Doctor of Philosophy, The Ohio State University, 2024, Industrial and Systems Engineering

Sociotechnical systems in safety-critical domains are distributed and contain interdependencies between the different elements, including human and automated roles that need to coordinate and synchronize their activities with dynamic events in the environment. The advancement of technology and the introduction of machines capable of acting at a higher level of autonomy has increased the complexity of such Distributed Work Systems (DWSs). An envisioned DWS is described by a set of static paper-based documents and will be deployed in the next few years. The short-range low-altitude air mobility system is one very good example of an envisioned DWS. Interactions between human and automated roles and their environment are dynamic, evolve, and change over time, causing emergent effects like taskload peaks and coordination breakdowns. A well-designed DWS will be able to keep pace with the work environment dynamics (like the dynamics of aircraft governed by laws of flight in a short-range low-altitude air mobility system) and succeed in responding to the disturbance. This creates the need to understand the dynamics of envisioned DWS, such as how a DWS performs in high-paced situations like anomaly response. Assessing the feasibility and robustness of an envisioned DWS comes with challenges: the physical system does not yet exist, its design and operations are often underspecified, and multiple versions may exist within a designer community about what future operations will look like. Therefore, as a part of this dissertation, an exploratory early-stage computational modeling and simulation technique is described and demonstrated to evaluate an envisioned DWS. Using functional modeling and computational simulation capabilities, the dissertation shows a technique that can help evaluate envisioned DWS by discovering things that are not uncovered by traditional normative simulations. The primary advantage of the technique is the ability to evaluate the dynamics of work in (open full item for complete abstract)

Committee: Martijn Ijtsma (Advisor); Michael Rayo (Committee Member); David Woods (Committee Member) Subjects: Industrial Engineering; Systems Design

Master of Science, University of Toledo, 2019, Engineering (Computer Science)

The world is on the brink of an era of Unmanned Aerial Vehicles (UAVs), widely known to public as drones, where we will get to experience multiple UAVs flying in the national airspace carrying out diverse tasks such as monitoring, surveillance, product deliveries, law enforcement, fertilizing crop fields, aerial photography, and transport. In such scenarios, where multiple UAVs are flying in a smaller airspace, there is a possibility of collisions, path overlaps, mix-ups, and uncertainties as far as their flying routes are concerned. These flying routes could be inside constructed air corridors where the UAVs would be allotted to fly, similar to the air corridors of commercial aircraft. There is a growing need to identify and construct these air corridors for UAVs to fly in their respective corridors to avoid such mishaps as is what is done with commercial airplanes. The airplanes fly in their designated air corridors from one location to another without any uncertainty. It would be really useful to devise and design such a system for multiple UAVs as well, that would be able to construct air corridors for them to fly through. This served as the primary motivation behind proposing a novel approach to estimate and visualize air corridors for autonomous multi-UAV flights in an airspace. In addition to it, we studied various popular uncertainty visualization techniques and came up with a cutting-edge way to incorporate uncertainty into the visualization of the air corridors. Furthermore, we provide a standalone web application with a user-friendly graphical user interface (GUI) developed using HTML5, CSS3, JavaScript and an open-source JavaScript library for visualizing world-class 3-D maps called CesiumJS. Subsequently, we present the estimation and visualization results and discuss possible application areas where the proposed technique could be put to use. Finally, we discuss the summarized research findings and future research directions.

Committee: Ahmad Javaid (Committee Chair); Vijay Devabhaktuni (Committee Co-Chair); Devinder Kaur (Committee Member) Subjects: Computer Engineering; Computer Science

Master of Science (MS), Ohio University, 2024, Mechanical Engineering (Engineering and Technology)

In recent years, lithium-ion batteries (LIBs) have played an essential role in nowadays energy storage system, especially electric vehicles (EVs) and portable electronics because of its high energy density and long cycle life [1, 2]. However, one of the biggest challenges is how to guarantee their dependability and trustworthiness. In the present investigation, Acoustic Emission (AE) and Ultrasound Testing (UT) techniques are systematically employed to verify probable critical defects in the LIBs. Where AE technology is able to record the stress waves produced by the growth of the defects, UT uses high-frequency sound waves to penetrate the batteries and provide an indication of the internal voids. The performances of these approaches were systematically tested on as-received, pre-damaged and cold-soaked batteries. Different AE and UT activity patterns were shown in the results under various environmental conditions that influenced battery performance. Combining Acoustic Emission (AE) and Ultrasound Testing (UT) with clustering and outlier analysis machine learning algorithms improved defect detection effectiveness. Such research highlights that AE and UT can be robust noninvasive techniques for on-line health monitoring of LIBs that should aid in maintaining the longevity and operability of LIBs.

Committee: Brian Wisner (Advisor) Subjects: Acoustics; Mechanical Engineering

MS, University of Cincinnati, 2022, Engineering and Applied Science: Mechanical Engineering

In modern manufacturing setups, linear motion systems are extensively used for producing straight-line motion with positional control. Applications such as computer numerical control (CNC) machining, precision laser printing, moving multi-axis robots, etc., feature linear motion systems. These systems, however, are susceptible to degradation and develop faults over prolonged usage. Structural health degradation of different system components gives rise to increased mechanical and thermal loads along with increased vibrations. This degradation eventually restricts the ability of linear motion systems to deliver the required quality of performance in terms of positional accuracy, precision, and reliability. Determining the location of degradation is important for maintaining the system's components in a healthy state of operation. Furthermore, identifying the type and location of the faults generated through the degradation of one or more components is also instrumental for conducting repairs/replacements before the systems fail to deliver the required performance. Hence there is a need to develop prognostics and health management (PHM) methodologies capable of location-specific condition monitoring and location-specific fault classification. Data signals collected from motion controllers and external sensors are used to train machine learning algorithms that consider healthy state signals as the baseline and quantify the deviation of new signals from this baseline in terms of health indicators (HI). In this thesis, a PHM methodology is proposed for developing system health indicators (HI) using self-organizing maps and principal component analysis. Data preprocessing steps of signal extraction, signal segmentation, feature extraction, feature selection, and data normalization are followed by training baseline models for health indicators. These HI are then evaluated over signal data with unknown health, to monitor the gradual degradation of the linear motion system. (open full item for complete abstract)

Committee: Jay Lee Ph.D. (Committee Member); Jonathan Tan Ph.D. (Committee Member); Jing Shi Ph.D. (Committee Member) Subjects: Mechanical Engineering

Doctor of Philosophy, The Ohio State University, 2022, Electrical and Computer Engineering

Wireless technologies have become a vital part of our daily lives over the past few decades. Today, the cellular communication technologies are used by billions of people, and many types of devices rely on the wireless technologies, such as Wi-Fi, Bluetooth. The ubiquitous deployment of wireless networks and devices has us surrounded by the wireless signals emitted from them. This motivates researchers to exploit these signals for different indoor and outdoor wireless sensing applications. In this dissertation, we aim to take advantage of the wireless signals sent in a vehicular ad hoc network (VANET) that enables the communication between vehicles and infrastructure units over an ad hoc network. Given the tremendous effort by the government agencies and the industry into realizing the vehicular networks on a large scale, we believe there are many opportunities for different applications relying on the vehicular communication besides the safety-related VANET applications. In this dissertation, we use the communication signals in a vehicular network to make situational inference on the road traffic conditions and the user authentication in the case of Sybil attacks. First, we focus on the road state inference using the wireless signals. Although a wide variety of sensor technologies are recently being adopted for traffic monitoring applications, most of these technologies rely on wired infrastructure. The installation and maintenance costs limit the deployment of the traffic monitoring systems. In this dissertation, we introduce a novel traffic inference approach that exploits physical layer samples in vehicular communications processed by machine learning techniques. We verify the feasibility of the proposed approach with extensive simulations and real-world experiments. We first simulate wireless channels under realistic traffic conditions using a ray-tracing simulator and a traffic simulator. Next, we conduct experiments in a real-world environment and collect (open full item for complete abstract)

Committee: Can Emre Koksal (Advisor); Ness Shroff (Committee Member); Eylem Ekici (Committee Member) Subjects: Computer Engineering; Computer Science; Electrical Engineering; Engineering

Master of Science in Engineering, University of Akron, 2019, Electrical Engineering

This thesis proposes a superior magnetic field based energy harvesting system, with a wide voltage range operation and low start-up voltage. Design parameters have been analyzed to determine their impact on the amount of power that can be harvested. An efficient and novel power processing unit which produces a regulated DC voltage and distributes the power between the load and the backup energy storage element is proposed. Experimental results have demonstrated that the proposed nanocrystalline harvester core achieves very high power density and can produce as much as 55W of power from a power line carrying 615A of 60Hz current, which is much higher than that reported in many research papers, and when implemented with the associated power processing unit results in a complete energy harvesting system that can start to operate at a low harvester coil AC voltage of 2.7V and processes the power to obtain a regulated DC voltage of 12.5V. The proposed energy harvester system can be used as a power source for high power condition monitoring systems, weather stations, and systems where the use of conventional mains supply, batteries, or renewable energy sources such as solar or wind may not be convenient, practical, or economical.

Committee: J. Alexis De Abreu García Dr. (Advisor); Yilmaz Sozer Dr. (Advisor); Robert J. Veillette Dr. (Committee Member) Subjects: Electrical Engineering; Electromagnetics; Energy

Master of Science, University of Akron, 2018, Electrical Engineering

In this thesis, a phase locked loop based signal processing approach is proposed for analyzing and estimating the radio frequency characteristics of partial discharge. This method estimates the frequency component magnitudes of partial discharge with high speed, accuracy and low computational complexity as it involves simple mathematical calculations. A threshold value is set for the harmonic component magnitudes for the identification of damage and for reporting failure events in the power cables. The effectiveness of the proposed technique is verified and validated via simulation, experimental, and field test results.

Committee: Yilmaz Sozer Dr. (Advisor); Jose Alexis De Abreu Garcia Dr. (Committee Co-Chair); Robert J. Veillette Dr. (Committee Member) Subjects: Electrical Engineering

PhD, University of Cincinnati, 2018, Engineering and Applied Science: Electrical Engineering

The future of disease diagnostics and health care wearables lies in the development of low-cost sensors and devices that can detect minute traces of pathogens or antigens from body fluids. These devices will allow patients to run point of care diagnostics tests, thereby saving time and cost of running clinical tests and ultimately can provide early stage disease diagnosis and enable physicians to provide better-personalized treatment. There have been developments that focus on integrating multiple different tests into a single device that measures analytes from biofluids. Detection of glucose together with some single ions in a single device and test is the current attractive research advancement. Electrochemistry Impedance Spectroscopy (EIS) is widely popular in the medical field where it is used to analyze biological materials as well as characterization of body fluids. It is a complex technique requiring expensive equipment that is also bulky making it difficult to integrate into small form-factor systems that are handheld, wearable and intended for use in point of care testing. This research work focused on developing a proof of concept prototype system with a flexible architecture that can be used for testing multiple sensors using EIS electroanalytical technique. The system is based on an embedded system design to be factored to achieve small valuation time for results along with being compact and portable enough to be used outside laboratory bench setting. The prototype successfully calculates the magnitude and phase of the impedance responses multiple electrochemical cells. The device transmits test data wirelessly to a personal computer or tablet which works together with an analysis and control display.

Committee: Fred Beyette Ph.D. (Committee Chair); Jason Heikenfeld Ph.D. (Committee Member); Carla Purdy Ph.D. (Committee Member); Ryan White Ph.D. (Committee Member); Philip Wilsey Ph.D. (Committee Member) Subjects: Electrical Engineering

Master of Science (MS), Ohio University, 2016, Environmental Studies (Voinovich)

The efficiency of watershed management depends on the frequency of monitoring water quality. Remote water quality monitoring can improve watersheds management. However, this is often very costly and difficult to implement. This study focused on designing and building a low cost remote water quality monitoring system. This was achieved by integrating low cost computing technology, power management, monitoring sensors and `disruption tolerant networking' (DTN). This system was used to measure water pH, electrical conductivity and temperature. The composite system is made up of three main components which includes the data acquisition node, communication module and the cloud database. The data acquisition node is made up of the sensor nodes which includes pH, conductivity and temperature sensors, credit-card sized computer and microcontroller. A side-by-side test between the low cost water quality monitoring system and a reference YSI 600 XLM sonde was conducted to demonstrate the effectiveness of the low cost system.

Committee: Natalie Kruse (Advisor) Subjects: Communication; Environmental Management; Information Systems; Information Technology

Master of Science (MS), Ohio University, 2015, Industrial and Systems Engineering (Engineering and Technology)

The direction of this thesis is to design systems to better understand the complexity of a business cycle. First questions are asked; what is the forecasted demand to satisfy customers? How will the company manufacture the products in an efficient way? This study emphasizes on the complexity of each step of the process. The study first introduces the demand allocation to satisfy current customers, but has a future strategy to expand upon their current market position. Reducing inefficiencies in the system, calculations were done for demand, standard deviation, demand coverage probability, and manufacturing cell utilization. Then a simulation model was designed to expedite the user enter values using VBA coding to simulate the manufacturing system. Final systems were compared to figure out if a future business strategy is manageable and desirable for the company.

Committee: Gursel Suer Dr. (Advisor); Sormaz Dusan Dr. (Advisor) Subjects: Engineering; Finance; Industrial Engineering; Systems Design

MS, University of Cincinnati, 2015, Engineering and Applied Science: Electrical Engineering

Electrochemical Impedance Spectroscopy (EIS) is an experimental procedure and important technique to evaluate the underlying characteristics of biosensors, body fluids, electrochemical fuel cells, and electronic circuits. Existing EIS systems are expensive, bulky, and difficult to integrate with other systems such as wearable medical devices. This thesis presents a prototype of a low-cost, portable, microcontroller-based EIS platform for integration with health monitoring systems. A major challenge is to eliminate the use of sophisticated and expensive hardware and provide an alternative low-cost solution that can maintain the ability of measuring over an acceptable range of frequencies and impedance values. The prototype of the portable EIS system is developed using an off-the-shelf, fast and, powerful digital signal controller that serves as the main control unit of the system. The in-built modules like Pulse Width Modulation, Analog-to-Digital Converter, Direct Memory Access and Universal Asynchronous Receiver Transmitter along with low pass-filters are used for signal generation, sampling as well as signal processing. The system also employs a low-cost and effective analog interface module for conditioning digital signals generated from the controller, which are as analog inputs in electrical cell impedance models as well as commercial electrochemical cell in the form of interdigitated electrodes with Phosphate Buffer Saline(PBS) and vice versa. With an operating sampling frequency in the range of 2 Hz – 2 KHz, the overall cost of the system is estimated to be less than $100. The overall efficiency of the system is fair for complex impedance amplitude and phase computation with error in computation calculated to be less than 10%. These results demonstrate the feasibility of a portable EIS system for electrochemical as well as bioelectrical impedance analysis.

Committee: Fred Beyette Ph.D. (Committee Chair); Jason Heikenfeld Ph.D. (Committee Member); Carla Purdy Ph.D. (Committee Member) Subjects: Electrical Engineering

MS, University of Cincinnati, 2007, Engineering : Electrical Engineering

The need for instrumented health monitoring systems has been felt by the research community to observe the health of the detiorating highway infrastructure system. University of Cincinnati Infrastructure Institute(UCII) in collaboration with the Applied Systems Research Laboratory(ASRL) has been monitoring multiple steel stringer bridges. Among the various bridges monitored, an elaborate monitoring setup was installed on the HAM-126-0881L to monitor the long term and short term behavior of the bridge through high speed and low speed data collection systems. The high speed monitoring system collects vital information of the bridge as heavy trucks pass through the bridge. Each instance of a truck represents a truckload test on the bridge and the onsite monitoring system collects the data and processes it to rate the bridge as per UCII and AASHTO guidelines.[16] This is done on a real time basis. These ratings have been traditionally used by bridge inspectors to evaluate the condition of bridges. Through the continuous monitoring of the bridge ratings, the researchers at UCII/ ASRL are trying to see the detioration of the bridge as it ages. As a first attempt to developing a monitoring system and conversion of theoretical truckload test rating schemes, the UCII team was successful in collecting useful data. The following thesis has taken the data generated from the monitoring system and performed a thorough analysis of the resultant data. The analysis involved taking a dataset of 11100 individual observations from the raw data files stored on the onsite computer. The raw data files were used to extract vehicle information characteristics such as weight, speed, vehicle code, etc. The stored HS20 and UIL data was used to calculate the bridge rating for each instance of truck passage. We observed multiple cases of faulty bridge ratings in which the monitoring system misfired/malfunctioned to give us faulty ratings. A thorough analysis was done to pinpoint the possible cau (open full item for complete abstract)

Committee: Dr. Arthur Helmicki (Advisor) Subjects:

Doctor of Philosophy, The Ohio State University, 2012, Industrial and Systems Engineering

Departure demand routinely exceeds capacity at several airports in the United States. Under traditional “first-come, first-served” approaches to airport surface management, demand exceeding capacity can cause longer departure queues than necessary to maintain efficient traffic flow. Long queues can lead to longer taxi out times and greater fuel burn than necessary, and can increase uncertainty and limit flexibility for flight operators while increasing workload for air traffic control personnel. Departure metering is one alternative approach that controls access to the active movement area relative to expected departure capacity and the desired number of aircraft in the departure queue (or similar measures). While the main goal is to control the number of aircraft in the departure queue, metering also can increase flexibility, reduce emissions, and improve information about the time a flight is likely to take off. Managing a departure metering procedure is a new role that is an example of a distributed adaptive planning task. This research examined human-centered design concepts for supporting people responsible for such tasks. In particular, the project developed information requirements and prototype displays to support a human agent(s) responsible for managing a departure metering procedure. These information requirements are intended to support proactive efforts to adapt a surface management plan under evolving conditions, appropriately modifying the plan, and scheduling implementation of the new plan. Departure metering procedure management requires re-planning in response to events that impact the departure process (such as an unexpected temporary runway closure). It also may require adapting the plan before any change in the departure process takes place and when information indicating the trajectory of the departure process is uncertain (such as a forecast change in weather conditions). Rather than always implementing the new plan immediately, a person may s (open full item for complete abstract)

Committee: Philip Smith PhD (Advisor); David Woods PhD (Committee Member); Emily Patterson PhD (Committee Member) Subjects: Engineering; Industrial Engineering; Systems Design; Transportation

Master of Sciences, Case Western Reserve University, 2012, EECS - Computer and Information Sciences

After applying some significant performance improvements to PathCase SB and making it run faster and smoother we build a monitoring tool for the system that would facilitate future maintenance. Hence, in this thesis we propose a performance monitor specialized for the current version 4.0 of PathCase SB but that is able to automatically adapt to newer versions. The system can also be used to monitor other applications of the PathCase set of applications. We show the problems that we detected and solved and then we use the performance monitor to detect and fix even more bugs.

Committee: Dr. Meral Ozsoyoglu PhD (Advisor); Dr. Vincenzo Liberatore PhD (Committee Member); Dr. Andy Podgurski PhD (Committee Member); Dr. Gultekin Ozsoyoglu PhD (Committee Member) Subjects: Computer Science

Doctor of Philosophy (PhD), Ohio University, 2013, Mechanical and Systems Engineering (Engineering and Technology)

Strategy denotes actions or patterns of actions intended for the attainment of goals. In an organizational setting, the term strategy covers more than just intended or planned strategy; it also includes the sequence of decisions that exhibit posteriori consistencies in decisional behavior, involving the selection of product markets or industries and the allocation of resources among them. Within the broader purpose of developing a decision making framework for competitive strategy development practices, the thrust of this study is to investigate the impact of environmental uncertainty on corporate strategy, and the influence of corporate strategy on business performance, operational structure and market dynamics. Another incidental purpose of the study is to review, classify, clarify, define, and integrate ideas and concepts from diverse disciplines including Engineering, Economics and Business Administration to consequently establish a strategic decision making framework. The factors influencing the short term and long term standing of companies in a particular market are focused with the objectives of increasing the business capability and profitability as well as improving the market share. The case studied is the global blood sugar monitoring industry. The demand structure of the market is modeled considering four major companies in three regional markets; Asia, Europe, North America. LifeScan Inc., a Johnson & Johnson Company, is selected as the focus of greater discussions. The decision making framework is established for LifeScan Inc. incorporating a layered cellular manufacturing design integrated with different supply chain alternatives. The framework is then employed in a multi-period strategic analysis where competition games are developed and studied in three categories; price competition, quality/reputation competition and product competition. The outcomes of different competition strategies are presented and evaluated in terms of profitability and (open full item for complete abstract)

Committee: Gursel Suer (Advisor); Douglas Adie (Advisor); David Koonce (Committee Member); Dusan Sormaz (Committee Member); Namkyu Park (Committee Member); Ana Feger (Committee Member) Subjects: Business Administration; Economics; Industrial Engineering

Master of Arts, University of Toledo, 2012, Geography

The typical approach to mapping groundwater contaminant plumes involves drawing plume contours out to each contaminant's site-specific cleanup criterion. Cleanup criteria differ between contaminants, sites and U.S. states. For this reason, it is difficult to determine which monitoring wells, plumes and sites are most contaminated within a given area or region. For the same reason, it is also difficult to determine which individual contaminant is most concentrated within a single monitoring well. The Contaminant Exceedance Rating System (CERS) was developed to address these issues by normalizing groundwater contaminant data against their site-specific cleanup criteria. Each contaminant's laboratory analytical result is divided by its respective site-specific cleanup criterion and the result is a unitless ratio which is then compared against other CERS Values. The CERS Values are then ranked into a set of CERS Ranking Categories for data grouping purposes and ease of mapping. The CERS was successfully implemented utilizing data from the Former Wurtsmith Air Force Base (WAFB) in Oscoda, Michigan (provided by the Air Force Center for Engineering and the Environment[AFCEE]). Basewide groundwater volatile organic compound (VOC) data from Summer/Fall 2009 was utilized. ESRI¿¿ ArcGIS Version 10.0 was used to map the resultant CERS Values, symbolized by their Ranking Categories. By implementing the CERS, the following were successfully determined for this data: the most concentrated contaminant in each sample, the most contaminated well(s) within each site, the most contaminated wells on the entire base, and the most contaminated plumes on the base. It is recommended that the CERS be further implemented using additional temporal data from the Former WAFB. It is also recommended that the CERS be implemented using contaminant data from other Department of Defense (DoD) installations. The CERS could allow for comparison of maximum degree of contamination between entire installa (open full item for complete abstract)

Committee: Patrick Lawrence PhD (Committee Chair); Peter Lindquist PhD (Committee Member); Robert Beckwith PG (Committee Member) Subjects: Chemistry; Environmental Economics; Environmental Management; Environmental Science; Environmental Studies; Geochemistry; Geographic Information Science; Geography; Hydrologic Sciences; Hydrology; Information Science; Information Systems; Natural Resource Management; Water Resource Management