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Title: Uncertainty quantification in assessment of damage ship survivability
Author: Chen, Qi
ISNI:       0000 0004 2743 962X
Awarding Body: University of Strathclyde
Current Institution: University of Strathclyde
Date of Award: 2012
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Ongoing developments in improving ship safety indicate the gradual transition from a compliance-based culture to a sustainable safety-oriented culture. Sophisticated methods, tools and techniques are demanded to address the dynamic behaviour of a ship in a physical environment. This is particularly true for investigating the flooding phenomenon of a damaged ship, a principal hazard endangering modern ships. In this respect, first-principles tools represent a rational and cost-effective approach to address it at both design and operational stages. Acknowledging the criticality of ship survivability and the various maturity levels of state-of-the-art tools, analyses of the underlying uncertainties in relation to relevant predictions become an inevitable component to be addressed. The research presented in this thesis proposes a formalised Bayesian approach for quantifying uncertainties associated with the assessment of ship survivability. It elaborates a formalised procedu re for synthesizing first-principles tools with existing knowledge from various sources. The outcome is a mathematical model for predicting time-domain survivability and quantifying the associated uncertainties. In view of emerging ship life-cycle safety management issues and the recent initiative of "Safe Return to Port", emergency management is recognised as the last remedy to address an evolving flooding crisis. For this reason, an emergency decision support framework is proposed to demonstrate the applicability of the presented Bayesian approach. A case study is enclosed to elucidate the devised shipboard decision support framework for flooding-related emergency control. Various aspects of the presented methodology demonstrate considerable potential for further research, development and application. In an environment where more emphasis is placed on performance and probabilistic-based solutions, it is believed that this research has contributed positiv ely and substantially towards ship safety, with particular reference to uncertainty analysis and ensuing applications.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available