG Geng, YAO Jianxi
2024, 58 (2):  175-187.  doi: 10.16183/j.cnki.jsjtu.2022.247
Abstract ( 1036 )   HTML ( 6 )   PDF (14901KB) ( 134 )  

The hydrodynamic performance of propeller is mostly studied in calm water, but the propeller working behind ship is often affected by waves. According to the literature, there is relatively little research on hydrodynamic performance of propeller in waves at present. In view of this, RANS solver based on OpenFOAM is used to calculate and analyze the influence of waves on the thrust and torque of propeller. The results show that time history curves of thrust and torque oscillate under the influence of waves. The disturbance of free surface and the oscillation amplitude of time history curves increase with the decrease of immersion depth and advance coefficient. Compared with the calm water condition, the average thrust and torque of propeller in waves are reduced when the immersion depth and advance coefficient are the same. The computational results are in good agreement with the experimental data.

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An Rapid Prediction Method for Propeller Hydrodynamic Performance Based on Deep Learning
GAO Nan, HU Ankang, HOU Lixun, CHANG Xin
2024, 58 (2):  188-200.  doi: 10.16183/j.cnki.jsjtu.2022.331
Abstract ( 908 )   HTML ( 2 )   PDF (5139KB) ( 24 )  

In order to achieve rapid and accurate prediction of the hydrodynamic performance of propellers, a set of propeller hydrodynamic performance prediction model was established based on the improved residual connection network. The residual connection method greatly improves the depth of the model. In combination with the Inception structure to simultaneously extract data features from different scales, the depthwise separable convolution reduces the model parameters. The sample space for training the deep neural network is built based on the propeller geometric parameters and model test results. An improved beetle swarm antennae search algorithm is proposed to optimize the initial weights and thresholds of the model to further improve the prediction accuracy of the model. The research results indicate that the improved beetles swarm antennae algorithm significantly improves the accuracy of the model and solves the problem of overfitting of it. The prediction results of the model are in good agreement with the experimental values, and its prediction performance for the propellers which are not in the dataset is basically the same as that of the CFD method. The model has an excellent universality and its calculation period is extremely short, which can meet the requirements of real-time and accurate prediction of propeller open water performance.

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Layout Optimization Design of Human Machine Interface in Wheelhouse Based on Ergonomics
JI Yuheng, LI Chuntong, LUO Xiaomeng, YANG Xuelian, WANG Deyu
2024, 58 (2):  201-210.  doi: 10.16183/j.cnki.jsjtu.2022.401
Abstract ( 950 )   HTML ( 5 )   PDF (6622KB) ( 54 )  

To solve the problems of empiricism, subjectivity and randomness in the manual layout of human machine interface in wheelhouse, an optimization layout design method of human machine interface that combines virtual simulation and optimization algorithm is proposed. First, the optimal operating point and the operating comfort of each area of the human machine interface are obtained through virtual simulation. Then, the layout criteria and ergonomics criteria of human machine interface are quantified as objective functions and constraints, a layout optimization mathematical model of human machine interface is established, and a large number of initial positions of the particles in the particle swarm optimization (PSO) algorithm are obtained through the differential evolution algorithm. Finally, the optimal layout scheme is obtained, and virtual simulation evaluation is conducted. Taking a control panel as an example for layout optimization and virtual simulation, the optimal layout scheme obtained is proved to satisfy ergonomic criteria, and the performance of the human machine interface has been improved. This paper can provide references for the layout design of the high performance human machine interface in wheelhouse.

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Load-Reducing Characteristics of Gas Screen During Underwater Launch of the Vehicle
SHI Yao, LU Jiewen, DU Xiaoxu, GAO Shan, REN Jinyi
2024, 58 (2):  211-219.  doi: 10.16183/j.cnki.jsjtu.2022.323
Abstract ( 973 )   HTML ( 2 )   PDF (6389KB) ( 84 )  

During the underwater launching process, a gas screen channel is formed near the opening of the cylinder, which can effectively reduce the high-frequency pulsation load on the surface of the vehicle exiting the cylinder. Based on the volume of fluid (VOF) homogeneous multiphase flow theory, the standard RNG k-ε turbulence model, and the overlaid grid technology, this paper studies the influence law of the gas screen on the surface of the vehicle to improve the pulsating load of the vehicle, and analyses the flow field structure and hydrodynamic evolution under the gas screen environment. The characteristics of the gas curtain flow field structure evolution and the discharge load reduction effect at different cross-flow intensities and gas mass flow rates were compared. The results show that the high-speed gas ejected from the nozzles approximately covers the surface of the vehicle during the exiting process, and gradually forms a gas channel around the opening of the launch vessel, thereby reducing the surface load of the vehicle significantly. Under the condition of gas screen, both the moment and the surface load on the body have been significantly reduced, with the peak value of the moment reduced by 80.3%, and the peak pressure on the surface of the vehicle reduced by 81.2%. However, the peak pressure on the surface of the vehicle increases by a maximum of 56.7% upon increasing cross-flow intensity. Finally, the mass flow rate increases from 2 kg/s to 16 kg/s, with the moment on the vehicle reduced by 80.8% and the peak surface pressure reduced by 82.8%.

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Refined Simulation of Near-Surface Wind Field of Atmospheric Boundary Layer Based on WRF-LES Model
LIU Dalin, TAO Tao, CAO Yong, ZHOU Dai, HAN Zhaolong
2024, 58 (2):  220-231.  doi: 10.16183/j.cnki.jsjtu.2022.415
Abstract ( 1465 )   HTML ( 5 )   PDF (9950KB) ( 290 )  

Extreme meteorological disasters such as typhoons pose a serious threat to the safety of engineering structures. Therefore, the refined simulation on the near-surface atmospheric boundary layer (ABL) is valuable for civil engineering. Large-eddy simulation (LES) implemented in the weather research and forecating (WRF) model has the advantages of multiple options of numerical schemes and high accuracy. It is generally suitable for the refined simulation of the near-surface wind field, although the performance of simulation results is closely related to the numerical methods. This paper assesses the impacts of vital parameters regarding subfilter-scale (SFS) stress models, mesh size, and spatial difference schemes within WRF-LES to simulate the ideal ABL in order to figure out appropriate numerical schemes for the refined simulation of the near-surface wind field. The wind field characteristics are addressed and analyzed such as mean wind speed profile, turbulence intensity profile, and power of spectrum. Comparisons of simulation results among different SFS stress models indicate that the nonlinear backscatter and anisotropy one (NBA1) SFS stress model can effectively improve the accuracy of simulation in the near-surface wind profiles. Investigations of mesh resolution effects indicate that the nonuniformly refined vertical grid near the surface agrees much better with the expected profiles and reduces the expenditure of computational resources. Furthermore, the results show that the even-order spatial difference schemes produce more small-scale turbulent structures than the odd-order difference schemes. The numerical methods of WRF-LES proposed can provide a technical reference for refined simulation of the near-surface wind field and typhoon boundary layer.

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In-Situ X-Ray CT Characterization of Damage Mechanism of Plain Weave SiCf/SiC Composites Under Compression
CHENG Xiangwei, ZHANG Daxu, DU Yonglong, GUO Hongbao, HONG Zhiliang
2024, 58 (2):  232-241.  doi: 10.16183/j.cnki.jsjtu.2022.322
Abstract ( 1004 )   HTML ( 3 )   PDF (27080KB) ( 117 )  

In order to reveal the damage evolution and failure mechanism of ceramic matrix composites (CMCs), in-situ X-ray CT compression tests of plain weave SiCf/SiC composites were conducted, and the CT data during loading and after failure were obtained. Displacement and strain distributions of the material were evaluated by the digital volume correlation (DVC) technology. The three-dimensional visual model of the composite was created by using image processing software. The spatial distributions of tow split and other damages were segmented by the deep learning algorithm. The qualitative and quantitative analysis of compression damage evolution were performed. The results show that there is a relatively large expansion induced by barreling in the thickness direction and a little shrinkage in the width direction during the unidirectional compression, while the barreling in the thickness direction is the main reason to trigger compressive damages of the material. Damages such as matrix falling-off at surface, tow split, delamination, will occur as the compression was approaching the ultimate load. Fiber kinking results in the final compressive failure of the material, while an obvious V-shaped shear band is observed in the fracture. The analysis of compressive damage evolution of plain weave SiCf/SiC shows that the DVC technology and deep learning-based image segmentation methods could effectively reveal the compressive damage evolution mechanism of ceramic matrix composites.

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Prediction of Slip and Torsion Performance of Right-Angle Fasteners Based on Machine Learning Methods
BAO Zhujie, LI Zhen, WANG Feiliang, PANG Bo, YANG Jian
2024, 58 (2):  242-252.  doi: 10.16183/j.cnki.jsjtu.2022.399
Abstract ( 1028 )   HTML ( 4 )   PDF (11483KB) ( 84 )  

Aiming at the issue of large CPU costs and low calculation accuracy in the design of right-angle fasteners in scaffolding structures, prediction models of fastener anti-slip performance and torsion performance based on machine learning are proposed. A three-dimensional solid model of right-angle fasteners is established using the finite element method, the effectiveness of the numerical simulation method is verified through test results, and the comprehensive influence of various design parameters on the performance of fasteners is revealed by the parametric analysis method. The database is established by combining the test and numerical simulation results, and the fastener stiffness prediction models are proposed based on random forest (RF), support vector machine (SVM) and K-most proximity algorithm (K-NN), respectively. The expressions for the measured point displacement of the anti-slip model and the stiffness prediction of the torsion model are proposed in combination with genetic expression programming. The results indicate that SVM and GEP can predict the displacement and torsional stiffness of right-angle fasteners more accurately, which is important for guiding the safety design of fasteners in engineering scaffolding structures.

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