A Fast Algorithm for Onboard Progressive Flooding Simulation

Abstract

The need for decision support after a flooding casualty requires the development of fast and accurate progressive flooding simulation procedures. Here, a new quasi-static technique is presented, proposing a differential algebraic formulation capable to consider independently the flooding process in the internal rooms. The proposed method is efficient while simulating long flooding chains along rooms connected by similar size openings, a condition that likely occurs on large passenger ships. Moreover, the computational performances of the simulation procedure have been enhanced by adapting the time step to the progressive flooding pace. The adoption of an adaptive time step algorithm reduces significantly the calculation time. The novel procedure has been tested on the recommended benchmark cases for flooding simulations, highlighting the accuracy and flexibility of the proposed method.

Effect of Database Generation on Damage Consequences’ Assessment Based on Random Forests

“…In a previous study [17], it was observed that the longitudinal position of the damage center has only a limited impact on progressive flooding, whereas its vertical position has a relevant effect. Hence, all the single-room damages were applied at half of the room longitudinal extension assuming an L d equal to the room longitudinal extension.…”

“…In the present section, several options are proposed to generate the training database according to a different characterization of the damages. All the progressive flooding simulations were carried out using a quasi-static technique based on the solution of a linearized differential-algebraic equation system [18,19]. The method represents a good compromise between accuracy and computational effort [20]; hence, it was considered adequate for the generation of large databases of progressive flooding simulations.…”

“…These features make RFs more resilient to noise/missing data and more capable of dealing with higher-dimensional data compared to standard decision trees and other ensemble methods. Hence, the choice of such an ML technique was initially considered for the studied problems, involving a large number of predictors for higher t * and progressive flooding being affected by several uncertainties [16,17].…”

Prediction of Flooded Compartment Damage Locations in Ships by Using Spectrum Analysis of Ship Motions in Waves

“…Here, F is the number of columns of the spectrum matrix, which can be calculated using Equation (13). s H n.m.i refers to the entry of the i-th row in the m-th p-vector among the spectrum matrix of the n-th case of heave motion in the ship motion database.…”

“…The development of time-domain progressive flooding simulation tools is underway, which is operated on board as a way to help decision makers make decisions after detecting flooding locations [6][7][8][9][10][11][12][13]. These simulation tools implement virtually progressive flooding scenarios in a complex onboard structure.…”