Appalachian writing brings a voice to the region that is often obstructed or excluded by popular culture throughout the United States. Crowded with stereotypes, many stories of Appalachian culture are misconstrued or never heard at all. This makes the work of modern Appalachian writers especially significant. Perhaps one of the best ways to reach a broader audience of people in this fast-paced digital time is through shorter writings, and in this thesis I will be presenting my process of writing modern flash fiction and poetry and of sharing the truths of working class, Appalachian people.

<p>Flash sintering was first demonstrated in 2010, where a ceramic green body was rapidly densified within seconds by applying an electric field during the heating process. The ultra-fast densification can occur as current abruptly flows through the material and self-heats by Joule heating. This process has potentials for large energy savings due to the reduction in furnace temperatures and shortened sintering time compared to conventional sintering. In addition, the ultra-high heating and cooling rates, along with the impact of electric field and current leads to the formation of unique non-equilibrium features in ceramics, which could greatly enhance their properties. Despite the potential of flash sintering, there are many challenges in moving this technique towards practical applications, such as the microstructure inhomogeneity and lack of understanding of the defects characteristics.</p> <p>In this dissertation, flash sintering was performed on ZnO to investigate the influence of various electrical conditions on the microstructure and defects. Detailed characterization was performed on flash sintered ZnO with and without a controlled current ramp, and contrasting types of current (DC and AC). These parameters show significant impact on the gradient microstructure and defects, and provide a way to tailor the desired characteristics for a wide range of applications. On the other hand, flash sintering of ZnO performed with a high electric field and low current density resulted in the growth of nanostructures. These nanostructures are unique compared to other growth techniques as they contain high density basal-plane stacking faults, and exhibit ultraviolet excitonic emission and red emission at room temperature. The nanostructure growth mechanism was investigated by varying the current density limit and revealed the formation of liquid phases which allowed growth by the vapor-liquid-solid mechanism. These findings present a new exciting route for flash sintering to produce highly defective nanostructures for device applications with new functionalities.</p>

Longer target-to-target intervals (TTI) produce greater P300 event-related potential amplitude, which can increase brain-computer interface (BCI) classification accuracy and decrease the number of flashes needed for accurate character classification. However, longer TTIs requires more time for each trial, which will decrease the information transfer rate of BCI. In this paper, a P300 BCI using a 7 × 12 matrix explored new flash patterns (16-, 18- and 21-flash pattern) with different TTIs to assess the effects of TTI on P300 BCI performance. The new flash patterns were designed to minimize TTI, decrease repetition blindness, and examine the temporal relationship between each flash of a given stimulus by placing a minimum of one (16-flash pattern), two (18-flash pattern), or three (21-flash pattern) non-target flashes between each target flashes. Online results showed that the 16-flash pattern yielded the lowest classification accuracy among the three patterns. The results also showed that the 18-flash pattern provides a significantly higher information transfer rate (ITR) than the 21-flash pattern; both patterns provide high ITR and high accuracy for all subjects.

P300 brain-computer interface (BCI) systems typically use a row/column (RC) approach. This article presents a P300 BCI based on a 12 × 7 matrix and new paradigmatic approaches to flashing characters designed to decrease the number of flashes needed to identify a target character. Using an RC presentation, a 12 × 7 matrix requires 19 flashes to present all items twice (12 columns and seven rows) per trial. A 12 × 7 matrix contains 84 elements (characters). To identify a target character in 12 × 7 matrix using the RC pattern, 19 flashes (sub-trials) are necessary. In each flash, the selected characters (one column or one row in the RC pattern) are flashing. We present four new paradigms and compare the performance to the RC paradigm. These paradigms present quasi-random groups of characters using 9, 12, 14 and 16 flashes per trial to identify a target character. The 12-, 14- and 16-flash patterns were optimized so that the same character never flashed twice in succession. We assessed the practical bit rate and classification accuracy of the 9-, 12-, 14-, 16- and RC (19-flash) pattern conditions in an online experiment and with offline simulations. The results indicate that 16-flash pattern is better than other patterns and performance of an online P300 BCI can be significantly improved by selecting the best presentation paradigm for each subject.

This dissertation introduces desalination processes in general and multistage flash (MSF) and reverse osmosis (RO) in particular. It presents the fundamental and practical aspects of neural networks and provides an overview of their structures, topology, strengths, and limitations. This study includes the neural network applications to prediction problems of large-scale commercial MSF and RO desalination plants in conjunction with statistical techniques to identify the major independent variables to optimize the process performance. In contrast to several recent studies, this work utilizes actual operating data (not simulated) from a large-scale commercial MSF desalination plant (48 million gallonsper day capacity, MGPD) and RO plant (15 MGPD) located in Kuwait and the Kingdom of Saudi Arabia, respectively. We apply Neural Works Professional II/Plus (NeuralWare, 1993) and SAS (SAS Institute Inc., 1996) software to accomplish this task. This dissertation demonstrates how to apply modular and equation-solving approaches for steady-state and dynamic simulations of large-scale commercial MSF desalination plants using ASPEN PLUS (Advanced System for Process Engineering PLUS) and SPEEDUP (Simulation Program for Evaluation and Evolutionary Design of Unsteady Processes) marketed by Aspen Technology, Cambridge, MA. This work illustrates the development of an optimal operating envelope for achieving a stable operation of a commercial MSF desalination plant using the SPEEDUP model. We then discuss model linearization around nominal operating conditions and arrive at pairing schemes for manipulated and controlled variables by interaction analysis. Finally, this dissertation describes our experience in applying a commercial software, DynaPLUS, for combined steady-state and dynamic simulations of a commercial MSF desalination plant. This dissertation is unique and significant in that it reports the first comprehensive study of predictive modeling, simulation, and optimization of large-scale commercial desalination plants. It is the first detailed and comparative study of commercial desalination plants using both artificial intelligence and computer-aided design techniques. The resulting models are able to reproduce accurately the actual operating data and to predict the optimal operating conditions of commercial desalination plants. / Ph. D.

This research aims to investigate the application of infrared thermography (IRT) as a method of nondestructive evaluation (NDE) for the detection of defects in the rail base area. Rails have to withstand harsh conditions during their application. Therefore, defects can develop in the base area of rails due to stresses such as bending, shear, contact, and thermal stresses, fatigue, and corrosion. Such defects can cause catastrophic failures in the rails, ultimately leading to train derailments. Rail base defects due to fatigue and corrosion are difficult to detect and currently there are no reliable or practical non-destructive evaluation (NDE) methods for finding these types of defects in the revenue service. Transportation Technology Center, Inc. (TTCI) had previously conducted a research on the capability of flash IRT to detect defects in rail base area based on simulation approach. The research covered in this thesis is the continuation of the same project.In this research, three rail samples were prepared with each containing a notched-edge, side-drilled holes (SDHs), and bottom-drilled holes (BDHs). Two steel sample blocks containing BDHs and SDHs of different sizes and depths were also prepared. Preliminary IRT trials were conducted on the steel samples to obtain an optimal IRT setup configuration. The initial inspections for one of the steel samples were outsourced to Thermal Wave Imaging (TWI) where they employed Thermographic Signal Reconstruction (TSR) technique to enhance the resulting images. Additional inspections of the steel samples were performed in the Southern Illinois University-Carbondale (SIUC) facility. In case of the rail samples, the SDHs and the notched-edge reflectors could not be detected in any of the experimental trials performed in this research. In addition, two more rail samples containing BDHs were prepared to investigate the detection capabilities for three different surface conditions: painted, unpainted, and rusted. The painted surface provided a best-case scenario for inspections while the other conditions offered further insight on correlating the application to industry-like cases.A 1300 W halogen lamp was employed as the heat source for providing continuous thermal excitation for various durations. Post-processing and analysis of the resulting thermal images was performed within the acquisition software using built-in analysis tools such as temperature probes, Region of Interest (ROI) based intensity profiles, and smoothing filters. The minimum defect diameter to depth (aspect) ratio detected in preliminary trials for the steel sample blocks were 1.0 at a diameter of 4.7625 mm (0.1875 in) and 1.5 at a diameter of 3.175 mm (0.125 in). For the inspection of painted rail sample, the longest exposure times (10 sec) provided the best detection capabilities in all sets of trials. The three holes having aspect ratio greater or equal to 1.0 were indicated in the thermal response of the painted and rusted samples while only the two holes having aspect ratio greater or equal to 1.5 were indicated in the unaltered sample. Indications of reflectors were identified through qualitative graphical analysis of pixel intensity distributions obtained along a bending line profile. The results obtained from the painted sample provided a baseline for analyzing the results from the unpainted and rusted rail samples. This provided an insight on the limitations and requirements for future development. The primary takeaway is the need for an optimized heat source. Poor contrast in the resulting image for the unpainted and rusted rail samples is experienced due to both noise and lack of penetration of the heat energy. This could have been due to decreased emissivity values. Moreover, the excitation method employed in this research does not comply with current industry standards for track clearances. Therefore, exploration of alternative excitation methods is recommended.

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第19183号 / 工博第4060号 / 新制||工||1626(附属図書館) / 32175 / 京都大学大学院工学研究科合成・生物化学専攻 / (主査)教授 吉田 潤一, 教授 杉野目 道紀, 教授 松原 誠二郎 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第20681号 / 工博第4378号 / 新制||工||1680(附属図書館) / 京都大学大学院工学研究科都市社会工学専攻 / (主査)教授 角 哲也, 准教授 竹門 康弘, 准教授 Sameh Kantoush / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

京都大学 / 0048 / 新制・課程博士 / 博士(理学) / 甲第20924号 / 理博第4376号 / 新制||理||1628(附属図書館) / 京都大学大学院理学研究科地球惑星科学専攻 / (主査)教授 田上 高広, 教授 山路 敦, 教授 平原 和朗 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DGAM

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