Deformation and damage processes in brittle and quasi-brittle materials, such as rock and concrete, are strongly influenced by their heterogeneous nature, related to their formation processes. The presence of heterogeneities leads in fact to noticeable variation in material properties values: it is of extreme importance that a numerical model which aims to realistically, reliably reproduce with low computational effort deformation and damage processes is able to include the effect of laminations, micro-cracks, voids and other types of heterogeneities; this is even more important when a numerical models has to reproduce the propagation of fractures. This thesis presents the development of a numerical framework for the simulation of crack propagation in shale rocks and concrete which also looks at the optimisation problem in the sense of computational efficiency (defined as optimal computational time needed to obtain realistic and accurate results). The numerical framework for crack propagation developed in this thesis is a variational phase-field model based on a finite elements smeared approach, able to automatically and realistically capture crack initiation processes for a variety of loading conditions; this numerical framework is based on the relation between potential energy associated to body deformation and the energy released during fracture formation. Heterogeneity is considered in the model by means of a stochastic approach based on the assumption that some mechanical properties of heterogeneous brittle materials (such as fracture energy) follow a non-Gaussian Weibull distribution. To guarantee adequate convergence of the results, Monte Carlo Simulation (MCS) method has been used in combination with the developed stochastic methodology. A non-linear dimensionality reduction technique has been developed and incorporated in the algorithm to reduce the computational effort required for the generation of sample realisations. The methodology has been validated using experimental results from both laboratory tests on shale rocks and literature on fracture in concrete. Results show that the developed algorithm is capable of realistically reproducing the mechanical behaviour of the chosen case studies, showing an applicability to problems where cracks propagate in mode-I, mode-II and mixed-mode I and II, guaranteeing a fast generation of sampling realisations of realistic stochastic fields and convergence of results after a maximum of 130 MCS analyses. This methodology can be applied to materials with random spatially-distributed variations of mechanical properties and to those showing laminar natural formations.

Multiphase flow measurement is important in chemical processing, water treatment and oil & gas industry. The multiphase flow sensor proposed in this research utilizes the resonant frequencies that occur inside a cavity and the differences in the permittivity of the measures phases. By measuring this response over the range of discrete frequencies the sample can be characterised. Polar material like water has relatively high permittivity (ε_r= 81), while non-polar material such as oil and gas have low permittivity value (ε_r= 2.2-2.5) and (ε_r= 1) respectively. Hence, a small change in the water fraction may result in a comparatively large frequency shift. In this research, the electromagnetic cylindrical cavity sensor system successfully demonstrated its capability to analyze various fractions of water-gas mixture. The results were consistent in the case of both the static and dynamic flow. The statistical analysis of the captured data showed a linear relationship of the amplitude data with the change in the water fractions. It was also found that the technique was independent of the temperature change. The system was able to successfully detect the stratified, wavy, elongated bubbles and homogeneous flow regimes. The electromagnetic rectangular cavity sensor system is introduced to pick up the tiny shifts in the permittivity when the low permittivity material is used or temperature changes. The microwave sensor system is able to detect water-air fraction, water-oil fraction, oil-air fraction and water temperature. The novel solution of the combination of both cylindrical and rectangular sensor system demonstrates the ability to detect both high and low permittivity changes. These dual-cavity sensor cavity systems have been able to detect water level, flow regime and temperature in the pipe. It also demonstrates that microwave sensors based on the principle of changing permittivity can replace conventional measurement techniques.

Acquiring new knowledge often requires an agent or a system to explore, search and discover. Yet us humans build upon the knowledge of our forefathers, as did they, using previous knowledge; there does exist a mechanism which allows transference of knowledge without searching, exploration or discovery. That mechanism is known as imitation and it exists everywhere in nature; in animals, insects, primates, and humans. Enabling artificial, cognitive and software agents to learn by imitation could potentially be crucial to the emergence of the field of autonomous systems, robotics, cyber-physical and software agents. Imitation in AI implies that agents can learn from their human users, other AI agents, through observation or using physical interaction in robotics, and therefore learn a lot faster and easier. Describing an imitation learning framework in AI which uses the Internet as the source of knowledge requires a rather unconventional approach: the procedure is a temporal-sequential process which uses reinforcement based on behaviouristic Psychology, deep learning and a plethora of other Algorithms. Ergo an agent using a hybrid simulating-emulating strategy is formulated, implemented and experimented with. That agent learns from RSS feeds using examples provided by the user; it adheres to previous research work and theoretical foundations and demonstrates that not only is imitation learning in AI possible, but it compares and in some cases outperforms traditional approaches.

A system for the shear horizontal guided wave screening of pipelines is developed and optimised. The system is considered in terms of the circumferential shear horizontal guided wave behaviour as opposed to the majority of other studies that approximate the structure of an unwrapped pipe as a plate. This allows for consideration of the effect of a defect on both the lowest order symmetric and antisymmetric modes. The assessment of the guided wave interaction with a corrosion patch defect is carried out for a basic defect from which the axial sizing can be determined from encoded scans of the sample and amplitude changes. The circumferential positioning capabilities can be found using the effect seen on different modes and the presence of reflections. The behaviour of the two lowest order shear horizontal modes when incident on a defect above and below the cut off thickness of the lowest order antisymmetric mode can be seen in the experimental measurements and visualised through finite element modelling. Once the behaviour of the modes when they interact with different depths of a defect is understood, the technique is expanded to a real corrosion patch of known dimensions. It is extended to more complex samples with multiple, varied positioned corrosion patches and blind trial situations where the geometry and depth of defects is unknown. Although the size and depth of these defects is unknown, the knowledge of the interaction of the waves with the other defects can be used to estimate the defect size and depth. The calculation of the remaining wall thickness in the current iteration of the system is limited to a broad range, unless there is prior knowledge of the defect geometry. This is because the defect geometry is shown to have a large effect on the arrival time of the through transmitted waves. Consideration is given to the effect of welds on a signal and the differences between calibration defects and real corrosion patch style defects. The system has been tested further in extended blind trials and proved effective as a screening tool for the detection of corrosion patch style defects, with detection capabilities dependent on the axial size and depth of the defect.

Conventional seismic-resistant moment-resisting frames (MRFs) designed to Eurocode 8 develop inelastic deformations in beams and column bases that result in residual drifts and structural damage. Self-centering MRFs (SC-MRFs) with post-tensioned beam-column connections have been proposed to address these problems. However, SC-MRFs cannot avoid plastic hinges in their column bases, resulting in difficult-to-repair damage and first-storey residual drifts. Therefore, a damage-free self-centering column base connection (referred to as column base) is needed to further enhance the earthquake resilience of SC-MRFs. A novel column base is proposed in this study. The column base uses post-tensioning technology to achieve self-centering behaviour and replaceable web-hourglass shape steel pins (WHPs) to dissipate seismic energy, while the rest of its components remain damage-free. The column base requires no field welding, it is easy to construct, deconstruct and rehabilitate, and thus facilitates sustainable (green) construction. The study develops an analytical model to predict the column base hysteretic behaviour and identify its limit states. A performance-based design procedure is developed for the column base which ensures self-centering and damage-free behaviour and designs its main components. A high-fidelity nonlinear finite element method (FEM) model for the column base is developed in software Abaqus. The Abaqus model verifies the accuracy of the analytical model and identifies failure modes that cannot be predicted analytically. A FEM model for the column base is also developed in software OpenSees. The model validates the accuracy of the previous models and facilitates the seismic assessment of the novel column base. Design recommendations for practical application to real buildings are also provided. The conventional MRF of a prototype steel building is redesigned as: (a) SC-MRF with conventional column bases; and (b) as SC-MRF with the novel column bases. The two design cases are modelled in OpenSees and nonlinear analyses are performed to compare their seismic response. The results of the analyses demonstrate the resilient performance of the novel column base under strong earthquakes, achieving self-centering and damage-free behaviour. The beneficial effect of the novel column base on the seismic response of SC-MRFs is demonstrated by reducing their peak and residual drifts in the upper storeys, eliminating the latter in the first storey, and pushing their critical structural limit states to higher seismic intensities. Recommendations for future research are also provided.

In new product development, knowledge is the key to innovation. In order to remain competitive in today’s engineering world, knowledge is a crucial asset for organisations that enable them to gain a sustainable competitive edge. An extensive industrial investigation has been conducted in this project to bring out real industrial requirements in the product development and testing context within the collaborating company. Based on the industrial investigation and literature survey, the research direction is identified, i.e., to develop methodologies to capture and share testing related knowledge to address the special nature and application context of the integrated global product development and testing operations of multi-national companies. Currently, engineering companies are still mainly using traditional information systems with structured databases such as computer aided engineering, enterprise resource planning and product lifecycle management systems. This project explores whether the fast developing social media tools are capable of facilitating the capture and sharing of employee knowledge, especially tacit and un-structured knowledge, and addressing the social aspects of knowledge management. The project also explores the benefit of using a knowledge framework that is directly driven by the knowledge users by providing both knowledge content and how it is structured, rather than relying on the role of knowledge administrators. The developed methodology with social media, video sharing and storytelling techniques would substantially enhance and extend the capabilities of traditional engineering knowledge management tools, by providing the ability to quickly browse and absorb user-contributed testing knowledge, like lessons learned, suggested product improvement or process training material, and identify specific knowledge experts within an global organisation. A comprehensive case study has been conducted within the collaborating company to validate the usefulness and effectiveness of the developed methodology. While keeping the collaborating company’s requirements in mind during the research, the developed methodology and tools can also be applied in other product development and engineering business environments as an enabling tool to promote collaboration, learning and knowledge sharing in global operations.

No description available.

Surface texture, a core part of geometrical product specifications and verification (GPS), is embraced by the whole surface manufacture chain from design through manufacture and measurement, and plays a significant role in determining the functional performance of workpieces. The delivery and implementation of surface texture knowledge in GPS, however, is undergoing critical problems in current practice. Surface specification/design systems lag far behind the measurement systems. This is caused by knowledge gaps between design, manufacture and measurement systems exemplifying the necessity of an infrastructure which synergy seamlessly between different stages. This thesis documents the development of a surface texture platform called CatSurf to bridge the knowledge gaps. A category theory based knowledge modelling methodology is proposed to underpin the mathematical foundation of the CatSurf. Deploying this methodology, the knowledge modelling for areal and profile surface texture is carried out. The design and implementation of the CatSurf system is developed based on modelling. In addition, the CatSurf system is integrated with Computer Aided Design systems by utilising a Component Object Model (COM) and XML (Extensible Markup Language) based integration methodology. The integrated CatSurf system provides unambiguous surface texture information for designers and metrologists, and enables metrology assisted design and manufacture to become reality. Currently, it is an executable system with three different modules which can be integrated with CAD systems such as AutoCAD and SolidWorks. A special module is developed for Rolls Royce with a single roughness parameter Ra for gas washed surfaces. The system is tested and recognised by various parties such as Rolls Royce, CAx and GPS experts, computing and mechanical engineers and researchers, etc.

Density is an important physical property and its measurement has wide application in a vast number of industries including; oil and gas, petrochemical, pharmaceutical, brewing, food & beverage production and mining. Density is often required to be accurately measured either as a standalone property or in combination with other flow properties for the purpose of quality assessment, process control, and custody transfer. Given the increasing importance of density measurement, extensive research has been conducted over recent years to develop newer and more accurate density measurement sensors and to improve the accuracy of existing sensors. This thesis describes the design and development of a novel, non-invasive, non-radioactive Vibrating Density Measurement System (VDMS) capable of measuring fluid density in both single phase and multiphase flows. The device is also capable of measuring mean in-situ phase volume fractions in two-phase flows. The VDMS comprises three sub-units; (i) a measurement unit which includes a straight length of sensing pipe with corrugated bellows at both ends, an actuator and relevant sensors; (ii) a signal conditioning and processing unit; and (iii) a data acquisition unit. The thesis also reports the development of a novel mathematical density prediction model which is used in conjunction with the VDMS. It then goes on to report the results of static bench test experiments that were conducted on the VDMS using a bespoke test rig. These tests were performed (i) to obtain the mass of the sensing pipe, its stiffness constant and damping constant; (ii) to investigate the frequency response characteristics of the VDMS; (iii) to obtain the VDMS constant; (iv) to investigate the sensing pipe displacement pattern; (v) to investigate the capability of the VDMS to give accurate density measurements of static fluids and (vi) to define the optimal VDMS operating conditions. Computation of density was achieved using the VDMS, the density prediction model and a novel signal processing technique. This signal processing technique used the Discrete Fourier Transforms (DFTs) of the measured force, used to mechanically excite the sensing pipe at its centre, and the measured displacement at the sensing pipe centre. Next, the thesis reports a novel computer based control system that was developed to ensure that the VDMS automatically operated at its optimal operating conditions, so that errors in the density measurement were minimised. The control system was also capable of providing online computation of the flow mixture density. Results are reported of several experiments conducted by the author on the VDMS to measure the fluid density in a range of “water only” flows, “solids-in-water” flows and “air-in-water” flows. These flows were all vertically upward and were established in the working section of a multiphase flow loop. These multiphase flow experiments were subsequently extended to compute the mean in-situ phase volume fraction of the solids phase in “solids-water” flows and the gas phase in “air-water” flows. For the “water only” and “solids-water” flow experiments, the mean error in the predicted density was consistently within 0.5% of the reference density and the standard deviation of the error was less than 1%. For “air-in-water” flows the predicted density was within 1% of the reference density for flows where the air volume fraction in the mixture was less than 10%. The mean in-situ volume fractions, measured by the VDMS, of the dispersed solids in “solids-in-water” flows and of the dispersed air in “air-in-water” flows were within 10% of the reference measurements for the vast majority of measurements taken. Finally, the thesis describes a modified mathematical model, used with the VDMS, for predicting mixture density in “air-in-water” flows. This modified model is extended to make use of the predicted coupling stiffness between the VDMS sensing pipe and the multiphase mixture. The modified model gave density measurements with a higher order of accuracy than the earlier model which did not consider the effect of the flow compressibility on the coupling between the sensing pipe and the pipe contents.

The uncertainty and complexity of the interdependent global economy have amplified collective exposure of supply chains to disruptive events. In the construction world, the fragmented nature of the temporary project teams and the uncertain operating environment make construction supply chains more vulnerable to these disruptive events. In Malaysia, the construction industry has become the focal point for development through the Government’s “Malaysia Vision 2020” transformation programme, in the effort to become a developed country by the year 2020. However, despite good plans for the development of public projects, the Malaysian Auditor General Report 2014 identified several weaknesses in the delivery of construction projects that caused poor project performance. The dynamics and effects of interconnected risks among construction organisations tend to be overlooked across the Malaysian public project supply chains, making them highly vulnerable to supply chain disruptions. This calls for the need to go beyond the traditional silo approach of the risk management process. This research aims to investigate the Malaysian public sector supply chain’s resilience capabilities and vulnerabilities in handling disruptions in the effort to build supply chain resilience against disruptions and improve the delivery of public projects. A comprehensive questionnaire survey was conducted with 105 construction professionals from two groups of respondents, the public and private organisations in the public sector supply chain to identify their current vulnerabilities and capabilities. Data were analysed using descriptive statistics and compared using the Mann-Whitney U and Kruskal-Wallis tests. The findings revealed that the public organisations faced significantly higher political threats whilst the private organisations faced significant market pressures. Subsequent semistructured interviews were conducted with 12 professionals in the field to identify the inherent pathogens that make the supply chain highly vulnerable in these critical areas. The emergent pathogenic influences include practice, circumstance, convention, organisation and behavior. Finally, a resilience response framework was developed based on the triangulation of these results. The framework allows the experts from the public sector supply chain to understand the critical vulnerabilities and pathogenic influences of their organisation and their supply chain members, along with the set of capabilities to reduce the disruptive impacts arising from these critical vulnerabilities.