Simplified methods of analysis described in codes and specifications for seismically isolated structures are always used either directly in special cases or for checking the results of nonlinear response history analysis (RHA). Important predictions for seismically isolated structures by simplified methods are the maximum displacements and base shears of the isolation system. In this study, the maximum isolator displacements and base shears determined by nonlinear RHA are compared with those determined by the equivalent lateral force (ELF) procedure in order to assess the accuracy of the simplified method in the case of bi-directional excitations with near-field characteristics. However, although there are currently many methods for ground motion selection and scaling, little guidance is available to classify which method is more appropriate than the others in any applications. Features of this study are that the ground motions used in analysis are selected and scaled using contemporary concepts and that the ground excitation is considered biv directional. The variations in response of isolated structures due to application of ground motions uni-directionally and bi-directionally are also studied by employing a scaling procedure that is appropriate for the bi-directional analysis. The proposed new scaling methodology is an amplitude scaling method that is capable of preserving the horizontal orthogonal components and it is developed especially for dynamic analysis of isolated structures. Analyses are conducted for two different symmetric reinforced concrete isolated structure for two different soil conditions in structural analysis program SAP2000. Effect of asymmetry in superstructure on isolator displacement is also investigated with further analyses considering 5% mass eccentricity at each floor level. Furthermore, once the significance of the orthogonal horizontal component on the response of isolation system is shown, the biaxial interaction of hysteretic behavior of lead rubber bearings is implemented in OpenSees by developing a subroutine which was not readily available.

In this thesis, a cavity-backed slot antenna array is designed for relatively wide instantaneous bandwidth, high gain and low sidelobes. The array consists of four, rectangular, slot elements, arranged side-by-side in a linear array and developed around 5GHz. Two feed points, at opposing sides of the printed array, each excite two of the slot elements through a series feed. This bidirectional feed presents symmetry to the design and prevents the tendency of beam-drift versus frequency as is common with many series-fed arrays. While being fed in-phase, the array will maintain boresight at broadside over the entire operating bandwidth. Also, the additional port allows for the potential introduction of a phase offset and, therefore, beam tilt. Finally, the printed array is designed to function within a quarter-wave, metallic cavity to achieve unidirectional radiation and improve gain.

This thesis has contributed to the design of suitable decision-making techniques for energy management in the smart grid with emphasis on energy efficiency and uncertainty analysis in two smart grid applications. First, an energy trading model among distributed microgrids (MG) is investigated, aiming to improve energy efficiency by forming coalitions to allow local power transfer within each coalition. Then, a more specific scenario is considered that is how to optimally schedule Electric Vehicles (EV) charging in a MG-like charging station, aiming to match as many as EV charging requirements with the uncertain solar energy generation. The solutions proposed in this thesis can give optimal coalition formation patterns for reduced power losses and achieve optimal performance for the charging station. First, several algorithms based on game theory are investigated for the coalition formation of distributed MGs to alleviate the power losses dissipated on the cables due to power transfer. The seller and buyer MGs can make distributed decisions whether to form a coalition with others for energy trading. The simulation results show that game theory based methods that enable cooperation yield a better performance in terms of lower power losses than a non-cooperative approach. This is because by forming local coalitions, power is transferred within a shorter distance and at a lower voltage. Thus, the power losses dissipated on the transmission lines and caused by power conversion at the transformer are both reduced. However, the merge-and-split based cooperative games have an inherent high computational complexity for a large number of players. Then, an efficient framework is established for the power loss minimization problem as a college admissions game that has a much lower computational complexity than the merge-and-split based cooperative games. The seller and buyer MGs take the role of colleges and students in turn and apply for a place in the opposite set following their preference lists and the college MGs’ energy quotas. The simulation results show that the proposed framework demonstrates a comparable power losses reduction to the merge-and-split based algorithms, but runs 700 and 18000 times faster for a network of 10 MGs and 20 MGs, respectively. Finally, the problem of EV charging using various energy sources is studied along with their impact on the charging station’s performance. A multiplier k is introduced to measure the effect of solar prediction uncertainty on the decision-making process of the station. A composite performance index (the Figure of Merit, FoM) is also developed to measure the charging station’s utility, EV users charging requirements and the penalties for turning away new arrivals and for missing charging deadlines. A two-stage admission and scheduling mechanism is further proposed to find the optimal trade-off between accepting EVs and missing charging deadlines by determining the best value of the parameter k under various energy supply scenarios. The numerical evaluations give the solution to the optimization problem and show that some of the key factors such as shorter and longer deadline urgencies of EVs charging requirements, stronger uncertainty of the prediction error, storage capacity and its initial state will not affect significantly the optimal value of the parameter k.

No description available.

Isolator displacements, floor accelerations, roof displacements, base shear and torsional moments are basic parameters that are considered in the design of seismically isolated structures. The aim of this study is to evaluate the effects of bidirectional earthquake excitations of near fault records on the response of base isolated structures in terms of basic parameters mentioned above. These parameters computed from nonlinear response history analysis (RHA) and they are compared with the parameters computed from equivalent lateral force procedure (ELF). Effect of asymmetry in superstructure is also examined considering mass eccentricity at each floor level. Torsional amplifications in isolator displacements, floor accelerations, roof displacements and base shear are compared for different level of eccentricities. Two buildings with different story heights are used in the analyses.The building systems are modeled in structural analysis program SAP2000. The scaling of ground motion data are taken from the study of &ldquo / Response of Isolated Structures Under Bi-directional Excitations of Near-fault ground Motions&rdquo / (Ozdemir, 2010). Each ground motion set (fault normal and fault parallel) are applied simultaneously for different range of effective damping of lead rubber bearing (LRB) and for different isolation periods.

The goal of neuromorphic engineering is to create electronic systems that model the behavior of biological neural systems. Neuromorphic systems can leverage a combination of analog and digital circuit design techniques to enable computational modeling, with orders of magnitude of reduction in size, weight, and power consumption compared to the traditional modeling approach based upon numerical integration. These benefits of neuromorphic modeling have the potential to facilitate neural modeling in resource-constrained research environments. Moreover, they will make it practical to use neural computation in the design of intelligent machines, including portable, battery-powered, and energy harvesting applications. Floating-gate transistor technology is a powerful tool for neuromorphic engineering because it allows dense implementation of synapses with nonvolatile storage of synaptic weights, cancellation of process mismatch, and reconfigurable system design. A novel neuromorphic hardware system, featuring compact and efficient channel-based model neurons and floating-gate transistor synapses, was developed. This system was used to model a variety of network topologies with up to 100 neurons. The networks were shown to possess computational capabilities such as spatio-temporal pattern generation and recognition, winner-take-all competition, bistable activity implementing a "volatile memory", and wavefront-based robotic path planning. Some canonical features of synaptic plasticity, such as potentiation of high frequency inputs and potentiation of correlated inputs in the presence of uncorrelated noise, were demonstrated. Preliminary results regarding formation of receptive fields were obtained. Several advances in enabling technologies, including methods for floating-gate transistor array programming, and the creation of a reconfigurable system for studying adaptation in floating-gate transistor circuits, were made.

In this study, an appearance reconstruction method based on extraction of material re&amp / #64258 / ectance properties of a three-dimensional (3D) object from its twodimensional (2D) images is explained. One of the main advantages of this system is that the reconstructed object can be rendered in real-time with photorealistic quality in varying illumination conditions. Bidirectional Re&amp / #64258 / ectance Distribution Functions (BRDFs) are used in representing the re&amp / #64258 / ectance of the object. The re&amp / #64258 / ectance of the object is decomposed into di&amp / #64256 / use and specular components and each component is estimated seperately. While estimating the di&amp / #64256 / use components, illumination-invariant images of the object are computed from the input images, and a global texture of the object is extracted from these images by using surface particles. The specular re&amp / #64258 / ectance data are collected from the residual images obtained by taking di&amp / #64256 / erence between the input images and corresponding illumination-invariant images, and a Lafortune BRDF model is &amp / #64257 / tted to these data. At the rendering phase, the di&amp / #64256 / use and specular components are blended into each other to achieve a photorealistic appearance of the reconstructed object.

This thesis investigates topology optimization techniques for periodic continuum structures at the macroscopic level. Periodic structures are increasingly used in the design of structural systems and sub-systems of buildings, vehicles, aircrafts, etc. The duplication of identical or similar modules significantly reduces the manufacturing cost and greatly simplifies the assembly process. Optimization of periodic structures in the micro level has been extensively researched in the context of material design, while research on topology optimization for macrostructures is very limited and has great potential both economically and intellectually. In the present thesis, numerical algorithms based on the bi-directional evolutionary structural optimization method (BESO) are developed for topology optimization for various objectives and constraints. Soft-kill (replacing void elements with soft elements) formulations of topology optimization problems for solid-void solutions are developed through appropriate material interpolation schemes. Incorporating the optimality criteria and algorithms for mesh-independence and solution-convergence, the present BESO becomes a reliable gradient based technique for topology optimization. Additionally, a new combination of genetic algorithms (GAs) with BESO is developed in order to stochastically search for the global optima. These enhanced BESO algorithms are applied to various optimization problems with the periodicity requirement as an extra constraint aiming at producing periodicity in the layout. For structures under static loading, the present thesis addresses minimization of the mean compliance and explores the applications of conventional stiffness optimization for periodic structures. Furthermore, this thesis develops a volume minimization formulation where the maximum deflection is constrained. For the design of structures subject to dynamic loading, this thesis develops two different approaches (hard-kill and soft-kill) to resolving the problem of localized or artificial modes. In the hard-kill (completely removing void elements) approach, extra control measures are taken in order to eliminate the localized modes in an explicit manner. In the soft-kill approach, a modified power low material model is presented to prevent the occurrence of artificial and localized modes. Periodic stress and strain fields cannot be assumed in structures under arbitrary loadings and boundaries at the macroscopic level. Therefore being different from material design, no natural base cell can be directly extracted from macrostructures. In this thesis, the concept of an imaginary representative unit cell (RUC) is presented. For situations when the structure cannot be discretized into equally-sized elements, the concept of sensitivity density is developed in order for mesh-independent robust solutions to be produced. The RUC and sensitivity density based approach is incorporated into various topology optimization problems to obtain absolute or scaled periodicities in structure layouts. The influence of this extra constraint on the final optima is investigated based on a large number of numerical experiments. The findings shown in this thesis have established appropriate techniques for designing and optimizing periodic structures. The work has provided a solid foundation for creating a practical design tool in the form of a user-friendly computer program suitable for the conceptual design of a wide range of structures.

District heating systems are common in Nordic countries today and accounts for a great portion of the heat demand. In Sweden, total district heating end use in the last years has been around 50 TWh and district heating accounts for roughly 50 % of the total heat demand. Suppliers of district heating must balance demand and supply, often in large and complex networks. Heat propagation can be in the range of hours and it is not known in detail how the heat will propagate during transient conditions. A dynamic model has been developed in OpenModelica and a method for modeling, handling data, simulating and visualizing the results of a district heating network was developed using Matlab as core. Data from Mälarenergi AB, a district heating producer and grid operator, was used for validation of the model. Validation shows that the model works well in predicting heat propagation and temperature distribution in the network and that the model can be scaled up to a large number of heat exchangers and pipes. The model is robust and can handle bi-directional and reversing flows in complex ring structures. It was concluded that OpenModelica together with Matlab is a good combination for creating models of district heating networks, as a high degree of standardization and automation can be achieved. This, together with visualization of the heat propagation, makes it useful for the understanding of the district heating network during transient conditions. / Smarta Flöden

M-PESA (a mobile banking service in Kenya) was introduced to offer a person-to-person money transfer service. Its extensive adoption and appropriation for purposes other than person-to-person transfers has influenced the technology providers (Safaricom) to widen their services beyond their original intentions. M-PESA provides a wide range of financial services including services for people who were previously unbanked. Users of M-PESA can now pay different utilities, those without credit cards can purchase products online, others can repay loans to microfinance institutions, pay insurance premiums, withdraw money from ATMs, use it as Point of Sale Payment and open savings accounts. This research examines the existence of “bi-directional” influences between technology and society by taking M-PESA business users as a case. It specifically investigates how M-PESA as a technology has influenced the business environment in Kenya and how the design of M-PESA has in turn been influenced by its adoption. The research adopts the Adaptive Structuration Theory as the theoretical framework and interpretive case study research as a methodological approach. Interviews with different stakeholders in the industry were used to collect data. Data was analyzed using Diachronic Analysis. The results of the research show that there is a “bi-directional” influence between technology and people as they affect each other over time. Mobile technologies shape the way businesses operate, allowing them to provide new services and improve existing ones. At the same time, usage and adoption trends affect the design of mobile technologies. Over time, technology is adapted to accommodate the new needs of businesses and other needs in the wider community. This research shows that the impact of technology depends not only on its functionality but also on its use and appropriation in society. / Dissertation (MCom)--University of Pretoria, 2011. / Informatics / unrestricted