This study proposes simulations which present optimized methods for producing fatty acids, fatty alcohols and alkanes using Zymomonas mobilis bacterium by the energy efficient β-oxidation reversal pathway, an eco-friendly alternative to the present petroleum based processes. Zymomonas has advantages of higher carbon intake, higher ethanol tolerance and higher ethanol production efficiency than other organisms. I have improved an earlier Zymomonas genome scale model and used Constraint Based Reconstruction and Analysis (COBRA), a linear optimization based computational tool in Matlab, and to perform flux balance analysis (FBA) based simulations. FBA accounts for formation, consumption, accumulation and removal rate or flux of each metabolite. The results present solution spaces of cell growth rate and product formation rate, which trend with products and their carbon chain length. I have analyzed these solution space trends gaining insight into the Zymomonas’ metabolism, enabling efficient product formation and opening a way for future improvement.

Boundary spanners-in-practice are individuals who inhabit more than one social world and bring overlapping place perspectives to bear on the function(s) performed within and across each world. Different from nominated boundary spanners, they are practitioners responsible for the 'translation' of each small world's perspectives thereby increasing collaboration effectiveness to permit the small worlds to work synergistically. The literature on Knowledge Management (KM) has emphasized the organizational importance of individuals performing boundary spanning roles by resolving cross-cultural and cross-organizational knowledge system conflicts helping teams pursue common goals through creation of "joint fields" - a third dimension that is co-jointly developed between the two fields or dimensions that the boundary spanner works to bridge. The Copeland and O'Connor Nondeterministic Model of Engineering Design Activity was utilized as the foundation to develop models of communication mechanics and dynamics when multiple simultaneous interactions of the single nondeterministic user model, the BSIP and two Subject Matter Experts (SMEs), engage during design activity in the Problem-Solving Space. The Problem-Solving Space defines the path through the volumes of plausible answers or 'solution spaces' that will satisfice the problem presented to the BSIP and SMEs. Further model refinement was performed to represent expertise seeking behaviors and the physical and mental models constructed by boundary spanners-in-practice during knowledge domain mapping. This was performed by mapping the three levels of communication complexity (transfer, translation and transformation) to each knowledge boundary (syntactic, semantic and pragmatic) that must be bridged during knowledge domain mapping.

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Submitted by Maicon Juliano Schmidt (maicons) on 2015-06-11T19:24:34Z No. of bitstreams: 1 Débora de Oliveira Lemos Rocha de Souza.pdf: 11262812 bytes, checksum: 1afc26309c47e8dc71f1c5e88aae7409 (MD5) / Made available in DSpace on 2015-06-11T19:24:34Z (GMT). No. of bitstreams: 1 Débora de Oliveira Lemos Rocha de Souza.pdf: 11262812 bytes, checksum: 1afc26309c47e8dc71f1c5e88aae7409 (MD5) Previous issue date: 2015-03-27 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / FAPERGS - Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul / Algumas ações do processo projetual se restringem aos pensamentos dos designers, gerando uma dificuldade para compreender o processo e torná-lo explícito. As pesquisas nessa área tentam transpor essas limitações, buscando perceber o modo como os designers resolvem os problemas para aprimorar a sua atuação. Esses problemas são caracterizados como mal-estruturados e podem ser vistos de diferentes perspectivas, gerando respostas distintas. O conceito de coevolução percebe a resolução de problemas de forma evolutiva: à medida que compreende-se um pouco mais o problema, as respostas tornam-se mais aprimoradas. Esta dissertação tem como objetivo geral compreender a coevolução do problema de design. Para isso, realizou-se uma pesquisa exploratória em um workshop em design, coletando as informações por meio de grupos focais e do registro, em vídeo, do processo realizado pelos participantes. A técnica utilizada para analisar as informações coletadas nos grupos focais e nos vídeos foi a análise de conteúdo, com algumas adaptações necessárias à pesquisa realizada. Na análise, percebeu-se que a coevolução é influenciada: 1) pela formulação inicial do problema que funciona como uma força motora, impulsionando o processo de resolução do problema; 2) pela forma como as equipes se articulam, levando-se em conta o modo como os integrantes desempenham diferentes papeis e estabelecem um ritmo de resolução do problema de acordo com experiências anteriores que trazem para o projeto; 3) pelos questionamentos em relação ao problema ou à solução, caracterizando-se como uma das estratégias utilizadas pelos designers para avançar no espaço-problema ou no espaço-solução. Concluiu-se, assim, que não só o espaço-problema e o espaço-solução se modificam no percurso do projeto de forma a provocar uma evolução mútua, mas os diversos fatores que envolvem o processo projetual também influenciam na coevolução do problema de design. / Some actions in the design process are restricted to the designers’ thoughts, what may cause some difficulties in understanding the process itself and making it explicit. Studies in this area attempt to overcome these limitations by looking into the way designers solve problems to improve their performance. These problems are usually characterized as ill-structured and can be seen from different perspectives, leading to distinct answers. The concept of co-evolution regards problem resolution in an evolutive manner: as the problem is better understood, the answers become more refined. The overall objective of this work is to understand the co-evolution of the design problem. In order to do this, an exploratory research was conducted within a design workshop, where data was collected by means of both focal groups and videos recording the participants’ process. The technique used to analyse all this data was Content Analysis, with some necessary adaptations to the context of the present research. In the analysis, it was possible to observe that co-evolution is influenced by: 1) the initial formulation of the problem that works as a driving force, boosting the problem resolution process; 2) the way the groups manage themselves, taking into consideration the manner in which different members play distinct roles and establish a problem resolution pace based on previous experiences they bring to the project; and 3) inquiries related to the problem or the solution, which can be regarded as one of the strategies used by designers to move forward into the problem space or the solution space. In conclusion, all these observations lead to the understanding that not only the problem space and the solution space modify themselves in the course of the project, triggering mutual evolution, but the diverse aspects involved in the design context also have some influence on the co-evolution of the design problem.

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Videogame tinkerers, players, and activists of the 21st century are continuing, yet redefining, the avant-garde art and literary movements of the 20th century. Videogames are diverging as a social, cultural, and digital medium. They are used as political instruments, artistic experiments, social catalysts, and personal means of expression. A diverse field of games and technocultural play, such as alternate reality games, griefer attacks, arcade sculptures, and so on, can be compared and contrasted to the avant-garde, such as contemporary tactical media, net art, video art, Fluxus, the Situationists, the work of Pollock or Brecht, Dada, or the Russian Formalists. For example, historical avant-garde painters played with perspectival space (and its traditions), rather than only within those grid-like spaces. This is similar in some ways to how game artists play with flow (and player expectations of it), rather than advancing flow as the popular and academic ideal. Videogames are not only an advanced product of technoculture, but are the space in which technoculture conventionalizes play. This makes them a fascinating site to unwork and rethink the protocols and rituals that rule technoculture. It is the audacity of imagining certain videogames as avant-garde (from the perspective of mainstream consumers and art academics alike) that makes them a good candidate for this critical experiment.

La conception assistée par ordinateur (CAO), les effets visuels, la robotique et de nombreux autres domaines tels que la biologie computationnelle, le génie aérospatial, etc. reposent sur la résolution de problèmes mathématiques. Dans la plupart des cas, des méthodes de calcul sont utilisées pour résoudre ces problèmes. Le choix et la construction de la méthode de calcul ont un impact important sur les résultats et l'efficacité du calcul. La structure du problème peut être utilisée pour créer des méthodes, qui sont plus rapides et produisent des résultats qualitativement meilleurs que les méthodes qui n'utilisent pas la structure. Cette thèse présente trois articles avec trois nouvelles méthodes de calcul s'attaquant à des problèmes de simulation et d'optimisation contraints par des équations aux dérivées partielles (EDP). Dans le premier article, nous abordons le problème de la dissipation d'énergie des solveurs fluides courants dans les effets visuels. Les solveurs de fluides sont omniprésents dans la création d'effets dans les courts et longs métrages d'animation. Nous présentons un schéma d'intégration temporelle pour la dynamique des fluides incompressibles qui préserve mieux l'énergie comparé aux nombreuses méthodes précédentes. La méthode présentée présente une faible surcharge et peut être intégrée à un large éventail de méthodes existantes. L'amélioration de la conservation de l'énergie permet la création d'animations nettement plus dynamiques. Nous abordons ensuite la conception computationelle dont le but est d'exploiter l'outils computationnel dans le but d'améliorer le processus de conception. Plus précisément, nous examinons l'analyse de sensibilité, qui calcule les sensibilités du résultat de la simulation par rapport aux paramètres de conception afin d'optimiser automatiquement la conception. Dans ce contexte, nous présentons une méthode efficace de calcul de la direction de recherche de Gauss-Newton, en tirant parti des solveurs linéaires directs épars modernes. Notre méthode réduit considérablement le coût de calcul du processus d'optimisation pour une certaine classe de problèmes de conception inverse. Enfin, nous examinons l'optimisation de la topologie à l'aide de techniques d'apprentissage automatique. Nous posons deux questions : Pouvons-nous faire de l'optimisation topologique sans maillage et pouvons-nous apprendre un espace de solutions d'optimisation topologique. Nous appliquons des représentations neuronales implicites et obtenons des résultats structurellement sensibles pour l'optimisation topologique sans maillage en guidant le réseau neuronal pendant le processus d'optimisation et en adaptant les méthodes d'optimisation topologique par éléments finis. Notre méthode produit une représentation continue du champ de densité. De plus, nous présentons des espaces de solution appris en utilisant la représentation neuronale implicite. / Computer-aided design (CAD), visual effects, robotics and many other fields such as computational biology, aerospace engineering etc. rely on the solution of mathematical problems. In most cases, computational methods are used to solve these problems. The choice and construction of the computational method has large impact on the results and the computational efficiency. The structure of the problem can be used to create methods, that are faster and produce qualitatively better results than methods that do not use the structure. This thesis presents three articles with three new computational methods tackling partial differential equation (PDE) constrained simulation and optimization problems. In the first article, we tackle the problem of energy dissipation of common fluid solvers in visual effects. Fluid solvers are ubiquitously used to create effects in animated shorts and feature films. We present a time integration scheme for incompressible fluid dynamics which preserves energy better than many previous methods. The presented method has low overhead and can be integrated into a wide range of existing methods. The improved energy conservation leads to noticeably more dynamic animations. We then move on to computational design whose goal is to harnesses computational techniques for the design process. Specifically, we look at sensitivity analysis, which computes the sensitivities of the simulation result with respect to the design parameters to automatically optimize the design. In this context, we present an efficient way to compute the Gauss-Newton search direction, leveraging modern sparse direct linear solvers. Our method reduces the computational cost of the optimization process greatly for a certain class of inverse design problems. Finally, we look at topology optimization using machine learning techniques. We ask two questions: Can we do mesh-free topology optimization and can we learn a space of topology optimization solutions. We apply implicit neural representations and obtain structurally sensible results for mesh-free topology optimization by guiding the neural network during optimization process and adapting methods from finite element based topology optimization. Our method produces a continuous representation of the density field. Additionally, we present learned solution spaces using the implicit neural representation.