A System-Theory and Complex Network-Fused Approach to Analyze Vessel–Wind Turbine Allisions in Offshore Wind Farm Waters

Author:

Yan Kai1234,Wang Yanhui12,Wang Wenhao12,Qiao Chunfu34,Chen Bing34,Jia Limin124

Affiliation:

1. State Key Laboratory of Advanced Rail Autonomous Operation, Beijing Jiaotong University, Beijing 100044, China

2. School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China

3. Transport Planning and Research Institute, Ministry of Transport, Beijing 100028, China

4. Laboratory of Transport Safety and Emergency Technology, Beijing 100028, China

Abstract

Given the national goal of “emission peaking and carbon neutralization”, China has become the largest country in the world for offshore wind farm construction. At the same time, navigational safety problems in offshore wind farm waters have become increasingly frequent. Owing to the complexity of offshore wind farm waters and the small number of accident data samples available for reference, the system theory method is more suitable for selection than the traditional method. Based on causal analysis based on system theory (CAST) and a complex network (CN), in this study, a qualitative and quantitative accident analysis model, CAST-CN, is constructed to analyze a complete case of vessel and wind turbine allision in offshore wind farm waters. The results show that, at the micro level, in addition to the master, crew, shipping company, and typhoon Hato, the maritime safety administration and the wind farm operation management department have a certain impact on the development of the accident discussed in this study. At the macro level, internal and external factors leading to the lack of system safety are identified, and measures and suggestions for system safety improvement are proposed based on analysis. This study can fill the research gap in the systematic analysis of traffic accidents in offshore wind farm waters and provide support for the safety assessment and decision-making of government management departments and research institutes.

Funder

State Key Laboratory of Advanced Rail Autonomous Operation

Publisher

MDPI AG

Subject

Ocean Engineering,Water Science and Technology,Civil and Structural Engineering

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