Chenxu Wang

Dr. Chenxu Wang

School of Marine Science and Technology, Tianjin University, Tianjin, China
orcid

Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2021 in International Journal of Naval Architecture and Ocean Engineering
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Open access
JZJian Zhou
Jian Zhou
FDFeng Ding
Feng Ding
JYJiaxuan Yang
Jiaxuan Yang
ZPZhengqiang Pei
Zhengqiang Pei
Chenxu WangChenxu Wang
Chenxu Wang
AZAnmin Zhang
Anmin Zhang

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JZJian Zhou
Jian Zhou
Chenxu WangChenxu Wang
Chenxu Wang
AZAnmin Zhang
Anmin Zhang
Unmanned Surface Vehicles (USVs) are intelligent machines that have been widely studied in recent years. The safety of USVs’ activities is a priority issue in their applications; one effective method is to delimit an exclusive safety domain around the USV. Besides considering collision avoidance, the safety domain should satisfy the requirements of encounter situations in the COLREGs (International Regulations for Preventing Collisions at Sea) as well. Whereas the model providing the safety domain for the USVs is defined through the experience of the manned ships, a specific model for USVs has been rarely studied. A dynamic navigation safety domain (DNSD) for USVs was proposed in this paper. To construct the model, the essential factors that could affect the navigation safety of the USVs were extracted via a rough set, and the extension functions of these factors were carried out. The DNSD was employed in various situations and compared with the ship domain models of common ships. It was found that the domain boundary can be automatically corrected according to the change in the working conditions when the DNSD is in use. Compared with the Fujii and Coldwell models, the DNSD can provide a larger safety area for a USV’s action of collision avoidance.

7 August 2019 in Applied Sciences
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SLShuai Liu
Shuai Liu
Chenxu WangChenxu Wang
Chenxu Wang
AZAnmin Zhang
Anmin Zhang
The depth of water is of great significance to the safe navigation of unmanned surface vehicles (USV)in shallow waters, such as islands and reefs. How to consider the influence of depth on the safety of USV navigation and path planning is relatively rare. Under the condition of ocean disturbance, the hydrodynamic characteristics of unmanned surface vehicles will affect its draft and depth safety. In this paper, the hydrodynamic model of unmanned surface vehicles is analyzed, and a water depth risk level A* algorithm (WDRLA*) is proposed. According to the depth point of the electronic navigation chart (ENC), the gridding depth can be obtained by spline function interpolation. The WDRLA* algorithm is applied to plan the path, which takes hydrodynamic characteristics and navigation errors into account. It is compared with the traditional A* shortest path and safest path. The simulation results show that the WDRLA* algorithm can reduce the depth hazard of the shortest path and ensure the safety of navigation.

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HZhao zhang
hao zhang
AZAnmin Zhang
Anmin Zhang
Chenxu WangChenxu Wang
Chenxu Wang
liuyang zhangliuyang zhang
liuyang zhang
SLShuai Liu
Shuai Liu
Due to the absence of a comprehensive knowledge system for modeling ocean circulation, there is ambiguity and diversity in the semantic expression of ocean circulation. This makes it difficult to organize and share relevant spatiotemporal data effectively. This paper addresses the issue of ocean circulation by introducing ontological theory and methodology based on a comprehensive analysis of domain knowledge. Through a comprehensive analysis of the conceptual and relational characteristics of different elements, we define classes, properties, spatiotemporal relationships, and inference conditions with which to formally express concepts and relationships in ocean circulation, and finally complete the construction of ocean circulation ontology. The formal expression of the Equatorial Counter Current is presented as an example with which to validate the effectiveness of ontological construction. Additionally, an ontology-based knowledge base of ocean circulation is proposed. The construction framework is described, and several examples of knowledge base queries are also illustrated. The results demonstrate that this ontology can effectively represent the relevant knowledge within ocean circulation and provide a meaningful reference for investigating knowledge sharing and semantic integration within this field.

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HLHui Li
Hui Li
NZNan Zhao
Nan Zhao
JZJian Zhou
Jian Zhou
XCXiangyu Chen
Xiangyu Chen
Chenxu WangChenxu Wang
Chenxu Wang
Maneuver simulation of a standard ship model gives indication of numerical accuracy. In the numerical calculation of ship maneuvering, uncertainty analysis is a necessary step to ensure the accuracy of the calculation. In this study, uncertainty pair analysis is carried out in the simulation of the turning circle motion of the standard ship model ONRT in waves. According to the uncertainty analysis procedure recommended by the International Towing Tank Conference (ITTC), the change of ship resistance caused by the number of grids is studied to determine the influence of grid density on the numerical prediction. The simulation of turning motion in waves is carried out based on the uncertainty analysis. It is found that the minimum number of overset grids for this simulation is 1.4 million. The numerical results are fairly accurate compared to experimental results, and this technique provides a method with low calculated cost for this simulation.

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YLYunmiao Li
Yunmiao Li
JZJian Zhou
Jian Zhou
HWHeping Wang
Heping Wang
Chenxu WangChenxu Wang
Chenxu Wang
Field observations revealed that a mooring buoy rapidly drifts in a reciprocating motion along an arcuate path between two extreme positions. When the anchor point is considered the origin and viewed from an aerial perspective, this movement resembles a pendulum. The implications of this motion for data acquisition efficiency prompted our inquiry into this phenomenon. The comparative analysis of the model’s different movements under wave-only, current-only, and wave–current conditions demonstrates that currents are the source inducing this pendulum-like motion. To investigate the mechanism of this current-driven motion, the flow field around the buoy was visualized through numerical simulations. Specifically, the CFD results aligned with the field data and confirmed that periodic vortex shedding induces oscillatory forces, which dominate the rapid reciprocating movement. The findings emphasize the significant impact of fluid viscosity and the resulting vortex effects on the motion characteristics of buoys. They can provide a foundation for addressing more applied problems of data error-correcting and trajectory predictions.