A Simulation Tool to Quantify the Consequences of Fires on Board Ro-Ro ShipsShow others and affiliations
2024 (English)In: Fire technology, ISSN 0015-2684, E-ISSN 1572-8099, Vol. 60, no 1, p. 459-499Article in journal (Refereed) Published
Abstract [en]
Every year, fires aboard roll-on roll-off (ro-ro) ships result in costly damage to ships and their cargo and, fortunately less frequently, in tragic loss of life. On the other hand, statistical studies have shown that a large proportion of major fire accidents originated in the vehicle decks. To improve the issue of vehicle-deck fires on board ro-ro ships, a performance-based simulation tool was developed to quantify the consequences of these fires on people, ship, and cargo. This tool combines a deterministic computational fluid dynamics model to assess the fire consequences in the vehicle decks and open areas of the ship; a stochastic network model in the accommodation spaces; and a deterministic evacuation model to evaluate the consequences of fire to people on board. This article briefly presents the numerical tools used and their extension to ro-ro ships, then the results obtained for selected fire scenarios on two generic ro-ro ships, varying the location of the fire source, wind conditions, and including one accidental situation due to a loss of integrity of the insulation at the ceiling of the deck from which the fire originated and one scenario where some openings of this deck were closed. People evacuation was simulated for the accidental scenario. Fire consequences are further evaluated in terms of human survivability, in compliance with the life safety performance criteria of the International Maritime Organization, damage to the ship and cargo. A qualitative comparison with reported accident data is presented to assess the consistency of model results.
Place, publisher, year, edition, pages
2024. Vol. 60, no 1, p. 459-499
Keywords [en]
Performance-based approach, CFD model, Network model, Evacuation model, Fire scenario
National Category
Other Engineering and Technologies
Identifiers
URN: urn:nbn:se:ri:diva-68745DOI: 10.1007/s10694-023-01515-3OAI: oai:DiVA.org:ri-68745DiVA, id: diva2:1824093
Projects
LASH FIRE (Horizon 2020, grant agreement ID # 814975)
Note
This work was supported by the European Union’s Horizon 2020 research and innovation program (Grant Agreement No. 814975).
2024-01-042024-01-042024-06-11Bibliographically approved