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Yes / Here the design and functional optimisation of thermoformed thin-walled structures made from plastics is considered. Such objects are created in great numbers especially in the food packaging industry. In fact these objects are produced in such vast numbers each year, that one important task in the design of these objects is the minimisation of the amount of plastic used, subject to functional constraints. In this paper a procedure for achieving this is described, which involves the automatic optimisation of the mold shape taking into account the strength of the final object and its thickness distribution, thus reducing the need to perform inefficient and expensive `trial and error¿ experimentation using physical prototypes. An efficient technique for parameterising geometry is utilised here, enabling to create a wide variety of possible mold shapes on which appropriate analysis can be performed. The results of the analysis are used within an automatic optimisation routine enabling to find a design which satisfies user requirements. Thus, the paper describes a rational means for the automatic optimal design of composite thermoformed thin-walled structures.

This thesis is about how you can use shapes, proportions and compositions that humans fundamentally enjoy on a biological and evolutionary level. To create architectural elements that aid in creating an urban environment that humans enjoy being in and to live in.   The thesis is based around research by design and focuses on designing a residential building that is located in the central part of Malmö, Sweden. Furthermore theories such as Jan Gehl's theories on city planning are used to ensure a good connection between the private and public parts of the city. Moreover, other theories such as Dennis Dutton's theory on evolutionary beauty and the theories found in the book Cognitive Architecture lay a foundation for the design choices made all through the building.   To create an urban environment that people enjoy being in and that promotes people to spend their time in. The architecture needs to be designed in a way that reflects and encourages this behavior. Humans are visual creatures and need visual stimuli from their environment. The architecture needs to contain details and variation within its design to create environments that are visually interesting for us people.

Fiber-reinforced polymeric (FRP) composites are being considered for structural members in bridge construction as lighter, more durable alternatives to steel and concrete. Extensive testing and analysis of a pultruded, hybrid double web beam (DWB) developed for use in bridge construction has been conducted at Virginia Tech. A primary purpose of this testing is the development of a structural design guide for the DWB, which includes stiffness and strength data. The design manual also includes design allowables determined through a statistical analysis of test data. Static testing of the beams, including failure tests, has been conducted in order to determine such beam properties as bending modulus, shear stiffness, failure mode, and ultimate capacity. Measuring and calculating the shear stiffness has proven to be an area of particular interest and difficulty. Shear stiffness is calculated using Timoshenko beam theory which combines the shear stiffness and shear area together along with a shear correction factor, k, which accounts for the nonuniform distribution of shear stress/strain through the cross-section of a structure. There are several methods for determining shear stiffness, kGA, in the laboratory, including a direct method and a multi-span slope method. Herein lays the difficulty as it has been found that varying methods produces significantly different results. One of the objectives of current research is to determine reasons for the differences in results, to identify which method is most accurate in determining kGA, and also to examine other parameters affecting the determination of kGA that may further aid the understanding of this property. This document will outline the development of the design guide, the philosophy for the selection of allowables and review and discuss the challenges of interpreting laboratory data to develop a complete understanding of shear effects in large FRP structural members. / Master of Science

Les différentes étapes et processus de la fabrication additive (FA) induisent des erreurs de sources multiples et complexes qui soulèvent des problèmes majeurs au niveau de la qualité géométrique du produit fabriqué. Par conséquent, une modélisation effective des écarts géométriques est essentielle pour la FA. Le paradigme Skin Model Shapes (SMS) offre un cadre intégral pour la modélisation des écarts géométriques des produits manufacturés et constitue ainsi une solution efficace pour la modélisation des écarts géométriques en FA.Dans cette thèse, compte tenu de la spécificité de fabrication par couche en FA, un nouveau cadre de modélisation à base de SMS est proposé pour caractériser les écarts géométriques en FA en combinant une approche dans le plan et une approche hors plan. La modélisation des écarts dans le plan vise à capturer la variabilité de la forme 2D de chaque couche. Une méthode de transformation des formes est proposée et qui consiste à représenter les effets de variations sous la forme de transformations affines appliquées à la forme nominale. Un modèle paramétrique des écarts est alors établi dans un système de coordonnées polaires, quelle que soit la complexité de la forme. Ce modèle est par la suite enrichi par un apprentissage statistique permettant la collecte simultanée de données des écarts de formes multiples et l'amélioration des performances de la méthode.La modélisation des écarts hors plan est réalisée par la déformation de la couche dans la direction de fabrication. La modélisation des écarts hors plan est effectuée à l'aide d'une méthode orientée données. Sur la base des données des écarts obtenues à partir de simulations par éléments finis, deux méthodes d'analyse modale: la transformée en cosinus discrète (DCT) et l'analyse statistique des formes (SSA) sont exploitées. De plus, les effets des paramètres des pièces et des procédés sur les modes identifiés sont caractérisés par le biais d'un modèle à base de processus Gaussien.Les méthodes présentées sont finalement utilisées pour obtenir des SMSs haute-fidélité pour la fabrication additive en déformant les contours de la couche nominale avec les écarts prédits et en reconstruisant le modèle de surface non idéale complet à partir de ces contours déformés. Une toolbox est développée dans l'environnement MATLAB pour démontrer l'efficacité des méthodes proposées. / The intricate error sources within different stages of the Additive Manufacturing (AM) process have brought about major issues regarding the dimensional and geometrical accuracy of the manufactured product. Therefore, effective modeling of the geometric deviations is critical for AM. The Skin Model Shapes (SMS) paradigm offers a comprehensive framework aiming at addressing the deviation modeling problem at different stages of product lifecycle, and is thus a promising solution for deviation modeling in AM. In this thesis, considering the layer-wise characteristic of AM, a new SMS framework is proposed which characterizes the deviations in AM with in-plane and out-of-plane perspectives. The modeling of in-plane deviation aims at capturing the variability of the 2D shape of each layer. A shape transformation perspective is proposed which maps the variational effects of deviation sources into affine transformations of the nominal shape. With this assumption, a parametric deviation model is established based on the Polar Coordinate System which manages to capture deviation patterns regardless of the shape complexity. This model is further enhanced with a statistical learning capability to simultaneously learn from deviation data of multiple shapes and improve the performance on all shapes.Out-of-plane deviation is defined as the deformation of layer in the build direction. A layer-level investigation of out-of-plane deviation is conducted with a data-driven method. Based on the deviation data collected from a number of Finite Element simulations, two modal analysis methods, Discrete Cosine Transform (DCT) and Statistical Shape Analysis (SSA), are adopted to identify the most significant deviation modes in the layer-wise data. The effect of part and process parameters on the identified modes is further characterized with a Gaussian Process (GP) model. The discussed methods are finally used to obtain high-fidelity SMSs of AM products by deforming the nominal layer contours with predicted deviations and rebuilding the complete non-ideal surface model from the deformed contours. A toolbox is developed in the MATLAB environment to demonstrate the effectiveness of the proposed methods.

Spark plasma sintering (SPS) is a powder consolidation technique used to rapidly densify a variety of material systems. SPS is capable of precisely controlling material microstructures and achieving non-equilibrium phases due to rapid heating and cooling rates through the simultaneous application of pressure and direct current. Due to these characteristics, SPS is an ideal processing technique for high temperature ceramics which require processing at temperatures greater than 1500°C. Due to the desirable properties obtained on small diameter materials processed by SPS, larger and more complex geometries are desired while maintaining sample microstructures. In order to accurately scale ceramics produced by SPS, a finite element model must be developed that can be used as a predictive tool. My research focuses on developing a finite element model for the spark plasma sintering furnace at the University of Arizona and validating modeled results using experimentally obtained data. Electrical and thermal conductivity as functions of temperature vary widely among different grades of commercially available electrode grade graphite at constant density. Modeled material properties are optimized in order to calibrate modeled results to experimentally obtained data (i.e. measured current, voltage, and temperature distributions). Sensitivity analysis is performed on the model to better understand model physics and predictions. A calibrated model is presented for 20mm ZrB2 and Si3N4 discs. Sample temperature gradients are experimentally confirmed using grain size and β-Si3N4 phase composition. The model is used to investigate scale up from 20mm to 30mm discs and 30mm rings as well as effects of processing conditions on β-Si3N4 content.

In nature we see a wide variety of bold colors and unique shapes. Trees personify these characteristics with their curved branches creating distinctive lines and shapes. Leaves and blossoms enhance their structures with an array of colors. Trees possess awe inspiring energy. Each tree is a living thing, its growth shaped by its environment.Similarly, my work is a response to the environment. I employ a spontaneous and bold technique in an attempt to capture the energy I perceive in nature. The use of vigorous lines and high keyed contrasting colors with varied textures conveys that trees are living, growing entities, each one unique. I remain open to new ways of expressing this aesthetic so that my work will continue to grow like a tree and evolve.

Gallium nitride (GaN)-based light-emitting diodes (LEDs) with cylindrical nanostructures have been the subject of significant research interest in the past decade, due to the potential of such structures to increase light extraction efficiency and deliver highly directional light emission. Nanorod LEDs, where the light emission is within the nanocylinder, have the additional potential to increase internal quantum efficiency and emit in colours previously thought impractical with GaN-based LEDs. Optical modelling of nanostructured LEDs is usually carried out using finite-difference time-domain methods, which are computationally intensive and do not always provide sufficient insight into the physics underlying the simulation results. This thesis proposes an intuitive, quasi-analytic method based on modal expansion. It is found that it is possible to calculate the far field diffraction patterns of all guided modes supported by a single nanorod, with full consideration of Fabry-Perot effects, in minutes using a standard office desktop computer. Focus is placed on the case of a nanorod of radius 140 nm, for which angular photoluminescence measurements were available to provide a means of validating the model. Consideration of the guided modes alone provides a compelling explanation for gross features in the measured data where none previously existed. It is shown that, using a standard equation from a textbook, it is possible to calculate how much each of the guided and radiation modes of a single nanorod is excited by a Hertzian dipole of known position and orientation with respect to the nanorod geometry. When interference between these modes is considered, it is possible to calculate the total far field angular emission pattern due to that dipole. Comparing these patterns with photoluminescence measurements allows one to infer the locations and orientations of dipole current sources; the results are found to be consistent with those of cathodoluminescence studies.