ABSTRACT

The intrinsic complexity of the flooding process on ships renders accurate quantification of the flooding risk a highly arduous task, particularly in the context of emergency management. This is especially true for large cruise vessels where convolution stems from innovative designs and complex internal subdivision resulting in a multitude of variables and their interdependencies. This augments the uncertainty and imposes challenges on the crew in obtaining a complete overview and in making fully informed decisions. This paper presents a methodology whereby sensors and analytics are combined utilising probabilistic multi-sensor data fusion to predict the flooding extent with reduced uncertainty to facilitate informed decision-making in emergencies, forming the basis for optimised implementation of emergency response measures for vessel survival and subsequent safe return to port. The accurate prediction of flooding extent as presented, is a fundamental prerequisite for, and could be of great assistance in, decision making in emergencies, thus saving lives.

摘要

船上洪水过程的内在复杂性使得准确量化洪水风险成为一项艰巨的任务，尤其是在应急管理的情况下。对于大型游轮而言尤其如此，因为卷积源自创新设计和复杂的内部细分，从而导致多种变量及其相互依存关系。这增加了不确定性，并给船员带来了挑战，他们需要获得完整的概览并做出充分知情的决定。本文提出了一种方法，该方法可利用概率多传感器数据融合来结合传感器和分析方法，以减少不确定性的方式预测洪水泛滥的程度，从而有助于在紧急情况下做出明智的决策，为优化实施应急措施以维持船舶生存和随后的安全返回港口奠定基础。所提出的对洪水泛滥程度的准确预测，是紧急情况下决策的基本前提，并且可以提供极大帮助，从而挽救生命。