Master of Science in Engineering, Youngstown State University, 2025, Department of Mechanical, Industrial and Manufacturing Engineering

A continuously variable transmission (CVT) is a type of transmission used commonly in small engine racing such as snowmobiling, go-karting, or in Society of Automotive Engineers (SAE) Baja racing. These transmissions allow for a constantly varying gear ratio while driving, without requiring the driver to shift gears manually. The continually changing ratio adapts well to varying course conditions such as frequent stops and starts, turns, and jumps. CVTs must be properly installed and tuned to reach their highest level of performance, which is a common difficulty for these complex systems. A MATLAB code has been developed that characterizes the torque, horsepower, and shift profile of a Gaged GX9 CVT. This predictive model may be used to select a tune for a vehicle and evaluate its performance without requiring extensive test time on a track. Multiple setups of the primary and secondary were analyzed, including different primary and secondary springs, flyweights, and ramps. The numerical characterization of torque, horsepower, shift curve, and acceleration has been validated experimentally, through the use of an inertia dynamometer, Kohler CH440Pro 14HP engine, and DynoMiteTM analysis software. Theoretical comparison was completed using free body and kinetic diagrams of the forces acting in the system, which were entered into a MATLAB code.   A new inertia dynamometer system has been installed within Youngstown State University's (YSU) engine laboratory, providing a hands-on application of methods learned in the classroom for students. The new installation has been used by several student groups to date. An operator's manual for the system focusing on safety and proper machine operation has been developed to aid in correct usage of the dynamometer. The new installation and numerical modeling completed has also been used to develop a laboratory for mechanical engineering students in the Dynamic Systems Modeling (DSM) class. Within the lab students will learn t (open full item for complete abstract)

Committee: C. Virgil Solomon PhD (Advisor); Hazel Marie PhD (Committee Member); Fred Persi PhD (Committee Member) Subjects: Applied Mathematics; Automotive Engineering; Mechanical Engineering

Doctor of Philosophy, The Ohio State University, 2021, Computer Science and Engineering

Sustainable computing, dark silicon and approximate computing have ushered a new era in which some processing capacity is available only as ephemeral bursts, a technique called computational sprinting. Computational sprinting speeds up query execution by increasing power usage, dropping tasks, precision scaling, and etc. for short bursts. Sprinting policy decides when and how long to sprint. Poor policies inflate response time significantly. However, sprinting alters query executions at runtime, creating a complex dependency between queuing and processing time. Sprinting can speed up query processing and reduce queuing delay, but it is challenging to set efficient policies. As sprinting mechanisms proliferate, system managers will need tools to set policies so that response time goals are met. I provide a method to measure the efficiency of sprinting policies and a framework to create response time models for sprinting mechanisms such as DVFS, CPU throttling, cache allocation, and core scaling. I compared sprinting policies used in competitive solutions with policies found using our models.

Committee: Christopher Stewart PHD (Advisor); Radu Teodorescu PHD (Committee Member); Xiaorui Wang PHD (Committee Member); Xiaodong Zhang PHD (Committee Member) Subjects: Computer Science

Master of Science in Mechanical Engineering (MSME), Wright State University, 2019, Mechanical Engineering

Usually power take off (PTO) with a two-spool turbofan engine has been accomplished via the high pressure (HP) shaft and bleed air from the high-pressure compressor (HPC). The PTO is used to run various aircraft components such as generators and hydraulic pumps, which also produce waste heat. To better understand the coupled transient nature of balancing engine thrust, power take off and thermal management, a transient variable cycle three stream turbofan engine model has been developed to investigate the integrated behavior. The model incorporates many dynamic features including a third-stream heat exchanger as a heat sink for thermal management and HP/LP shaft PTO. This paper describes a method of controlling HPC surge margin and maintaining the desired thrust while extracting power using both the HP and LP spools. The transient interactions as both PTO and 3rd stream heat rejection are simultaneously applied to the transient variable cycle engine model utilizing different control effectors were investigated. The rate of transient heat rejection was found to impact surge margin. Rapidly applied heat loads caused larger surge margin transients than heat loads applied more gradually despite the same maximum heat rejection. Optimal PTO profiles between the LP and HP shaft to minimize the amount of fuel used for a given PTO amount and flight envelope were also investigated. Finally, a notional mission was simulated with varying flight parameters and dynamic PTO based on optimal PTO profiles along with heat generation and afterburner. The controls were found to be sufficient to successfully run the mission however such simplified controls could induce numerical instabilities in certain mission profiles. This shows that while these simple controls are sufficient for these notional test runs more sophisticated controls will be necessary for a proper generic engine model.

Committee: Rory Roberts Ph.D. (Committee Chair); George Huang Ph.D. (Committee Member); Mitch Wolff Ph.D. (Committee Member) Subjects: Aerospace Engineering; Engineering; Mechanical Engineering; Systems Design

MA, University of Cincinnati, 2017, Arts and Sciences: Psychology

The actualization of action possibilities (or affordances) can often be accomplished in numerous, equifinal ways. For instance, an individual could walk over to a rubbish bin to drop an item in or throw the piece of rubbish into the bin from some distance away. The aim of the current study was to investigate the behavioral dynamics arising from such metastable task-spaces using a ball-to-bin transportation task. Participants were instructed to transport balls from a starting area to a bin located 9 meters away. Time interval between the sequential presentation of 52 balls was manipulated as a control parameter and was expected to push participants through different behavioral modes (i.e. the degree to which participants modulated the distance moved prior to throwing or dropping the ball into the target bin). As expected, the results revealed a large degree of within and between participant variability in task actualization. To better understand how this behavioral variability emerged as a function of task constraints, a two-parameter task manifold was devised using the Cusp Catastrophe Model. Simulations demonstrated that this two parameter state manifold can not only effectively capture the wide range of participant behaviors observed, but also explains how these behaviors are an emergent consequence of under-constrained task goals.

Committee: Anthony Chemero Ph.D. (Committee Chair); Rachel Kallen Ph.D. (Committee Member); Michael Richardson Ph.D. (Committee Member) Subjects: Psychology

Doctor of Philosophy, The Ohio State University, 2017, Electrical and Computer Engineering

Dynamic eco-driving is an umbrella term describing speed control schemes that utilize connected and automated vehicle technology for the purpose of saving fuel. If dynamic eco-driving is to be widely prescribed as an integral part of widespread fuel-saving endeavors, its expected performance as part of the overall traffic system must be analyzed. Specifically, it must be determined to what extent this type of control remains effective in the presence of dense traffic. We present first a series of multi-vehicle traffic simulations which begin to answer important questions surrounding the effects of dynamic eco-driving on traffic and its potential for fuel savings in a mixed traffic environment. Three representative methods of dynamic eco-driving are tested in traffic scenarios and the estimated fuel economy, trip time, and average speed results are compared. Independent variables include technology penetration rate and amount of traffic, quantified by the delay level of service of the road network's traffic light facility. It is shown that, for the given test cases, average mpg increases linearly with technology penetration rate and dynamic eco-driving causes an increase in average mpg regardless of traffic amount. Overall, results are promising for the usefulness of this clever class of fuel-saving technologies, in high traffic as well as low. Naturally occurring flocks and swarms have long commanded human attention, with much engineering inspiration being drawn from their beauty, order, and cooperation. Recent simulation and modeling of swarms has given rise to interesting mathematical problems as well as useful control strategies for machine applications. To our knowledge, no microscopic, decentralized model of vehicle interactions based on swarming philosophy exists. Here we develop a new model of vehicle interactions on a two-lane highway, made up of ordinary differential equations and smooth functions. The new model's purpose is not primarily traffic simula (open full item for complete abstract)

Committee: Umit Ozguner PhD (Advisor); Keith Redmill PhD (Committee Member); Andrea Serrani PhD (Committee Member) Subjects: Electrical Engineering

Doctor of Philosophy, The Ohio State University, 2007, Mechanical Engineering

This dissertation uses a robotics-inspired approach to develop a low-dimensional forward dynamic model of normal human walking. The analytical model captures the dynamics of walking over a complete gait cycle in the sagittal plane. The model for normal walking is extended to model asymmetric gait. The asymmetric model is applied to study the gait dynamics of a transtibial prosthesis user. Modeling human walking is complex because walking involves (i) the body's many degrees of freedom (DOF), (ii) constraints that change, and (iii) intermittent contact with the environment that may be impulsive. Complex forward dynamic models that attempt to capture details such as joints with multiple DOF, musculature, etc., are analytically intractable; it is impossible to describe the model's behavior in mathematically manageable terms because of the enormous number of variables and redundancies involved. Observation of human walking from a systems point of view reveals that the human body coordinates its many DOF in a parsimonious manner to accomplish the task of moving the body's center of mass from one point to another. This dissertation's approach exploits this parsimony to derive an analytically tractable model that has the minimum DOF necessary to describe the task of walking in the sagittal plane. The low-dimensional hybrid model is derived as an exact sub-dynamic of a higher-dimensional anthropomorphic hybrid model. The hybrid nature is the result of continuous sub-models of single support (SS) and double support (DS), and discrete maps that model the transitions from SS to DS and DS to SS. The modeling is validated using existing gait data. To extend the clinical usefulness of the modeling approach, the model for normal walking is extended to model asymmetric gait. The asymmetric model can accommodate asymmetries in the parameters and joint motions of the left and right legs. The asymmetric model is applied to analyze the gait dynamics of a transtibial prosthesis user. Co (open full item for complete abstract)

Committee: Eric Westervelt (Advisor) Subjects:

Doctor of Philosophy, The Ohio State University, 2005, Electrical Engineering

This dissertation presents circuit models and control algorithms of fuel cell based distributed generation systems (DGS) for two DGS topologies. In the first topology, each DGS unit utilizes a battery in parallel to the fuel cell in a standalone AC power plant and a grid-interconnection. In the second topology, a Z-source converter, which employs both the L and C passive components and shoot-through zero vectors instead of the conventional DC/DC boost power converter in order to step up the DC-link voltage, is adopted for a standalone AC power supply. In Topology 1, two applications are studied: a standalone power generation (Single DGS Unit and Two DGS Units) and a grid-interconnection. First, dynamic model of the fuel cell is given based on electrochemical process. Second, two full-bridge DC to DC converters are adopted and their controllers are designed: an unidirectional converter for the fuel cell and a bidirectional converter for the battery. Third, for a three-phase DC to AC inverter without or with a Δ/Y transformer, a discrete-time state space circuit model is given and two discrete-time feedback controllers are designed for voltage control and current control. And last, for load sharing of two DGS units and power flow control of two DGS units or the DGS connected to the grid, real and reactive power controllers are proposed. Particularly, for the grid-connected DGS application, a synchronization issue between an islanding mode and a paralleling mode to the grid is investigated, and two case studies are performed. In Topology 2, this dissertation presents system modeling, modified space vector PWM implementation and design of a closed-loop controller of the Z-source converter for the standalone AC power generation. The fuel cell system is modeled by an electrical R-C circuit in order to include slow dynamics of the fuel cells and a voltage-current characteristic of a cell is also considered. A discrete-time state space model is derived to implement digital (open full item for complete abstract)

Committee: Ali Keyhani (Advisor); Donald Kasten (Other); Vadim Utkin (Other) Subjects: