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Tesla Turbine Torque Modeling for Construction of a Dynamometer and Turbine

Description: While conventional turbines have been extensively researched and tested, Tesla and boundary layer type turbines have not. In order to construct a dynamometer, thermodynamic flow apparatus and future turbines, we modeled the Tesla turbine using theoretical calculations and preliminary experiments. Thus a series of experiments were run to determine stall torque and maximum run speed for a known pressure range. This data was then applied to modeling formulas to estimate stall torque over an extended range of variables. The data were then used to design an appropriate dynamometer and airflow experiment. The model data also served to estimate various specifications and power output of the future turbine. An Obi Laser SSTG‐001 Tesla turbine was used in the experiments described. Experimental stall torque measurements were conducted in two stages. Shaft speed measurements were taken with an optical laser tachometer and Tesla turbine stall torque was measured using a spring force gauge. Two methods were chosen to model Tesla turbine stall torque: 1) flow over flat plate and 2) free vortex with a sink. A functional dynamometer and thermodynamic apparatus were constructed once the model was confirmed to be within the experimental uncertainty. Results of the experiments show that the experimental turbine at 65 PSI has a speed of approximately 27,000 RPM and a measured stall torque of 0.1279 N‐m. 65 PSI is an important data point because that data set is the cut‐off from laminar to turbulent flow. Thus at 65 PSI, a rejection of the null hypothesis for research question one with respect to the flow over flat plate method can be seen from the data, while the vortex model results in a failure to reject the null hypothesis. In conclusion, the experimental turbine was seen to have a laminar and a turbulent flow regime at different air pressures, rather ...
Date: May 2011
Creator: Emran, Tamir Ali
Partner: UNT Libraries

A Study of the Synthesis and Surface Modification of UV Emitting Zinc Oxide for Bio-Medical Applications

Description: This thesis presents a novel ZnO-hydrogel based fluorescent colloidal semiconductor nanomaterial system for potential bio-medical applications such as bio-imaging, cancer detection and therapy. The preparation of ZnO nanoparticles and their surface modification to make a biocompatible material with enhanced optical properties is discussed. High quality ZnO nanoparticles with UV band edge emission are prepared using gas evaporation method. Semiconductor materials including ZnO are insoluble in water. Since biological applications require water soluble nanomaterials, ZnO nanoparticles are first dispersed in water by ball milling method, and their aqueous stability and fluorescence properties are enhanced by incorporating them in bio-compatible poly N-isopropylacrylamide (PNIPAM) based hydrogel polymer matrix. The optical properties of ZnO-hydrogel colloidal dispersion versus ZnO-Water dispersion were analyzed. The optical characterization using photoluminescence spectroscopy indicates approximately 10 times enhancement of fluorescence in ZnO-hydrogel colloidal system compared to ZnO-water system. Ultrafast time resolved measurement demonstrates dominant exciton recombination process in ZnO-hydrogel system compared to ZnO-water system, confirming the surface modification of ZnO nanoparticles by hydrogel polymer matrix. The surface modification of ZnO nanoparticles by hydrogel induce more scattering centers per unit area of cross-section, and hence increase the luminescence from the ZnO-gel samples due to multiple path excitations. Furthermore, surface modification of ZnO by hydrogel increases the radiative efficiency of this hybrid colloidal material system thereby contributing to enhanced emission.
Date: May 2009
Creator: John, Sween
Partner: UNT Libraries

An investigation into graph isomorphism based zero-knowledge proofs.

Description: Zero-knowledge proofs protocols are effective interactive methods to prove a node's identity without disclosing any additional information other than the veracity of the proof. They are implementable in several ways. In this thesis, I investigate the graph isomorphism based zero-knowledge proofs protocol. My experiments and analyses suggest that graph isomorphism can easily be solved for many types of graphs and hence is not an ideal solution for implementing ZKP.
Date: December 2009
Creator: Ayeh, Eric
Partner: UNT Libraries

Trajectories As a Unifying Cross Domain Feature for Surveillance Systems

Description: Manual video analysis is apparently a tedious task. An efficient solution is of highly importance to automate the process and to assist operators. A major goal of video analysis is understanding and recognizing human activities captured by surveillance cameras, a very challenging problem; the activities can be either individual or interactional among multiple objects. It involves extraction of relevant spatial and temporal information from visual images. Most video analytics systems are constrained by specific environmental situations. Different domains may require different specific knowledge to express characteristics of interesting events. Spatial-temporal trajectories have been utilized to capture motion characteristics of activities. The focus of this dissertation is on how trajectories are utilized in assist in developing video analytic system in the context of surveillance. The research as reported in this dissertation begins real-time highway traffic monitoring and dynamic traffic pattern analysis and in the end generalize the knowledge to event and activity analysis in a broader context. The main contributions are: the use of the graph-theoretic dominant set approach to the classification of traffic trajectories; the ability to first partition the trajectory clusters using entry and exit point awareness to significantly improve the clustering effectiveness and to reduce the computational time and complexity in the on-line processing of new trajectories; A novel tracking method that uses the extended 3-D Hungarian algorithm with a Kalman filter to preserve the smoothness of motion; a novel camera calibration method to determine the second vanishing point with no operator assistance; and a logic reasoning framework together with a new set of context free LLEs which could be utilized across different domains. Additional efforts have been made for three comprehensive surveillance systems together with main contributions mentioned above.
Date: December 2014
Creator: Wan, Yiwen
Partner: UNT Libraries

Evaluating the Feasibility of Accelerometers in Hand Gestures Recognition

Description: Gesture recognition plays an important role in human computer Interaction for intelligent computing. Major applications like Gaming, Robotics and Automated Homes uses gesture recognition techniques which diminishes the usage of mechanical devices. The main goal of my thesis is to interpret SWAT team gestures using different types of sensors. Accelerometer and flex sensors were explored extensively to build a prototype for soldiers to communicate in the absence of line of sight. Arm movements were recognized by flex sensors and motion gestures by Accelerometers. Accelerometers are used to measure acceleration in respect to movement of the sensor in 3D. Flex sensors changes its resistance based on the amount of bend in the sensor. SVM is the classification algorithm used for classification of the samples. LIBSVM (Library for Support Vector Machines) is integrated software for support vector classification, regression and distribution estimation which supports multi class classification. Sensors data is connected to the WI micro dig to digitize the signal and to transmit it wirelessly to the computing device. Feature extraction and Signal windowing were the two major factors which contribute for the accuracy of the system. Mean Average value and Standard Deviation are the two features considered for accelerometer sensor data classification and Standard deviation is used for the flex sensor analysis for optimum results. Filtering of the signal is done by identifying the different states of signals which are continuously sampled.
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Date: December 2014
Creator: Karlaputi, Sarada
Partner: UNT Libraries

Evaluation of Fine Particulate Matter Pollution Sources Affecting Dallas, Texas

Description: Dallas is the third largest growing industrialized city in the state of Texas. the prevailing air quality here is highly influenced by the industrialization and particulate matter 2.5µm (PM2.5) has been found to be one of the main pollutants in this region. Exposure to PM2.5 in elevated levels could cause respiratory problems and other health issues, some of which could be fatal. the current study dealt with the quantification and analysis of the sources of emission of PM2.5 and an emission inventory for PM2.5 was assessed. 24-hour average samples of PM2.5 were collected at two monitoring sites under the Texas Commission on Environmental Quality (TCEQ) in Dallas, Dallas convention Centre (CAMS 312) and Dallas Hinton sites (CAMS 60). the data was collected from January 2003 to December 2009 and by using two positive matrix models PMF 2 and EPA PMF the PM2.5 source were identified. 9 sources were identified from CAMS 312 of which secondary sulfate (31% by PMF2 and 26% by EPA PMF) was found to be one of the major sources. Data from CAMS 60 enabled the identification of 8 sources by PMF2 and 9 by EPA PMF. These data also confirmed secondary sulfate (35% by PMF2 and 34% by EPA PMF) as the major source. to substantiate the sources identified, conditional probability function (CPF) was used. the influence of long range transport pollutants such as biomass burns from Mexico and Central America was found to be influencing the region of study and was assessed with the help of potential source contribution function (PSCF) analysis. Weekend/weekday and seasonal analyses were useful in understanding the behavioral pattern of pollutants. Also an inter comparison of the model results were performed and EPA PMF results was found to be more robust and accurate than PMF 2 results.
Date: May 2012
Creator: Puthenparampil Koruth, Joseph
Partner: UNT Libraries

Hydrophobicity of Magnetite Coating on Low Carbon Steel

Description: Superhydrophobic coatings (SHC) with excellent self-cleaning and corrosion resistance property is developed on magnetite coated AISI SAE 1020 steel by using a simple immersion method. Roughness measurement, scanning electron microscopy (SEM), atomic force microscopy (AFM), X-ray diffraction (XRD), contact angle measurement (CAM), energy dispersive spectroscopy (EDS), Fourier transform infrared spectroscopy (FTIR), potentiodynamic polarization test, electrochemical impedance spectroscopy (EIS), and qualitative characterization of self-cleaning behavior, antifouling property and durability of the coatings are assessed. A water contact angle as high as 152o on the coated surface with excellent self-cleaning and resistivity to corrosion and good longevity in atmospheric air is obtained. Self-cleaning test results prove that these surfaces can find applications in large scale production of engineering materials. Potentiodynamic polarization tests and EIS tests confirm that the superhydrophobic low carbon steel surfaces have better resistance to corrosion compared to bare steel and magnetite coated steel in 3.5% NaCl solution. But the longevity of the coated steel surfaces in 3.5% salt solution is limited, which is revealed by the immersion durability test. However, hydrophobic coatings (HC) have better stability in normal tap water, and it can stay unharmed up to 15 days. Finally, hydrophobic coatings on low carbon steel surface retains hydrophobic in open atmosphere for more than two months. Results of this investigation show surface roughness is a critical factor in manufacturing hydrophobic steel surfaces. Higher contact angles are obtained for rougher and more uniform surfaces. A linear mathematical relationship (y =6x+104; R2 = 0.93) is obtained between contact angle (y) and surface roughness (x).
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Date: August 2018
Creator: Akhtar, Mst Alpona
Partner: UNT Libraries

Use of Bio-Product/Phase Change Material Composites in the Building Envelope for Building Thermal Control and Energy Savings

Description: This research investigates the bio-products/phase change material (PCM) composites for the building envelope application. Bio-products, such as wood and herb, are porous medium, which can be applied in the building envelope for thermal insulation purpose. PCM is infiltrated into the bio-product (porous medium) to form a composite material. The PCM can absorb/release large amount of latent heat of fusion from/to the building environment during the melting/solidification process. Hence, the PCM-based composite material in the building envelope can efficiently adjust the building interior temperature by utilizing the phase change process, which improves the thermal insulation, and therefore, reduces the load on the HVAC system. Paraffin wax was considered as the PCM in the current studies. The building energy savings were investigated by comparing the composite building envelope material with the conventional material in a unique Zero-Energy (ZØE) Research Lab building at University of North Texas (UNT) through building energy simulation programs (i.e., eQUEST and EnergyPlus). The exact climatic conditions of the local area (Denton, Texas) were used as the input values in the simulations. It was found that the EnergyPlus building simulation program was more suitable for the PCM based building envelope using the latent heat property. Therefore, based on the EnergyPlus simulations, when the conventional structure insulated panel (SIP) in the roof and wall structures were replaced by the herb panel or herb/PCM composite, it was found that around 16.0% of energy savings in heating load and 11.0% in cooling load were obtained by using PCM in the bio-product porous medium.
Date: August 2018
Creator: Boozula, Aravind Reddy
Partner: UNT Libraries

Room and Elevated Temperature Sliding Wear Behavior of Cold Sprayed Ni-WC Composite Coatings

Description: The tribological properties of cold sprayed Ni-WC metal matrix composite (MMC) coatings were investigated under dry sliding conditions from room temperature (RT) up to 400°C, and during thermal cycling to explore their temperature adaptive friction and wear behavior. Characterization of worn surfaces was conducted using scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and Raman spectroscopy to determine the chemical and microstructural evolution during friction testing. Data provided insights into tribo-oxide formation mechanisms controlling friction and wear. It was determined that the steady-state coefficient of friction (CoF) decreased from 0.41 at RT to 0.32 at 400˚C, while the wear rate increased from 0.5×10-4 mm3/N·m at RT to 3.7×10-4 mm3/N·m at 400˚C. The friction reduction is attributed primarily to the tribochemical formation of lubricious NiO on both the wear track and transfer film adhered to the counterface. The increase in wear is attributed to a combination of thermal softening of the coating and a change in the wear mechanism from adhesive to more abrasive. In addition, the coating exhibited low friction behavior during thermal cycling by restoring the lubricious NiO phase inside the wear track at high temperature intervals. Therefore, cold sprayed Ni-WC coatings are potential candidates for elevated temperature and thermally self-adaptive sliding wear applications.
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Date: August 2018
Creator: Torgerson, Tyler B.
Partner: UNT Libraries

Microcantilever Based Viscosity Measurement as it Applies to Oscillation Amplitude Response

Description: The goal of this research is to measure viscosity via the analysis of amplitude response of a piezo driven vibrating cantilevers partially immersed in a viscous medium. As a driving frequency is applied to a piezoceramic material, the external forces acting on the system will affect its maximum amplitude. This thesis applies this principle through experimental and analytical analyses of the proportional relationship between viscosity and the amplitude response of the first natural frequency mode of the sinusoidal vibration. Currently, the few cantilever-based viscometer designs that exist employ resonant frequency response as the parameter by which the viscosity is correlated. The proposed piezoelectric viscometer employs amplitude response in lieu of resonant frequency response. The goal of this aspect of the research was to provide data confirming amplitude response as a viable method for determining viscosity. A miniature piezoelectric plate was mounted to a small stainless-steel cantilever beam. The tip of the cantilever was immersed within various fluid test samples. The cantilever was then swept through a range of frequencies in which the first frequency mode resided. The operating principle being as the viscosity of the fluid increases the amplitude response of cantilever vibration will decrease relatively. What was found was in fact an inversely exponential relationship between dynamic viscosity and the cantilever beam's vibrational amplitude response. The experiment was performed using three types of cantilevers as to experimentally test the sensitivity of each.
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Date: August 2018
Creator: Siegel, Sanford H.
Partner: UNT Libraries

Laser Surface Modification of AZ31B Mg Alloy Bio-Implant Material

Description: Magnesium and its alloys are considered as the potential biomaterials due to their biocompatibility and biodegradable characteristics but suffer from poor corrosion performance. Various surface modification techniques are employed to improve their corrosion resistance. In present case, laser surface melting was carried out on AZ31B Mg alloy with various laser energy densities using a continuous wave ytterbium laser. Effect of laser treatment on phase and microstructure evolution was evaluated by X ray diffraction and scanning electron microscopy. Multi-physics thermal model predicted time temperature evolution along the depth of the laser treatment zone. Additionally, electrochemical method and bio-immersion test were employed to evaluate the corrosion behavior in simulated body fluid medium. Microstructure revealed grain refinement and even distribution of Mg17Al12 phase along the grain boundary for laser treated samples leading to substantial enhancement in the corrosion resistance of the laser treated samples compared to the untreated alloy. The laser processed samples also possessed a superior wettability in SBF solution than the untreated sample. This was further reflected in enhanced bio-integration behavior of laser processed samples. By changing the parameters of laser processing such as power, scanning speed, and fill spacing, a controllable corrosion resistance and bioactivity/biocompatibility of the implant material was achieved.
Date: August 2018
Creator: Wu, Tso-chang
Partner: UNT Libraries

Multi-Modal Insider Threat Detection and Prevention based on Users' Behaviors

Description: Insider threat is one of the greatest concerns for information security that could cause more significant financial losses and damages than any other attack. However, implementing an efficient detection system is a very challenging task. It has long been recognized that solutions to insider threats are mainly user-centric and several psychological and psychosocial models have been proposed. A user's psychophysiological behavior measures can provide an excellent source of information for detecting user's malicious behaviors and mitigating insider threats. In this dissertation, we propose a multi-modal framework based on the user's psychophysiological measures and computer-based behaviors to distinguish between a user's behaviors during regular activities versus malicious activities. We utilize several psychophysiological measures such as electroencephalogram (EEG), electrocardiogram (ECG), and eye movement and pupil behaviors along with the computer-based behaviors such as the mouse movement dynamics, and keystrokes dynamics to build our framework for detecting malicious insiders. We conduct human subject experiments to capture the psychophysiological measures and the computer-based behaviors for a group of participants while performing several computer-based activities in different scenarios. We analyze the behavioral measures, extract useful features, and evaluate their capability in detecting insider threats. We investigate each measure separately, then we use data fusion techniques to build two modules and a comprehensive multi-modal framework. The first module combines the synchronized EEG and ECG psychophysiological measures, and the second module combines the eye movement and pupil behaviors with the computer-based behaviors to detect the malicious insiders. The multi-modal framework utilizes all the measures and behaviors in one model to achieve better detection accuracy. Our findings demonstrate that psychophysiological measures can reveal valuable knowledge about a user's malicious intent and can be used as an effective indicator in designing insider threat monitoring and detection frameworks. Our work lays out the necessary foundation to establish a new generation ...
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Date: August 2018
Creator: Hashem, Yassir
Partner: UNT Libraries

Computational Methods to Optimize High-Consequence Variants of the Vehicle Routing Problem for Relief Networks in Humanitarian Logistics

Description: Optimization of relief networks in humanitarian logistics often exemplifies the need for solutions that are feasible given a hard constraint on time. For instance, the distribution of medical countermeasures immediately following a biological disaster event must be completed within a short time-frame. When these supplies are not distributed within the maximum time allowed, the severity of the disaster is quickly exacerbated. Therefore emergency response plans that fail to facilitate the transportation of these supplies in the time allowed are simply not acceptable. As a result, all optimization solutions that fail to satisfy this criterion would be deemed infeasible. This creates a conflict with the priority optimization objective in most variants of the generic vehicle routing problem (VRP). Instead of efficiently maximizing usage of vehicle resources available to construct a feasible solution, these variants ordinarily prioritize the construction of a minimum cost set of vehicle routes. Research presented in this dissertation focuses on the design and analysis of efficient computational methods for optimizing high-consequence variants of the VRP for relief networks. The conflict between prioritizing the minimization of the number of vehicles required or the minimization of total travel time is demonstrated. The optimization of the time and capacity constraints in the context of minimizing the required vehicles are independently examined. An efficient meta-heuristic algorithm based on a continuous spatial partitioning scheme is presented for constructing a minimized set of vehicle routes in practical instances of the VRP that include critically high-cost penalties. Multiple optimization priority strategies that extend this algorithm are examined and compared in a large-scale bio-emergency case study. The algorithms designed from this research are implemented and integrated into an existing computational framework that is currently used by public health officials. These computational tools enhance an emergency response planner's ability to derive a set of vehicle routes specifically ...
Date: August 2018
Creator: Urbanovsky, Joshua C
Partner: UNT Libraries

Dataflow Processing in Memory Achieves Significant Energy Efficiency

Description: The large difference between processor CPU cycle time and memory access time, often referred to as the memory wall, severely limits the performance of streaming applications. Some data centers have shown servers being idle three out of four clocks. High performance instruction sequenced systems are not energy efficient. The execute stage of even simple pipeline processors only use 9% of the pipeline's total energy. A hybrid dataflow system within a memory module is shown to have 7.2 times the performance with 368 times better energy efficiency than an Intel Xeon server processor on the analyzed benchmarks. The dataflow implementation exploits the inherent parallelism and pipelining of the application to improve performance without the overhead functions of caching, instruction fetch, instruction decode, instruction scheduling, reorder buffers, and speculative execution used by high performance out-of-order processors. Coarse grain reconfigurable logic in an energy efficient silicon process provides flexibility to implement multiple algorithms in a low energy solution. Integrating the logic within a 3D stacked memory module provides lower latency and higher bandwidth access to memory while operating independently from the host system processor.
Date: August 2018
Creator: Shelor, Charles F.
Partner: UNT Libraries

Reconfigurable Aerial Computing System: Design and Development

Description: In situations where information infrastructure is destroyed or not available, on-demand information infrastructure is pivotal for the success of rescue missions. In this paper, a drone-carried on-demand information infrastructure for long-distance WiFi transmission system is developed. It can be used in the areas including emergency response, public event, and battlefield. In years development, the Drone WIFI System has developed from single-CPU platform, twin-CPU platform, Atmega2560 platform to NVIDIA Jetson TX2 platform. By the upgrade of the platform, the hardware shows more and more reliable and higher performance which make the application of the platform more and more exciting. The latest TX2 platform can provide real time and thermal video transmission, also application of deep learning of object recognition and target tracing. All these up-to-date technology brings more application scenarios to the system. Therefore, the system can serve more people in more scenarios.
Date: August 2018
Creator: Gu, Yixin
Partner: UNT Libraries

Simulation of Dengue Outbreak in Thailand

Description: The dengue virus has become widespread worldwide in recent decades. It has no specific treatment and affects more than 40% of the entire population in the world. In Thailand, dengue has been a health concern for more than half a century. The highest number of cases in one year was 174,285 in 1987, leading to 1,007 deaths. In the present day, dengue is distributed throughout the entire country. Therefore, dengue has become a major challenge for public health in terms of both prevention and control of outbreaks. Different methodologies and ways of dealing with dengue outbreaks have been put forward by researchers. Computational models and simulations play an important role, as they have the ability to help researchers and officers in public health gain a greater understanding of the virus's epidemic activities. In this context, this dissertation presents a new framework, Modified Agent-Based Modeling (mABM), a hybrid platform between a mathematical model and a computational model, to simulate a dengue outbreak in human and mosquito populations. This framework improves on the realism of former models by utilizing the reported data from several Thai government organizations, such as the Thai Ministry of Public Health (MoPH), the National Statistical Office, and others. Additionally, its implementation takes into account the geography of Thailand, as well as synthetic mosquito and synthetic human populations. mABM can be used to represent human behavior in a large population across variant distances by specifying demographic factors and assigning mobility patterns for weekdays, weekends, and holidays for the synthetic human population. The mosquito dynamic population model (MDP), which is a component of the mABM framework, is used for representing the synthetic mosquito population dynamic and their ecology by integrating the regional model to capture the effect of dengue outbreak. The two synthetic populations can be linked to each other ...
Date: August 2018
Creator: Meesumrarn, Thiraphat
Partner: UNT Libraries

Heat Transfer in Low Dimensional Materials Characterized by Micro/Nanoscale Thermometry

Description: In this study, the thermal properties of low dimensional materials such as graphene and boron nitride nanotube were investigated. As one of important heat transfer characteristics, interfacial thermal resistance (ITR) between graphene and Cu film was estimated by both experiment and simulation. In order to characterize ITR, the micropipette sensing technique was utilized to measure the temperature profile of suspended and supported graphene on Cu substrate that is subjected to continuous wave laser as a point source heating. By measuring the temperature of suspended graphene, the intrinsic thermal conductivity of suspended graphene was measured and it was used for estimating interfacial thermal resistance between graphene and Cu film. For simulation, a finite element method and a multiparameter fitting technique were employed to find the best fitting parameters. A temperature profile on a supported graphene on Cu was extracted by a finite element method using COMSOL Multiphysics. Then, a multiparameter fitting method using MATLAB software was used to find the best fitting parameters and ITR by comparing experimentally measured temperature profile with simulation one. In order to understand thermal transport between graphene and Cu substrate with different interface distances, the phonon density of states at the interface between graphene and Cu substrate was calculated by MD simulation.As another low dimensional material for thermal management applications, the thermal conductivity of BNNT was measured by nanoscale thermometry. For this work, a noble technique combining a focused ion beam (FIB) and nanomanipulator was employed to pick and to place a single BNNT on the desired location. The FIB technology was used to make nanoheater patterns (so called nanothermometer) on a prefabricated microelectrode device by conventional photolithography processes. With this noble technique and the nanoheater thermometry, the thermal conductivity of BNNT was successfully characterized by temperature gradient and heat flow measurements through BNNT.
Date: August 2018
Creator: Jeong, Jae Young
Partner: UNT Libraries

Ultrasonic Processing of Aluminum 2139 and 7050

Description: Acoustics is the study of all sound waves, with ultrasound classified as those frequencies above 20,000 Hz. Currently, ultrasound is being used in many industries for a variety of purposes such as ultrasonic imaging, ultrasonic assisted friction stir welding, and ultrasonic spot welding. Despite these uses, the effects of ultrasound on phase stability and resultant mechanical properties has been minimally analyzed. Here we study the impact waves play in ultrasonic welding and design an apparatus to maximize waves entering aluminum alloy samples. Aluminum 2139 and 7050 are used because they are precipitation strengthened by metastable phases so temperature change, and the corresponding phase stability, can greatly impact their strength. Results suggest that the ultrasonic welder primarily imposes a localized temperature spike due to friction, averaging over 200°C in a few seconds, which generally lowers the Vickers hardness due to coarsening or even dissolution of strengthening precipitates. Conversely, the new design increases the Vickers hardness by up to 30% over the initial hardness of approximately 63HV for aluminum 2139 and 83HV for aluminum 7050, respectively, while only increasing the temperature by an average of approximately 10°C. This new design was unable to achieve peak hardness, but the strengthening it achieved in two minutes was equivalent to one month of natural aging. If this system was able to be fine-tuned, it could serve as a quick strengthening process for recently weakened aluminum alloys, such as after friction stir welding.
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Date: August 2018
Creator: Reed, Jordan Derek
Partner: UNT Libraries

Reading with Robots: A Platform to Promote Cognitive Exercise through Identification and Discussion of Creative Metaphor in Books

Description: Maintaining cognitive health is often a pressing concern for aging adults, and given the world's shifting age demographics, it is impractical to assume that older adults will be able to rely on individualized human support for doing so. Recently, interest has turned toward technology as an alternative. Companion robots offer an attractive vehicle for facilitating cognitive exercise, but the language technologies guiding their interactions are still nascent; in elder-focused human-robot systems proposed to date, interactions have been limited to motion or buttons and canned speech. The incapacity of these systems to autonomously participate in conversational discourse limits their ability to engage users at a cognitively meaningful level. I addressed this limitation by developing a platform for human-robot book discussions, designed to promote cognitive exercise by encouraging users to consider the authors' underlying intentions in employing creative metaphors. The choice of book discussions as the backdrop for these conversations has an empirical basis in neuro- and social science research that has found that reading often, even in late adulthood, has been correlated with a decreased likelihood to exhibit symptoms of cognitive decline. The more targeted focus on novel metaphors within those conversations stems from prior work showing that processing novel metaphors is a cognitively challenging task, for young adults and even more so in older adults with and without dementia. A central contribution arising from the work was the creation of the first computational method for modelling metaphor novelty in word pairs. I show that the method outperforms baseline strategies as well as a standard metaphor detection approach, and additionally discover that incorporating a sentence-based classifier as a preliminary filtering step when applying the model to new books results in a better final set of scored word pairs. I trained and evaluated my methods using new, large corpora from two sources, ...
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Date: August 2018
Creator: Parde, Natalie
Partner: UNT Libraries

Secure and Trusted Execution for Virtualization Workloads

Description: In this dissertation, we have analyzed various security and trustworthy solutions for modern computing systems and proposed a framework that will provide holistic security and trust for the entire lifecycle of a virtualized workload. The framework consists of 3 novel techniques and a set of guidelines. These 3 techniques provide necessary elements for secure and trusted execution environment while the guidelines ensure that the virtualized workload remains in a secure and trusted state throughout its lifecycle. We have successfully implemented and demonstrated that the framework provides security and trust guarantees at the time of launch, any time during the execution, and during an update of the virtualized workload. Given the proliferation of virtualization from cloud servers to embedded systems, techniques presented in this dissertation can be implemented on most computing systems.
Date: August 2018
Creator: Kotikela, Srujan D
Partner: UNT Libraries

Molecular Dynamics Simulations of the Structure and Properties of Boron Containing Oxide Glasses: Empirical Potential Development and Applications

Description: Potential parameters that can handle multi-component oxide glass systems especially boron oxide are very limited in literature. One of the main goals of my dissertation is to develop empirical potentials to simulate multi-component oxide glass systems with boron oxide. Two approaches, both by introducing the composition dependent parameter feature, were taken and both led to successful potentials for boron containing glass systems after extensive testing and fitting. Both potential sets can produce reasonable glass structures of the multi-component oxide glass systems, with structure and properties in good agreement with experimental data. Furthermore, we have tested the simulation settings such as system size and cooling rate effects on the results of structures and properties of MD simulated borosilicate glasses. It was found that increase four-coordinated boron with decreasing cooling rate and system size above 1000 atoms is necessary to produce converged structure. Another application of the potentials is to simulate a six-component nuclear waste glass, international simple glass (ISG), which was for first time simulated using the newly developed parameters. Structural features obtained from simulations agree well with the experimental results. In addition, two series of sodium borosilicate and boroaluminosilicate glasses were simulated with the two sets of potentials to compare and evaluate their applicability and deficiency. Various analyses on the structures and properties such as pair distribution function, total correlation function, coordination number analysis, Qn distribution function, ring size distribution function, vibrational density of states and mechanical properties were performed. This work highlights the challenge of MD simulations of boron containing glasses and the capability of the new potential parameters that enable simulations of wide range of mixed former glasses to investigate new structure features and design of new glass compositions for various applications.
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Date: December 2017
Creator: Deng, Lu
Partner: UNT Libraries

Design of Bioinspired Conductive Smart Textile

Description: Electrically conductive fabrics are one of the major components of smart textile that attracts a lot of attention by the energy, medical, sports and military industry. The principal contributors to the conductivity of the smart textiles are the intrinsic properties of the fiber, functionalization by the addition of conductive particles and the architecture of fibers. In this study, intrinsic properties of non-woven carbon fabric derived from a novel linear lignin, poly-(caffeyl alcohol) (PCFA) discovered in the seeds of the vanilla orchid (Vanilla planifolia) was investigated. In contrast to all known lignins which comprise of polyaromatic networks, the PCFA lignin is a linear polymer. The non-woven fabric was prepared using electrospinning technique, which follows by stabilization and carbonization steps. Results from Raman spectroscopy indicate higher graphitic structure for PCFA carbon as compared to the Kraft lignin, as seen from G/D ratios of 1.92 vs 1.15 which was supported by a high percentage of graphitic (C-C) bond observed from X-ray photoelectron spectroscopy (XPS). Moreover, from the XRD and TEM a larger crystal size (Lc=12.2 nm) for the PCFA fiber was obtained which correlates to the higher modulus and conductivity of the fiber. These plant-sourced carbon fabrics have a valuable impact on zero carbon footprint materials. In order to improve the strength and flexibility of the non-woven carbon fabric, lignin was blended with the synthetic polymer Poly acrylonitrile (PAN) in different concertation, resulting in electrical conductivity up to (7.7 S/cm) on blend composition which is enough for sensing and EMI shielding applications. Next, the design of experiments approach was used to identify the contribution of the carbonization parameters on the conductivity of the fabrics and architecture of the fibers, results show carbonization temperature as the major contributing factor to the conductivity of non-woven fabric. Finally, a manufacturing procedure was develop inspired by the ...
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Date: August 2017
Creator: Rizvi, Syed Hussain Raza
Partner: UNT Libraries

Analysis and Performance of a Cyber-Human System and Protocols for Geographically Separated Collaborators

Description: This dissertation provides an innovative mechanism to collaborate two geographically separated people on a physical task and a novel method to measure Complexity Index (CI) and calculate Minimal Complexity Index (MCI) of a collaboration protocol. The protocol is represented as a structure, and the information content of it is measured in bits to understand the complex nature of the protocol. Using the complexity metrics, one can analyze the performance of a collaborative system and a collaboration protocol. Security and privacy of the consumers are vital while seeking remote help; this dissertation also provides a novel authorization framework for dynamic access control of resources on an input-constrained appliance used for completing the physical task. Using the innovative Collaborative Appliance for REmote-help (CARE) and with the support of a remotely located expert, fifty-nine subjects with minimal or no prior mechanical knowledge are able to elevate a car for replacing a tire in an average time of six minutes and 53 seconds and with an average protocol complexity of 171.6 bits. Moreover, thirty subjects with minimal or no prior plumbing knowledge are able to change the cartridge of a faucet in an average time of ten minutes and with an average protocol complexity of 250.6 bits. Our experiments and results show that one can use the developed mechanism and methods for expanding the protocols for a variety of home, vehicle, and appliance repairs and installations.
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Date: December 2017
Creator: Jonnada, Srikanth
Partner: UNT Libraries

Shear and Compression Strength of Cold-formed Steel Clip Angles Subjected to Different Screw Patterns

Description: This thesis presents experiments and numerical analysis of the cold-formed steel clip angle in three different limit states which are shear, compression, and combination of the screw connection. A previous cold-formed steel clip angle test program (which is Phase 1) developed design methods for clip angle. Therefore, the object of this thesis is to further investigate the behavior and design methods of loading-bearing cold-formed steel clip angles under different screw pattern. For each limit state, a test program was conducted to investigate the behavior, strength, and deflection of the clip angle. The test result were compared with previous CFS clip angle design method. Amending existing CFS clip angle method were developed by each of the four limit states studied in this project.
Date: December 2017
Creator: Yan, Zhishan
Partner: UNT Libraries