PhD, University of Cincinnati, 2014, Engineering and Applied Science: Aerospace Engineering

Current industry trends demonstrate aircraft electrification will be part of future platforms in order to achieve higher levels of efficiency in various vehicle level sub-systems. However electrification requires a substantial change in aircraft design that is not suitable for re-winged or re-engined applications as some aircraft manufacturers are opting for today. Thermal limits arise as engine cores progressively get smaller and hotter to improve overall engine efficiency[8], while legacy systems still demand a substantial amount of pneumatic, hydraulic and electric power extraction. The environmental control system (ECS) provides pressurization, ventilation and air conditioning in commercial aircraft[7], making it the main heat sink for all aircraft loads with exception of the engine. To mitigate the architecture thermal limits in an efficient manner, the form in which the ECS interacts with the engine will have to be enhanced as to reduce the overall energy consumed and achieve an energy optimized solution. This study examines a tradeoff analysis of an electric ECS by use of a fully integrated Numerical Propulsion Simulation System (NPSS) model that is capable of studying the interaction between the ECS and the engine cycle deck. It was found that a peak solution lays in a hybrid ECS where it utilizes the correct balance between a traditional pneumatic and a fully electric system. This intermediate architecture offers a substantial improvement in aircraft fuel consumptions due to a reduced amount of waste heat and customer bleed in exchange for partial electrification of the air-conditions pack which is a viable option for re-winged applications.

Master of Science (MS), Ohio University, 2000, Electrical Engineering & Computer Science (Engineering and Technology)

Integration of local area augumentation system and inertial navigation system for aircraft surface movement guidance

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

Due to the increased penetration of inverter-based resources (IBRs) in bulk power system (BPS) networks, to conduct interconnection studies, generic dynamic mod- els of the second-generation renewable energy system models were developed by the Western Electricity Coordinating Council (WECC) Renewable Energy Modeling Task Force. The dynamic models have been extensively implemented in various power system simulation software packages, and the block diagram representation of the dynamic models is widely present in various technical reports and literature. However, there is a gap between the mathematical model and knowledge of key parameters for the second-generation renewable energy system dynamic models. The complex nonlinear nature of the dynamic models makes it highly challenging for the transmission planning engineers to identify the key parameters when the IBRs are subjected to large-scale voltage and frequency disturbances. This is needed to ensure grid stability under contingencies. For instance, the Type 3 wind turbine generator (WTG-3) model consists of 7 modules with 118 user-defined parameters, interfaced through 26 states and 9 control flags to facilitate the plant operation in different control modes. Thus, this work presents a methodology for the key parameter identification in non- linear models of power systems. The proposed methodology is applied to identify the key parameters of the transmission-scale IBRs (solar PV power plants, wind power plants, and battery energy storage system plants) dynamic models using proposed global sensitivity analysis techniques. It fills up the gap regarding the requirement of the mathematical model and knowledge of key parameters. In contrast to the state-of-the-art methods, the proposed modified Morris, modified Sobol', and modified eFAST sensitivity analysis techniques do not linearize the dynamic models of IBRs around an operating point, providing critical insights into the large-signal stability analysis. The (open full item for complete abstract)

MS, University of Cincinnati, 2020, Education, Criminal Justice, and Human Services: Information Technology

Internet of things (IoT) applications in our daily lives has made life easier, but also comes with associated security threats. The vulnerability of the IoT system stems from the vulnerability of each connected device and transmission of threats through an interconnected home network. Smart homes are one of the applications of IoT, which is comprised of connected devices for easier interaction. An isolated IoT system with no internet connection has some level of safety from attacks because it is not exposed to the internet, although these devices have their innate vulnerabilities from the manufacturer. IoT gateways connecting IoT devices to the internet can create a backdoor into the smart home system that an attacker can exploit. Therefore, Internet-connected IoT devices have a high-security risk and one of the ways to detect an intrusion into an IoT gateway is through anomalies in the traffic passing through it. This thesis introduces early work on an intrusion detection system (IDS) by detecting anomalies in the smart home network using Extreme Learning Machine and Artificial Immune System (AIS-ELM). AIS uses the Clonal Algorithm for the optimization of the input parameters, and ELM analyzes the input parameter for better convergence in detecting anomalous activity. The larger implications of this work are the potential to apply this approach to a smart home network gateway and combine it with a push notification system that will allow the homeowner to identify any abnormalities in the smart home network and take appropriate action to mitigate threats.

Doctor of Philosophy, The Ohio State University, 2019, Electrical and Computer Engineering

In this dissertation, I will discuss methods to mitigate detrimental effects of malicious attacks on electric power systems. My work is motivated by the growing concern over security of electric power delivery due to intentional/terrorist attacks, which imposes urgency to upgrade for resiliency. In the second chapter, I present my research works on hedging against attacks on transmission lines by proposing a resilience-oriented transmission system operation model. I developed a tri-level optimization problem to model interactions between the operator and the attacker. The proposed optimization model will identify the operation strategy allowing for the minimum load shedding with attacks in the worst-case scenario. In the third chapter, I introduce a distributed energy management strategy for a zonal shipboard power system for enhanced resilience against contingencies. A modified nested energy management method is proposed for decentralizing energy scheduling to prevent entire system collapse caused by single-node failure. Furthermore, the system resilience is enhanced against energy deficiency due to generators failures by reserving more energy in the energy storage system. This is achieved by applying a distributed algorithm, known as alternating direction method of multiplier, to coordinate involved operators with contradicting objectives. In the fourth chapter, I provide a solution for the optimal defending resource allocation to mitigate the impacts of coordinated cyber-physical attacks. The coordinated attack involves physical short-circuiting of transmission lines after intruding the communication network of protection relays. A tri-level optimization model is proposed to formulate the coordinated attack scenario and identify the optimal defending strategy. In the fifth chapter, I present a graph theory-based power line expansion strategy for a medium voltage direct current (MVDC) shipboard power system. The proposed strategy simultaneously maximizes the algeb (open full item for complete abstract)

Master of Science in Aerospace Systems Engineering (MSASE), Wright State University, 2017, Mechanical Engineering

Next generation aircraft, more specifically NASA aircraft concepts, will include new technologies and make many advancements in fuel economy and noise. However, there are some challenges associated with the latest technologies that NASA is planning to use for the next generation aircraft. For example, these aircraft concepts require large amounts of electrical power to generate the required thrust throughout a notional flight profile. One of the new technologies is using advanced propulsion systems, such as the Turboelectric Distributed Propulsion (TeDP) system, which is significantly different from current aerospace high bypass turbofan based propulsion system. The TeDP propulsion system replaces the traditional turbofan engines with a series of embedded electrical fans. The blended wing body aircraft, N3-X (Boeing 777 class), that NASA proposed will have as many as 14 electric fans mounted on the upper aft surface of the aircraft wings. In addition to improved aircraft efficiency, this propulsion system change will significantly reduce noise generation, and provide the capability of short take-off and landing. A dynamic model of the ducted fan distributed propulsion system was developed and simulated for different notional flight profiles. The results show that the ducted fan distributed propulsion system dynamic model and the control system successfully generate the required thrust for the flights and capture the transient behavior of the system throughout the flight profiles. In addition, the dynamic model was used to model a 50 passenger regional aircraft. This study shows the benefit of both the TeDP system and the flexibility of the developed model. The contribution to knowledge is the evolution of the evaluation model that helps researcher's understand propulsion systems such as the TeDP system of NASA N+3 class aircraft. By identifying and understanding the principal challenges and possibilities provided by the technology, this research further contribu (open full item for complete abstract)

Master of Science (MS), Ohio University, 2018, Environmental Studies (Voinovich)

Relationship between organizations and ecosystem services produced in the Truckee-Carson River System is many-to-many. This implies that production of each ecosystem service requires inputs from multiple organizations, and each organization is involved in co-production of several ecosystem services. Given geographical location of the Truckee-Carson River System and unfolding effects of a changing climate such as chronic water shortages punctuated by periods of floods, it is inevitable to make challenging decisions about which ecosystem services should be produced in a particular year or season. Analyzing what organizations are involved in production of selected ecosystem services and how they are linked to production of each ecosystem service could be the first step towards understating complexity of a decision making context and role that organizations play in allocation of limited water resources in the Truckee-Carson River System.

Master of Science in Computer Engineering (MSCE), Wright State University, 2017, Computer Engineering

The traditional education systems that have been used for several centuries have evolved very slowly and might be ineffective for addressing diverse learning styles and levels of preparation. This system is characterized by many students interacting with a single teacher, who is unable to address the individual needs of every student. Therefore, some students can become frustrated and fail to reach their educational potential. An Intelligent Tutoring System (ITS), which is a computer application used to provide students with one-to-one supplemental tutoring tailored to the student's learning style and pace, is of interest to educators for improving student learning. To evaluate the effectiveness of ITS, a systematic review of the recent literature was performed using a carefully crafted protocol designed to provide data to support a meta-study of the effectiveness of ITS. The research question guiding this study is: “Does an intelligent tutoring system improve students' learning abilities more than traditional learning?” A t-test, one-way ANOVA test, and KNIME program that does Latent Dirichlet allocation were performed. The results support the conclusion that ITS causes a significant improvement in learning over traditional instructional methods.

PhD, University of Cincinnati, 2003, Engineering : Civil Engineering

Productivity improvement of manufactured housing (MH) production systems has been a great concern to manufacturers and production managers. The evaluation of the production system efficiency in the factory is essential for meeting the growing demand of customers with respect to design and size of the manufactured housing product (MH). The purpose of this research is to resolve some of the problems of the MH production system. The problems of the existing system are identified in the masters thesis, Abu Hammad 2001, as follows: i) process bottlenecks hindering productivity, ii) unbalanced processes, and iii) layout limitations to the production capacity. Moreover, a lack of technology is observed in the existing MH operations. Existing production systems employing the traditional production line have low throughput and are inefficient. This dissertation research explores alternative layout designs that are proven via simulation to be more efficient and productive. Additionally, an advanced MH production system employing recent theories in technology and manufacturing is addressed in this research. The major contribution of this dissertation is to develop a decision support system (DSS), which provides the MH industry with an efficient tool to streamline the performance of existing MH facilities. This dissertation investigates the interrelation impact of multiple factors on the productivity of four modules: (i) market, (ii) factory, (iii) manufactured housing processes, and (iv) production system layout. The following objectives have been achieved in support of the stated goal: 1.Develop a streamlined MH process; 2.Develop optimization models to streamline the activities and predict relevant parameters; 3.Develop advanced layout designs employing recent theories in manufacturing (i.e., lean production theory). The DSS provides assistance in the following decisions: (i) selecting an efficient system layout matching user requirements, (ii) streamlining activities and op (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2005, Mathematics

Steiner triple systems are known to exist for orders $n equiv 1,3 mod 6$. There are many known constructions for infinite classes of Steiner triple systems. However, Steiner triple systems that lack prescribed configurations are harder to find. This thesis resolves the problem of determining the spectrum of orders of anti-mitre Steiner triple systems and gives a proof that the spectrum of orders of 5-sparse Steiner triple systems has arithmetic density 1 as compared to the admissible orders. Several anti-mitre and 5-sparse Steiner triple system constructions are provided as well.

Doctor of Philosophy, The Ohio State University, 2004, Computer and Information Science

The advent in both storage architectures and networking technologies has facilitated storage services using networked storage systems. Often, as many researchers and developers are acutely aware of, hardware and architecture developments that purport to improve performance lack synergy with the software systems they were intended to enhance. New developments in both storage architectures and networking technologies have a profound impact on the design and implementation of networked storage software. In this dissertation, we explore the effects of these advances on the development of networked storage software systems. In particular, how these advances influence communication and memory management and how to design new communication and memory management schemes to take advantage of these advances are investigated. This dissertation first focuses on communication and memory management in the transport layer of a cluster file system over InfiniBand to make the most out of InfiniBand benefits. This dissertation then presents an integrated communication buffer and cache management. This integrated management not only eliminates redundant memory copying and multiple buffering which are considered as main performance bottlenecks of networked storage systems in the general-purpose operating systems, but also enables networked storage software to take full advantage of RDMA benefits in emerging network technologies. This dissertation also introduces a buffering scheme to achieve efficient exclusive caching in multi-level cache hierarchy which is often formed in networked storage systems, which makes better use of memory resources in different cache levels. The main conclusion of this dissertation is that using innovative methods to manage communication and memory can significantly improve performance and scalability of a networked storage system. To achieve this requires studying and taking advantage of the new features in the emerging networking technologies and storage a (open full item for complete abstract)

Master of Science (MS), Ohio University, 2011, Electrical Engineering (Engineering and Technology)

The thesis develops, tests and implements a hybrid frequency domain and state space system identification method. A frequency domain least squares system identification algorithm, along with a coherence function technique for eliminating noisy data is used to sequentially develop discrete single-input, multiple-output (SIMO)transfer function models between each input and the outputs. From the transfer function models, difference equations are obtained. Using the difference equations, discrete impulse responses between each input and each output are computed. These impulse responses are then processed by a state space system identification technique to create a minimum order state space multiple-input, multiple-output (MIMO) model. This process is illustrated with a MIMO example and with data from a laboratory facility called Flexlab.

Master of Science (MS), Ohio University, 1982, Industrial and Manufacturing Systems Engineering (Engineering)

A methodology of space allocation for implementation at Ohio University

Master of Science (MS), Ohio University, 1994, Electrical Engineering & Computer Science (Engineering and Technology)

A shipboard global positioning system carrier phase interferometric aircraft flight reference system

Master of Science (MS), Ohio University, 1996, Electrical Engineering & Computer Science (Engineering and Technology)

Investigating the effect of the DGNSS SCAT-I data link on VOR signal reception

Master of Science (MS), Ohio University, 2001, Industrial and Manufacturing Systems Engineering (Engineering)

This research is aimed at presenting a meta-model that will be used as a basic structure of modeling an on-line selling distribution system. In an electronic commerce (EC) business system, demand, operating conditions and environment are random and unpredictable. An EC business system also involves several sub-systems, such as:information, manufacturing, communication, and management. In addition to this, the entire system is based on a static distribution system and operated in a dynamic environment. Therefore, a reliable mathematic model is not to be available. Instead of modeling this system in a direct way, we can separate the modeling into two levels. Within the first level, we will define and model the static distribution system. At the second level, we will define and model the dynamic characteristics and behaviors. Then we can combine these two together as a meta-model for the decision makers. Decision makers can use this meta-model as a basic structure for systems such as this.

Master of Science (MS), Ohio University, 2001, Electrical Engineering & Computer Science (Engineering and Technology)

The next generation of advanced aircraft landing system will utilize the Global Positioning System (GPS). The availabilityof GPS is augmented by the use of pseudolites "pseudo satellites." Pseudolites transmit a GPS-like signal that can be used as a ranging source in place of or in addition to ranging sources from a satellite. The Local Area Augmentation System (LAAS) is being used to further augment GPS for precision approaches and landings by using a concept known as Differential GPS (DGPS). One major error source in DGPS is due to transmitted signal reflections (multipath) off nearby obstacles. Efficient antenna design can be used to mitigate multipath by severely attenuating signals from negative elevation angles. The research contained in this document was conducted in order to optimize the current wideband airport pseudolite (WBAPL) multipath limiting antenna (MLA) for pseudolite transmission in the LAAS. To that end, three phases of study were conducted. The first stage modeled the ground-to-air link between the WBAPL transmitting MLA and the reception antenna during approaches with an attempt to define optimal WBAPL antenna locations. The second stage was conducted to characterize the basic pattern requirements of the WBAPL transmitting MLA and sought to project a hypothetical coverage volume given a preliminary pseudolite antenna pattern. The third stage was performed to attain some level of validation for the new WBAPL MLA transmitting antenna pattern measured by an external contractor through the independent synthesis of a similar antenna radiation pattern.

PHD, Kent State University, 2012, College of Business and Entrepreneurship, Ambassador Crawford / Department of Management and Information Systems

Timely identification and reporting of rare infectious diseases has important economic, social and health implications. In this study, we investigate how different stakeholders in the existing reporting system influence the timeliness in identification and reporting of rare infectious diseases. Building on the vision of the information supply chain (Marinos, 2005; Sun & Yen, 2005) and drawing upon co-ordination theory to investigate inter-organizational dependencies, this dissertation treats information processing and transfer as an information supply chain system whose key performance indicator is timeliness. Jajosky and Groseclose (2004) identified that information reporting lead time is related to the number of layers of reporting. In this dissertation, we look at three layers of reporting rare infectious diseases in the Ohio Disease Reporting System (ODRS), and identify factors that influence the delay in processing and reporting of these diseases. The three layers considered are those for which the county public health system is responsible for the preventive and control measures of any event of rare infectious diseases and is also responsible for entering the confirmatory information into the state reporting system i.e. ODRS. This dissertation investigates the rare infectious disease reporting system in a way different from traditional approaches. Our view of a reporting system is an information supply chain, just as any product supply chain, with different layers in reporting, in which exist interactions between the members (hospitals, laboratories and public health system). We no longer treat the rare infectious disease information supply chain system as point-to-point, but instead as layer-to-layer relationships and examine in detail the factors influencing the delay in these layers. We use simulation based modeling to represent in a more natural way the individual interactive entities in the information supply chain system and to investigate the lead tim (open full item for complete abstract)

Master of Sciences (Engineering), Case Western Reserve University, 2011, EECS - Electrical Engineering

This thesis describes a cost effective, accurate, and precise electronic navigation system which is suitable for outdoor commercial mobile robots. The hardware design of the system incorporates commercial off the shelf Global Positioning System receiver modules and support electronics. The software design of the system makes use of an open source positioning library to enable Real Time Kinematic satellite positioning. The designed navigation system has been integrated with a preexisting mobile robot platform, an autonomous robot lawn mower, which includes a set of reference sensors to provide accurate robot pose information. The reference platform is used to quantitatively evaluate the performance of the new cost effective system. A degradation factor of 1.7 in terms of positional accuracy is traded off in favor of achieving a cost savings factor of about thirty.

Master of Science, University of Akron, 2009, Biology

The immune system is responsible for protecting the body from disease by identifying by destroying pathogenic microorganisms, materials and even dangerous self-cells. This protection is carried out by specialized cells which are found in the bone marrow, circulating blood, thymus, lymph nodes, spleen, as well as other lymphatic tissues. These cells each carry out specific functions and convey different types of protection. Modulation of the balance of either the number or functionality of these immune cells can lead to immune deficiency, susceptibility to disease, or autoimmune disorders such as chronic inflammation. A number of studies have shown that the immune system can be affected by both physical and psychological stresses, such as depression and post-traumatic stress disorder (PTSD). In the present study we examined immune status in women victims of intimate partner violence (IPV). Immune system parameters measured included both immune cell counts as well as functionality of the cells. The results indicated that victims of IPV who suffered from depression and PTSD showed significantly higher baseline activity of natural killer (NK) cells and decreased change in NK cell activity when stimulated with heat shock protein 60 (HSP60). This drop in reactivity to a typical cellular stress signal could put PTSD positive IPV victims at risk for a number of diseases, including cancer development and viral infection. Also, an increased basal activity of NK cells could indicate an autoimmune pathology. These results may lead to a better understanding of the health issues associated with IPV, PTSD, and depression, and will hopefully assist in the development of better and more complete therapies.