<p>The advent of small-scale, distributed generators of energy has resulted in the problem of integrating them in the conventional electric power system, which is characterized by large-scale, centralized energy generators. MicroGrids have emerged as a promising solution to the integration problem and have duly received increasing research attention. Microgrids are semi-autonomous collections of controllable microsources and loads, which present themselves to the utility grid as single, controlled entities. In order to achieve the semi-autonomous and controlled nature of microgrids, especially,overcoming the challenge of balancing demand and power generation, an intelligent energy management scheme is required.</p> <p>Developing an energy management scheme is an interesting and challenging task, which provides the potential to exploit ideas from a plethora of fields like Artificial Intelligence and Machine Learning, Constrained Optimization, etc. However, testing energy management strategies on a microgrid would pose a multitude of problems,the most important of them being the unreliability and inconvenience of testing an energy management strategy, which is not optimal, on a functional microgrid. Errors in a test strategy might cause power outages and damage installed devices. Hence it is necessary to test energy management strategies on simulated microgrids.</p> <p>This thesis presents a Software Testbed of MicroGrids, specifically designed to suit the purposes of development of energy management strategies. The testbed consists of two components: Simulation Framework and Analysis Tool. The modular simulation framework enables simulation of a microgrid with microsources and loads,whose configurations can be specified by the user. The analysis tool enables visual analysis of data generated using simulations, which would enable the improvement of not only the management strategy and prediction techniques, but also the computer models used in the simulation framework. A demonstration of the software testbed's simulation and analysis capabilities is presented and possible directions for future research are suggested.</p> / Master of Science (MSc)

<p>Ytterbium-doped optical fibers have extensive applications in high-power fiber lasers, optical amplifiers, and amplified spontaneous emission light sources. In this thesis two sub-projects associated with ytterbium doped fibers are discussed.</p> <p>Numerical simulations have been used to model high-repetition rate ultrafast ytterbium-doped fiber amplifier systems assuming continuous-wave input signals under variable situations, such as one-sided and two-sided pumping. Different system configurations are also developed, such as a single-stage amplification system, a two-stage amplification system and a separated amplification system, providing alternative choices for experiments and applications. The simulation results are compared with experimental data and the simulation results from some other software. The influence of nonlinear effects in the fiber is also very briefly discussed in this thesis.</p> <p>In a second research activity, the distribution of ytterbium atoms is being investigated in a range of double-clad ytterbium-doped fibers. Using aberration-corrected electron microscopy, ytterbium atoms are directly observed from the wedge-shaped specimen, which was prepared from ytterbium-doped optical fibers by tripod polishing combined with ion milling. Challenges related to sample preparation and the interpretations of images are discussed, but the approach shows great potential to investigate the doping behaviors down to atomic scale in the fibers. The work is expected to help reveal mechanisms affecting the performance for the doped fibers, such as photodarkening which is potentially associated with clustering effects.</p> / Master of Applied Science (MASc)

<p>Simulator systems are becoming increasingly popular within the automotive industry. Driving simulations are used to train new drivers, and to research and improve automobile related technologies. While recent technological advances have made simulators more affordable, they have also made simulators more complex. At McMaster's motion simulator laboratory, we wished to create a system to analyze how drivers behave when behind the wheel in a variety of situations. To accomodate this, we have created a complex, robust system capable of presenting the driver with customized scenarios, and measuring their reactions to those scenarios using a variety of standard psychology techniques, such as EEG. Our system utilizes a variety of software components such as scenario management, artificial intelligence, image generation, and content creation. This thesis describes the use of one software component, the Presagis AI.implant. The AI.implant is an artificial intelligence system used to control autonomous characters within the simulation, which the driver can interact with. The AI.implant has also been extended to allow for more possible experiment scenarios, and to improve the quality of the simulation. These extensions include: the addition of signal lights for vehicles, emergency vehicle characters, and improved character movement at intersections. This thesis demonstrates that an artificial intelligence is a useful component of a more complex simulation, in order to promote further research in this field.</p> / Master of Applied Science (MASc)

<p>Vibrating screens are mechanical machines used to sort granulated materials based on their particle size. Utilized in the mining industry, these machines can sort tonnes of materials per hour. In the past, McMaster University developed sensor devices that measure and transmit vibration data of these machines to a central data acquisition unit for analysis, tuning, and maintenance purposes. In this thesis, I present the development of two new software systems that are used to process, manage, and present the information gained from these measurements. The first system, the offline vibration analysis software, is used to analyze the vibration data in both time and frequency domain, and presents the measured and calculated data in textual and graphical forms. The second system, the online vibration analysis software, is used by vibrating screens manufacturers and their customers to gather and manage vibration data collected from their vibrating screens by utilizing a central storage. The development process of these systems followed an iterative and incremental approach with continuous feedback from stakeholders. It included extensive requirements gathering to define a model, in terms of data representation, that captures the business logic and practices of the industry. Furthermore, it used standard architectures such as Model View Controller (MVC) and advanced technologies such as Object Relationship Mapping (ORM) for data access to increase flexibility and maintainability. Finally, comprehensive unit testing and thorough security risks evaluation were conducted in order to ensure that these systems are secure and bug free.</p> / Master of Applied Science (MASc)

<p>Free solidification molecular dynamics simulations were used to study solute trapping behaviour in the Ni-Cu alloy system. The segregation coefficient, K, as a function of crys- tallization rate was compared with several theories of trapping and, in agreement with a model proposed by Sobolev, it was found that complete trapping (K=1) occurs at a finite velocity. In order to gain further insight into the thermodynamic and kinetic factors affect- ing solute trapping, forced velocity phase field crystal (PFC) simulations were performed on a model binary alloy. We find that the complete trapping limit only occurs if a com- bination of wave-like and diffusive dynamics equation of motion of the PFC alloy model. Finally, an amplitude expansion analysis of the PFC formulation for constant velocity so- lidification was performed and an analytic expression for the complete trapping limit and solute drag was obtained.</p> / Doctor of Philosophy (PhD)

<p>This thesis documents research encompassing the design of dynamic electronic performance support systems. Essentially, an Electronic Performance Support System (EPSS) is complex distributed software that provides on-the-job support in order to facilitate task performance within some particular target application domain. In view of the rapid pace of change in current business and industrial environments, the conventional practice of issuing a new release of Electronic Performance Support System (EPSS) every few years to incorporate changes, is no longer practical. An EPSS is required to adapt to the changes as soon as possible and without the need for major code modification. This is accomplished by creating a design in which task specific knowledge is not hard coded in the software but is extracted on the fly. The design also enables a loose coupling among different modules of the system so that functionalities may be added, removed, modified or extended with minimum disruption. In this thesis we show how to combine service-oriented architecture with the concepts of software agents to achieve a software architecture that provides the required agility. Traditionally Unified Modeling Language (UML), which lacks formal semantics, has been the tool of choice for design and analysis of such systems and that means formal analysis techniques cannot be used for verification of UML models, whereas Software Engineering practices require analysis and verification at an early stage in the software development process. In this thesis we present an algorithm to transform UML state chart models to Object Coloured Petri (OCP) nets that have a strong mathematical foundation and can be implemented by standard tools such as Design/CPN for simulation and dynamic analysis in order to verify behavioural properties of the model. We show how to apply this technique to verify some of the desirable behavioural properties of the proposed EPSS architecture. To demonstrate the feasibility of our approach we have successfully implemented a prototype of an EPSS based on the proposed design.</p> <p>The main contributions of this research are: 1. Proposed an anthropomorphic architecture for a dynamic PSS. 2. Combined the concepts of services oriented architecture and software agents to achieve dynamic updating of task specific knowledge and minimal coupling between different modules of complex software to allow painless evolution. 3. Brought formal methods to the design phase in the development of agent based software systems by proposing an algorithm to transform UML state diagrams to OCP nets for dynamic analysis. 4. Modelled the dynamic creation and deletion of objects/agents using OCP net concepts and Design/CPN. 5. Proposed an architecture that can be used for creating families of agile PSS.</p> / Doctor of Philosophy (PhD)

<p>Multi-input multi-output (MIMO) systems are expected to playa crucial role in future wireless communications and a significant increase of interest in all aspects of MIMO system design has been seen in the past decade. The primary interest of this thesis is in the receiver part of the MIMO system. In this area, continuous interest has been shown in developing blind-adaptive decoding algorithms. While blind decoding algorithms improve data throughput by enabling the system de:signer to replace training symbols with data, they also tend to perform robustly against any environment disturbances, compared to their training-based counterparts. On the other hand, considering the fact that the wireless end user environment is becoming increasingly mobile, adaptive algorithms have the ability to improve the performance of a system regardless of whether it is a blind system or a training-based one. The primary difficulty faced by blind and adaptive algorithms is that they generally are computationally intense. In this thesis, we develop semi-blind and blind decoding algorithms that are adaptive in nature as well as computationally efficient for multi-antenna systems.</p> <p>First, we consider the problem of channel tracking for MIMO communication systems where the MIMO channel is time-varying. We consider a class of MIMO systems where orthogonal space-time block codes (OSTBCs) are used as the underlying space-time coding schemes. For a general MIMO system with any number of transmitting and receiving antenna combinations, a two-step MIMO channel tracking algorithm is proposed. As the first step, Kalman filtering is used to obtain an initial channel estimate for the current block based on the channel estimates obtained for previous blocks. Then, in the second step, the so-obtained initial channel estimate is refined using a decision-directed iterative method. We show that, due to specific properties of orthogonal space-time block codes, both the Kalman filter and the decision-directed algorithm can be significantly simplified. Then, we extend the above receiver for MIMO-OFDM systems and propose a computationally efficient semi-blind receiver for MIMO systems in frequency-selective channels. Further, for the proposed receivers, we have derived theoretical performance analysis in terms of probability of error. Assuming the knowledge of the transmitted symbols for the first block, we have derived the instantaneous signal to interference and noise ratio (SINR) for consecutive transmission blocks in the absence of training, by exploiting Kalman filtering to track the channel in a decision-directed mode. Later, we extend the the theoretical performance limit comparisons for time-domain vs. frequency-domain channel tracking for MIMO-OFDM systems. Further, we study the advantage of adaptive channel tracking algorithms in comptype pilot aided channel estimation schemes in practical MIMO-OFDM systems.</p> <p>After that, an efficient sequential Monte-Carlo (SMC) algorithm is developed for blind detection in MIMO systems where OSTBCs are used as the underlying space-time coding scheme. The proposed algorithm employs Rao-Blackwellization strategy to marginalize out the (unwanted) channel coefficients and uses optimal importance function to generate samples to propagate the posterior distribution. The algorithm is blind in the sense that, unlike the earlier ones, the transmission of training symbols is not required by this scheme. The marginalization involves the computation of (hundreds of) Kalman filters running in parallel resulting in intense computer requirement. We show that, the marginalization step can be significantly simplified for the speci1ied problem under no additional assumptions - resulting in huge computational savings. Further, we extend this result to frequency selective channels and propose a novel and efficient SMC receiver for MIMO-OFDM systems.</p> <p>Finally, a novel adaptive algorithm is presented for directional MIMO systems. Specifically, the problem of direction of arrivall (DOA) tracking of an unknown time-varying number of mobile sources is considered. The challenging part of the problem is the unknown, time-varying number of sources that demand a combination of source enumeration techniques and sequential state estimation methods to track the time-varying number of DOAs. In this thesis, we transform the problem into a novel state-space model, and, by employing probability hypothesis density (PHD) filtering technique, propose a simple algorithm that is able to track the number of sources as well as the corresponding directions of arrivals. In addition to the fact that the proposed algorithm is simple and easier to implement, simulation results show that, the PHD implementation yields superior performance over competing schemes in tracking rapidly varying number of targets.</p> / Doctor of Philosophy (PhD)

<p>Recent developments in signal processing called Compressive Sampling (CS) show that the measurement and reconstruction of sparse signals often requires fewer samples than is estimated by the sampling theorem. CS is a combination of a linear sampling scheme and a reconstruction method and, typically, the signal is assumed to be sparse, compressible, or having a prior distribution, with the reconstruction error measured in the \ell^2 norm. This thesis investigates the application of CS to turbulence signals, particularly for estimating some statistics or nonlinear functions of the signals. The main original research result of the thesis is a proposed method, Spectrum Estimation by Sparse Optimization (SpESO), which uses a priori information about isotropic homogeneous turbulent flows and the multilevel structure of wavelet transforms to reconstruct energy spectra from compressive measurements, with errors measured on a logarithmic scale. The method is tested numerically on a variety of 1D and 2D turbulence signals, and is able to approximate energy spectra with an order of magnitude fewer samples than with traditional fixed rate sampling. The results demonstrate that SpESO performs much better than Lumped Orthogonal Matching Pursuit (LOMP), and as well or better than wavelet-based best M-term methods in many cases, even though these methods require complete sampling of the signal before compression.</p> / Master of Science (MSc)

In the last two decades there has been an increasing interest in the field of haptics science. Real-time simulation of haptic interaction with non-rigid deformable object/tissue is computationally demanding. The computational bottleneck in finite- element (FE) modeling of deformable objects is in solving a large but sparse linear system of equations at each time step of the simulation. Depending on the mechanical properties of the object, high-fidelity stable haptic simulations require an update rate in the order of 100 − 1000 Hz. Direct software-based implementations that use conventional computers are fairly limited in the size of the model that they can process at such high rates. In this thesis, a new hardware-based parallel implementation of the iterative Conjugate Gradient (CG) algorithm for solving linear systems of equations is pro- posed. Sparse matrix-vector multiplication (SpMxV) is the main computational kernel in iterative solution methods such as the CG algorithm. Modern micro- processors exhibit poor performance in executing memory-bound tasks such as SpMxV. In the proposed hardware architecture, a novel organization of on-chip memory resources enables concurrent utilization of a large number of fixed-point computing units on a FPGA device for performing the calculations. The result is a powerful parallel computing platform that can iteratively solve the system of equations arising from the FE models of object deformation within the timing constraint of real-time haptics applications. Numerical accuracy of the fixed-point implementation, the hardware architecture design, and issues pertaining to the degree of parallelism and scalability of the solution are discussed in details. The proposed computing platform in this thesis is successfully employed in a set of haptic interaction experiments using static and dynamic linear FE-based models. / Master of Applied Science (MASc)

Programmers forgo existing solutions to problems in other programming lan- guages where software interoperation proves too cumbersome; they remake so- lutions, rather than reuse them. To facilitate reuse, interoperation must resolve language incompatibilities transparently. To address part of this problem, we present a model of computation that resolves incompatible lazy and eager eval- uation strategies using dual notions of evaluation contexts and values to mirror the lazy evaluation strategy in the eager one. This method could be extended to resolve incompatible evaluation strategies for any pair of languages with common expressions.