Thesis (Ph. D.)--Ohio State University, 2005. / Title from first page of PDF file. Includes bibliographical references (p. 115-117).

Recently, wireless sensor networks have become one of the most exciting areas for research and development. However, sensor nodes are battery operated, thus the sensor's ability to perform its assigned tasks is limited by its battery capacity; therefore, energy efficiency is considered to be a key issue in designing WSN applications. Clustering has emerged as a useful mechanism for trade-off between certain design goal conflicts; the network life time, and the amount of data obtained. However, different sources of energy waste still exist. Furthermore, in such dynamic environments, different data rate requirements emerge due to the current network status, thus adapting a response to the changing network is essential, rather than following the same principle during the network's lifespan. This thesis presents dynamic techniques to adapt to network changes, through which the limited critical energy source can be wisely managed so that the WSN application can achieve its intended design goals. Two approaches have been taken to decreasing the energy use. The first approach is to develop two dynamic round time controllers, called the minimum round time controller MIN-RC and the variable round time controller VAR-RC, whereas the second approach improves intra-cluster communication using a Co-Cluster head; both approaches show better energy utilisation compared to traditional protocols. A third approach has been to develop a general hybrid protocol H-RC that can adapt different applications requirements; it can also tolerate different data rate requirements for the same application during the system's lifetime.

There is a considerable scope for improving the temperature control of exothermic processes. In this thesis, a sub-optimal control strategy is developed through utilizing the dynamic, simulation tool. This scheme is built around easily obtained knowledge of the system and still retains flexibility. It can be applied to both exothermic batch and fed-batch processes. It consists of servo and regulatory modes, where a Generalized Predictive Controller (GPC) was used to provide self-tuning facilities. The methods outlined allow for limited thermal runaway whilst keeping some spare cooling capacity to ensure that operation at constraints are not violated. A special feature of the method proposed is that switching temperatures and temperature profiles can be readily found from plant trials whilst the addition rate profile Is capable of fairly straightforward computation. The work shows that It is unnecessary to demand stability for the whole of the exothermic reaction cycle, permitting a small runaway has resulted in a fast temperature response within the given safety margin. The Idea was employed for an exothermic single Irreversible reaction and also to a set of complex reactions. Both are carried out in a vessel with a heating/cooling coil. Two constraints are Imposed; (1) limited heat transfer area, and (11) a maximum allowable reaction temperature Tmax. The non-minimum phase problem can be considered as one of the difficulties in managing exothermic fed-batch process when cold reactant Is added to vessel at the maximum operating temperature. The control system coped with this within limits, a not unexpected result. In all cases, the new strategy out-performed the conventional controller and produced smoother variations in the manipulated variable. The simulation results showed that batch to batch variations and disturbances In cooling were successfully handled. GPC worked well but can be susceptible to measurement noise.

L’évaluation de risques est conditionnée par les connaissances et les informations disponibles au moment où l’analyse est faite. La modélisation et la simulation sont des moyens d’explorer et de comprendre le comportement du système, d’identifier des scénarios critiques et d’éviter des surprises. Un certain nombre de simulations du modèle sont exécutées avec des conditions initiales et opérationnelles différentes pour identifier les scénarios conduisant à des conséquences critiques et pour estimer leurs probabilités d’occurrence. Pour les systèmes complexes, les modèles de simulations peuvent être : i) de haute dimension ; ii) boite noire ; iii) dynamiques ; iv) coûteux en termes de calcul, ce qu’empêche l’analyste d’exécuter toutes les simulations pour les conditions multiples qu’il faut considérer.La présente thèse introduit des cadres avancés d’évaluation des risques basée sur les simulations. Les méthodes développées au sein de ces cadres sont attentives à limiter les coûts de calcul requis par l’analyse, afin de garder une scalabilité vers des systèmes complexes. En particulier, toutes les méthodes proposées partagent l’idée prometteuse de focaliser automatiquement et de conduire d’une manière adaptive les simulations vers les conditions d’intérêt pour l’analyse, c’est-à-dire, vers des informations utiles pour l'évaluation des risques.Les avantages des méthodes proposées ont été montrés en ce qui concerne différentes applications comprenant, entre autres, un sous-réseau de transmission de gaz, un réseau électrique et l’Advanced Lead Fast Reactor European Demonstrator (ALFRED). / Risk assessment is conditioned on the knowledge and information available at the moment of the analysis. Modeling and simulation are ways to explore and understand system behavior, for identifying critical scenarios and avoiding surprises. A number of simulations of the model are run with different initial and operational conditions to identify scenarios leading to critical consequences and to estimate their probabilities of occurrence. For complex systems, the simulation models can be: i) high-dimensional; ii) black-box; iii) dynamic; and iv) computationally expensive to run, preventing the analyst from running the simulations for the multiple conditions that need to be considered.The present thesis presents advanced frameworks of simulation-based risk assessment. The methods developed within the frameworks are attentive to limit the computational cost required by the analysis, in order to keep them scalable to complex systems. In particular, all methods proposed share the powerful idea of automatically focusing and adaptively driving the simulations towards those conditions that are of interest for the analysis, i.e., for risk-oriented information.The advantages of the proposed methods have been shown with respect to different applications including, among others, a gas transmission subnetwork, a power network and the Advanced Lead Fast Reactor European Demonstrator (ALFRED).

CoordenaÃÃo de AperfeiÃoamento de Pessoal de NÃvel Superior / A animaÃÃo de tecido vem sendo estudada abundantemente nas Ãltimas dÃcadas por haver demanda na indÃstria do entretenimento bem como no comÃrcio eletrÃnico de roupas. Esse tipo de animaÃÃo, na maioria das vezes, à feita com base em simulaÃÃo fÃsica, havendo muito gasto computacional. Esse trabalho tenta usufruir de vÃrios modelos para diminuir esse gasto. à feito uma modelagem do tecido com uma malha triangular e usa-se um modelo massa-mola-amortecedor para simular as forÃas entre as partÃculas, que sÃo os vÃrtices dessa malha. Dependendo da disposiÃÃo do modelo do tecido e dos objetos da cena, sÃo detectadas colisÃes entre eles. A malha à discretizada ou simplificada, levando em consideraÃÃo a compressÃo, a colisÃo e a curvatura das molas, para que seja usada uma malha boa em cada passo ao longo da animaÃÃo. Portanto, o objetivo principal desse trabalho à estudar o comportamento do tecido utilizando o modelo de remalhamento para adaptar essa malha. / In the last decades, cloth animation has been the focus of much research, due to demands from the entertainment industry and from e-commerce. That type of animation is most often the result of a physics-based simulation and has a great computational cost. This work investigates how to reduce the computational cost of the simulation, by refining the mesh only in regions that need a fine level of detail. The fabric model consists of a triangular mesh and uses a spring-mass-damper system to compute the forces among the particles, which are located at the meshâs vertices. The collision detection depends on the arrangement of the cloth model and the objects in the scene. The mesh is refined or simplified, taking into account the spring compression, collision and curvature, so the simulation uses a better mesh every time step. Therefore, this workâs main objective is to study the dynamic behavior of cloth, using a remeshing procedure in order to adapt the mesh.