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Any machining operation induces significant deformation and associated stress states within the component being machined. Once the component has been finished and is removed from the machining tool, a portion of these stresses remain within the finished component, and are termed residual stresses. These stresses have a significant effect upon the performance of the final component. However, despite their importance there is no accurate and cost effective method for measuring residual stresses. For this reason predicting these stresses without the need for measurement is highly desirable. The focus of this thesis is on advancing the development and implementation of finite element models aimed at predicting residual stresses induced by metal cutting operations. There are three main focus areas within this research, the first of which is concerned with predicting residual stresses when small feed rates are used. It is shown that in the existing cutting models residual stress prediction accuracy suffers when feed rates are small. A sequential cut module is developed, which greatly increases the accuracy of the predicted residual stress depth profiles. A second area of focus concerns the influence of friction models on predicted residual stresses. A detailed set of simulations is used to elucidate the effect of friction not only for sharp tools, but also for tools which have accrued wear. It is shown that whilst friction is not of critical importance for new tools, as tools continue to wear the choice of friction model becomes significantly more important. The third area of focus is on phase transformations, induced by the cutting process. A decoupled phase transformation module is developed in order to predict the depth, if any, of a phase transformed layer beneath the newly machined surface. Furthermore, the effect of this layer on the residual stress depth profile was also studied. All three focus areas present new and novel contributions to the field of metal cutting simulations, and serve to significantly increase the capabilities of predictive models for machining. / Thesis / Doctor of Philosophy (PhD)

The point of departure for this thesis is a case study of Linköping University and its goal to reduce air travel carbon emissions by 30% by 2024 compared to the year 2019 level. The aim of this study is to identify aspects that influence current academic work-related travel behaviour within the “Three spheres of transformation” to explore how changes on different levels would support or hinder the implementation of the air travel carbon emission reduction goal. As human activities have been distinctly linked to climate change, it can be justified to address human behaviour concerning climate change mitigation mechanisms. To fulfil the research aim, interviews with Linköping University’s employees were conducted and the results were analysed by applying the “Three spheres of transformation” framework and the main findings from the human behaviour field. Several aspects that affect travel behaviour were identified in all three spheres of transformation that are interconnected. This study concludes that such aspects as increased data availability concerning each employee’s air travel carbon footprint to increase the understanding of the current situation and the shift in academic structures, especially in such aspects as internationalization and academic networking that can determine researcher evaluation criteria, can support the implementation of the goal. In addition to that, the shift in paradigms regarding academic success and travel in general, as well as the understanding of how these drivers affect human behaviour, can significantly support the implementation of the University’s goal and ensure a long-term change.

A major challenge of developing faster and smaller microelectronic devices is that high flux of heat needs to be removed efficiently to prevent overheating of devices. The conventional way of heat removal using liquid reaches a limit due to low thermal conductivity and limited heat capacity of fluids. Adding solid nanoparticles into fluids has been proposed as a way to enhance thermal conductivity of fluids, but recent results show inconclusive anomalous enhancements in thermal conductivity. A possible way to improve heat transfer is to increase the heat capacity of liquid by adding phase change nanoparticles with large latent heat of fusion into the liquid. Such nanoparticles absorb heat during solid to liquid phase change. However, the colloidal suspension of bare phase change nanoparticles has limited use due to aggregation of molten nanoparticles, irreversible sticking on fluid channels, and dielectric property loss. This dissertation describes a new method to enhance the heat transfer property of a liquid by adding encapsulated phase change nanoparticles (nano-PCMs), which will absorb thermal energy during solid-liquid phase change and release heat during freeze. Specifically, silica encapsulated indium nanoparticles, and polymer encapsulated paraffin (wax) nanoparticles have been prepared using colloidal method, and dispersed into poly-α-olefin (PAO) and water for high temperature and low temperature applications, respectively. The shell, with a higher melting point than the core, can prevent leakage or agglomeration of molten cores, and preserve the dielectric properties of the base fluids. Compared to single phase fluids, heat transfer of nanoparticle-containing fluids have been significantly enhanced due to enhanced heat capacities. The structural integrity of encapsulation allows repeated uses of nanoparticles for many cycles. iv By forming porous semi crystalline silica shells obtained from water glass, supercooling has been greatly reduced due to low energy barrier of heterogeneous nucleation. Encapsulated phase change nanoparticles have also been added into exothermic reaction systems such as catalytic and polymerization reactions to effectively quench local hot spots, prevent thermal runaway, and change product distribution. Specifically, silica-encapsulated indium nanoparticles, and silica encapsulated paraffin (wax) nanoparticles have been used to absorb heat released in catalytic reaction, and to mitigate the gel effect during polymerization, respectively. The reaction rates do not raise significantly owing to thermal buffering using phase change nanoparticles at initial stage of thermal runaway. The effect of thermal buffering depends on latent heats of fusion of nanoparticles, and heat releasing kinetics of catalytic reactions and polymerizations. Micro/nanoparticles of phase change materials will open a new dimension for thermal management of exothermic reactions.

<p> This thesis details work done in the development of the phase field model which allows simulation of elasticity with diffuse interfaces and the extension of a thin interface analysis developed by previous authors to study non-dilute ideal alloys. These models are coupled with a new finite difference adaptive mesh algorithm to efficiently simulate a variety of physical systems. The finite difference adaptive mesh algorithm is shown to be at worse 4-5 times faster than an equivalent finite element method on a per node basis. In addition to this increase in speed for explicit solvers in the code, an iterative solver used to compute elastic fields is found to converge in O(N) time for a dynamically growing precipitate, where N is the number of nodes on the adaptive mesh. A previous phase field formulation is extended such as to make possible the study of non-ideal binary alloys with complex phase diagrams. A phase field model is also derived for a free energy that incorporates an elastic free energy and is used to investigate the competitive development of solid state structures in which the kinetic transfer rate of atoms from the parent phase to the precipitate phase is large. This results in the growth of solid state dendrites. The morphological effects of competing surface anisotropy and anisotropy in the elastic modulus tensor is analyzed. It is shown that the transition from surfaceenergy driven dendrites to elastically driven dendrites depends on the magnitudes of the surface energy anisotropy coefficient (E4 ) and the anisotropy of the elastic tensor (β) as well as on the super saturation of the particle and therefore to a specific Mullins-Sekerka onset radius. The transition point of this competitive process is predicted from these three controlling parameters. </p> / Thesis / Doctor of Philosophy (PhD)

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