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(2022)ThesisUnmanned aerial vehicles (UAV) usage is constantly on the increase. Future skies have a risk of being congested with busy UAVs assisting humans in many different ways. Such congestion could lead to aerial collisions. To avoid disastrous situations, potential for aerial collisions should be addressed. Avoiding aerial collisions has been reported in various different ways in the literature. Out of all the ways available in the literature, collision cones have the ability to predict a future collision beforehand with a low computational burden. Many variants of the collision cone approach have been proposed for various different collision avoidance tasks in past research. However, avoiding a collision will have an effect on the total mission time. In spite of the large volume of past work, time-efficient collision avoidance has not been examined extensively in collision cone literature. This research presents methodologies to avoid aerial collisions in a time-efficient manner using the collision cone approach. The research in this thesis has considered all possible scenarios including heading change and speed change, to avoid a collision. The heading based method was mathematically proven to be time-efficient than the other methods. Initially, 2D collision avoidance methodologies are presented; however, in extreme cases, 3D collision avoidance is necessary and 2D methods have been extended to address 3D collisions. The proposed heading based method was compared with other works presented in the literature and validated with both simulations and experiments. A Matrice 600 Pro hexacopter is used for the collision avoidance experiments.
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(2022)ThesisWith the rapid growth of space technology, space robots play a critical role in on-orbit servicing missions, such as assembling, repairing, refueling, and transporting missions. Space robots can autonomously carry out on-orbit missions, avoiding dangerous and expensive tasks for astronauts. Unlike ground robots with fixed bases, the coupled dynamics between the free base and the manipulator of space robots need to be considered. Compared with single-arm space robots, dual-arm space robots can implement more complex tasks with a higher probability of success. Therefore, the modeling, motion control, hybrid position/force control, and post-capture control of a dual-arm space robot are investigated and presented in this thesis. The mathematical models of dual-arm space robots are developed by considering the reaction wheels (RWs) in the base. The kinematic model is constructed by the Generalized Jacobian Matrix (GJM). The dynamic models are inferred by the Newton-Euler method and the Lagrangian method, which are used in different application scenarios. The motion control of the two manipulators is used to implement a novel strategy to approach a defunct spinning target in space. By the nonlinear model predictive controller (NMPC), the end-effectors can track and plan smooth trajectories to approach and synchronize with a defunct spinning target. Meanwhile, the base attitude is regulated by the RWs to be stable at zero. The hybrid position/force control is applied to the dual-arm space robot to conduct contact operations. Novel capture and on-orbit assembly strategies are investigated. With the model uncertainties of the space robot, a robust sliding mode controller (SMC) is developed for better robust performance than the conventional computed torque controller. Furthermore, the unknown inertial parameters of the target can be precisely estimated during the capture phase. When a space robot and a target are rigidly connected during the post-capture phase, they form a combined system. The combined system can be stabilized to rest status by the space robot. The space robot can also release the target at the desired velocity. The proposed modeling, capturing of a spinning target, on-orbit assembling, and post-capturing processes are validated in the numerical simulations, which show the feasibility and effectiveness. The proposed work will improve the accuracy and efficiency of space robot technology.
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(2023)ThesisBiodegradable implant materials are more appropriate for temporary support applications compared with their inert counterparts since the former requires no removal surgery because they naturally degrade and eventually dissolve completely during healing. Iron and its alloys are a possible substitute for the commercial magnesium biodegradable implants because of their superior mechanical properties and slower corrosion rates. The addition of manganese and silicon in iron imparts another interesting property to the material–the shape memory effect. There is copious research on the structure and properties of the biodegradable face centred cubic (FCC) Fe-30Mn-6Si shape memory alloy (SMA) that exhibits the reversible FCC austenite to hexagonal close packed (HCP) ε-martensite transformation. However, recent advances in additive manufacturing of metals, brought by the development of the laser powder bed fusion (LPBF) technique, warrant the need for an investigation on the adaptability of the technique in fabricating this alloy composition. The LPBF technique is limited by the need for specialty raw material powder, and this thesis extends the application of the technique in fabricating the Fe-30Mn-6Si shape memory alloy (SMA) from homogenised powder precursors. More so, LPBF processing of Fe-30Mn-6Si alloy from either pre-alloyed powder or blended powder has not been reported. To successfully fabricate a Fe-30Mn-6Si LPBF product, the influence of key LPBF processing parameters on product quality was identified as a major challenge. This was addressed by investigating the influence of laser power, laser scan speed, laser re-scanning, and their equivalent input energy on the relative density and defect formation. A relative density of over 99% with few processing defects was achieved using the optimised parameters of 175 W laser power, 400 mm/s scan speed, and no re-scanning. The influence of these parameters on the solidification microstructure was also investigated using key techniques, such as X-ray diffraction (XRD) and scanning electron microscopy (SEM) in conjunction with energy dispersive spectroscopy (EDS) and electron backscatter diffraction (EBSD). Further, the simulated thermal profile of the melt pool region as a function of process parameters via single scan track experiments was calculated using the finite element method (FEM). These data were used to explain the key microstructural features observed in the as-solidified microstructure of the LPBF alloy as a function of the processing parameters. The mechanical properties of the LPBF alloy were then assessed by hardness and tensile testing and then compared with a reference alloy produced by arc melting. The hardness of the LPBF as-built alloy was ∼20% higher than the reference alloy. To identify the factors affecting the increased hardness of the former, the influence of grain size and morphology, crystallographic texture, phase constituents (mainly austenite and martensite), and residual strain were investigated. The hardness of the reference alloy was affected mainly by the grain size and residual strain, but for the LPBF-built alloy, the relative volume fractions of austenite and martensite strongly influenced the hardness. Meanwhile, the tensile properties of the LPBF alloy, such as the yield stress, ultimate tensile stress, and ductility, were adversely affected by the internal defects present, such that high temperature homogenisation and hot isostatic pressing (HIP) post-process treatments were investigated to improve these properties. The homogenisation and HIP treatments increased both the tensile strength and ductility of the LPBF-built alloy. Homogenisation altered the grain morphology by promoting recrystallisation and grain growth, and this increased the tensile strength by ∼80%. The hardness, however, decreased due to a reduction in the volume fraction of HCP martensite in the FCC austenitic microstructure. HIP retained some of the columnar microstructure generated by the LPBF process, marginally increased the density, and increased the tensile strength by ∼65%. The improvement in tensile properties through these post-process treatments allowed for the measurement of LPBF alloy’s shape memory behaviour, whereby a tensile recovery strain of 2% was achieved for the HIP-treated alloy. Finally, the biocorrosion behaviour of the LPBF-processed and HIP-treated alloy was investigated, whereby the in vitro corrosion potential and current density of the alloy were determined to be -769 mV and 5.6 μA/cm2, respectively, indicating a reasonable corrosion rate for this material. Overall, this thesis enabled the first demonstration of the shape memory effect in an LPBF-built Fe-based alloy fabricated from homogenised powder, an alloy which also exhibits biodegradable properties.
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(2023)ThesisA comprehensive literature review of the conventional and advanced laser machining processes was carried out focusing on laser physics, efforts toward damage-free laser micromachining process, fabrication of micro-/nano-structural arrays using lasers, and material removal mechanisms in the laser ablation process. It has been revealed that laser ablation is a viable method for material processing. However, laser-induced thermal effects confine the applications of the laser machining process. The femtosecond laser has been found to be able to achieve nearly damage-free micromachining over a wide range of materials due to its extremely short pulse width and high fluence. Because of its increasing significance in many industrial applications, Ti6Al4V has attracted considerable interests, but fabricating Ti6Al4V samples remains a challenge without machining-induced damages. Reported studies have found that femtosecond laser micro-/nano-machining of Ti6Al4V samples have been confined to experimental demonstrations with little research contributed to the fundamental understanding of the mechanisms behind the process. An experimental study has been conducted to investigate the femtosecond laser micro-grooving process on Ti6Al4V samples. The effects of different micro-grooving performance measures, such as groove characteristics (depth and width) and heat affected zone size, with respect to the process parameters, have been presented. An increase in the laser fluence can increase the groove depth and width. The ablation depth will increase with an increase in the laser pulse repetition rate and a decrease in the scan speed, but the relevant effect on the groove width is not significant. A finite element model for the femtosecond laser ablation process has been developed, in which the two-temperature model is incorporated to represent the equilibration process of electron and lattice subsystems. Using the developed finite element model, a simulation study of the femtosecond laser ablation on Ti6Al4V material has been carried out to investigate the relevant physical phenomena. By increasing the laser fluence and/or decreasing the pulse width, the ablation depth can be increased. The femtosecond laser ablation of Ti6Al4V is a complex process and four thermal ablation mechanisms are discussed dependent on the different laser fluence ranges.
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(2022)ThesisDeep drawing is one of the most important sheet metal forming technologies for the production of numerous kinds of thin-walled metal components such as automobile body panels. However, in a deep drawing process, the high contact stresses between the die and workpiece surfaces often bring about scratching damage to the counterpart surfaces. Over the past many decades, manufacturers have found extreme difficulty in predicting the development of surface damages, such as the depth evolution of surface scratches, caused by the coupled effects of various factors in deep drawing processes. Therefore, this thesis aims to investigate the surface damage mechanisms in contact sliding and explore the application of artificial intelligence methods in the detection and prediction of surface damage. This thesis starts with an experimental investigation into the influence of tool and workpiece properties on the wear behaviour. Tribological experiments are carried out by concentrating on the differences in the friction coefficient, surface morphology and material wear. The impacts of tool materials, surface treatment processes and surface hardness are analysed, and the tribological properties of two advanced high-strength steel (AHSS) workpieces are discussed and compared. In addition, by conducting comparative experiments, this thesis also explores the role of wear debris in the surface damage evolution and reveals the influence of debris distribution and size variation on the tribological behaviours. To predict the evolution of surface scratching in sheet metals subjected to contact sliding, this thesis has successfully developed an intelligent prediction method based on fuzzy logic approach. Critical parameters are taken as the fuzzy variables to assess the contributions of individual variables to the surface damage. In addition, the quantum-behaved particle swarm optimisation algorithm is further developed by introducing adaptive control operators to refine the fuzzy prediction model. The verification results show that the optimised fuzzy model can predict the evolution of the surface scratching damage with smaller prediction error and error deviation. Afterwards, a lightweight convolutional neural network (CNN), called WearNet, is developed and trained for surface scratching detection in contact sliding. A customised convolutional block and a global average pooling layer are used in the WearNet, which enables the reduction of the network parameter number and the improvement of computational efficiency. The network response and decision mechanism are examined by using the t-distributed stochastic neighbour embedding function and the gradient-weighted class activation mapping technique, respectively. This thesis also compares the developed WearNet with other advanced CNN-based networks. The comparative tests demonstrate the advantages of WearNet in model size, computation efficiency as well as classification accuracy. Lastly, a hybrid data-driven approach is proposed to predict the remaining useful life (RUL) of forming tools. Ball-on-disc sliding contact will be used to mimic the contact conditions encountered in metal forming processes. The lightweight WearNet is retrained using transfer learning to detect the wear states of workpiece surfaces under new contact conditions, then the detection results and other relevant input parameters are incorporated into a regression model for RUL prediction, in which the bidirectional long short-term memory (BLSTM) network is employed. The prediction performance of the hybrid approach is evaluated and compared with other state-of-the-art methods to demonstrate its effectiveness and superiority in complicated RUL prediction problems.
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(2022)ThesisBody temperature is a primary health marker of metabolic health, circadian rhythm, physiological activities, infection, and disease. Accurate and real-time monitoring of skin temperature changes offers a new way for disease diagnosis, infection monitoring, fitness tracking, and athlete performance. Wearable temperature sensors for healthcare and fitness monitoring are required to meet the high resolution (±0.1-0.2 °C) of medical-grade thermometers. However, achieving this goal has proven challenging because wearable sensors have been found to respond strongly to mechanical deformation, primarily associated with skin-stretching and touch pressure. This thesis presents the progresses that I have made towards high-accuracy wearable temperature sensors by minimizing cross-interferences of wearable temperature sensors. To achieve this aim, two complementary strategies have been developed: (1) increasing the temperature sensitivity and (2) reducing the deformation-induced cross-interferences. These strategies have been applied to two different types of sensors: resistive and capacitive. In the first strategy, several approaches have been used to enhance the sensors’ sensitivity depending on their sensing mechanisms, as briefly summarized below • New methods for controlling the density and pattern of microcracks have been developed to improve the temperature sensitivity of a resistive sensor, which consists of a Poly(3,4-ethylenedioxythiophene) Polystyrene Sulfonate (PEDOT:PSS) sensing layer deposited on a thin Poly(dimethylsiloxane) (PDMS) substrate. The temperature sensitivity is found to be strongly influenced by the crack morphology in the PEDOT:PSS layer, which can be controlled by three fabrication parameters: pre-stretching strain, substrate roughness, and acid treatment time. The maximum temperature sensitivity achieved is 0.042 °C-1 when crack length is 185.2 μm and crack density is 22.84 mm-1. This is a 42-times improvement as compared to the reference sensor without microcracks. • New methods have been developed to improve the sensitivity of capacitive temperature sensors by rational design of dielectric separates. Since the sensitivity of capacitive temperature sensors depends on the coefficient of thermal expansion and the temperature coefficient of permittivity, it is found that by selecting the low-melting-temperature (65°C) thermoplastic polyurethane (TPU) with significant thermo-responsive dielectric properties around skin temperature (30 – 45 °C) as the dielectric layer, the temperature sensitivity can achieve 0.007 °C-1. Replacing the TPU dielectric layer with Polyvinyl Alcohol (PVA)-based organogel, the temperature sensitivity can be further improved to 0.093 °C-1. In the second strategy, the following new approaches to suppress strain and pressure interferences have been investigated. • Patterning the electrodes of capacitive sensors into kirigami cut to suppress the cross-interference of stretching. The electrodes of capacitive sensors consist of silver nanowires (AgNWs). The kirigami pattern is demonstrated to effectively reduce strain interference. Computational modeling of kirigami geometry’s effects on strain and temperature sensitivities of capacitive sensors reveals that tailoring kirigami design can reduce the strain cross-sensitivity by a factor of 3125, which enables the capacitive temperature sensors to achieve the resolution of 0.14 °C. • A pressure-insensitive supercapacitive sensor has been develop by synthesising PVA organogels consisting of Na+ and Cl- ions to be used as redox-active separator. The resulting temperature sensors show very low sensitivity to surface pressure. The results reveal that the pressure interference is reduced to 0.068% (with the external pressure of 10 kPa) and the wearable temperature sensor can achieve an accuracy of 0.2 °C, matching typical medical grade thermometers. In summary, this thesis presents several major advances in creating high-accuracy wearable temperature sensors that can match the detection limits of of medical-grade thermometers. The high-precision wearable sensors have been demonstrated to offer reliable monitoring of daily skin temperature rhythm when subjected to stretch exerted by body movements and the pressure from medical compression garment. The results show that sensors can perform skin temperature monitoring with a minor error of 0.1°C compared to infrared devices. The new insights and understandings of the strategies to suppress cross-sensitivities of wearable temperature sensors to in-plane stretch and out-of-plane pressure will generate cross-cutting benefits to the design of wearable health sensors.
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(2023)ThesisThe high cooling rates in metal additive manufacturing (AM) of high-entropy alloys (HEAs) can not only prohibit the formation of intermetallic compounds and detrimental elemental segregation but also facilitate microstructural refinement, thereby providing improved mechanical properties. However, there are still many challenges, including the presence of AM fabrication defects and residual stresses as well as anisotropic properties. Thus, further understanding is needed regarding applying post heat treatment to release residual stresses in as-built HEAs, and the techniques that can be employed to reduce or minimize the property anisotropy in as-built HEAs. In this thesis, a model Cantor alloy was fabricated and subject to a series of post heat treatment conditions. The results showed that annealing at a temperature lower than 900 °C gave rise to the formation of M23C6 carbides while recrystallization took place at temperatures over 900 °C. Interestingly, three distinct types of microstructures were exhibited at the annealing temperature of 900 °C. This is primarily attributable to the different thermal histories undergone through the LPBF process among these areas where heterogeneity in chemical elements and microstructure was revealed. The second group of samples were fabricated to develop a machine learning coupled microstructure mapping approach for tailoring mechanical property anisotropy. Three distinct types of microstructures were generated by varying the laser power and scanning speed, namely, herringbone, bimodal, and columnar microstructures. Epitaxial grain growth and side-branching in the melt pool center and overlapped regions are the main reasons responsible for the different microstructures. The underlying mechanisms were discussed in terms of effective grain size, heterogeneous microstructure, and the twinning induced plasticity (TWIP) effect. Subsequently, pre-deforamtion was applied before post heat treatment to study the influence of grain boundary engineering (GBE) on the recrystallization and resultant deformation behavior. Twinning-assisted recrystallization nucleation accelerated the formation of a nearly a fully recrystallized microstructure in the heavily deformed sample. As a result, the present strategy of GBE can provide further insight regarding the manipulation of the post heat treatment in as-built alloys particularly for those precipitation hardenable alloys where precipitation kinetics can be varied.
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(2023)ThesisWith the increase of environment awareness and sustainable energy demand, green and renewable energy derived from inexhaustible natural sources, such as solar and wind, has attracted much interest. Wind energy, a key participant in the green energy market, is embraced by many countries as a replacement of traditional energy. Wind power generation, for its robust system structure and economic efficiency achieved by mass production, has a lower cost in the ever-growing market than most energy production relying on other technical routes. Building wind power facilities also have certain benefits of land shielding and ecology protection, because they are mostly three-dimensional constructions that would have little impact on the local environment. Since wind turbines need to be installed in areas with unabated wind flow for maximising energy production, they are often placed on the land with high annual average wind speed and long valid wind time, such as plateaus, mountains, and coasts. However, that also means the turbines would operate in a harsher environment for a considerable length of time; thus, it is crucial to maintain their operation safety, and the study of turbine components through numerical simulation is essential to achieve a balance between cost and safety. In the past decades, the direct-drive wind turbine has been one of the most widely used wind turbines. However, in recent years, the problem of parts aging has surfaced for the earlier batch of direct-drive wind turbines – the bearing has been detected as one of the many vulnerable parts. In direct-drive wind turbine, the temperature in the shaft plays a significant role and should be considered as a design parameter. The operation of the rotating shaft, fixed axle, and bearing is governed by the presence of the lubrication and the proper alignment of the assembly, Nevertheless, as the bearing of the wind turbines fatigues due to long-term stress and strain, the friction begins to increase, and the temperature of the bearing during its operation tends to increase. The rotating shaft with a relatively high temperature would heat the lubricating fluid and result in the change of physical properties of the lubricant. This causes a positive feedback circle in which the friction between the shaft and bearing will keep increasing, and eventually the bearing breakdowns and resulting in the failure of the direct-drive wind turbine system. Hence, it is imperative that the temperature in the shaft is maintained as low as possible so as to prevent further degradation of the bearing. This thesis aims to study the heat increase in a bearing of a wind turbine by focusing primarily on the heat increase in the bearing structure. The consideration of fins to increase the surface area for heat removal is investigated in this thesis. Fin structure is a typical structure that could be attached to the original structure as minor protrusions to enhance the heat transfer from the rotating shaft to the environment. Understanding of the mechanism of the fin enhanced heat transfer in rotation structure will be obtained, and feasibility of using a fin structure to reduce the bearing temperature of the wind turbine as recorded by the maximum temperature being experienced in the assembly will be attained for design considerations. Moreover, optimisation study of fin spacing and height in the rotating motion is also carried out. Additional information on the pressure on the surface of the fins, as well as the shear stress and maximum deformation caused by the rotation of the fins are analysed.
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(2023)ThesisCarbon fibre all-composite tanks offer a promising opportunity for the energy-efficient transportation of liquid hydrogen (LH2) at cryogenic temperatures owing to their potential weight savings compared with existing metal tanks or composite overwrapped metal tanks. The weight-saving benefits of all-composite tanks have long been recognised for space applications, and the growing use of hydrogen as a fuel for aviation and other hard-to-decarbonise industries now creates an unprecedented need for safe and cost-effective cryogenic storage and transportation. However, existing carbon fibre reinforced polymer (CFRP) composites are prone to matrix cracking at cryogenic temperatures due to the high residual thermal stress and the reduced toughness of the polymer matrix. The matrix cracks extend through the thickness of the laminate, leading to leakage and reduced structural integrity of all-composite vessels. Thus, the suppression of matrix cracking in CFRPs at cryogenic temperatures remains a significant challenge. This research thesis aims to develop new scientific understanding of the effects of cryogenic temperature on the matrix cracking phenomenon in CFRPs and new technologies to address this challenge. This thesis presents a novel nano-toughening technique that uses CuO nanorods to improve the fracture resistance of epoxy matrix at cryogenic temperatures. The technique has been shown to increase the fracture energy of the matrix by over 160%, which is significantly higher than the target level required to suppress matrix cracking in CFRPs at cryogenic temperatures. Additionally, a new mechanistic model has been developed to quantify the toughening performance of nanomaterials. This model predicts the size dependence of the nano-toughening effect, suggesting a potential optimising analysis of the particle size for nano-toughening and contributing to filling a critical gap in the multiscale modelling of CFRP structures. Moreover, a computationally efficient analysis of through-thickness matrix cracking in composite laminates has been developed, offering new insights into the suppression of ply cracking at cryogenic temperatures. This analysis quantitatively demonstrates the potential of using thin-ply technologies in augmenting the nano-toughening of the matrix to suppress ply cracking at cryogenic temperatures. The key contributions of this research include novel nano-toughening techniques, fundamental insights, and mechanistic models for quantifying the effectiveness of nano-toughening and thin-ply design in suppressing matrix cracking in CFRPs at cryogenic temperatures. The new knowledge and the nano-toughening strategies developed in this research mark major advances in the development of multiscale fibre composites and have the potential to achieve significant potential weight-saving benefits for cryogenic storage applications.
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(2022)ThesisStructural composite supercapacitors have been investigated as a promising weight-saving technology for electrical vehicles (EV), electric aircraft, and mobile robots. The main objective is to maintain excellent (ideally the same as the existing structure of the same weight) mechanical properties while storing adequate electrical energy. This thesis aims to develop structural composite supercapacitors with both outstanding mechanical properties and electrical energy storage performance. The main findings and contributions of my research presented in this thesis are: (1) A novel structural electrolyte made of carbon nanofibers, epoxy, and ionic liquid (IL) that offers ionic conduction properties as well as mechanical stiffness and rigidity. The incorporation of carbon nanofibres (CNFs) into epoxy-ionic liquid-based electrolytes creates pathways for ion migration, resulting in a 40-fold boost in the ionic conductivity for the resulting electrolytes. The tensile strength and Young’s modulus of the resulting electrolytes exhibit only a slight drop. Therefore, the new solid epoxy-based electrolyte offers great potential for use in energy storage structures, for example structural composite supercapacitors and/or batteries; (2) A structural composite supercapacitor consisting of the high-performance electrodes made by grafting manganese dioxide onto carbon fibre fabrics and the epoxy-ionic liquid electrolyte. Mixing 40 wt.% of IL and 60 wt.% of epoxy (denoted as the 40IL electrolyte) yields the best combination of ionic conductivity and tensile properties. A structural composite supercapacitor has been fabricated using a 40IL electrolyte with high-capacity manganese dioxide coated carbon fibre electrodes. The resulting composite supercapacitors demonstrate excellent mechanical and electrochemical performance compared to the literature data. (3) A novel silane treatment method to enhance the ionic conduction between the electrolyte and the electrodes. The results show that the silane treatment enables the composite supercapacitors to achieve a 3-fold increase in areal capacitance without deterioration of the mechanical properties. Finally, potential opportunities for future studies of the structural composite supercapacitors are discussed.