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Service network design for emerging modes in air transport: autonomous airport inter-terminal bus shuttle and air metro(2022) Zhao, RunqingThesisEmerging modes of air transport such as autonomous airport shuttle and air taxi are potentially efficient alternatives to current transport practices such as bus and train. This thesis examines bus shuttle service within an airport and air metro as two examples of network design. Within an airport, the bus shuttle serves passengers between the terminals, train stations, parking lots, hotels, and shopping areas. Air metro is a type of pre-planned service in urban air mobility that accommodates passengers for intra- or inter-city trips. The problems are to optimise the service, and the outputs including the optimal fleet size, dispatch pattern and schedule. Based on the proposed time-space networks, the service network design problems are formulated as mixed integer linear programs. The heterogeneous multi-type bus fleet case and stochastic demand case are extended for the airport shuttle case, while a rolling horizon optimisation is adopted for the air metro case. In the autonomous airport inter-terminal bus shuttle case, a Monte Carlo simulation-based approach is proposed to solve the case with demand stochasticity, which is then further embedded into an "effective" passenger demand framework. The "effective" demand is the summation of mean demand value and a safety margin. By comparing the proposed airport shuttle service to the current one, it is found that the proposed service can save approximately 27% of the total system cost. The results for stochastic problem suggest estimating the safety margin to be 0.3675 times of the standard deviation brings the best performance. For the second case, the service network design is extended with a pilot scheduling layer and simulation is undertaken to compare the autonomous (pilot-less) and piloted service design. The results suggest that an autonomous air metro service would be preferable if the price of an autonomous aircraft is less than 1.6 times the price of a human-driven one. The results for rolling horizon optimisation suggest to confirm the actual demand at least 45 minutes prior to departure. Based on data from the Sydney (Australia) region, the thesis provides information directly relevant for the service network design of emerging modes of air transport in the city.
(2021) Alohali, Ruaa Tawfiq AThesisThe Arabian basin was subject to several tectonic events, including Lower Cambrian Najd rifting, the Carboniferous Hercynian Orogeny, Triassic Zagros rifting, and the Early/Cretaceous and Late/Tertiary Alpine orogenic events. These events reactivated Precambrian basement structures and affected the structural configuration of the overlying Paleozoic cover succession. In addition to a 2D seismic array and several drill well logs, a newly acquired, processed 3D seismic image of the subsurface in part of the basin covering an area of approximately 1051 km2 has been provided to improve the understanding of the regional tectonic evolution associated with these deformation events. In this study, a manual interpretation is presented of six main horizons from the Late Ordovician to the Middle Triassic. Faults and folds were also mapped to further constrain the stratigraphic and structural framework. Collectively, this data is used to build a geological model of the region and develop a timeline of geological events. Results show that a lower Paleozoic sedimentary succession between the Late Silurian to the Early Permian was subject to localised tilting, uplift, and erosion during the Carboniferous Hercynian Orogeny, forming a regional unconformity. Subsequent deposition occurred from the Paleozoic to the Mesozoic, producing a relatively thick, conformable, upper succession. The juxtaposition of the Silurian rocks and Permian formations allows a direct fluid flow between the two intervals. Seismic analysis also indicated two major fault generations. A younger NNW-striking fault set with a component of reverse, east-side-up displacement affected the Lower Triassic succession and is most likely related to the Cretaceous and Tertiary Alpine Events that reactivated the Najd fault system. These fault structures allow vertical migration that could act as conduits to form structural traps. Manual mapping of fault structures in the study area required significant time and effort. To simplify and accelerate the manual faults interpretation in the study area, a fault segmentation method was developed using a Convolutional Neural Network. This method was implemented using the 3D seismic data acquired from the Arabian Basin. The network was trained, validated, and tested with samples that included a seismic cube and fault images that were labelled manually corresponding to the seismic cube. The model successfully identified faults with an accuracy of 96% and an error rate of 0.12 on the training dataset. To achieve a more robust model, the prediction results were further enhanced using postprocessing by linking discontinued segments of the same fault and thus, reducing the number of detected faults. This method improved the accuracy of the prediction results of the proposed model using the test dataset by 77.5%. Additionally, an efficient framework was introduced to correlate the predictions and the ground truth by measuring their average distance value. This technique was also applied to the F3 Netherlands survey, which showed promising results in another region with complex fault geometries. As a result of the automated technique developed here, fault detection and diagnosis were achieved efficiently with structures similar to the trained dataset and has a huge potential in improving exploration targets that are structurally controlled by faults.
(2018) Jin, XiaohengThesisGraphene oxide is a single layer of carbon atoms with decorated oxygen functional groups. Stacked monolayers in the laminate form create an interlayer space of sub-nanometer scale with oxygenated functional group to attract water molecules, and graphitic domains to allow frictionless flow of water molecules and achieve maximum efficiency of water transportation. The research reported herein is aimed to understand and explore characteristics of the diffusion-dependent mass transportation across an array of cascading nanochannels confined by graphene oxide laminates at sub-nanometer level. This dissertation has 6 Chapters. Chapter 1 is the introduction and Chapter 2 reports the recent progress in graphene oxide for mass transport application. Chapter 3 discusses efforts of engineering the channel confinement, which is represented by the interlayer spacing in between graphene oxide laminates. By adjusting the fundamental factors of graphene oxide suspension, the interlayer spacing can be controlled at 0.7 to 0.8 nm. Based on the engineered interlayer spacing, separation of vaporous mixture by graphene oxide membrane is studied in Chapter 4. Numerical description of nanochannels enclosed by graphene oxide monolayers is determined by time lag analysis. The feature of ethanol vapor transportation with the support of water vapor is revealed, showing accelerated transportation of non-permeable matter, which enriches the existing knowledge. A geometrical model of graphene oxide membrane for vapor separation was established and analyzed. In Chapter 5, adsorption and intercalated of molecules and solvated ions are studied and proved as a size-dependent enlargement of graphene oxide nanochannels. Carriers such as water and ethanol are used for transporting ions and molecules into graphene oxide slits. Taking the adsorption into consideration, permeation of vaporous substances through adsorbed graphene oxide membrane is investigated in Chapter 6. The research initiates researching crystallization of adsorbed matters in graphene oxide interlayer structure. A simplified model was directed to predict the water vapor permeation behavior of intercalated graphene oxide membrane. Such efforts not only lead to a better understating of graphene oxide membrane for gas separation but also give a hint of spatially efficient matter transport in achieving excellent electrochemical devices with graphene oxide components.
Influence of dynamic topography to deposition and the evolution of the Australian landscape through numerical modelling(2023) Baker, MackenzieThesisThe Australian continent provides an excellent canvas to study the impacts of dynamic topography due to the flat nature of the continent. Previous work into Australian studies of biota have mainly focused on climate being the main contributor to biotic distribution and evolution. This study will investigate the influence dynamic topography contributes to this evolution of the landscape and biota through implementing three landscape evolution models (AuM1, AuM2 and AuM3), created using Badlands software. These models will establish the impacts dynamic topography has to the evolution of the Australian landscape and biota over the last 40 million years. All three models possessed the same inputs of elevation, precipitation, sea-level and erodibility regions, however differed in their dynamic topography input. The first of these models (AuM1) involves a best fit model of the Australian continent with a dynamic topography input that was an accurate depiction of the dynamic topography within the Australian continent. The second model acted as a control model, with the subtraction of a dynamic topography input. Lastly the third model (AuM3) involved the input of a varying dynamic topography inconsistent with AuM1. The comparison of these models exhibits that changes to the Australian landscape have taken place. The main finding was the deposition rate of sediment changes between AuM1 and AuM2, where AuM2 possess lower rates of deposition in the northern region. With these lower rates of sediment deposition, there was an accompanying narrower confluence angle of river channels in the northeastern region, indicating a more arid environment for those simulations without dynamic topography (AuM2). With these new findings through the numerical modelling of the Australian continent new constraints to the evolution of the Australian landscape and biota have been gained.
Development of Innovative Ultra-Filtration Fibre Technologies for Waste-Water Treatment in Membrane Bio-Reactors (MBR)(2024) James, LeoThesisThe design of advanced hollow fibre ultrafiltration (UF) membrane technologies for use in wastewater treatment facilities has culminated from a combination of improvements in plant operation and optimising feed water interactions. With global demands in water quality increasing, this has placed increased pressure on MBR factories to develop high strength, anti-fouling fibre modules with improved permeabilities. The fabrication of such membranes, however, is restricted by the trade-off that exists between mechanical strength and filtration properties, as well as scalability concerns that arise when transitioning from laboratory trials to field testing of prototypes. This places increased importance on the need to establish a reliable formulation plan that addresses these trade-off limitations, in addition to furthering our understanding of membrane-foulant interactions. Modifications of polymer concentration will offer deeper insight into the role that polymer phase materials have on membrane formation and high strength performance. Further variations in pore-former content will provide a route towards optimising membrane surface porosity, translating into potential improvements in fibre permeability and anti-fouling propensity. Three different experimental approaches were implemented to assess the impact of fibre composition on membrane performance. These include (1) modifying the total concentration of poly(vinylidene fluoride) (PVDF) material, (2) tailoring the composition of PVDF material with distinct molecular weights, and (3) adjusting the proportion of poly(vinyl pyrrolidone) (PVP) and poly(ethylene glycol) (PEG) pore-forming additives. Microscopy techniques were used to document any structural changes across each formulation series, whilst porometer and tensile testing instruments were utilised to provide insight into membrane permeability and strength, respectively. Membranes formulated with elevated PVDF concentrations were found to exhibit improvements in mechanical integrity at the expense of reduced clean water fluxes. This was overcome by optimizing the incorporated PVDF molecular weight, which allowed for incremental boosts in toughness without adversely affecting permeability. Testing also revealed that fibres formed with higher concentrations of pore-forming agents, most notably PEG material, were found to be more permeable. Feedwater filtration cycling was implemented to provide insight into the relative fouling behaviour of membranes formed via these three approaches. Changes in resistance were found to be primarily dictated by membrane pore size, with intermediary pore size distributions being desirable targets for balancing out the effects of short- and long-term filtration. By tracing these trends in fouling propensity back to underlying fibre compositions, this study reinforces the importance of adjusting polymer formulations for achieving high strength, anti-fouling membranes. This study also acknowledges the limitations that exist in comparing laboratory-scale filtration data of fibre samples to prototype field testing of full-scale modules. Addressing these drawbacks through an analysis of feedwater conditions used in research and industry allows us to reach an informed decision on selecting appropriate formulations in the design of innovative membrane technologies.