A new ship safety management approach - learning from the past, managing future risks

Learning from the past has been recognised as an effective means to manage future challenges. This is particularly true for ship safety management in the maritime industry as the records of historical safety-related failures are generally accompanied by the losses of human lives, damage to the environment and the ships. However, the current 'learning' practice is not rationalised to facilitate effective safety management both from design and operational points of view. By proposing a unique approach of 'learning from the past', this paper elaborates on a formal methodology towards ship safety management so that future risk control decisions can be made in an objective, transparent, and well-informed manner

A data mining framework for risk-based ship design

This thesis was previously held under moratorium from 31st January 2012 until 31st Janury 2014.The Risk-Based Ship Design (RBD) methodology, advocating the systematic integration of risk assessment in the conventional design process so that ship safety is treated as an objective rather than a constraint, has swept through a wide spectrum of the maritime industry over the past fifteen years. Through this methodology, safety is situated at a central position alongside conventional design objectives, so that wellbalanced design effort could be spent and consequently comprehensive design optimisation can be performed. Despite the recognition and increasing popularity, important factors that could potentially undermine its implementation arise both from qualitative and quantitative aspects. This necessitates the development of an objective, reliable and efficient methodology for risk-based ship design implementation. The research presented in this thesis proposes a formalised methodological framework to fulfil this global objective. It comprises three interrelated stages to be performed during risk assessment, namely the development of next generation marine accident/incident database, risk modelling in Bayesian networks by deploying data mining techniques, and the integration with the framework for risk-based design decision making. Working procedures, techniques, methods and algorithms have been developed and applied to representative examples and case studies to demonstrate the applicability and the potential offered by this framework. Each stage of the framework is a field with vast potential for further research, development and application. The ensuing findings firm the faith that an optimal approach towards risk-based design is achievable and extensive applications need to be conducted before experience and confidence can be gained. It is believed that this research has contributed positively towards the evolvement of risk-based ship design.The Risk-Based Ship Design (RBD) methodology, advocating the systematic integration of risk assessment in the conventional design process so that ship safety is treated as an objective rather than a constraint, has swept through a wide spectrum of the maritime industry over the past fifteen years. Through this methodology, safety is situated at a central position alongside conventional design objectives, so that wellbalanced design effort could be spent and consequently comprehensive design optimisation can be performed. Despite the recognition and increasing popularity, important factors that could potentially undermine its implementation arise both from qualitative and quantitative aspects. This necessitates the development of an objective, reliable and efficient methodology for risk-based ship design implementation. The research presented in this thesis proposes a formalised methodological framework to fulfil this global objective. It comprises three interrelated stages to be performed during risk assessment, namely the development of next generation marine accident/incident database, risk modelling in Bayesian networks by deploying data mining techniques, and the integration with the framework for risk-based design decision making. Working procedures, techniques, methods and algorithms have been developed and applied to representative examples and case studies to demonstrate the applicability and the potential offered by this framework. Each stage of the framework is a field with vast potential for further research, development and application. The ensuing findings firm the faith that an optimal approach towards risk-based design is achievable and extensive applications need to be conducted before experience and confidence can be gained. It is believed that this research has contributed positively towards the evolvement of risk-based ship design

Development of bayesian models for marine accident investigation and their use in risk-based ship design

Historical marine accident/incident data remain severely underused in regulatory development as well as during design and operation. It is widely recognized that this is mainly the result of underreporting in commercially available databases and in databases maintained by national authorities. A factor further signifying this underuse is the evident improper reporting because most data are maintained as textual information requiring significant amounts of time and effort to distill and use the essential characteristics of accidents. Compounded with improved accessibility to an ever increasing amount of historical records, there is a need to develop the means that all the available information from marine accident/incidents is fully used in decision-making during development of new regulations, design, and operation. This article elaborates on the underlying causes for the current unsatisfactory state of affairs and details the description of the structures adopted for the development of appropriate marine accident databases using Bayesian Belief Networks as the platform for translating the information contained in the databases to probabilistic risk-based knowledge-intensive models. The article further explains the use of these models within a risk-based ship design framework, concluding with an example case study of application for fire safety onboard passenger ships

Development of Bayesian Network Models for Risk-Based Ship Design

In the past fifteen years, the attention of ship safety treatment as an objective rather than a constraint has started to sweep through the whole maritime industry. The risk-based ship design (RBD) methodology, advocating systematic integration of risk assessment within the conventional design process has started to takeoff. Despite this wide recognition and increasing popularity, important factors that could potentially undermine the quality of the results come from both quantitative and qualitative aspects during the risk assessment process. This paper details a promising solution by developing a formalized methodology for risk assessment through effective storing and processing of historical data combined with data generated through first-principle approaches. This method should help to generate appropriate risk models in the selected platform (Bayesian networks) which can be employed for decision making at design stage

Fabrication of Large-Area Suspended MEMS Structures Using GaN-on-Si Platform

In this letter, piezosensitive elements featuring large-size suspended gallium nitride (GaN) microstructures are fabricated with a two-step dry-release technique using the GaN-on-Si platform. The suspended microstructures are integrated with highly piezosensitive AlGaN/GaN heterostructures as sensing units to realize the GaN-based integrated microsensors. To characterize the residual-stress distribution of the fabricated microstructures, micro-Raman spectroscopy is employed. A microaccelerometer structure with a 250 x 250-mu m(2) proof-mass area is fabricated with the proposed fabrication technique, and the piezoresponse properties of the integrated sensing elements are characterized through bending experiment

Strong Sulfur Binding with Conducting Magnéli-Phase Ti_<i>n</i>O_{2<i>n</i>–1} Nanomaterials for Improving Lithium–Sulfur Batteries

Lithium–sulfur batteries show fascinating potential for advanced energy storage systems due to their high specific capacity, low-cost, and environmental benignity. However, the shuttle effect and the uncontrollable deposition of lithium sulfide species result in poor cycling performance and low Coulombic efficiency. Despite the recent success in trapping soluble polysulfides via porous matrix and chemical binding, the important mechanism of such controllable deposition of sulfur species has not been well understood. Herein, we discovered that conductive Magnéli phase Ti₄O₇ is highly effective matrix to bind with sulfur species. Compared with the TiO₂–S, the Ti₄O₇–S cathodes exhibit higher reversible capacity and improved cycling performance. It delivers high specific capacities at various C-rates (1342, 1044, and 623 mAh g^–1 at 0.02, 0.1, and 0.5 C, respectively) and remarkable capacity retention of 99% (100 cycles at 0.1 C). The superior properties of Ti₄O₇–S are attributed to the strong adsorption of sulfur species on the low-coordinated Ti sites of Ti₄O₇ as revealed by density functional theory calculations and confirmed through experimental characterizations. Our study demonstrates the importance of surface coordination environment for strongly influencing the S-species binding. These findings can be also applicable to numerous other metal oxide materials