Mechanical Engineering - Theses
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ItemComputational wake acoustics : effects of freestream disturbances on wake structure and sound emission(University of Melbourne, 2010)
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ItemAnalysis of numerical error on unstructured meshes: with applications to fluid dynamics(University of Melbourne, 2010)
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ItemTurbulent plumes in confined spaces( 2019)Studies pertaining to turbulent plumes in confined spaces are of utmost interest due to its relevance in practical flows that are associated with, but not restricted to, the propagation of smoke and hot gases generated by fires in buildings, road and railway tunnels, etc. In this dissertation, direct numerical simulations (DNS) of the governing equations are carried out to analyze such flows with the focus on (i) free turbulent line plumes, and (ii) wall attached turbulent line plumes, in confined spaces. In all cases, the computation domain is rectangular with no-slip and adiabatic boundary conditions at the top, bottom, and lateral side walls. In free turbulent line plume simulations, the plume originates from a line heat source of length, L, located at the centre of the bottom wall and rises until it impinges on the top wall and eventually spreading out laterally thereby producing a buoyant fluid layer at the top wall. Since the region is confined, the continuous heat source forces the top layer to move downwards, until it reaches the bottom wall, when the flow is said to be at the asymptotic state (Baines and Turner 1969). DNS data at three Reynolds numbers (ReH), 1800, 3600 and 7200, based on box height H and the buoyant velocity scale, F_1/3 0 , where F_0 is buoyancy flux per unit length, are presented for plume lengths, L/H = 1, 2 and 4 and box aspect ratio, R/H = 1. Here, R is the box half-width. Following the initial transient dynamics, a flapping motion of the plume is observed, where the plume oscillates around the centre plane of the box. The DNS results reveal that the long-term behavior of the flow consists of a meandering, flapping plume with a counter-rotating vortex pair on either side of the plume. Additionally, the plume volume, momentum, and buoyancy fluxes obtained from the simulations are compared to the theoretical models proposed by Baines and Turner (1969) and Barnett (1991). Further, simulations of turbulent line plumes are carried out at increased box aspect ratios R/H = 1, 2, 4, 8 and 16, to study the horizontal outflow of the buoyant fluid layer after the plume impinges on the top wall. Following the axisymmetric plume model of Kaye and Hunt (2007), a theoretical model to compute the horizontal outflow properties is developed for turbulent line plumes. In the case of wall attached thermal plumes, the plume originates from a local line heat source placed at the bottom left corner of the box. The plume develops along the vertical side wall while remaining attached to it before spreading across the top wall forming a buoyant fluid layer and eventually moving downwards and filling the whole box. The simulations are carried out at ReH = 14530 and L/H = 0.5, and a parametric study is conducted for boxes of aspect ratios R/H = 1 and 2. Furthermore, the original filling box model of Baines and Turner Baines and Turner (1969) is modified to incorporate the wall shear stress and are compared against the results obtained from the DNS. A reasonable agreement is observed for the volume and momentum fluxes in the quiescent uniform environment and for the time-dependent buoyancy profiles calculated further away from the plume. Finally, the entrainment processes in both free and wall attached line plumes are assessed, using the DNS data. Both cases show similar contributions to entrainment due to net buoyancy. However, a deficit in the entrainment coefficient is observed for wall plumes due to the effect of the wall, which in turn suppressed the turbulent kinetic energy production.
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ItemThe Application of Surface Effect Ships to Freight Transport( 2019)The research project was conducted in two phases. The first phase, a policy-based investigation of the application of a suitable technology to commercial freight transport in Southeast Asia, concluded that the candidate technology that best met the sought objectives was a hybrid catamaran hovercraft configuration, or Surface Effect Ship (SES). In the second phase, a specific physical issue associated with the Surface Effect Ship (SES) reported in the available literature was investigated, specifically, the control of water-wave induced ship motions caused by air pressure resonance in the SES air cushion. Air pressure resonance was investigated experimentally using a custom designed and fabricated air chamber apparatus and associated numerical simulation validation studies. The novel phenomenon of increase in time-wise mean air cushion pressure at higher frequency oscillations of an air cushion volume was predicted using numerical simulation. Experimental observations were in agreement with the predicted behaviour. It was concluded that some dynamic characteristics of the SES that could inhibit the wider use of this type of craft were able to be replicated in laboratory apparatus and predicted with a numerical model, thereby facilitating future design tools for practical SESs.
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ItemMicrostructures of TiAl additively manufactured by EBM and LMD( 2019)Titanium aluminide (mainly TiAl) based intermetallic alloys have superior mechanical properties up to 800 C and are much lighter than the currently used nickel superalloys. They have been developed for turbine engine applications in the aerospace, automobile and energy industries. Because of the inherent brittleness of TiAl, conventional manufacturing requires specially designed post processing, which is not cost and time effective. Additive manufacturing (AM) is considered as an alternative production technique, that can replace the conventional process. AM facilitates printing of complex TiAl components directly from alloy powders. Solid-state transformations (SST) associated with the unique layer-by-layer manufacturing and in situ cyclic heating in AM offer the potential to tailor the microstructure of components, creating opportunity for improving mechanical properties. The aim of this study is to systematically investigate the microstructural evolution at different processing conditions and the effect of in situ heat treatment on different solid-state transformations of gamma-TiAl alloy during additive manufacturing by Electron Beam Melting (EBM) and Laser Engineered Net Shaping (LENS). Nearly fully dense Ti-48Al-2Cr-2Nb samples with minimum defects were printed by EBM and LENS, at high, medium and low energy input conditions. Detailed microstructural characterisation along the build direction of samples printed by EBM at a high energy density (ED) of 6 J/mm2 was conducted. X-Ray Diffraction (XRD) studies and analytical electron microscopic analysis at different locations along the build direction of the sample revealed microstructural instabilities such as discontinuous coarsening (DC) and alpha2 decomposition, caused by the in situ cyclic heating with the peak temperature of each cycle approaching close to the melting point of TiAl and gradually reducing in intensity. Discontinuous coarsening with associated grain boundary migration was identified to be the dominant solid-state transformation taking place in alpha2+gamma primary lamellar structure (PLS), resulting in high coherence lamellar interphases in the TiAl alloy produced by both EBM and LENS. It was shown that DC replaces fine PLS by coarsened lamellae with reduced colony size, along with significant change in chemical composition and volume fraction of phases. Reduction in interphase energy achieved by the coarsening of lamellae, with an average coarsening ratio around 18.6, was identified as a driving force for DC. High chemical free energy in PLS mainly caused by supersaturated alpha2 phase with a non-equilibrium phase fraction of 26%, can be considered as another factor inducing DC. Ascertaining this assumption, alpha2 phase fraction approaches its equilibrium composition after 11 cycles of in-situ heating. Colony size also considerably reduced as a consequence of DC reaction. beta phase formation, which is identified as another side outcome of these driving forces, shows a variation in phase fraction with build temperature, from 3.5% at 950 C to 8% at 1050 C. DC, along with beta phase formation greatly influences microstructural morphology and mechanical properties of TiAl. A similar trend was observed in LENS fabricated samples. The major variation was the absence of beta formation in LENS, which is attributed to the lack of pre-heating during LENS. Alloy modifications such as addition of 0.5 Si (at.%) as experimented in this study, result in precipitate pinning at interphase, potentially reducing excessive coarsening. This study summarises the process of DC and beta phase formation in TiAl alloys during EBM and LENS processes and discusses the strategies to regulate DC and beta formation through AM of TiAl and utilize the intrinsic solid-state transformations in AM for controlling the microstructure to achieve application-specific material properties.
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ItemInvestigation of Direct Combustion Noise in Turbulent Premixed Jet Flames Using Direct Numerical Simulations( 2019)Direct combustion noise plays a key role in initiating thermoacoustic instability in lean, premixed gas turbines. Moreover, many combustion devices produce a high level of noise while being subjected to increasingly stringent noise regulations. Therefore, achieving a better understanding of sound generation by premixed flames is crucial for designing safer and quieter combustion devices. With the advancement in High-Performance Computing (HPC), high fidelity simulations such as Direct Numerical Simulation (DNS) have received increasing attention as a means to improve our fundamental understanding of turbulent flames. This thesis aims to study the mechanism of sound generation in turbulent premixed jet flames using DNS and state-of-the-art post-processing methods. A DNS dataset featuring sound generation by turbulent premixed flames with simple chemistry is first analysed. Using Spectral Proper Orthogonal Decomposition (SPOD), two types of flame coherent structures responsible for combustion noise are identified. The first type arises in the jet's shear layer, originating from the Kelvin-Helmholtz (K-H) instability and is indirectly producing sound through the deformation of the flame front. The second type is found near the jet centreline and is linked to small, non-linear flame dynamics. Even though their energy content is lower than that of K-H structures, they are an important feature to explain the broadband nature of combustion noise. Then, a framework to identify the location and topology of annihilation events, and to study their generated sound, is presented. This study reveals that different topologies are similar in terms of the generated sound. In addition, a spectral analysis shows that flame annihilation is the physical mechanism by which air-fuel ratio affects the radiated sound amplitude at high frequencies. Finally, DNS datasets of turbulent premixed jet flames with a semi-global and a skeletal chemical mechanism are produced and analysed, to investigate the impact of chemical modelling on combustion noise. Large differences between the two cases are observed in the OASPL value and on the high-frequency side of the acoustic spectrum. Analysis of the acoustic source term resulting from the heat release rate fluctuations demonstrates that the post-flame region has minimal contribution in terms of sound generation. Furthermore, the most exothermic reaction in each mechanism is by far the dominant source of heat release rate fluctuations, and hence sound generation. It is observed that the OASPL discrepancy between the two chemical mechanisms arises from the differences in the peak amplitude of the heat release rate. Then, a modelling approach shows that the acoustic spectrum in the high frequency range results from highly curved flamelets and can be estimated from the flame curvature statistics. This approach demonstrates that the high-frequency acoustic discrepancy arises from a more wrinkled flame in the case featuring the more complex chemistry. Overall, to accurately predict the sound generated by turbulent premixed flames, a reduced chemical mechanism needs to correctly capture the flame response to turbulence.
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ItemOptimal Performance of a Wind Farm with and without Battery Energy Storage( 2019)The increasing penetration of wind in power systems can result in various challenges for system security and reliability, as well as wind farm investability. These challenges require further research to develop an understanding of the operation of a wind farm with and without the use of complementary technologies, such as energy storage, particularly, when the wind turbines have Frequency Control Ancillary Services (FCAS) capability. This thesis therefore first presents a hierarchical, data-driven, reduced order model of a wind farm, which accounts for the correlation between wind turbines' power output. It finds that the cross-correlation between each turbines' power generation is dependent on the frequency of the wind disturbance and the distance between wind turbines, so that the cross-correlation can be related to the convective length scale in the incoming wind. An investigation of the number of wind turbines required to simulate the wind farm's power generation then indicates that there is an inherent trade-off between model accuracy and complexity. An optimisation model is then developed to investigate the optimal performance of the wind farm participating in the energy and FCAS markets with and without a battery storage system. This requires modelling of the battery costs along with the revenues in the energy and FCAS markets, as well as a simplified version of the Causer Pays Method used in the Australian National Electricity Market (NEM). The optimal performance of the Mt Mercer wind farm, located in Victoria, Australia, is then examined. It is found that the wind farm participation in the FCAS markets can improve its financial performance. This analysis shows that the wind farm mainly tends to participate in the FCAS lower regulation market due to the higher prices of this service and no requirement for curtailment before starting a dispatch interval (precurtailment). An investigation of the impact of wind generation forecast accuracy on the system performance also finds that with a better forecasting system, the total performance of the wind farm improves. Finally, the optimal integration of a lithium-ion battery into a wind farm is examined. Assessments find that the battery is not investable without substantial subsidies when the battery participates only in the energy market. However, it is also found that participation in the FCAS markets can significantly improve the battery's investability, but its financial viability is highly sensitive to FCAS prices. In addition, it is found that the introduction of wind farm frequency control capability reduces the optimal value and capacity of battery storage. Investigation of different wind generation forecasting systems identifies that the improvement of forecast accuracy also reduces the optimal battery value and capacity, as there are fewer opportunities for the battery to reduce the wind farm regulation payments.
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ItemDynamic clamp analysis of ion channel function( 2019)Ion channels regulate neuronal excitability by controlling the ion flow through the neuronal membrane. Therefore, neuronal ion channel dysfunction can directly impact the function of neurons in the brain and lead to numerous disorders such as epilepsy and autism. As such, characterizing ion channels can provide valuable insights into these disorders and facilitate treatment. Current ion channel characterization methods predominantly use the voltage clamp (VC) approach which typically involves multiple time-consuming step protocols to capture ion channel dynamics corresponding to different membrane voltages. As such, these approaches neither recapitulate the natural behavior of the ion channel in the brain nor provide the means to directly investigate the relationship between these dynamics and neuronal excitability. This thesis addresses the limitations in current VC methods and implements the dynamic clamp (DC) approach to characterize ion channels. DC represents a real-time closed-loop system that incorporates computational models of neuronal systems with real ion channels. It provides biologically more natural recordings and is capable of directly determining the impact of ion channel dynamics on neuronal excitability. I investigate two applications to characterize ion channels using DC in this thesis. First, ion channel kinetics are mathematically modelled based on DC recordings. Second, the ion channels are functionally characterized using features extracted from DC recordings. My approach to mathematically model fast kinetics of ion channels requires only DC recordings of short time durations. It utilizes efficient global optimization algorithms to estimate the model that best matches the recorded DC data. To further enhance the performance of the approach, I have identified an optimal DC stimulation strategy, and extended optimization method is proposed when recorded DC data is noisy. This approach was more accurate than two existing VC based methods. The model derived from this approach could also predict firing patterns of experimental data with high accuracy. The DC-based approach was next extended to model slow kinetics together with fast kinetics. This involved a new DC stimulation strategy to record DC data and a three-step post-hoc optimization to estimate model parameters. The extended approach could estimate models that accurately predict AP firing patterns that occur during longer/sustained stimulation and could recreate the AP firing seen in experimental data. This thesis also proposes a workflow to functionally characterize ion channel variants such as mutations using DC data. The workflow creates a two-dimensional map of the variants where their positionings correspond to their functional characteristics. Multiple variants of two major neuronal sodium channels, Nav1.1 and Nav1.2, were investigated and their two-dimensional mappings were determined. The results suggested a clear functional separation between variants, not only corroborating the findings of previous conventional functional studies but also providing new insights into variant functionality. The two applications of the DC presented in this thesis demonstrate the potential of DC for ion channel characterization. Collectively, they provide crucial information on ion channel dynamics that will assist the development of effective treatments for neurological disorders involving mutant channels and will enable assessing the direct impact of pharmacological interventions on neuronal excitability.
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ItemComputational coronary arterial fluid dynamics: from stenotic to rough-wall flow( 2018)Coronary heart disease (CAD) is a leading cause of mortality. CAD is usually caused by the built-up plaque, clinically known as stenosis, that narrows the arteries and hence limits blood flow to the heart. It has been found the development of stenosis is closely associate with local haemodynamics, which can be altered by the changes in arterial shape, such as plaque formation or stenting. The objective of this study is to better understand the post-narrowing and in-stent haemodynamic environments to gain insights into the flow physics associated with the stenosis development. Computational fluid dynamics (CFD) technique is used to firstly simulate pulsatile blood flow in full-scale straight and curved stenotic coronary arteries under a physiological inlet velocity waveform. Flow-pressure relation in simplified multiple sequential stenotic flow is then discussed. Lastly, investigations are carried out in simplified smooth models superposed with the egg carton type surface to mimic in-stent coronary arterial flow. The findings of flow characteristics can contribute towards the future prediction and diagnosis of coronary-related complications. Straight and curved arterial flows with three different degrees of stenosis are studied in both Newtonian and non-Newtonian fluids. The time-dependent inertial momentum is found to contribute to reverse flow development in the proximity of post-stenotic region and negatively correlate with the reverse flow size. Flow velocity and WSS in Newtonian and non-Newtonian fluids exhibit larger difference in response to the increase of stenosis degree. In the presence of curvature, low WSS is found to concentrate at the inner wall after the stenosis collocated with the reverse flow region. With the progressive stenosis severity, the secondary flow morphology distal to the stenosis also evolves into double-paired vortices structure and promotes the growth of reverse flow size. For non-Newtonian flow, smaller reverse flow bubble distal to the stenosis are observed and the difference in Newtonian and non-Newtonian fluids is more profound in higher degree stenosis cases. Overall, the haemodynamic behaviours downstream of stenosis are affected simultaneously by stenosis degree, the instant inertial momentum and secondary flow morphology if curvature presented. The relative location of low WSS (and reverse flow) becomes the potential trigger for the growth of stenosis. The correlation between the haemodynamics in post-stenotic region and potential clinical complications implies the necessity to determine the severity of stenosis. Virtual Fractional Flow Reserve (vFFR), a computational technique calculating pressure drop across stenosis, is considered as an adjunct application to invasive determined FFR, a current standard of clinical practice. Flow-pressure relation across multiple stenoses are analysed using both experimental and numerical approaches. Linear correlation between pressure drop and flow rate irrespective the number of stenosis is found. Negligible difference between steady and pulsatile flows is also observed. The conclusion may improve the clinical applicability of vFFR. In the in-stent coronary arterial flow, both increasing the roughness height and decreasing spacing reduces the shear rates (due to the increased proportion of pressure drag) near the trough of roughness, and hence encourage reverse flow formation. In non-Newtonian fluids, elevated relative viscosities are pronounced near the trough of the roughness while low viscosities are found around the peak of the roughness. This trend becomes more profound by increasing roughness height or decreasing wavelength. As a result, reverse flow is less likely to occur near the trough of roughness in non-Newtonian fluid. By comparing time-averaged velocity and WSS using different blood rheology models, the results show consistency in both qualitative and quantitative perspectives and suggest an interchangeable aspect of rheology models in simulations.
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ItemCompressible turbulent wakes in constant area pressure gradients: simulation and modelling( 2019)Improving turbomachinery efficiency today is directly related to quantifying and reducing the various sources of losses. Of these, the wake mixing loss, resulting from wakes produced by the blade trailing edge, is of prime interest. These wakes, when developing spatially through the periodic constant area passage in the stator-rotor row, are exposed to pressure gradients which can impact the wake evolution and consequently the wake mixing loss. Since a study on the effect of the pressure gradient in isolation is not possible in an actual turbomachine stage, a canonical case study of a statistically two-dimensional turbulent wake is proposed to understand the underlying flow physics arising from the presence of pressure gradients. The usual canonical setup of subjecting a wake to pressure gradients is achieved by changing the passage area, i.e. if the downstream area decreases (increases) a favourable pressure gradient or FPG (adverse pressure gradient or APG) exists. However, as turbomachinery wakes develop in a constant area passage in the presence of pressure gradients, imposition of pressure gradients in the proposed canonical setup is through a ramped body force term to the momentum and total energy equations while the wake is allowed to develop spatially in a region of fixed width. Employing compressible high-fidelity simulations, the resultant mean velocity statistics, wake width, energy budgets and entropy generation rates are scrutinised to assess the effect of the pressure gradients, and where possible, the similarities and differences to the conventional case of variable area pressure gradients are discussed. The results show that the effect of a constant area pressure gradient on flow statistics is non-trivial, resulting from significant density changes. The pressure gradients also have an effect on the different energy budgets, which produces a gain for FPG and loss for APG in the mean kinetic energy. Consequently, the entropy generation rate, which is indirectly related to the wake mixing loss, diminishes and augments for the FPG and APG respectively, compared to the zero pressure gradient (ZPG). Additionally, the effect of different passage heights ($H$) relative to the wake half-width ($\delta$) is also studied where it was observed that $\delta$ and hence the spreading depends primarily on the wake-wake interaction for small H and pressure gradients for larger H. While the understanding developed through the data generated by the high-fidelity simulations is invaluable, prediction of these flows are still a challenge with the existing low-fidelity tools such as URANS, which are still used for designing turbomachines in the industry. The main issue with URANS is the poor underlying turbulence closure: the Boussinesq approximation. In recent years, turbulence modelling development has received a boost through the assimilation of machine-learning methods and the increasing availability of high-fidelity datasets. Thus, in the next phase of the project, the prediction of the wake flow using URANS is improved by developing a new turbulence closure using the high-fidelity data and a symbolic machine-learning algorithm: the Gene-Expression Programming. The closure is obtained as part of a novel framework developed specifically for flows exhibiting organised unsteadiness, such as the vortex shedding in the wake. The framework, titled the data-driven stochastic closure simulation (DSCS) consists of three parts. First, using triple decomposition, the high-fidelity data is split into organised motion and stochastic turbulence. A data-driven machine-learning approach is then used to develop a closure only for the stochastic part of turbulence. Finally, unsteady calculations are conducted, which resolve the organised structures and model the unresolved turbulence using the developed bespoke turbulence closure. A demonstration for DSCS is presented using the canonical dataset of the ZPG wake generated previously. The obtained closure suggests lowered turbulent diffusion from the closure, which upon implementation shows a significant improvement in the mean velocity and Reynold stress profiles compared with the standard turbulence closure. The developed closure is then evaluated on 6 different case studies: ZPG wakes at different Reynolds numbers and wakes in the presence of pressure gradients, where the new closure consistently outperforms the standard closure in all the cases, which means the closure is not only re-usable but robust to changing flow conditions. Thus, the results and observations on the turbulent wake evolution in the presence of constant area pressure gradients, both from a simulative and modelling standpoint, can serve as a guide in the design of turbomachinery, i.e. in predicting and minimising the loss produced by wake mixing.