Abstract

In the present paper, a hierarchical multi-scale method is developed for the nonlinear analysis of composite materials undergoing heterogeneity and damage. Starting from the homogenization theory, the energy equivalence bet... | Find, read and cite all the research you need on Tech Science Press

Highlights

  • There are many hazards on a ship that can cause an emergency evacuation, the most severe; flooding, fire or explosion cause thousands of injuries annually [EMSA (2018)]

  • This stochastic approach make sense since if an evacuation drill is repeated using the same conditions and population of the same characteristics, the evacuation will be performed differently obtaining a probabilistic distribution of total evacuation time (TET)

  • The International Maritime Organization (IMO) guidelines Maritime Safety Committee (MSC)/Cir. 1238 [IMO (2016)] have recently been updated, specifying that 500 simulations runs must be performed and their 95th percentile represents the predicted evacuation time value, as opposed to the older versions of the IMO which indicated that 50 simulations were sufficient

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Summary

Introduction

There are many hazards on a ship that can cause an emergency evacuation, the most severe; flooding, fire or explosion cause thousands of injuries annually [EMSA (2018)]. A ship is a elaborated vehicle which, in the case of passenger ships, gets more complex, since recent cruise liners reach up a capacity of several thousand people on board [Ginnis, Kostas, Politis et al (2010)]. The safety of large passenger ships is becoming an. Increasingly important issue because of the high number of naval accidents happened worldwide throughout history. While the number of marine accidents, victims involved and its negative impact on the environment, scarce literature exists on naval disasters and factors affecting the success of safety and evacuation procedures

Evacuation modeling background
Related works
Passenger ships
Naval ships
The evacuation process in a naval ship
Evacuation time confidence interval
Methodology
Experimental data sets of occupants in naval ships
Modeling LHD amphibious ship
Modeling crew and embarked troops: behaviors and speeds
Simulation modeling tool
Performing simulations and results
Queues
Findings
Conclusions
Full Text
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