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(2021)ThesisNavigation is a technique for the determination of position and attitude of a moving platform with respect to a known reference. Global Navigation Satellite System (GNSS) has become a dominating navigation technology. However, GNSS signals are degraded or denied in indoor environments. It is necessary to develop alternative positioning techniques for indoor navigation to realize seamless navigation. Inertial Navigation System (INS) and Vision are both regarded to be highly promising because of their ubiquitous and self-contained nature. A new indoor navigation system with vision, INS and reality-based 3D maps are proposed. The main contributions of this thesis are summarized as follows: 1. A new strategy for the integration of vision with a low-cost INS has been developed based on a smartphone. This new approach solves the difficulty of precise calibration of INS errors in such a scenario and enables MEMS INS to generate stable position and attitude solutions. 2. Results show that improved accuracy and reliability of the geo-referenced solution can be achieved. Vision-based navigation with reality-based 3D maps (Vision)/INS integration improves the accuracy and robustness of a navigation solution compared with an INS only solution. 3. Aiding Optical Flow (OF) and Visual Odometry (VO) navigation solution to Vision/INS integrated system improved geo-referenced results during Vision outages. The results confirmed the effectiveness of integration for high accuracy positioning applications. 4. A novel geo-referenced system based on Vision/OF/VO/INS integration has been developed and tested for indoor navigation. Real experiments are conducted to evaluate the influence of different integrated configurations on the performance of the navigation system. 5. Integrated indoor navigation requires a robust outlier detection mechanism to ensure good performance. Outlier detection and identification are explored and researched on the integrated indoor navigation system. Besides, a multi-level outlier detection scheme for the navigation system has been proposed. 6. Analyzing the factors that influence the correlation coefficients between fault test statistics in Vision/INS measurements and the dynamic model is another essential contribution of this thesis. Reliability and separability analysis of outlier detection theory was extended by providing a more reliable estimation of MDB and MSB.
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(2021)ThesisDue to the large variety and unique physiochemical properties, such as high electrical conductivity, adjustable interlayer spacing, intercalation chemistry and so on, two-dimensional (2D) materials have attracted tremendous attention for their suitability in the development of high-performing supercapacitors. Despite that great progress has been made, there is still no single 2D material that can perfectly meet all the requirements to replace the existing material, mainly activated carbon, used in commercial supercapacitors. Therefore, continuing efforts for exploring novel, high-performing 2D materials with low cost are desirable. In this dissertation, the prior studies on the development of 2D materials ranging from layered inorganic materials to organic-inorganic hybrids for supercapacitors are first reviewed. As an emerging type of 2D material, layered organic-inorganic hybrids start to show promising results to be used to fabricate high-density, nonporous, and thick electrodes for compact capacitive energy storage. However, the studies in this area are still lacking. Thus, the goal here is to explore the opportunities of 2D organic-inorganic hybrids for applications in supercapacitors. The relevant techniques and methods used throughout the study are then outlined. Next, three research chapters supporting the main findings of the investigation are included. The first research chapter describes a facile mechanical strategy to improve the kinetics and rate performance of 2D organic-inorganic hybrid electrodes at ultrahigh mass loadings (up to 30 mg cm-2). The second research chapter reports the synthesis of a new layered organic-inorganic hybrid material with excellent volumetric and areal capacitances even at mass loadings reaching 50 mg cm-2, highlighting the good electrode kinetics. The third research chapter presents the wafer-scale electrochemical deposition synthesis of 2D organic-inorganic composite films with controlled size and thickness, which are promising for the development of flexible and transparent electrochemical energy storage devices. Finally, conclusions and recommendations are given at the end of this dissertation.
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(2021)ThesisUnderwater sound can have a detrimental effect on marine animals due to the ever-increasing noise levels in their pristine habitat. It has also been commonly used to detect underwater floating objects via a sonar system. To absorb unwanted underwater sound, polymers (e.g., rubber), which have similar impedance to that of water, are widely used for sound absorption in water. Nanocomposites have attracted considerable attention due to their ability to improve sound absorption properties of polymer-based sound absorption materials. This project aims to develop a thin-layer nanocomposite with high underwater sound absorption at low frequency and high pressure. A water-filled impedance tube, an essential facility to test new materials developed in this PhD thesis, was designed and constructed. The established research facility consists of four main components: a stainless steel tube and its supporting devices, a sound source (a projector) and its associated electronics, an underwater sound pressure measurement system, and a water pressurized system. Subsequent calibrations and measurements showed that the established apparatus could be used to measure the underwater sound absorption coefficient in a frequency range of 1500 Hz to 7000 Hz and under hydrostatic pressure in a range of 0 to 1.5 MPa. Carbon nanotubes (CNTs) reinforced polydimethylsiloxane (PDMS) nanocomposites were designed, fabricated, and tested. This development comprised of two stages. In the first stage, PDMS was selected as the material matrix, surfactant and carboxyl functionalized multi-walled carbon nanotubes (MWCNT-COOH) as inclusions, and a new nanocomposite, namely PSM (PDMS/surfactant/MWCNT-COOH), was then developed. Effects of the added surfactant and MWCNT-COOH on the mechanical properties, chemical properties, and morphology were investigated, which indicated the nanocomposite’s potential for sound absorption improvement. Underwater acoustic tests showed high underwater sound absorption coefficients (>0.8) in the most frequency range 1500 Hz to 7000 Hz. However, it was observed that a significant drop in the underwater sound absorption performance under high hydrostatic pressure. It was found that the high compression of PSM was the cause of poor performance under high hydrostatic pressure. In the second stage, a core-shell structure was designed to maintain the high sound absorption coefficient of PSM under high hydrostatic pressure. A novel structure of a 2-mm-thick hard shell with a 2-mm-thick soft layer was developed to encapsulate the PSM sample so that its deformation can be minimized and its superior sound absorption property was improved under high pressure. Experimental results on the water-filled impedance tube demonstrated that the new structure offered a promising solution to the demand for advanced underwater materials, which are thin and have high sound absorption performance under high hydrostatic pressures. In summary, this study has developed a polymer-based nanocomposite. Mechanical properties, chemical properties, morphology, and underwater acoustic properties of the nanocomposite have been studied. The nanocomposite is thinner than existing underwater acoustic materials and has excellent underwater sound absorption performance in the frequency range of 1.5 to 7 kHz and under atmospheric pressure. For applications in high hydrostatic pressure up to 1.5 MPa, the proposed new structure with a total thickness of 14 mm, in comparison to 50 mm or more thickness of other developed materials for marine applications, showed good sound absorption results and potentially addressing the on-going technical challenge of poor sound absorption performance of acoustic materials under high hydrostatic pressure.
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(2021)ThesisCataracts are responsible for almost half of worldwide blindness, making it one of the biggest health challenges in this era. Cataracts are irreversible because of their pathology, which is controlled by the aging and biochemical change of eye tissues. As a result cataract surgery is currently the only effective treatment. The general procedure of cataract surgery includes separation and removal of the failed lens tissue from the surrounding soft tissue in the eye, followed by artificial lens implantation. Lens removal requires successful separation of lens tissues as a critical step that determines surgical success. However key parts of cataract separation affected by fluid mechanics and rheology are uncharacterised. This project aims to explain the behaviors of such separation phenomena and connect fundamentals with possible explanations and enhancements. A multi-layer bio-polymer injection model is developed to mimic the separation process in cataract surgeries. The separation can be considered peeling of a soft elastic tissue by a pressure-driven fluid flow, whose performance is closely related to properties such as flow rate and velocity as well as fluid viscosity, normal stress and yield stress. In our project, the separation physics is studied as a hydraulic fracture problem. Theories are proposed to discuss the effectiveness and safety of hydraulic fracture with different flow and fluid parameters. It is found both higher flow rate and viscosity will cause tissue to be deformed more, which may increase the risks of tissue damage. Yield stress fluids with significant elasticity are not suitable as in most cases they rupture the tissue. Normal stress fluids have the potential to provide safe and effective separation. It is found that with a small scale separation, however, the separation effectiveness is mainly affected by the flow rate, and the fluid properties play a more minor role. General ideas and potential improvements according to our results and theories are also proposed for cataract surgeries, which we hope will contribute to easier and safer separation.
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(2021)ThesisThe bismuth/erbium co-doped optical fibres (BEDFs) have attracted much attention due to their ultra-broadband luminescence in the near-infrared (NIR) region with great potential for optical amplifiers and fibre lasers in the telecommunication system. To gain the fundamental understanding of bismuth active centres (BACs) and know the nature of their NIR luminescence in BEDF, a number of studies that focus on the fabrication process, spectral properties, and post-treatment effects have been conducted. These studies revealed that the BACs in BEDFs could be sensitive to the post-draw processes/conditions, such as laser irradiation, ionizing irradiation, H2 loading and thermal treatment. Based on the reported work, the understandings of both the nature of BACs and their responses to various post-draw processes are still quite limited. My PhD research has been aimed at better understanding the thermal effects on BACs in BEDFs and studies several special cases of thermal treatments/processes that show significant effects on the optical characteristics of BACs. In this thesis, I report: The thermal activation effect on BAC-Si in BEDF. The evolution of BAC-Si luminescence is systematically investigated with different thermal treatment conditions (temperature, dwell time and cooling rate). By optimizing these dynamics parameters, the luminescence of BAC-Si at 1405 nm could be enhanced to ~2.5 times. The thermal activation effect on BAC-P in BEDF. In this work, the significant increase of BAC-P related absorption and luminescence is observed after the thermal treatment. The thermal activation of BAC-P is studied in terms of treatment temperature and dwell time. The maximum enhancement of BAC-P luminescence at 1290 nm (~4.3 times) is achieved by optimizing the dynamics parameters. Thermal effect on photobleaching of BAC-Al in BEDF. The effect of temperature on photobleaching of BAC-Al is comprehensively investigated from room temperature up to 350°C under the irradiation of 980 nm laser. No visible bleaching of BAC-Al is observed at room temperature, but significant bleaching appears at higher temperatures above 150°C. Such thermal aggravation of photobleaching effect needs to be considered in the design and application of BEDF-based devices at different temperatures. The thermal bleaching effect on BAC-Al in BEDF. The variation of luminescence spectra is inquired into when the BEDF is thermally treated with different treatment conditions. The higher temperature and longer dwell time can lead to more severe thermal bleaching of BAC-Al. To the best of our knowledge, this is the first observation of thermal bleaching of BAC-Al in BEDF, which provides a better understanding of thermal effects on BACs. The thermal bleaching effect on BAC-Si in BEDF. For the first time, the thermal bleaching of BAC-Si peak luminescence is characterized by the stretched exponential function. Besides, the temperature dependence of bleaching ratio and bleaching rate are analysed. Based on the results, the possible mechanism of thermal bleaching of BAC-Si is discussed. The dynamic study on the thermal bleaching process provides a deeper understanding of the variation rule, which helps to reveal its mechanism. The findings/discoveries from this thesis work allow us to better understand the fundamental structure of BACs and the thermal-induced effects on their luminescence characteristics in BEDF. Especially, the thermal activation effect, thermally aggravated photobleaching effect and thermal bleaching effect on various BACs are studied, providing more comprehensive cognition of thermal properties of BACs. With further knowledge of the BACs, it helps to develop an effective way to control the BACs with better optical performance in BEDF for practical applications.
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(2021)ThesisRice bran is a major, underutilised by-product of the rice industry and the high proportion (~90%) of insoluble fibre is the main reason limiting its applications in foods. This thesis is aimed at modifying the physicochemical properties of rice bran by physical (ultrasound and steam explosion) and enzymatic treatments, thereby improving its technological and health properties. Purified (starch and protein removed) and un-purified defatted rice brans were treated by ultrasound and steam explosion under different intensities (amplitude, time, steam pressure), followed by enzymatic hydrolysis using ShearzymePlus. Changes in physicochemical properties of the bran were determined. The physical treatments strongly impacted on the physicochemical properties, which were affected by both treatment intensity and bran purity. For purified bran, increasing treatment intensity generally led to decreases in particle size and bulk density, and increases in porosity, swelling, water and oil binding capacities, as well as the increased yield of soluble fibre. The greatest changes in these properties were generally achieved with ultrasound treatment at 60% amplitude for 20 min, where the highest yield of soluble fibre (35.2g/100g) was obtained. For un-purified rice bran, the presence of starch and proteins complicated the efficacy of the treatments. The steam explosion was found to be less effective than ultrasound in modifying the physicochemical properties of rice bran. Soluble fibre produced from both physical treatments mainly contained oligosaccharides with MW <25kDa, which showed good prebiotic potentials in promoting the growth of L. acidophilus and B. Bifidum with the highest MW fraction (~17kDa) being the most effective. Shearzyme Plus hydrolysed the insoluble fibre into the soluble fibre; however, the hydrolysis was more effective on untreated than physically treated bran. Incorporation of ultrasound and enzymatically treated rice bran to flour (15%) caused minimum deterioration in bread volume, texture and colour compared to untreated bran. The enrichment significantly improved the glucose adsorption capacity and glucose dialysis retardation, reduced glucose diffusion and glycaemic index (GI), and greatly increased the sodium cholate binding capacity of the bread. Overall, this thesis demonstrated that ultrasound and enzymatic treatment is a feasible method to modify rice bran with significantly enhanced technological and health functional properties.
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(2021)ThesisA literature review about the surface texture fabrication technologies and the previous studies of using surface textured cutting tools to improve the cutting performance is reported. It is shown that cutting tool surface texture is a promising technology to reduce the friction at the tool-chip and tool-work interfaces and cutting tool wear in machining. However, a comprehensive investigation is imperative to provide an insight into the mechanisms under which cutting tool surface textures improve the cutting performance. An experimental study is reported to investigate the effect of parallelly arranged micro-groove arrays on the surface wettability of cemented carbides to an emulsified cutting fluid, and the tribological performance of the textured surfaces. It is found that suitably designed micro-grooves can lead to complete wetting where liquid propagates quickly along the grooves to improve the tribological condition of the textured surfaces with much reduced frictional coefficient as compared to untextured samples. An experimental investigation into the effect of rake face textures on the cutting performance in orthogonal machining of the AISI 1040 steel is presented. It is revealed that micro-grooved surface textures on the rake face of cutting tools can reduce the thrust force by up to 14.68%, owing to the reduced tool-chip frictional force and the increased shear angle in the share plane as compared to untextured tools. A predictive cutting force model for machining with rake face textured cutting tools is then developed using the unified mechanics of cutting approach and experimentally verified for carbide cutting tools cutting the AISI 1040 steel. A finite element model representing the machining process using a rake face textured cutting tool is established and experimentally verified. A simulation study is then undertaken using the developed model, which reveals the mechanisms behind which cutting tool rake face textures affect the friction and wear on the rake face. It shows that rake face textured cutting tools affect the amount of heat generated during chip formation and heat conduction into the cutting tool, so as to reduce the cutting temperatures and tool wear on the rake face.
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(2021)ThesisThe complex structure of software applications can increase cognitive load and render tools incomprehensible. Since few studies have been conducted that focus on facilitating the learning of software applications for novice users, this thesis proposed a teaching solution by applying three elements of gamification including the use of Narrative, Interactivity and Avatar. The goal was to apply these gamification elements in an e-learning system and evaluate the effects on learners’ cognitive load while learning to use software tools with low and high element interactivity. Cognitive load theory was used as a guiding research principle. To this end, three integrated experiments were designed with the total of 160 participants. A mixture of objective and subjective quantitative measurement methods was used to measure cognitive load. For the subjective measurement, participants were asked to complete a self-reported difficulty Likert scale questionnaire. For the objective measure, participants performance including the following five factors was assessed: test task performance marks; test task performance speed; mouse movement distance; number of left and right clicks while finding the test task solution; time duration of reading each tutorial. In the first experiment, narrative which is a core element of gamification science, was selected as a procedure that can provide practical knowledge to software learners while impacting cognitive load by providing a familiar theme in worked-examples. The results showed that an e-learning system with a familiar narrative could decrease cognitive load in comparison to the no-narrative and unfamiliar narrative systems. In the second experiment, the effect of interactivity on delivering narrative-based content was evaluated by comparing animation versus interactive animation. The findings revealed that interactive animation was superior to the animation-based version which is in accord with embodied cognition theory. Finally, the third experiment evaluated the effect of a talking avatar versus plain audio on cognitive load in narrative-based e-learning systems that used interactive animation. The findings indicated that the talking avatar increased cognitive load during learning which is in accord with the redundancy effect.
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(2021)ThesisIn the recent decade there has been a sharp increase in the utilization of machine/deep learning models for the development of Natural Language Processing (NLP) applications, especially focused on language understanding, with end-goals targeted at, but not limited to: information retrieval, machine translation, sentiment analysis, question answering, etc. These applications call for the need of better models for in-depth understanding of the language structures which in turn help development of automated routines that may acquire vast variety of unstructured data from web resources, process the data and convert it to the desired information content. In the recent past many different models have been developed for language-specific information extraction and a better understanding of semantic aspects of the language, however, yet there are some challenges associated that need to be addressed for the improved utility of these models in the down-streaming tasks. In this thesis, we propose new models with the aims to improve upon the existing methods for the lexico-semantic relation and information extraction tasks. For lexico-semantic relation extraction, we work around distinguishing among different lexico-semantic relations captured from unstructured data, i.e., distinguishing antonyms from synonyms and hypernymy detection. For information extraction, we work with improving the Fine-Grained Named Entity Typing (FG-NET), which is a key component for different down-streaming information and relation extraction tasks. Given the fact that the fine-grained type hierarchy follows a hierarchical structure, in Chapter 5, we extend the concepts of FGET-RR to Fine-Grained Named Entity Typing with Refinement in Hyperbolic space (FGNET-RH) that combine the benefits of the non-euclidean geometry (hyperbolic space) along with the graph structures to perform FG-NET in performance-enhanced fashion. Finally, in order to evaluate the reliability of the machine/deep learning systems for information extraction in real-life scenarios, we evaluate the performance of these systems under uncustomized settings.
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(2021)ThesisStability of power system ensures continuous and uninterrupted power delivery from generation to demands and measures the dynamic behaviour of different system characteristics subject to disturbances. Failure to maintain stability can lead to consequences ranging from disconnected buses and areas to cascading failures and system blackouts. Increased integration of renewable energy sources and involvement of demand-side into system operation in the recent years have introduced more intermittency into the power system. This intermittency increases the difficulty to maintain system stability and requires better control strategies to accommodate the high-level penetration of uncertainties in the power system operation. In addition to conventional control methods such as generator dispatch, numerous measures are considered to reduce the uncertainty introduced, such as wind curtailment, to act timely in case of instability, such as emergency load shedding, and also to utilize the flexible resources, such as energy storage systems. This research consists of methodologies that account for control measures both before and after the contingency to achieve the optimal balance between the economy and stability in system operation. The main research contributions are listed below: Firstly, a hybrid approach is proposed for the improvement of conventional optimal power flow (OPF) calculation, which utilizes the critical machine (CM) theory in the Extended Equal Area Criteria (EEAC). A detailed composite load model is later applied to capture a more accurate dynamic behaviour of the system. Secondly, a preventive-emergency coordinated control method is developed to maintain system transient stability in the presence of uncertain wind power generation. It coordinates between preventive control (generator dispatch and wind curtailment) and emergency control (emergency demand response) to achieve the optimal trade-off between system stability and economy. Thirdly, the effects of having actively controlled utility-scale Battery Energy Storage Systems (BESSs) systems are investigated, and a coordinated strategy that utilizes generator redispatch in preventive control and energy storage in both preventive and emergency control stage are developed. Finally, the flexibility of BESS is investigated. The model performance and parameter sensitivity of a new generic BESS model are firstly evaluated. An emergency control scheme is designed based on the results of evaluation, which includes both BESS and emergency load shedding scheme as post-contingency control measures. Proposed methodologies and strategies are evaluated on benchmark systems with industry-grade dynamic models and simulation software. Applicable cases from literature are also performed for comparative purpose. The simulation experimental results have verified the effectiveness of the proposed methodologies and strategies.