Polymer decomposition is the key to understanding fire behaviour. It is a complex process involving heat transfer, breakdown of the polymer chain, volatile fuel formation and gasification occurring as a moving interface through the polymer bulk. Two techniques, chemical analysis using STA-FTIR, and pyrolysis modelling have been combined as a tool to better understand these processes. This work covers the experimental investigation of polymer decomposition using the STA-FTIR technique. Several polymers including polyacrylonitrile (PAN), polypropylene (PP) and ethylene-vinyl acetate (EVA) alone, and as potential fire retardant composites have been studied in different conditions to optimise the methodology and analysis of results. Polyacrylonitrile was used to optimise the experimental technique. Polypropylene, containing nanoclay and ammonium phosphate, was decomposed and the composition of the decomposition products analysed in order to investigate the fire retardant effects of the additives on the thermal decomposition. Ethylene-vinyl acetate copolymer containing nanoclay and/or either aluminium hydroxide or magnesium hydroxide was decomposed, with vapour phase FTIR analysis showing a change in the initial decomposition pathway with a shift from acetic acid evolution, to acetone production. In parallel, this experimental data has been used to perform early attempts towards validation of numerical models developed by the use of a 1-dimensional pyrolysis computational tool called ThermaKin. As ThermaKin is relatively new and still not widely used for fire modelling, a detailed description of its capabilities has been provided. A detailed study of heat transfer of cardboard, leading to thermal decomposition, accompanied by pyrolysis and char formation has been described. Several microscale kinetics models have been proposed with different levels of complexity. Not only do the numerical approximations reflect the experimental results of single compounds, describing the material’s behaviour (expressed in terms of mass loss) when exposed to external heat, but also predictive models of fire retardant mixtures have been developed for different atmospheres and heating rates. In addition, the powerful combination of pyrolysis modelling and chemical analysis by STA-FTIR has provided new insights into the decomposition and burning behaviour of both PP protected with nanoclay and ammonium phosphate, but also the industrially important cable sheathing materials based on EVA. The novelty of this work stems from the first use of the pyrolysis models to study fire retardant behaviour; the first reported combination of STA-FTIR with ThermaKin pyrolysis model, and a deep understanding of the pre-ignition behaviour of cardboard.

Nowadays, New Product Development (NPD) has become a business priority in manufacturing companies due to international competition in terms of meeting higher and changing customer requirements, generating high profit at low cost, and maintaining sustainable development and growth. Through literature review and industrial investigations, it has been recognised that NPD is an information and knowledge intensive process. However, in current practice, enterprise knowledge is not properly managed or easily accessible. Many service providers have not followed the good practice of considering business objectives and end users’ requirements as main drivers of knowledge management system development and implementation. This doctoral thesis presents a methodology for the design and development of Knowledge Management (KM) systems to support NPD based on Enterprise Architecture Frameworks (EAFs). The project focuses on IT system specifications generation driven by business and knowledge users’ requirements in the automotive industry. Current EAFs have been developed by researchers and practitioners to help enterprises to design their information systems based on business objectives and user requirements. However, these frameworks are mainly proposed to manage information and data such as finances, resources, management and engineering documents, not for the increasingly important enterprise knowledge, especially tacit and unstructured knowledge. This project aims to extend the capabilities of the latest enterprise architecture frameworks so that not only data and information, but also enterprise knowledge can be managed. A guideline in the form of a flowchart has been developed, which provides a process that can be followed and used by system developers and implementation. The extended EAF has been implemented as easy-to-use folders for the development of a structured knowledge base. A case study in an automotive company proved that the methodology can be used to produce the functional specifications of their IT systems to include knowledge management capability. The system specification can then be used, either to assess a company’s existing information systems and direct its future system development and implementation; or to develop/implement a complete new information system from scratch.

Sonca is a manufacturing operation producing torches and lanterns. In order for the Company to be competitive, one of the key factors is to introduce new products to market quicker and at a lower total product cost. A system titled "concurrent integrated design and assembly planning (CIDAP)" is developed to aid this process. It is identified that methods proposed by other researchers using different algorithms are not interactive enough and need too much space to store the representation of assembly sequences and time to process the assembly operations for a complex assembly. Besides, the commercially available systems and software are not integrated and are too universal. The data used is not compatible with the company's data file. The CIDAP framework focuses on concurrent and integration, in that the different processes in the whole product development cycle are carried out concurrently and are integrated. In the framework two techniques, namely KALG (Knowledge-based Assembly Liaison Graph) and KPN (Knowledge-based Petri Net) and four expert systems for selection of assembly system, feeder, gripper, and sensing technology are developed. Commercially available software such as Boothroyd and Dewhurst's DFMA (Design For Manufacture and Assembly) software, Rapid Prototyping and Quick Tooling are also applied in the framework. The frame work and the systems are applied to an actual case in designing a series of torches within the Company. Results show that the product development cycle time is improved by 25%, rework cost reduced by 20%, and final product cost reduced by 11 %. The Company has adopted the new framework. The developed systems and data files are not only applicable to the Company, but also to other small and medium size companies in Hong Kong and China with a similar scale and nature of operation.

The thesis develops themes around eight published works and as such the thesis encompasses a coherent caucus of work within the petrochemicals industry in the UK. The thesis provides evidence which confirms the widespread use of a strategy of flexibility but challenges the conception of strategy as a deliberate formal plan, and the rational economism of Transaction Cost Economics. It also casts doubt on the existence of distinct strategic levels. The multinationals in the industry have been exposed as not using a sophisticated rationale to underpin their strategy, relying instead on institutional ideologies or mimetic isomorphism. The thesis also challenges exiting conceptions of the role of Human Resources in the pursuit of strategy by showing the importance of the generic HR function in line management as opposed to an HR department.

This thesis addresses the needs of people who find reminiscence helpful in focusing on the development of a computerised reminiscence support system, which facilitates the access to and retrieval of stored memories used as the basis for positive interactions between elderly and young, and also between people with cognitive impairment and members of their family or caregivers. To model users’ background knowledge, this research defines a light weight useroriented ontology and its building principles. The ontology is flexible, and has simplified knowledge structure populated with semantically homogeneous ontology concepts. The user-oriented ontology is different from generic ontology models, as it does not rely on knowledge experts. Its structure enables users to browse, edit and create new entries on their own. To solve the semantic gap problem in personal information retrieval, this thesis proposes a semantic ontology-based feature matching method. It involves natural language processing and semantic feature extraction/selection using the user-oriented ontology. It comprises four stages: (i) user-oriented ontology building, (ii) semantic feature extraction for building vectors representing information objects, (iii) semantic feature selection using the user-oriented ontology, and (iv) measuring the similarity between the information objects. To facilitate personal information management and dynamic generation of content, the system uses ontologies and advanced algorithms for semantic feature matching. An algorithm named Onto-SVD is also proposed, which uses the user-oriented ontology to automatically detect the semantic relations within the stored memories. It combines semantic feature selection with matrix factorisation and k-means clustering to achieve topic identification based on semantic relations. The thesis further proposes an ontology-based personalised retrieval mechanism for the system. It aims to assist people to recall, browse and re-discover events from their lives by considering their profiles and background knowledge, and providing them v with customised retrieval results. Furthermore, a user profile space model is defined, and its construction method is also described. The model combines multiple useroriented ontologies and has a self-organised structure based on relevance feedback. The identification of person’s search intentions in this mechanism is on the conceptual level and involves the person’s background knowledge. Based on the identified search intentions, knowledge spanning trees are automatically generated from the ontologies or user profile spaces. The knowledge spanning trees are used to expand and reform queries, which enhance the queries’ semantic representations by applying domain knowledge. The crowdsourcing-based system evaluation measures users’ satisfaction on the generated content of Sem-LSB. It compares the advantage and disadvantage of three types of content presentations (i.e. unstructured, LSB-based and semantic/knowledgebased). Based on users’ feedback, the semantic/knowledge-based presentation is considered to have higher overall satisfaction and stronger reminiscing support effects than the others.

The computer graphics industry is constantly demanding more realistic images and animations. However, producing such high quality scenes can take a long time, even days, if rendering on a single PC. One of the approaches that can be used to speed up rendering times is Visual Perception, which exploits the limitations of the Human Visual System, since the viewers of the results will be humans. Although there is an increasing body of research into how haptics and sound may affect a viewer's perception in a virtual environment, the in uence of smell has been largely ignored. The aim of this thesis is to address this gap and make smell an integral part of multi-modal virtual environments. In this work, we have performed four major experiments, with a total of 840 participants. In the experiments we used still images and animations, related and unrelated smells and finally, a multi-modal environment was considered with smell, sound and temperature. Beside this, we also investigated how long it takes for an average person to adapt to smell and what affect there may be when performing a task in the presence of a smell. The results of this thesis clearly show that a smell present in the environment firstly affects the perception of object quality within a rendered image, and secondly, enables parts of the scene or the whole animation to be selectively rendered in high quality while the rest can be rendered in a lower quality without the viewer noticing the drop in quality. Such selective rendering in the presence of smell results in significant computational performance gains without any loss in the quality of the image or animations perceived by a viewer.

In this dissertation we study the routing problem for multi-commodity survivable network ows, with splittable demands, and propose end-to-end path-based solutions where maximum link utilization is minimized, in order to improve resilience in existing telecommunication networks. We develop mixed integer programming models, and demonstrate that, when the selection of disjoint paths is part of the optimization problem (rather than when k-shortest paths are pre-selected, as in earlier works), maximum link utilization is reduced and the overall network also balances out. We find that three paths are usually enough to reap the benefits of a multipath approach. A reduction in maximum link utilization also provides a margin by which demand values can grow without causing congestion. We also prove that the disjoint multipath selection problem is NPcomplete, even for the case of one node-pair. This warrants a recourse to effi- cient solution methods within ILP (such as decomposition), and to matheuristics. Our literature survey of applications of heuristic techniques, and those combining heuristics with exact methods, shows a research gap, which we attempt to bridge through a novel heuristic algorithm. The heuristic works well and, in several cases, yields better solutions than ILP (in a given time limit), or provides solutions for problems where ILP could not even find one valid solution in the given time limit. We also study this problem within a decomposition methods framework: i.e., column generation. The pricing sub-problem is a mixed non-linear programme, for which we propose an ILP formulation. We find some lower bounds for missing dual values and use them as surrogates. We then show that the lower bounds are valid and present examples where the proposed pricing is applied to path generation for self-protecting multipath routing.

This thesis is concerned with the detection of surface-breaking defects, such as stress corrosion cracking, using an ultrasonic scanning approach in which a laser source and detector are scanned over the near-field of a defect. Large increases in the amplitude and frequency content of an incident ultrasonic wave are present when either the source or the detector is very close to the defect, leading to a phenomenon known as ultrasonic near-field enhancement. The extent of the ultrasonic enhancement varies with defect characteristics such as defect depth and angle to the surface. Ultrasonic enhancement is observed in both experiment and finite element simulations using Rayleigh waves for both scanning laser detection and scanning laser source methods. The near-field enhancement is shown to vary as a function of the angle of the defect to the horizontal for Rayleigh wave enhancements, allowing the positioning and characterisation of artificial angled defects that are similar to rolling contact fatigue defects in railtrack. The mechanisms behind the near-field enhancement of Rayleigh waves at angled defects are identified, and this aids in the understanding of the behaviour of ultrasound as it interacts with surface-breaking defects. Ultrasonic enhancements are also reported to be present in individual Lamb wave modes for interactions with artificial open-mouthed defects in thin plates, which are similar to the open end of stress corrosion defects. The mechanisms behind both the scanning laser detection and scanning laser source enhancements are identified and used to explain the variation in the enhancement as a function of increasing defect severity. Positioning of these defects is also achieved by identification of the enhancement location. Finally, the scanning laser technique is applied to real stress-driven defects, and both scanning approaches are shown to be capable of detecting partially-closed defects in a variety of sample geometries. The position, geometric alignment and an estimate of the defect depth are obtained for real defects in thin plates, pipework sections and in irregularly shaped engine components.

Electromagnetic acoustic transducers (EMATs) have been used as a non-contact ultrasound approach for detecting and characterising surface defects in aluminium bars and billet. The characterisation was made from understanding the interaction of broadband Rayleigh surface waves with surface crack growing normal or inclined to the sample surface, based on rolling contact fatigue (RCF) cracks in rail tracks. The interaction with normal cracks have been previously reported. For inclined cracks, mode conversion of Rayleigh waves to Lamb-like waves occur in the wedge section formed by the crack, resulting in strong and prominent enhancement in the signal detected. This is confirmed by finite element analysis (FEA) models and Lamb waves arrival times calculation. Signal enhancement from the interaction creates features in B-scan images, and they have been used for initial crack classifications. Then, a number of analyses were performed to estimate the crack inclination, and accurately determine the crack vertical depth. A feature extraction and image classification program based on genetic programming have been developed (through a collaboration work) to perform automated classification on the B-scans. The program produces more than 90% accuracy using the experimental data set. The viability of EMATs to detect and fully characterise narrow cracks have been investigated through experiments using laser interferometer and comparison with EMATs measurements. The results confirmed that narrow cracks can be detected with EMATs, with initial classification (in B-scans) to normal/inclined. However, the depth sizing may not be accurate, and suggestion for better designs of EMATs have been made. FEA models have been used to study the interaction of the Rayleigh waves with branched cracks. Interesting results are observed in terms of Rayleigh waves reflections, which helps to determine the presence of a branch on RCF-like cracks. A method has been proposed for calculating the length of the branch, following a number of analyses.

This thesis presents an investigation of the selective growth of carbon nanotubes by examining the chemical and physical interaction of the catalyst with various catalyst supports, namely, Al, Ti and SiO2. Numerous surface analysis techniques including AFM, XPS, FESEM, TEM, and Raman spectroscopy have been employed to ascertain that the observed changes in nanotube growth for this system are related primarily to changes in the catalyst support. It is demonstrated that the nucleation density of single-walled carbon nanotubes, formed by thermal catalytic chemical vapor deposition, strongly depends on the grain size of Al catalyst supports covered with a native oxide (Al/Al2O3). By varying the substrate temperature during Al sputter deposition it was possible to investigate the effect of Al grain size on growth without inducing changes in the catalyst support thickness, surface chemistry, or any other growth parameter. Furthermore, it is also shown that by altering the degree of oxidation of physically deposited Al and Ti catalyst supports, the nucleation density of filamentary carbonaceous deposits, such as carbon nanotubes and carbon nanofibres, can be controlled. Using SiO2 as a catalyst support, the growth time, growth temperature, anneal time, carbon feedstock flow rate, and the effect of water vapour on the growth of CNTs was investigated. By varying these parameters, it was demonstrated that the number of active nucleation sites could be changed. Moreover, the unsuitability of physically deposited Ni catalyst on Si/SiO2 substrates to grow horizontally-bound ultralong CNTs, and vertically-aligned ultralong CNTs, using water vapour is also discussed. Two thermal CVD approaches, namely, heated-wall and localised-heating furnace designs, were used to synthesis carbon nanotubes. The heated-wall CVD system was a large 10 cm diameter by 180 cm long tubular furnace. The localised-heating system was comprised of a local source of heat that was encased in a 5 cm diameter by 35 cm long tube. Two separate methods of localised-heating were developed. The first method used a resistively-heated 1 cm wide by 4 cm long highly-doped silicon bridge, which was referred to as the cold-wall furnace. The second method used microheaters that were made of NiCr and Pt. It is shown by use of numerical modelling of both types of furnace designs that, depending on the design of the furnace, different gas flow schemes can occur, which will affect the concentration of gases and carbon feedstock during CNT growth. Using the cold-wall furnace, a simple novel approach was developed for rapid evaluation of carbon nanotube growth that permitted the investigation of a wide range of temperatures in one experimental cycle. A series of experiments, using alcohol-assisted thermal CVD, are shown to demonstrate the effectiveness of such an approach. Pt-based microheater designs are shown to successfully synthesise filamentous carbonaceous deposits. Future microheater devices are discussed with reference to characterisation methods and potential device concepts.