Time studies are an effective tool to analyze current production systems and propose improvements. The problem that motivated the project was that conducting time studies and observing the progression of components across the factory floor is a manual process. Four Industrial Engineering students worked with a manufacturing company to develop Computer Vision technology that would automate the data collection process for time studies. The team worked in an Agile environment to complete over 120 classification sets, create 8 strategy documents, and utilize Root Cause Analysis techniques to audit and validate the performance of the trained Computer Vision data models. In the future, there is an opportunity to continue developing this product and expand the team’s work scope to apply more engineering skills on the data collected to drive factory improvements.

High-entropy alloys possessing mechanical, chemical, and electrical properties that far exceed those of conventional alloys have the potential to make a significant impact on many areas of engineering. Identifying element combinations and configurations to form these alloys, however, is a difficult, time-consuming, computationally intensive task. Machine learning has revolutionized many different fields due to its ability to generalize well to different problems and produce computationally efficient, accurate predictions regarding the system of interest. In this thesis, we demonstrate the effectiveness of machine learning models applied to toy cases representative of simplified physics that are relevant to high-entropy alloy simulation. We show these models are effective at learning nonlinear dynamics for single and multi-particle cases and that more work is needed to accurately represent complex cases in which the system dynamics are chaotic. This thesis serves as a demonstration of the potential benefits of machine learning applied to high-entropy alloy simulations to generate fast, accurate predictions of nonlinear dynamics.

This thesis explores the potential for software to act as an educational experience for engineers who are learning system dynamics and controls. The specific focus is a spring-mass-damper system. First, a brief introduction of the spring-mass-damper system is given, followed by a review of the background and prior work concerning this topic. Then, the methodology and main approaches of the system are explained, as well as a more technical overview of the program. Lastly, a conclusion and discussion of potential future work is covered. The project was found to be useful by several engineers who tested it. While there is still plenty of functionality to add, it is a promising first attempt at teaching engineers through software development.

Micromachining has seen application growth in a variety of industries requiring a miniaturization of the machining process. Machining at the micro level generates different cutter/workpiece interactions, generating more localized temperature spikes in the part/sample, as suggested by multiple studies. Temper-etch inspection is a non-destructive test used to identify `grind burns' or localized over-heating in steel components. This research investigated the application of temper-etch inspection to micromachined steel. The tests were performed on AISI 4340 steel samples. Finding, indications of localized over-heating was the primary focus of the experiment. In addition, change in condition between the original and post-machining hardness in the machined slot bottom was investigated. The results revealed that, under the conditions of the experiment, no indications of localized over-heating were present. However, there was a change in hardness at the bottom of the machined slot compared to the rest of the sample. Further research is needed to test the applicability of temper-etch inspection to micromilled steel and to identify the source of the change in hardness.

ABSTRACT Ongoing research into wireless transceivers in the 60 GHz band is required to address the demand for high data rate communications systems at a frequency where signal propagation is challenging even over short ranges. This thesis proposes a mixer architecture in Complementary Metal Oxide Semiconductor (CMOS) technology that uses a voltage controlled oscillator (VCO) operating at a fractional multiple of the desired output signal. The proposed topology is different from conventional subharmonic mixing in that the oscillator phase generation circuitry usually required for such a circuit is unnecessary. Analysis and simulations are performed on the proposed mixer circuit in an IBM 90 nm RF process on a 1.2 V supply. A typical RF transmitter system is considered in determining the block requirements needed for the mixer to meet the IEEE 802.11ad 60 GHz Draft Physical Layer Specification. The proposed circuit has a conversion loss of 21 dB at 60 GHz with a 5 dBm LO power at 20 GHz. Input-referred third-order intercept point (IIP3) is 2.93 dBm. The gain and linearity of the proposed mixer are sufficient for Orthogonal Frequency Division Multiplexing (OFDM) modulation at 60 GHz with a transmitted data rate of over 4 Gbps.

This thesis presents a multi-modal motion tracking system for stroke patient rehabilitation. This system deploys two sensor modules: marker-based motion capture system and inertial measurement unit (IMU). The integrated system provides real-time measurement of the right arm and trunk movement, even in the presence of marker occlusion. The information from the two sensors is fused through quaternion-based recursive filters to promise robust detection of torso compensation (undesired body motion). Since this algorithm allows flexible sensor configurations, it presents a framework for fusing the IMU data and vision data that can adapt to various sensor selection scenarios. The proposed system consequently has the potential to improve both the robustness and flexibility of the sensing process. Through comparison between the complementary filter, the extended Kalman filter (EKF), the unscented Kalman filter (UKF) and the particle filter (PF), the experimental part evaluated the performance of the quaternion-based complementary filter for 10 sensor combination scenarios. Experimental results demonstrate the favorable performance of the proposed system in case of occlusion. Such investigation also provides valuable information for filtering algorithm and strategy selection in specific sensor applications.

This study analyzes the thermoelectric phenomena of nanoparticle suspensions, which are composed of liquid and solid nanoparticles that show a relatively stable Seebeck coefficient as bulk solids near room temperature. The approach is to explore the thermoelectric character of the nanoparticle suspensions, predict the outcome of the experiment and compare the experimental data with anticipated results. In the experiment, the nanoparticle suspension is contained in a 15cm*2.5cm*2.5cm glass container, the temperature gradient ranges from 20 °C to 60 °C, and room temperature fluctuates from 20 °C to 23°C. The measured nanoparticles include multiwall carbon nanotubes, aluminum dioxide and bismuth telluride. A temperature gradient from 20 °C to 60 °C is imposed along the length of the container, and the resulting voltage (if any) is measured. Both heating and cooling processes are measured. With three different nanoparticle suspensions (carbon nano tubes, Al2O3 nanoparticles and Bi2Te3 nanoparticles), the correlation between temperature gradient and voltage is correspondingly 8%, 38% and 96%. A comparison of results calculated from the bulk Seebeck coefficients with our measured results indicate that the Seebeck coefficient measured for each suspension is much more than anticipated, which indicates that the thermophoresis effect could have enhanced the voltage. Further research with a closed-loop system might be able to affirm the results of this study.

Building applied photovoltaics (BAPV) is a major application sector for photovoltaics (PV). Due to the negative temperature coefficient of power output, the performance of a PV module decreases as the temperature of the module increases. In hot climatic conditions, such as the summer in Arizona, the operating temperature of a BAPV module can reach as high as 90°C. Considering a typical 0.5%/°C power drop for crystalline silicon (c-Si) modules, a performance decrease of approximately 30% would be expected during peak summer temperatures due to the difference between rated temperature (25°C) and operating temperature (~90°C) of the modules. Also, in a worst-case scenario, such as partial shading of the PV cells of air gap-free BAPV modules, some of the components could attain temperatures that would be high enough to compromise the safety and functionality requirements of the module and its components. Based on the temperature and weather data collected over a year in Arizona, a mathematical thermal model has been developed and presented in this paper to predict module temperature for five different air gaps (0", 1", 2", 3", and 4"). For comparison, modules with a thermally-insulated (R30) back were evaluated to determine the worst-case scenario. This thesis also provides key technical details related to the specially-built, simulated rooftop structure; the mounting configuration of the PV modules on the rooftop structure; the LabVIEW program that was developed for data acquisition and the MATLAB program for developing the thermal models. In order to address the safety issue, temperature test results (obtained in accordance with IEC 61730-2 and UL 1703 safety standards) are presented and analyzed for nine different components of a PV module, i.e., the front glass, substrate/backsheet (polymer), PV cell, j-box ambient, j-box surface, positive terminal, backsheet inside j-box, field wiring, and diode. The temperature test results obtained for about 140 crystalline silicon modules from a large number of manufacturers who tested modules between 2006 and 2009 at ASU/TÜV-PTL were analyzed and presented in this paper under three test conditions, i.e., short-circuit, open-circuit, and short-circuit and shaded. Also, the nominal operating cell temperatures (NOCTs) of the BAPV modules and insulated-back PV modules are presented in this paper for use by BAPV module designers and installers.

Phase Change Material (PCM) plays an important role as a thermal energy storage device by utilizing its high storage density and latent heat property. One of the potential applications for PCM is in buildings by incorporating them in the envelope for energy conservation. During the summer season, the benefits are a decrease in overall energy consumption by the air conditioning unit and a time shift in peak load during the day. Experimental work was carried out by Arizona Public Service (APS) in collaboration with Phase Change Energy Solutions (PCES) Inc. with a new class of organic-based PCM. This "BioPCM" has non-flammable properties and can be safely used in buildings. The experimental setup showed maximum energy savings of about 30%, a maximum peak load shift of ~ 60 min, and maximum cost savings of about 30%. Simulation was performed to validate the experimental results. EnergyPlus was chosen as it has the capability to simulate phase change material in the building envelope. The building material properties were chosen from the ASHRAE Handbook - Fundamentals and the HVAC system used was a window-mounted heat pump. The weather file used in the simulation was customized for the year 2008 from the National Renewable Energy Laboratory (NREL) website. All EnergyPlus inputs were ensured to match closely with the experimental parameters. The simulation results yielded comparable trends with the experimental energy consumption values, however time shifts were not observed. Several other parametric studies like varying PCM thermal conductivity, temperature range, location, insulation R-value and combination of different PCMs were analyzed and results are presented. It was found that a PCM with a melting point from 23 to 27 °C led to maximum energy savings and greater peak load time shift duration, and is more suitable than other PCM temperature ranges for light weight building construction in Phoenix.

A major concern in the operation of present-day gas turbine engines is the ingestion of hot mainstream gas into rotor-stator disk cavities of the high-pressure turbine stages. Although the engines require high gas temperature at turbine entry for good performance efficiency, the ingested gas shortens the lives of the cavity internals, particularly that of the rotor disks. Steps such as installing seals at the disk rims and injecting purge (secondary) air bled from the compressor discharge into the cavities are implemented to reduce the gas ingestion. Although there are advantages to the above-mentioned steps, the performance of a gas turbine engine is diminished by the purge air bleed-off. This then requires that the cavity sealing function be achieved with as low a purge air supply rate as possible. This, in turn, renders imperative an in-depth understanding of the pressure and velocity fields in the main gas path and within the disk cavities. In this work, experiments were carried out in a model 1.5-stage (stator-rotor-stator) axial air turbine to study the ingestion of main air into the aft, rotor-stator, disk cavity. The cavity featured rotor and stator rim seals with radial clearance and axial overlap and an inner labyrinth seal. First, time-average static pressure distribution was measured in the main gas path upstream and downstream of the rotor as well as in the cavity to ensure that a nominally steady run condition had been achieved. Main gas ingestion was determined by measuring the concentration distribution of tracer gas (CO2) in the cavity. To map the cavity fluid velocity field, particle image velocimetry was employed. Results are reported for two main air flow rates, two rotor speeds, and four purge air flow rates.