In order to investigate the formation of different types of pit shapes on the crystalline surfaces, a mathematical model has been considered, which does not take into account surface diffusion and which defines the removal or transformation of different characteristic sites on the surface according to a set of frequencies. The characteristic sites are defined according to Terrace-Ledge-Kink model for the simple cubic crystal. With the help of the geometry of the step systems, specific conditions have been obtained under which the step systems considered could be obtained for a pit of monoatomic thickness. The dissolution of a simple cubic crystal has been simulated according to a set of probabilities. / Thesis / Master of Engineering (ME)

Electrochemical conversion devices are a developing technology that prove to be a viable and more efficient alternative to current environmentally friendly generation devices. As such, constant research has been done in the last few decades to increase their applications and reliability. One of these systems, and the focus of this research, is the single cell Solid Oxide Fuel Cell (SOFC). These systems are a developing technology which main caveat is the need of high operating temperatures and costs. As such, most multidisciplinary research has been focused on researching materials and/or processes that help mitigate the costs or lower the operating temperature. The research presented in this paper focused on the manufacturing of a cubic stabilized zirconia (CSZ) electrolyte thin membrane for a single cell SOFC through tape casting. Thus, the process was divided into slurry preparation, tape casting, further processing, and analysis of samples. First the tape was produced reaching optimal viscosity (between 500 to 6000 cP) and minimizing impurities. Then, the slurry was poured into the doctor's blade with a 200 micrometers gap and allowed to dry. Samples were punched from the green tape with a diameter of 28 inches. Afterwards, these samples were pressed and sintered with a force of 218016 N and temperature of 1550 degrees celsius, respectively. These steps are done to maximize density and grain growth and minimize porosity. Lastly, the tape went further analysis and it was stated that further research should be done to determine this tape viability for stationary SOFC application.

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Yes / In engineering design, there are many functional relationships which are difficult to express into a simple and exact mathematical formula. Instead they are documented within a form of line graphs (or plot charts or curve diagrams) in engineering handbooks or text books. Because the information in such a form cannot be used directly in the modern computer aided design (CAD) process, it is necessary to find a way to numerically represent the information. In this paper, a data processing system for numerical representation of line graphs in mechanical design is developed, which incorporates the process cycle from the initial data acquisition to the final output of required information. As well as containing the capability for curve fitting through Cubic spline and Neural network techniques, the system also adapts a novel methodology for use in this application: Grey Models. Grey theory have been used in various applications, normally involved with time-series data, and have the characteristic of being able to handle sparse data sets and data forecasting. Two case studies were then utilized to investigate the feasibility of Grey models for curve fitting. Furthermore, comparisons with the other two established techniques show that the accuracy was better than the Cubic spline function method, but slightly less accurate than the Neural network method. These results are highly encouraging and future work to fully investigate the capability of Grey theory, as well as exploiting its sparse data handling capabilities is recommended.

The mammalian cochlea has been the inspiration to develope contemporary cochlear implants and active dynamic sensors that operate in the sensor's resonance region and possess favorable nonlinear characteristics. In the present work, multi-channel and self-sensing active artificial hair cells (AHCs) made of piezoelectric cantilevers and controlled by a cubic damping feedback controller are developed numerically and experimentally. These novel AHCs function near a Hopf bifurcation and amplify or compress the output by a one-third power-law relationship with the input, analogous to the mammalian cochlear amplifier. The multi-channel AHCs have extended frequency bandwidth to sense over multiple resonant frequencies, unlike conventional single-channel AHCs. Therefore, the adoption of these AHCs reduces the number of required sensors to cover the desired bandwidth of interest in an array format. Furthermore, a novel self-sensing active AHC is created in this study using quadmorph beams for future cochlear implants or sensor design applications. The self-sensing scheme allows miniaturization of the system, embedding AHCs in a limited space, and fabrication of AHC arrays by omitting external sensors from the system for practical implementation. Preliminary research on the extension of this research to MEMS AHCs and arrays of AHCs is also presented. The active AHCs can lead to transformative improvements in the dynamic range, sharpness of the response, and threshold of sound detection in cochlear implants to aid individuals with sensorineural hearing loss. Additionally, they can enhance the dynamic properties of sensors such as fluid flow sensors, microphones, and vibration sensors for various applications. / Doctor of Philosophy / In the mammalian auditory system, the acoustic wave that enters the ear canal is transmitted to the cochlea of the inner ear where it is decomposed into its frequency components. The cochlea then amplifies faint sounds and compresses high-level signals and as these processes stop due to damage, severe hearing loss occurs. Therefore, the present work is focused on developing artificial hair cells (AHCs) that can accurately replicate cochlea's behavior and aid the creation of prostheses for hearing restoration. In this work, the AHC is a beam with piezoelectric layers that is integrated with a control system designed to apply the cochlea-like amplification/compression on the beam. Experimental and simulation results show that the AHC is able to amplify or compress the output based on its input level similar to the mammalian cochlea. In contrast to previous designs of AHCs where each AHC could sense a single frequency, the system developed in this work possesses multiple sensing channels to increase the frequency range of the AHC. Furthermore, the development of a novel self-sensing scheme allows the omission of the external sensor that was required for the AHC operation in previous devices. This advancement in the self-sensing AHC design paves the way for creating fully implantable AHCs to replace the damaged parts of the cochlea. These multi-channel self-sensing AHCs have the potential to be used in the creation of cochlear implants, or sensors such as accelerometers, microphones, and hydrophones with improved dynamic properties. AHCs with different lengths, i.e. different sensing frequencies, can be mounted in an array format to cover the speech frequency range for speech recognition in individuals with hearing loss.

Volume rendering, the direct display of data from 3D scalar fields, is an area of computer graphics still in its infancy. Only recently has graphics hardware advanced to a state where volume rendering became feasible. Volume rendering requires the analysis of large amounts of data, typically tens of megabytes. As hardware speeds increase, we can only expect the datasets to get larger. This thesis describes a reasonably fast, space efficient algorithm for volume rendering. The algorithm is device independent since it is written as an X Windows client. It makes no graphics calls to dedicated graphics hardware, but allows the X server to take advantage of such hardware when it exists. It can be run on any machine that supports X Windows, from an IBM-PC to a high-end graphics workstation. It produces a perspective projection of the volume, since perspective projections are generally easier to interpret than parallel projections. The algorithm uses progressive refinement to give the user a quick view of the dataset and how it is oriented. If a different orientation or dataset is desired, the user may interrupt the rendering process. Once the desired dataset and position have been determined, the progressive refinement process continues and the image improves in quality until the greatest level of detail is displayed. While this algorithm may not be as fast as algorithms written specifically for dedicated graphics hardware, its overall rendering time is acceptable. Hardware vendors who develop X servers that take advantage of their graphics capabilities will only enhance the performance of our algorithm. The device independence this algorithm provides is a major benefit for people who work in an environment of mixed hardware platforms. / Master of Science

Internet of Things (IoT) is the idea that every device around us is connected and these devices continually collect and communicate data for analysis at a large scale in order to enable better end user experience, resource utilization and device performance. Therefore, data is central to the concept of IoT and the amount being collected is growing at an unprecedented rate. Current networking systems and hardware are not fully equipped to handle influx of data at this scale which is a serious problem because it can lead to erroneous interpretation of the data resulting in low resource utilization and bad end user experience defeating the purpose of IoT. This thesis aims at improving data transportation for IoT. In IoT systems, devices are connected to one or more cloud services over the internet via an access link. The cloud processes the data sent by the devices and sends back appropriate instructions. Hence, the performance of the two ends of the network ie the access networks and datacenter network, directly impacts the performance of IoT. The first portion of the our research targets improvement of the access networks by improving access link (router) design. Among the important design aspects of routers is the size of their output buffer queue. %Selecting an appropriate size of this buffer is crucial because it impacts two key metrics of an IoT system: 1) access link utilization and 2) latency. We have developed a probabilistic model to calculate the size of the output buffer that ensures high link utilization and low latency for packets. We have eliminated limiting assumptions of prior art that do not hold true for IoT. Our results show that for TCP only traffic, buffer size calculated by the state of the art schemes results in at least 60% higher queuing delay compared to our scheme while achieving almost similar access link utilization, loss-rate, and goodput. For UDP only traffic, our scheme achieves at least 91% link utilization with very low queuing delays and aggregate goodput that is approx. 90% of link capacity. Finally, for mixed traffic scenarios our scheme achieves higher link utilization than TCP only and UDP only scenarios as well as low delays, low loss-rates and aggregate goodput that is approx 94% of link capacity. The second portion of the thesis focuses on datacenter networks. Applications that control IoT devices reside here. Performance of these applications is affected by the choice of TCP used for data communication between Virtual Machines (VM). However, cloud users have little to no knowledge about the network between the VMs and hence, lack a systematic method to select a TCP variant. We have focused on characterizing TCP Cubic, Reno, Vegas and DCTCP from the perspective of cloud tenants while treating the network as a black box. We have conducted experiments on the transport layer and the application layer. The observations from our transport layer experiments show TCP Vegas outperforms the other variants in terms of throughput, RTT, and stability. Application layer experiments show that Vegas has the worst response time while all other variants perform similarly. The results also show that different inter-request delay distributions have no effect on the throughput, RTT, or response time. / Master of Science / Internet of Things (IoT) is the idea that every electronic device around us, like watches, thermostats and even refrigerators, is connected to one another and these devices continually collect and communicate data. This data is analyzed at a large scale in order to enable better user experience and improve the utilization and performance of the devices. Therefore, data is central to the concept of IoT and because of the unprecedented increase in the number of connected devices, the amount being collected is growing at an unprecedented rate. Current computer networks over which the data is transported, are not fully equipped to handle influx of data at this scale. This is a serious problem because it can lead to erroneous analysis of the data, resulting in low device utilization and bad user experience, hence, defeating the purpose of IoT. This thesis aims at improving data transportation for IoT by improving different components involved in computer networks. In IoT systems, devices are connected to cloud computing services over the internet through a router. The router acts a gateway to send data to and receive data from the cloud services. The cloud services act as the brain of IoT i.e. they process the data sent by the devices and send back appropriate instructions for the devices to perform. Hence, the performance of the two ends of the network i.e. routers in the access networks and cloud services in datacenter network, directly impacts the performance of IoT. The first portion of our research targets the design of routers. Among the important design aspects of routers is their size of their output buffer queue which holds the data packets to be sent out. We have developed a novel probabilistic model to calculate the size of the output buffer that ensures that the link utilization stays high and the latency of the IoT devices stays low, ensuring good performance. Results show that that our scheme outperforms state-of-the-art schemes for TCP only traffic and shows very favorable results for UDP only and mixed traffic scenarios. The second portion of the thesis focuses on improving application service performance in datacenter networks. Applications that control IoT devices reside in the cloud and their performance is directly affected by the protocol chosen to send data between different machines. However, cloud users have almost no knowledge about the configuration of the network between the machines allotted to them in the cloud. Hence, they lack a systematic method to select a protocol variant that is suitable for their application. We have focused on characterizing different protocols: TCP Cubic, Reno, Vegas and DCTCP from the perspective of cloud tenants while treating the network as a black-box (unknown). We have provided in depth analysis and insights into the throughput and latency behaviors which should help the cloud tenants make a more informed choice of TCP congestion control.