Thesis (M. Journ.)--University of Hong Kong, 2001. / Includes bibliographical references (leaves i-vii).

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The purpose of this study was to complete a series of photographs utilizing trees as metaphors. This series of photographs is composed into book form for possible publication. It presents the psychological and symbolic impact of trees in different environments and from different perspectives through the development of a unique style of creative composition. The format consists of text and photographs. This project develops a working definition of metaphors and an approach using trees as the medium to convey various symbolic and psychological references. Both associated and inferred types of symbolisms are used. This type of approach is not necessarily unique and has been evidenced in the work of such "populist" poets as Robert Frost and the late photographer-poet Gordon Parks. With the basic inventory of symbols and psychological reference associations, whole trees, parts of trees, and/or groups of trees are identified to illustrate through the photographic medium that metaphors do indeed exist and can be found in trees. Photographs are produced, edited and composed to produce not only pleasing aesthetics, but also to provide continuity throughout the series. Photographs vary in size, shape, contrast, and composition to provide variation in the format.

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The aim of this thesis is to extend the current techniques available for the analysis of non-coherent fault trees. At present importance analysis of non-coherent systems is extremely limited. The majority of measures of importance that have been developed can only be used to analyse coherent fault trees. If these measures are used to analyse non-coherent fault trees the results obtained are inaccurate and misleading. Extensions for seven of the most commonly used measures of importance have been proposed to enable accurate analysis of non-coherent systems. The Binary Decision Diagram technique has been shown to provide an accurate and efficient means of analysing coherent fault trees. The application of this technique for the qualitative analysis of non-coherent fault trees has demonstrated the gains to be made in terms of efficiency and accuracy. Procedures for quantifying a non-coherent fault tree using this technique have been developed; these techniques enable significantly more efficient and accurate analysis than the conventional techniques for Fault Tree Analysis. Although the Binary Decision Diagram technique provides an efficient and accurate means of analysing coherent and non-coherent fault trees, large trees with many repeated events cannot always be analysed exactly. In such circumstances partial analysis must be performed if any conclusions regarding system safety and reliability are to be drawn. Culling techniques employed in conjuncfion with the Binary Decision Diagram method have been developed for the partial analysis of both coherent and non-coherent fault trees.

The development of computer based tools, to assist process plant operators in their task of fault/alarm diagnosis, has received much attention over the last twenty five years. More recently, with the emergence of Artificial Intelligence (AI) technology, the research activity in this subject area has heightened. As a result, there are a great variety of fault diagnosis methodologies, using many different approaches to represent the fault propagation behaviour of process plant. These range in complexity from steady state quantitative models to more abstract definitions of the relationships between process alarms. Unfortunately, very few of the techniques have been tried and tested on process plant and even fewer have been judged to be commercial successes. One of the outstanding problems still remains the time and effort required to understand and model the fault propagation behaviour of each considered process. This thesis describes the development of an experimental knowledge based system (KBS) to diagnose process plant faults, as indicated by process variable alarms. In an attempt to minimise the modelling effort, the KBS has been designed to infer diagnoses using a fault tree representation of the process behaviour, generated using an existing fault tree synthesis package (FAULTFINDER). The process is described to FAULTFINDER as a configuration of unit models, derived from a standard model library or by tailoring existing models. The resultant alarm diagnosis methodology appears to work well for hard (non-rectifying) faults, but is likely to be less robust when attempting to diagnose intermittent faults and transient behaviour. The synthesised fault trees were found to contain the bulk of the information required for the diagnostic task, however, this needed to be augmented with extra information in certain circumstances.

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Typescript. / Thesis (Ph. D.)--University of Hawaii, 1965. / Bibliography: leaves [106]-110. / ix, 110 l mounted illus., tables