Master of Science in Mechanical Engineering, Cleveland State University, 2024, Washkewicz College of Engineering

Utilizing pure hydrogen as an energy source is becoming more realistic as technology is advancing. Hydrogen has been historically difficult to produce, store, and transport. Natural gas is the main clean energy source currently. It is composed of mainly methane. Methane is made up of a carbon atom and four hydrogen atoms. When methane is burned to create heat in industrial processes, carbon emissions are released. This contributes to climate change. Burning pure hydrogen does not produce carbon emissions. Burning hydrogen, especially with the current infrastructure, has potential issues. This thesis investigates the combustion of a mixture of hydrogen and natural gas. This will better suit the current infrastructure and produce less pollution than just burning natural gas. This thesis will focus on the stability of laminar premixed combustion of different mixtures of hydrogen and methane. An issue with combustion is stability. There is generally a stability window in which a flame will be stable. This can be influenced by the flow rate, medium in which combustion is occurring, type of combustion, and oxidant-fuel ratio. This will provide theoretical stability limits based on the mass flow rate for each mixture. Stability limits are important as they set the limits for flow rate and Oxidant-Fuel ratio. There are improvements that can be made with the physical combustion medium to improve these limits. This thesis utilizes Ansys Chemkin. The Chemkin code utilized in this thesis was confirmed utilizing a peer reviewed article. This is a numerical study that can provide theoretical predictions based on calculations.

Master of Science, Miami University, 2025, Mechanical Engineering

Polydimethylsiloxane (PDMS), a versatile silicon-based polymer, is widely used in biomedical devices, microfluidic systems, wearable technology, and electronics due to its mechanical flexibility, optical clarity, electrical conductivity, and biocompatibility. However, its low Young's modulus and tensile strength limit its application in high-stress environments. To enhance its mechanical and functional properties, this study explores the incorporation of carbon fibers (CF) and graphene (Gr) as reinforcements. Despite the potential benefits of these nanomaterials, challenges such as aggregation, void formation, and poor interfacial bonding often compromise composite performance. This research integrates acoustic field (AF) technology into inkjet-based additive manufacturing (AM) to address these issues. The AF enhances material dispersion, reduces defects, and improves bonding between reinforcements and the PDMS matrix. The study evaluates the effects of CF and Gr reinforcements with AF treatment on the mechanical, microstructural, and dynamic properties of PDMS composites. Furthermore, it investigates the impact of different percentages of graphene content on the electrical resistance and mechanical properties graphene-reinforced-PDMS for wearable sensor applications. Results demonstrate that optimal graphene content balances dispersion and aggregation, thus, maximizing mechanical strength and electrical conductivity. By introducing AF-assisted AM, this study provides insights into producing high-performance PDMS composites for advanced applications, particularly in sensors and flexible electronics.

Master of Science in Aerospace Systems Engineering (MSASE), Wright State University, 2024, Mechanical Engineering

The development of high order numerical schemes has been instrumental in advancing computational fluid dynamics (CFD), particularly for applications requiring high resolution of discontinuities and complex flow phenomena prevalent in high-speed flows. This thesis introduces the Pade-ENO scheme, a high-order method that integrates Essentially Non-Oscillatory (ENO) techniques with compact Pade stencils to achieve superior accuracy, up to 7th order, while maintaining stability in harsh environments. The scheme's performance is evaluated through benchmark tests, including the advection equation, Burgers' equation, and the Euler equations. For high Mach number flows, such as the sod shock tube the Pade-ENO method demonstrates its ability to resolve sharp gradients and discontinuities with no smoothing required. Numerical results highlight the scheme's robustness and its potential as a powerful tool for high-speed aerodynamic simulations, paving the way for future advancements in CFD modeling.

Master of Science in Renewable and Clean Energy Engineering (MSRCE), Wright State University, 2024, Mechanical Engineering

Lithium-ion batteries are an integral component of energy storage systems for renewable energy applications owing to their high energy density. Extensive research has therefore been carried out, utilizing both experimental and computational methods, to aid in a deeper understanding of lithium-ion batteries. Challenges related to efficiency, safety and thermal management persist, particularly during high current draw, extreme temperature conditions and extreme dynamic current operation such as in electric vehicles. This thesis work presents an electrochemical-thermal model of a lithium-ion battery that simulates and analyzes the variation of electrical behavior, chemical behavior and thermal behavior. The electrochemical model is developed by computationally finding solutions to a set of partial differential equations that describe electrochemical and thermal processes in the anode, separator and cathode. These equations are mass conservation in electrodes (cathode and anode), charge conservation in electrodes, mass conservation in the electrolyte, charge conservation in the electrolyte, and a thermal energy balance throughout the battery. In addition, the Butler Volmer equation is used to describe the exchange of lithium ions between the solid electrodes and the electrolyte. The solutions to these equations are found using a finite volume numerical procedure implemented in MATLAB. This computational model builds on the work of Borakhadikar [1] who did not deal with the thermal issue. The results obtained by the developed program are validated against those from Smith and Wang [2] and Gu and Wang [4]. Once it is determined that the program is producing good results, a number of other results are generated for the reader to review. Profiles of the lithium-ion concentrations, profiles of the voltage, and profiles of the temperature across the battery at a given discharge level are presented. In addition, the voltage output and temperature as a function of time are g (open full item for complete abstract)

Doctor of Philosophy (Ph.D.), University of Dayton, 2024, Electrical and Computer Engineering

Additive manufacturing (AM) technology is rapidly advancing across diverse fields. For instance, the use of robotic arms in various AM processes has led to significant gains in printing flexibility and manufacturing scalability. However, despite these advancements, there remains a notable research gap concerning the mechanical properties of parts 3D-printed with robotic arms. This study focuses on developing a robotic fused filament fabrication (FFF) 3D-printing process with a layer resolution of 50 μm to 300 μm. The impact of the robotic printing process on the mechanical properties of printed parts is investigated and benchmarked against a commercial FFF 3D printer. In addition, we propose a novel tool path that can vary contour layer thickness within an infill layer to improve mechanical strength by minimizing air gaps between contours. SEM images suggest that this new tool path strategy leads to a significant reduction in the fraction of the void area within the contours, confirmed by a nearly 6% increase in the ultimate tensile strength. Furthermore, a novel strategy for non-planar contours is proposed, specifically designed for thin-shell 3D models. This approach aligns tool paths parallel to the Z-axis, organized into triangular segments, and utilizes planar slicing techniques. The method involves segmenting the point cloud and systematically printing non-planar contours on top of the planar contours. Axial compression testing reveals that samples produced using this strategy exhibit mechanical properties comparable to those of conventional 3D printing. However, distinct fracture patterns are observed: in conventional 3D-printed samples, fractures occur on both inner and outer surfaces, while in non-planar printed samples, fractures are confined to the inner surfaces (planar contours) and do not propagate to the outer non-planar contours. This demonstrates the potential of non-planar printing for improved structural integrity.

Master of Science in Engineering, Youngstown State University, 2024, Department of Mechanical, Industrial and Manufacturing Engineering

This is a study on optimizing the Laser Hot-wire Directed Energy Deposition (LHW-DED) process Invar 36 steel deposition onto an A36 mild steel substrate. This study aims to investigate Numerical Analysis as well as thermocouple measurements, on the transient thermal model to discuss potential solidification mechanisms. Unlike most-existing studies which focus is on single or few-layer geometries, this research presents a multi-layered model capable of predicting thermal analysis during deposition. A transient thermal model was developed to evaluate the effects of conduction, convection and radiation on the printing beads. The numerical model results were compared with the temperature data measured using thermocouples. The integration of experimental and numerical approaches enhance the accuracy of the findings, providing valuable insight into the thermal behavior of the DED process. This understanding is crucial for optimizing parameters and improving the quality of printed structures. The study highlights the significance of accurately modeling thermal interactions to advance the precision and efficiency of DED additive manufacturing. The detailed study of the LHW-DED additive manufacturing process focusing on the experimental setup, materials used, and the potential impact of the research on advancing the understanding and application of this innovative manufacturing technology. The numerical simulation with experimental data is to ensure the accuracy of the thermo-mechanical model. This will involve in measuring profiles, residual stresses, and material properties during the actual LHW-DED process.

MS, University of Cincinnati, 2024, Engineering and Applied Science: Mechanical Engineering

In industries such as mining and powder handling, workers are at risk of exposure to inhaling particulates as the powder can get aerosolized in their work environments. It is critical to characterize the dustiness or propensity of powders to get aerosolized to quantify workers' health risks. The Venturi Dustiness Tester (VDT) is widely used for this purpose. The aerosolization process in this device starts at the powder holding tube, where a dome or hill of powder is exposed to very high flow rate and the aerosol gets sucked into the measurement chamber where it is sampled for dustiness characterization. The process of powder hill aerosolization occurring in VDT is very complex as the obstruction caused by the dome leads to vortex shedding and the shape of the hill changes with aerosolization. To keep the problem tractable, a simplified model problem of flow over a solid hemisphere attached to a horizontal substrate in a rectangular duct is analyzed in this thesis. While this model does not account for changing shape of the hill during the aerosolization process, flow features like vortex shedding and their effect of shear and lift forces acting on the dome surface are captured. This information will be useful in understanding how particulate in a powder hill are likely to be affected by the flow. The flow dynamics in the simplified configuration were explored for different flow speeds, including creeping flow (Re<<1), laminar flow, and turbulent flow using computational fluid dynamics techniques. To obtain the inlet velocity profile to provide the inlet boundary condition for the unsteady simulations of flow over the solid dome, a set of steady-state empty duct simulations were performed first. A grid convergence study was carried out at Re = 1000 to establish grid-independent results for the unsteady simulations. The optimized grid was then used for all Reynolds numbers. In the creeping flow regime, the flow was found to be symmetric around the hemisphere as t (open full item for complete abstract)

PhD, University of Cincinnati, 2024, Engineering and Applied Science: Mechanical Engineering

Combining strain FRF data and acoustic pressure FRF data with displacement FRF data for modal parameter estimation is the focus of this research. While these measurements have been shown to work standalone for modal analysis, it has not been shown experimentally that different physical measurements can be combined to get the same modal results. Recent work by Coppolino [1], showing that at least in theory this combination should be possible and should yield the same modal results as when only accelerometer FRF data is used, was important to the following work. This dissertation attempts to experimentally obtain data for strain, pressure and displacement FRF data and combine these three datasets in different ways to explore if some displacement information can be replaced without changing the modal parameter results. The data acquired is from several impact hammer tests carried out on a flat rectangular plate. Two different ways of combining this data have been discussed with all the possible combinations explored. Modal frequencies and damping have been compared and modal assurance criterion used to compare modeshapes. Intuitively speaking, strain and displacement can seem to have ‘inversed' behavior as in the simple case of a cantilever beam. To evaluate this concern, finite element based analytical work has been presented to check which locations on the structure are best to measure strain FRFs to be able to replicate modal parameters obtained from an only displacement FRF analysis. A new criterion, local scale factor consistency, has been developed to be able to compare shapes degree of freedom by degree of freedom as well as mode by mode.

MS, University of Cincinnati, 2024, Engineering and Applied Science: Mechanical Engineering

Waste anesthetic gases (WAG) are composed of halogenated agents that pose adverse short and long-term health risks for personnel who are directly in contact with them in a routine manner. WAG can be released or leaked to the surrounding areas due to multiple reasons including ventilatory equipment failure and patient's breathing. In the post-anesthesia care unit (PACU), these gases represent a potential exposure risk particularly for healthcare staff including nurses and attendants. Long-term inhalation of WAG can lead to renal, liver failure and birth defects. To mitigate such adverse effects, a clear understanding of the flow dynamics, dilution, and dispersion of WAG along with their exposure rates is crucially needed. To address the associated knowledge gap in the literature, the current study investigates the flow and mixing of WAG after release from a patient and the potential exposure to a nurse using CFD simulations. A steady, three-dimensional turbulent flow in the PACU is numerically modeled by solving the mass, momentum, and species conservation equations. The computational domain includes a single room in a post-anesthesia care unit with a patient lying on a bed with a nurse standing next to the bed. Three different patient orientations of the patient face either towards the nurse or the room ceiling are considered. Different flow conditions for the PACU have also been analyzed including varying the flow rates from outlet vents, reversing the ventilatory flows, and changing the background wall conditions of the PACU room from periodic boundaries to solid walls. Additionally, breathing sensitivity analysis has been conducted by simulating different nurse inhalation and patient exhalation rates to account for the breathing processes in the dispersion and exposure of WAG. Furthermore, the role of closed and open-face tent masks in restricting or leaking the WAG from the patient's m (open full item for complete abstract)

MS, University of Cincinnati, 2024, Engineering and Applied Science: Mechanical Engineering

The development of dynamic systems (both physical plant and control systems) in a sequential manner often results in sub-optimal solutions. However, solutions obtained using combined physical and control system design methodologies have been observed to yield optimal solutions. The overarching interest in obtaining closed-loop solutions with decent computational cost requirements brings about the topic of interest - a comparison of two of the most popular methods employed to cater for this: Model Predictive Control and Dynamic Programming. If the primary requirement is real-time control with a need to handle constraints dynamically, Model Predictive Control (MPC) is the more practical choice. If the problem allows for offline computation and requires globally optimal solutions, and the state and action spaces are not extremely large, Dynamic Programming (DP) may be more practical. This work studies both methods with respect to accuracy, type of closed-loop feedback solutions, and computational efficiency. Both methods are incorporated within a nested control co-design formulation. To validate the accuracy of both techniques, their practical application is demonstrated through case studies involving a single link manipulator, a single pendulum-type crane, and a quarter car suspension system. Each case study includes a model description, problem formulation, and results obtained using both MPC and DP techniques. The findings highlight the effectiveness of nested formulations with feedback methods in achieving optimal control co-design, with comprehensive assessments of each approach.

Master of Science (M.S.), University of Dayton, 2024, Mechanical Engineering

The goal of this work is to analyze and characterize solid granular media in high temperature CSP applications. This work expands on commercially available Discrete Element Method (DEM) modeling software, Aspherix®, through development of two calibration templates designed to mimic both the experimental rigs for the slump test and rotary kiln discussed in this thesis. Whereas, designed experimental rigs were developed to isolate desired frictional behaviors in three different material types (CarboBead HSP, CarboBead CP, and Granusil) for temperatures varying from 25°C – 800°C. Additionally, improvements were made upon the previously constructed rotary kiln to facilitate high temperature testing experimentally.

Master of Science (M.S.), University of Dayton, 2024, Aerospace Engineering

Modern aircraft are overburdened by electrical systems, which are continually increasing their power demands. To generate power on aircraft flying in high speed regimes where high temperatures are imposed by viscous heating, solid state devices can be employed. The high temperature gradient across the thermal protection system of the aircraft creates an ideal environment for thermoelectric generator (TEG) application. The North American X-15 was chosen for its high speed fight profiles and wealth of information available. The fight profiles and geometry will be used to gather data in a more applied sense. One-dimensional codes have been written to model the system's performance over the course of a specified fight profile. Utilizing generic relations, the flow temperature was determined through radiative equilibrium methods, which was then fed to the remaining system. The performance of the system was evaluated over the X-15 high speed mission fight profile. The thicknesses of each component of the system were varied until an optimal range was found. The optimal values found were used as the basis for the remaining computational modeling and physical testing. A high-fidelity modeling effort has been completed to model both the high temperature flow and the transient thermoelectric generator operation. The high temperature flow model is solved in parallel with a conduction heat transfer model of the vehicle skin. This allows the flow and solid bodies to react to one another throughout the transient operation. The models are loosely coupled to a high-fidelity model of a thermoelectric generator. The specific TEG model has been constructed to represent a physical module that was obtained for the physical test articles. Accompanying the computational modeling, two physical test articles have been developed and studied. The first consists of a single TEG stack consisting of a skin material, the TEG, and a heat sink. The second test article includes multiple TEGs within s (open full item for complete abstract)

Master of Science, Miami University, 2025, Mechanical and Manufacturing Engineering

Reduced order modeling (ROM) methods, such as those based upon Proper Orthogonal Decomposition (POD) and Dynamic Mode Decomposition (DMD), offer data-based turbulence modeling with potential applications for flow control. While these models are often cheaper than numerical approaches, their results require validation with source data. Within the literature, the metrics and standards used to validate these models are often inconsistent. Chabot (2014) produced a data-driven framework for validating these ROMs that used surrogate Markov models (SMMs) to compare how the system dynamics evolved rather than how any single metric evolved. These SMMs were constructed by clustering the flow data into different states of suitably similar flow fields, and the Markov model then mapped how likely each state was to transition into another. While this method was successful, there persisted an amount of uncertainty in how the outlier states within this clustering scheme were determined. Additionally, the study only examined the application of this procedure to POD-Galerkin ROMs. This study aims to tie the outlier state determination directly to the models' parent data. The study will also apply this procedure to ROMs generated from DMD to investigate how this framework's effectiveness carries over to different classes of ROMs.

Master of Sciences (Engineering), Case Western Reserve University, 2025, EMC - Mechanical Engineering

Particle Image Velocimetry (PIV) is a technique that allows velocity measurements of a 2D plane of a fluid flow by illuminating seeding particles in the fluid with a laser sheet. However, the use of laser is often costly, introduces complexity, and poses a challenge in near-wall measurements due to light scattering from surfaces. Particle shadow velocimetry (PSV) is a novel velocimetry technique with the potential of being a low-cost, laser-free alternative to the established PIV technique. It works by tracking shadows cast by the seeding particles on an illuminated background. Little is known about the accuracy of this technique validated against PIV. This study starts by characterization the performance of this technique, presents results from two experiments using both PIV and PSV on the same plane, and discusses its advantages and potential applications.

Master of Science, Miami University, 2024, Mechanical and Manufacturing Engineering

Selective laser sintering (SLS) technique has emerged as an important method in additive manufacturing, facilitating the manufacturability of complex lattice structures, known for their high stiffness-to-weight ratios. However, these structures face mechanical limitations, such as low compressive strength and energy absorption, restricting their use in demanding industries like aerospace and automotive. This study addresses these challenges by reinforcing SLS-printed Nylon 12 (Polyamide 12, PA12) lattice structures with thermoset resins (Bisphenol A, BPA epoxy), forming layered composites that significantly improve compressive performance. A continuous rotation coating technique was introduced to overcome the uneven reinforcement observed in traditional dip-coating methods, achieving a uniform resin distribution. The optimized coating method resulted in a 13% improvement in compressive yield strength compared to dip-coated samples, contributing to an overall 139% increase relative to unreinforced PA12. Further enhancement was achieved through the incorporation of functionalized graphene nanofillers into the PA12/thermoset matrix, with the optimal configuration (68:32 PA12-to-BPA epoxy ratio with 0.1 wt% graphene) yielding a 201% increase in compressive yield strength and a 154% increase in specific energy absorption. Image analysis confirmed improved adhesion, and improved structural integrity at the samples with optimal configuration. Findings from this study provide a pathway for industrial applications of SLS-printed lattice structures, enabling lightweight, high-strength components for aerospace and automotive industries.

Doctor of Philosophy (Ph.D.), University of Dayton, 2024, Mechanical Engineering

Water scarcity is a growing challenge worldwide, resulting from increased population growth, industrial practices, and shifting climates. Researchers have been studying reliable, efficient, and cost effective, ways and techniques to obtain high quality fresh water using both a renewable and clean energy source such as power from solar energy or solar thermal concentration. Independent, self-operated, and low maintenance systems are highly desired for desalination systems. Deployable, solar-thermal desalination systems are promising technologies for promoting water security and sustainable community development in remote or storm-damaged coastal regions. However, these systems produce less distillate per unit energy input compared to industrial- scale desalination systems. The introduction of novel, metallic wicks in these systems increases distillate efficiency by generating an evaporation interface. It is proposed that metallic wicks with optimized micro-structure porous properties, i.e. porosity, permeability, capillary pressure, etc., will further increase distillate yields in capillary-driven desalination modules. Recent studies have demonstrated the potential of metallic wicks for increased distillate production at low-temperature (< 60 °C) operation. Many other studies assessed the quality of the distilled water, but they did not evaluate the salt accumulated at the water- vapor interface within the wick resulted from the evaporation. Another important issue that impacts the passive flow resulted from the wicking action is the dry-out that might occur within the metallic wick in the porous medium due to the evaporation process. A two-dimensional, steady-state heat and mass transfer study was performed to investigate the impact of various microstructure properties such as porosity and permeability, and environmental conditions such as solar irradiation on the distillate yield, wick dry-out, and salt diffusion/precipitation within candidate porous media struct (open full item for complete abstract)

Doctor of Philosophy, Case Western Reserve University, 2025, EMC - Mechanical Engineering

Cortical bone allograft sterilized with a standard gamma radiation sterilization dose of 25–35 kGy has demonstrated reduced cyclic fatigue fracture resistance compared with unirradiated bone. Understanding the potential dose-dependent response of fatigue behavior of cortical bone, as well as the response of collagen damage (i.e. chain fragmentation and crosslink accumulation) that may contribute to losses in fatigue behavior, may mitigate radiation damage of structural cortical bone allografts. Sequential irradiation has also been reported to mitigate the loss of fatigue life of tendons; however, whether this mitigates losses in fatigue life of cortical bone has not been explored. The objectives of this dissertation were: to evaluate the radiation dose-dependency of fatigue crack propagation resistance and the influence of collagen chain fragmentation and crosslinking on fatigue crack propagation resistance from 0–25 kGy; to evaluate the radiation dose-dependency of high-cycle fatigue life and the influence of radiation-induced collagen chain fragmentation and crosslinking on the high-cycle fatigue life from 0–15 kGy; and to evaluate the capability of sequential irradiation at 15 kGy to mitigate the loss of fatigue behavior and radiation-induced collagen damage. High-cycle fatigue life (n=7-10) and fatigue crack propagation tests (n=3-4) were conducted. Following fatigue testing, collagen was isolated from fatigue specimens, and collagen chain fragmentation and crosslink accumulation were quantified. Fatigue crack propagation resistance progressively decreased from 0-25 kGy (p<0.001). Collagen chain fragmentation increased progressively in a dose-dependent manner from 0-25 kGy (p<0.001) whereas crosslink accumulation increased but did not demonstrate dose-dependency (p<0.001). Both collagen chain fragmentation (p=0.006) and non-enzymatic crosslinking (p<0.001) influenced high-cycle fatigue life, which decreased with increasing radiation dose from 0-15 kGy (p=0.016). (open full item for complete abstract)

Master of Science (M.S.), University of Dayton, 2024, Mechanical Engineering

Supercritical carbon dioxide (sCO2) power cycles offer significant advantages in thermal efficiency, component flexibility, and adaptability to various heat sources. This study develops computational functions and multi-objective evolutionary optimization tools to enhance the performance of sCO2 power cycles, specifically targeting applications with finite thermal reservoirs. Leveraging the unique properties of sCO2, including its high density and excellent heat transfer capabilities, the research aims to optimize cycle efficiency, reduce component mass, and manage operational constraints. The research focuses on four primary sCO2 Brayton cycle configurations: Direct Heating – Recuperated Cycle (DH-RC), Direct Heating – Non-Recuperated Cycle (DH-NRC), Indirect Heating – Recuperated Cycle (IH-RC), and Indirect Heating – Non-Recuperated Cycle (IH-NRC). Each cycle is analyzed for its thermodynamic performance, component interactions, and potential for efficiency improvements. The simulation functions developed for these cycles incorporate iterative processes to ensure steady-state conditions and accurate energy conservation. Key to the optimization process are machine learning models and genetic algorithms, which handle the high-dimensional data and complex design criteria associated with sCO2 cycles. The NSGA-II algorithm is employed for multi-objective optimization, focusing on maximizing cycle efficiency and minimizing the mass of the turbine and compressor. This approach allows for the generation of Pareto-optimal solutions, providing a diverse set of optimal design configurations. The study also addresses the critical components of sCO2 cycles, including compressors, turbines, and heat exchangers. Detailed simulations and regression models are developed to predict the performance and mass of these components. The optimization framework integrates these models, allowing for comprehensive analysis and design refinement. For example, the heat exchanger models util (open full item for complete abstract)

Master of Science, The Ohio State University, 2024, Mechanical Engineering

Proton Exchange Membrane (PEM) fuel cells provide the transportation industry with a clean energy solution to significantly reduce greenhouse gas emissions. This thesis presents a comprehensive design and development of a state-of-the-art PEM fuel cell laboratory at the Center for Automotive Research (CAR) at The Ohio State University, intended to support cutting-edge research in fuel cell technology. The laboratory design enables testing across a range of operating conditions, providing insights into fuel cell efficiency, durability, and performance. A 250 cm2 fuel cell served as the foundation for the laboratory's design. A critical aspect of the laboratory design includes rigorous safety measures tailored to hydrogen-based research. Experimental protocols were developed for membrane conditioning and executing polarization curves across various operating conditions. These experimental results were applied to calibrate a control-oriented PEM fuel cell model, allowing for prediction of the fuel cell polarization curve at different operating conditions. The work outlined in this thesis provides the foundations for experimental, modeling and control activities that will advance PEM fuel cell technology and its application to the transportation industry.

Master of Science, The Ohio State University, 2024, Mechanical Engineering

Tooth bending fatigue failure is a primary design concern for gear designers in power transmission applications. Fracture of a gear tooth in operation results in overload conditions to adjacent teeth which cascades into catastrophic failure of the entire power transmission system. While standard constant stress amplitude fatigue evaluations are common to experimentally determine probabilistic stress life (P-S-N) relationships, they do not directly measure the fatigue lives under complex, non-constant amplitude loading applied to gears in most applications. To determine fatigue life under variable load, standard calculation methods for gears employ a linear damage rule; however, many experimental studies have shown that metals exhibit behavior representative of nonlinear damage accumulation. The implications of using linear versus nonlinear damage rules for gear lifetime analysis remain largely unexplored. Furthermore, drive-regen conditions, prevalent in electric vehicle powertrains, induce intermittent torque reversals on the geartrain. Current experimental data addressing this load case is limited and the models derived using that data lack robustness. This research study conducts a standard fatigue evaluation using a gear single tooth bending methodology. Six dual stress amplitude (DSA) datasets are compiled to examine the effects of multi-step loading in a gear specimen. Various cumulative damage fatigue models are then leveraged to estimate the accuracy of each model over two step loading. Select damage models are also applied to simulated load spectra which are more representative of stresses histories observed in a geartrain. Additionally, an experimental evaluation on the effect of intermittent torque reversal on gear bending life is leveraged to supplement an existing model for determining allowable bending stress under intermittent torque reversals.