Mechanical Engineering

Aortic dissection is one of the catastrophic cardiovascular diseases that have high mortality. It refers to an intimal tear in the aortic wall that initiates the formation of a false lumen due to blood flow between the layers of the vessel wall. Decisions about medical management or surgical intervention for long-term dissections are complex and still evolving, depending largely on the individual patient’s condition. In addition to conventional clinical images, the incorporation of more comprehensive physiological data would benefit clinicians in the decision-making process. Recent advancements in four-dimensional phase-contrast magnetic resonance imaging and computational fluid dynamics are promising in providing detailed data on haemodynamic parameters in cardiovascular diseases, including those that are challenging to predict or measure safely in clinical settings. In this work, the robustness and precision of a respiratory-controlled k-space reordering four-dimensional phase-contrast magnetic resonance imaging sequence were evaluated. Imaging data and pressure measurements are used to inform the development of numerical models of dissected aortas. The influence of different inlet boundary conditions on the outcomes of our simulations has also been investigated. The present results indicate that phase-contrast magnetic resonance imaging is valuable for providing patient-specific flow data. The evaluated magnetic resonance imaging sequence is reproducible and accurate in in-vivo flow metrics measurement. Computational fluid dynamics simulations based on multiple imaging modalities hold substantial promise for identifying potential risk factors associated with disease development. To accurately represent physiological haemodynamic parameters in aortic dissection, appropriate inlet boundary conditions and MRI data should be chosen.

Turbulence is of interest in many engineering applications, ranging from aerospace design to naval architecture. The inherent complexities of turbulence make it difficult to measure experimentally, and, to simulate numerically. The focus of this dissertation is the simulation of turbulent flow with the computational methodology known as large-eddy simulation (LES). LES uses a filter to partition a flow-field into large- (or resolved) and small- (or subgrid) scales and solves only for the large-scales. This method provides more accuracy when compared to other computational methods, such as those based on the Reynolds-averaged Navier--Stokes equations. The increased accuracy, however, comes with an associated increase in computational cost. Indeed, the computational cost of LES can often be prohibitive, especially for cases involving wall-bounded flow over complex geometries at high Reynolds numbers. This high computational expense is one of the primary limitations of LES. Methods to reduce the cost of LES form the focus of this dissertation. The high cost of LES is in great part due to the near-wall resolution requirement. To accurately represent a flow-field with LES, it is necessary to sufficiently resolve all of the dynamically important scales of motion. This is relatively inexpensive in free-shear flows, where the large-scales are the most energetic, but it is more difficult in wall-bounded flows, where the energy-containing scales get increasingly small near a wall. These near-wall small-scales make it impractical to resolve all of the energy containing scales. Therefore, models that mimic the effect of the near-wall turbulent structures on the wall and on the core of the flow are often used. These models are known as wall-models, and, if accurate, they are able to significantly reduce the computational cost of a large-eddy simulation. At present there is no wall-modelling approach that has been shown to be apposite in a broad range of applications. In particular, current wall-models are often inaccurate when applied to separating wall-bounded flow and are limited by their inability to predict fluctuations of wall-shear-stress and the near-wall velocity. Because of this, a key focus of this dissertation is the proposal and investigation of a new wall-model that aims to overcome these two limitations. In addition, the new model aims to reduce the computational cost of LES by significantly reducing the near-wall resolution requirement. Before introducing this new wall-model, flow over a circular cylinder is investigated in order to gain familiarity with the large-eddy simulation methodology and to assess the effect of some key computational parameters in LES. In this investigation, the effects of mesh resolution, discretisation schemes, SGS-models, and wall-models on prediction of the flow-field are assessed. One of the primary outcomes of this study is the finding that `standard' wall-models are inadequate for turbulent separating flows. This motivated the investigation of the new wall-model. The new wall-model is able to predict the fluctuating wall-shear-stress from a large-scale velocity input. The model is based on the spectral structure of the turbulent boundary layer and the interaction between large-scale events in the logarithmic layer and small-scale events near the wall. Importantly, the model includes many important parameters that are able to preserve the structure of the boundary layer while remaining relatively straightforward to implement in a solver. Further, the model does not increase the computational cost of a simulation compared to current wall-modelling approaches. The model is implemented in large-eddy simulations of channel flow to assess its efficacy compared to a standard wall-model. The influence of two subgrid-scale models on the large-scale velocity input is also investigated. Results show that the new wall-model is able to resolve more of the wall-shear-stress variance when compared to a standard wall-model, and it has a small effect in the outer-regions of the boundary layer.

Mechanical Engineering - Theses

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