Representation of distribution networks of ships using graph-theory

CETENA S.p.A., SISSA (International School for Advanced Studies) and Lloyd’s Register (Class Society) have recently been involved in a challenge aimed at developing smart algorithms capable to evaluate the effect of different failure modes — caused by a fire or a flooding—on the systems of passenger ships in order to improve the design of new passenger ships [1]. Considering that a failure may cause serious accidents both to the vessel and human lives, the goal of this project is to evaluate the best reconfiguration of current ship plants after each casualty scenario so as to guarantee the minimal functioning requirements. This implies a continuous cross check activity (design against installation) that follows the whole ship construction process. The urgency of this work is motivated by the necessity to meet the International Maritime Organizations (IMO) Safety Of Life At Sea (Solas) design prescriptions defined in the Safe Return to Port (SRtP) regulations [2]. According to these criteria, a vessel should be able to safely return to port under its own propulsion after an adverse event not exceeding any of the defined casualty thresholds and criteria imposed by the regulations. Thus, the identification of all the possible failure modes and their propagation through the on-board systems has become a task of paramount importance for the proper design of the ship’s systems against failure events. Currently, in accordance with IMO MSC.1/circ.1369 [3], CETENA produces the Operating Manuals that allow the crew to reconfigure the essential systems after a SRtP casualty so as to be able to bring the ship to a port with adequate comfort and safety standards. However, the ship can be operated in a different way from what is planned in the design stage. In these scenarios, the present static Operational Manuals can be a limitation. In order to be effective during emergency operation, Operational Manuals must be dynamic so as to provide interactive information and guidance to crew members about the reconfiguration of the ship and the recovery of her functions based on the systems configuration at the moment of the casualty. The focus of this work is the study of domino effects triggered by fire or flooding casualties in passenger ships in order to provide crew with a tool which speeds up and facilitates the decision-making process when choices have to be made to optimize the ship residual capability after a casualty. The framework of this study may be extended to other types of domino escalation.