摘要
为研究感潮港口船舶在不同潮时进港靠泊的引航过程风险演化规律,以优化泊位利用率和提高港口的生产效率,有必要进行多时段船舶引航过程风险的动态仿真。在对船舶引航任务场景和历史数据进行分析的基础上,采取HHM方法构建船舶引航过程的关键风险指标体系,采用AHP-CRITIC方法结合风险因素的主客观分布特点获取不同引航阶段中各指标权重,最后利用不确定人工智能云模型进行多时段船舶引航过程风险的建模仿真。通过某集装箱船的感潮水域引航过程场景分析,融合采样点的客观数据和专家知识对6个靠泊窗口期船舶引航过程风险进行动态仿真。结果表明:船舶引航过程风险演化整体呈U形曲线模式,相比正常航行阶段风险值,船舶引航初始和靠泊阶段风险值高60%左右;感潮港口6个窗口期的船舶引航过程风险略有差异,潮高、潮流对船舶交通流和起锚、靠泊作业安全影响明显。
To study the risk evolution law of the piloting process of ships entering the harbor and berthing at different times of tide in tidal ports,and to improve the production efficiency and optimize berth utilization rate,it is necessary to carry out a dynamic risk simulation of the whole process of multi-period piloted ship entering the harbor and berthing. Based on the analysis of the ship ’s piloting scenarios and historical data,the Hierarchical Holographic Modeling( HHM) method is used to obtain the main risk index system at different stages of the piloting process. Considering the characteristics of subjective and objective indicators,Analytic Hierarchy Process(AHP) and Criteria Importance Through Intercriteria Correlation(CRITIC) methods are used to obtain the weight of each indicator. Then,the uncertain artificial intelligence cloud model is used to model and simulate the multiperiod ship piloting process risk. Combined with the piloting scenario analysis of a container ship in tidal waters,the objective data of sampling points and expert knowledge are used to simulate the risk of the piloting process of the ship in the six tidal windows period. The results show that the overall risk evolution of the ship’s piloting process is in a U-shaped curve mode. Compared with the risk value in the normal navigation stage,the risk values in the initial pilotage and berthing stage are about 60% higher. The risk of the piloting process in six window periods of the tidal harbor is slightly different. The height and current of tide have an obvious influence on the ship traffic flow and the safety of anchoring and berthing operations. The dynamic simulation method based on the cloud model can be used to obtain the risk distribution of the ship piloting process of the tidal ports berthing at different tides,and analyze the key risk causes at different pilotage periods. The research results can provide a reference for optimizing port operation management and improving maritime management systems.
作者
郭云龙
张涛
胡甚平
赵观洋
吴建军
GUO Yun-long;ZHANG Tao;HU Shen-ping;ZHAO Guan-yang;WU Jian-jun(Merchant Marine College,Shanghai Maritime University,Shanghai 201306,China;School of Nautical Technology,Jiangsu Shipping College,Nantong 226010,Jiangsu,China)
出处
《安全与环境学报》
CAS
CSCD
北大核心
2021年第1期49-55,共7页
Journal of Safety and Environment
基金
国家自然科学基金项目(51909156)
江苏省高等学校自然科学研究面上项目(19KJB580017)
上海市2020年度“科技创新行动计划”软科学重点项目(20692108700)。
关键词
安全工程
感潮水域
船舶引航
过程风险
风险评估
动态仿真
safety engineering
tidal waters
ship pilotage
process risk
risk assessment
dynamic simulation
