MS, University of Cincinnati, 2023, Engineering and Applied Science: Mechanical Engineering

Bubble dynamics is an integral part of various industrial processes such as aeration, bubble column reactors, and has been a topic of active research for nearly eight decades. Significant progress has been made towards understanding the factors governing the departure bubble size and shape, in particular the effect of liquid physicochemical properties. Bubble dynamics plays an important role in industries such as cosmetics, pharmaceuticals, and paints where a large majority of the liquids being used are of non-Newtonian nature and undergo a change in their viscous properties under the effect of stress. The complex thermo-physical properties of non-Newtonian fluids play a huge role in dictating the bubble growth process and needs further investigation. The aim of this work is to gain a better understanding of the complex physics governing the growth of bubbles from capillary orifices submerged in liquid pools of aqueous solutions of polymers under constant gas flow rate through a combination of experimental and computational approaches. A comprehensive evaluation of existing computational techniques for studying single bubble growth is carried out and coupled level set VOF technique with modifications to the property estimation equation is suggested as a reliable technique to accurately model bubble growth in highly viscous fluids, with large capillary numbers greater than 1. Following this, a brief characterization of non-Newtonian fluids is made along with a comparison of most frequently used rheology models. Selecting the right model plays an important role in computational modeling as each model has its limitations and hence may only be applicable for certain concentrations of polymers. Rupesh Bhatia has shown in his work that the asymptotic forms of certain rheology models work better in characterizing the fluid and the importance of the Asymptotic Power Law (APL) model in the computational modeling of bubble growth in shear-thinning non-Newtonian fluids is esta (open full item for complete abstract)

Committee: Raj Manglik Ph.D. (Committee Chair); Milind Jog Ph.D. (Committee Member); Kishan Bellur Ph.D. (Committee Member) Subjects: Mechanical Engineering

Doctor of Philosophy, University of Akron, 2023, Chemical Engineering

Sustainable development becomes an important topic due to the escalating energy shortage and environmental change. Governments around the world have taken various steps and implemented several initiatives in addressing pressing environmental issues. Green technology and innovations have been largely promoted not only in cutting-edge research but also in industry and manufacturing sectors. Among those sustainable practices, methane conversion, hydrogen storage, and fuel cell play crucial roles that promote energy efficiency and contribute to a circular economy. The dissertation aims to understand the chemical aspects in these three fields for sustainable development. For example, (1) methane, as a potent greenhouse gas, significantly contributes to global warming. By converting methane into value-added chemicals under mild conditions, sustainable development benefits can be achieved. (2) Hydrogen as green energy is an important research topic but has great challenges in its storage with hydrogen's low density. Efficient hydrogen storage technologies are required to enable the efficient utilization of hydrogen. (3) Fuel cells offer a clean and efficient alternative to traditional energy conversion technologies, which convert the chemical energy of a fuel directly into electricity through an electrochemical reaction. A new concept of a regenerative fuel cell is being discussed that has the ability to convert electricity back to chemical energy. These sustainable practices: methane conversion, hydrogen storage, and regenerative fuel cell, drive technological innovation and opportunities in catalyst materials, new energy, and electrochemistry.

Committee: Zhenmeng Peng (Advisor); Qixin Zhou (Committee Member); George Chase (Committee Member); Chrys Wesdemiotis (Committee Member); Toshikazu Miyoshi (Committee Member) Subjects: Chemical Engineering; Chemistry; Computer Engineering; Environmental Engineering

MA, Kent State University, 2022, College of the Arts / School of Music, Hugh A. Glauser

Alexander Scriabin (1872–1915) is known for his synesthesia, piano music, and transition from late Romantic tonality to early post-tonality or atonality. While previous scholarship has explored different systems of analyzing Scriabin's developing pitch language, the metric aspects of his music are often overlooked. That said, Mauchley (1982) observed the predominance of triple and compound meter in Scriabin's ninety preludes. The abundance of ternary metric organizations in Scriabin's music is notable given a survey of Western music that found that simple, duple, and quadruple meters are most common. Literature in music perception and cognition also discusses a bias toward binary metric organization (Huron, 2006; London, 2012). This thesis supports and expands Mauchley's observation. A survey of time signatures across Scriabin's corpus of solo piano music is reported, which found that 3/4, 6/8, 9/8, and 3/8 are among Scriabin's most common time signatures. An analysis of meter in randomly selected phrases from eighty-two of Scriabin preludes using the mathematical model Inner Metric Analysis is also reported. The Inner Metric Analysis found that ternary metric organization is prevalent even in pieces Scriabin notated in a binary meter. A major contribution of this thesis is the Mysterium corpus of Scriabin's solo piano music.

Committee: Joshua Albrecht (Advisor); Adam Roberts (Committee Member); H. Gerrey Noh (Committee Member) Subjects: Music

Doctor of Philosophy, The Ohio State University, 2021, Mechanical Engineering

Turbomachinery, like jet engines and industrial gas turbines in power plants, are very advanced and complex machines. Due to the complexity and cost of modern turbomachinery, there is active research in accurately predicting the physical system dynamics using computational models. Two big mechanisms that affect the structural response are the prestress effects from high rotational speeds and mistuning effects from tolerance deviations, wear, or damage. Understanding the role these two mechanisms play in the computational modeling of these systems is an important step toward a complete digital twin of an entire jet engine. There previously existed modeling methods that enabled each to be analyzed independently, but not simultaneously in an efficient manner. This will be one of the focus points of this dissertation. The other focus being an experimental investigation into exciting system resonances of a rotating bladed disk using air jets. These experiments will be used to validate the computational modeling method developed. This dissertation has three primary objectives. The first objective is to present reduced order modeling methods that allow for the efficient modeling of coupled systems and rotating systems, both with small or large mistuning. By efficiently including these mechanisms, more realistic boundary conditions can be used to help validate the reduced order models (ROMs) with experimental data. Both modeling methods create models a fraction of the size of the full model while retaining key dynamic characteristics of the full model. The second objective of this work is to show the capability of air jets in exciting synchronous and non-synchronous vibrations in a rotating bladed disk. Much previous research in this field focused on experiments with stationary systems. These tests can help isolate specific mechanisms that may be present in bladed disks, but may limit the applicability of the results to actual rotating systems. This work presents a method (open full item for complete abstract)

Committee: Kiran D'Souza (Advisor); Randall Mathison (Committee Member); Manoj Srinivasan (Committee Member); Herman Shen (Committee Member) Subjects: Mechanical Engineering

Master of Science in Renewable and Clean Energy Engineering (MSRCE), Wright State University, 2020, Renewable and Clean Energy

Calcific aortic valve disease (CAVD), the most common valvular heart disorder, is associated with complications such as stroke, heart attack, aortic aneurysm, left ventricular hypertrophy, and ultimately death. While hypertension has been identified as a major risk factor for CAVD, the mechanisms by which it may promote calcification are still unknown. Given the sensitivity of valvular tissue to mechanical stress alterations, the hemodynamic abnormalities linked to hypertension may play a role in the development of CAVD. Further, the effects of hypertension on the left ventricular functionality and coronary flow resistance remain largely uninvestigated. Hence, the objectives of this thesis were 1.) to quantify computationally AV hemodynamics and regional leaflet mechanical stresses under normotensive, prehypertensive and stage-1 hypertensive conditions using Fluid- Structure interaction modeling, and 2.) characterize the effect of hypertensive conditions on ventricular workload and coronary flow resistance. This study will provide insights on the mechano-etiology of CAVD in hypertensive patients as well as the ventricular functionality and coronary flow under hypertension.

Committee: Philippe Sucosky Ph.D. (Advisor); Zifeng Yang Ph.D. (Committee Member); George P. Huang Ph.D. (Committee Member) Subjects: Biomechanics; Biomedical Engineering; Biomedical Research; Mechanical Engineering

Doctor of Philosophy, The Ohio State University, 2017, Biomedical Sciences

Cancer research is rapidly advancing toward more personalized treatments and diagnostics. The major driving force of this advancement are the technological developments of sequencing which has resulted in greatly reduced costs. The democratization of sequencing assays has produced a unique set of challenges that must be addressed in order to successfully conduct clinical research. DNA methylation (DNAm) has increasingly been assayed by sequencing due to its role in human disease and cancers, including breast cancer. DNAm is an epigenetic modification and primarily functions to regulate gene expression. In high-risk breast cancer subtypes, the focus of our most recent research, DNAm is able to predict survival for subtypes with no molecular markers of risk. There are many sequencing assays for DNAm, but the two most common approaches are methylation capture (MethylCap-seq) and bisulfite conversion (BS-seq). As with any sequencing analyte, choosing the appropriate approach for a study is made more difficult by the continual improvements made to the methods and the sequencing technologies. Additionally, each DNAm assay requires a unique data analysis workflow in order to derive valid conclusions. In this work, we will describe a novel computational quantification method for MethylCap-seq and the study design and analysis of a BS-seq experiment as applied to a preventative therapy in breast cancer. Together, these results demonstrate the development and planning needed for the successful implementation of a sequencing assay in clinical research. MethylCap-seq is an approach that uses a protein that binds to DNAm to capture methylated DNA fragments. A region with a large number of captured fragments is interpreted as having high DNAm. Therefore, quantification is based on the number of fragments. Although MethylCap-seq is an inexpensive genome-wide assay, it does have a few limitations. The one we sought to address was the limited resolution of the data. Biologically (open full item for complete abstract)

Committee: Lisa Yee MD (Advisor); Qianben Wang PhD (Advisor); Ralf Bundschuh PhD (Committee Member); Amanda Toland PhD (Committee Member) Subjects: Bioinformatics; Biomedical Research

Master of Science, University of Akron, 2016, Mechanical Engineering

An Ethanol fueled PPCI (Partially Premixed Compression Ignition) engine was computationally studied to understand the effect of injection strategies on efficiency, emissions, and noise. The CI engine selected for this study was a heavy duty single cylinder engine having a displacement of 2123 cm3 with a compression ratio of 17.3 at a medium load of approximately 12 bar IMEP. CFD modelling with detailed chemistry was done using converge CFD package. All the CFD simulations presented in this study were conducted on a single engine sector to reduce the computational time and the simulations were run from Intake valve closure (IVC) to Exhaust valve opening (EVO). The injection strategy used in this study is a double injection strategy. A series of simulations were run in order to obtain the optimum injection parameters. First, the start of the first injection was changed from -60 CAD (crank angle degree) to -20 CAD (crank angle degree) by keeping the start of second injection constant at -5 CAD. Secondly, the start of the second injection was changed from -10 CAD to -2 CAD by keeping the start of first injection constant at -5 CAD. Lastly, the injection mass percentage in the first and second injection was changed from 60-40 % to 90-10 % by keeping the start of first injection and second injection constant at -50 CAD and -10 CAD. The results obtained from these simulations give the optimum injection parameters which will have high thermal efficiency with reduced emissions and noise. The optimum injection parameters obtained are SOFI at -50 CAD and SOSI at -10 CAD with 70 % of the fuel injected in the first injection and 30 % in the second injection. Subsequently, the sensitivity of the engine combustion to change in inlet temperature and inlet pressure was studied by keeping the obtained optimum injection parameters. The results obtained from this showed that the engine combustion is highly sensitive to inlet temperature than the inlet pressure. Additionally, (open full item for complete abstract)

Committee: Gaurav Mittal Dr. (Advisor); Scott Sawyer Dr. (Committee Member); Guo-Xiang Wang Dr. (Committee Member) Subjects: Mechanical Engineering

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

Detailed description of flow through stationary particle beds is crucial for the design and implementation of municipal water filtration, material extraction systems for nuclear waste and industrial water purification systems. Knowledge of fluid-particle interactions and fluid flow properties through the bed is essential to design, but difficult to determine from experimental investigations. Combined granular-fluid simulation methods such as coupled Computational Fluid Dynamics and Discrete Element Method (CFD-DEM) have been used to bridge this gap in fundamental knowledge. Able to capture details of the small-scale and large-scale interactions that are difficult to study in physical beds, simulation findings have added great understanding to this field. Unfortunately, the reported results are occasionally flawed by a lack of understanding, specifically regarding the magnitude of numerical and modeling errors. Uniform reporting of error, investigations of simulation trend, and proof of mesh-independence have not been performed for granular-fluid simulations. A standard method of open-source granular-fluid flow simulation known as CFDEM is applied to the simulation of flow through a fixed bed. The Ergun equation is a validated empirical expression used to predict the drag force in fixed bed flow and this prediction is compared directly to simulation results. A grid-refinement procedure, standard for publication of CFD simulation results, is applied to the CFD-DEM simulations. The solution trend over the refinement range is investigated using the frequency of convergence, convergence types, and the proposed `offset' method; a comparison of the expected numerical error and actual extrapolated solution error. An optimal grid size resulting in the least amount of error is investigated by solution trend, drag profile comparison, and the grid-refinement study results. Error is seen to increase in the simulations at both large cell sizes and as the cell siz (open full item for complete abstract)

Committee: Urmila Ghia Ph.D. (Committee Chair); Christopher G. Stoltz Ph.D. (Committee Member); John Hecht Ph.D. (Committee Member); Kirti Ghia Ph.D. (Committee Member) Subjects: Mechanical Engineering; Textile Research; Theater

Master of Science in Engineering, Youngstown State University, 2013, Department of Mechanical, Industrial and Manufacturing Engineering

Valves are critical components in a fluid flow network. Based on the type of fluid used, valves may suffer unforeseen wear and tear that might lead to an inadvertent failure. Major work in this thesis is focused on high pressure water valves that are used for descaling purposes. Controlling fluid flow at high pressures is not only challenging but also becomes time-wise critical. Failure of one such high pressure un-loader valves was studied first for the feasibility of my thesis work. A reverse flow operation was set in one such valve due to piping constraints established by industrial requirements. Experience and data recording showed that the premature failures of such valves by BOC Water Hydraulics were seen in months which lasted for years in standard operation. Computer simulation was being utilized to understand the fluid phenomena at such high pressures. The highly energized fluid from the descaling pump sets off a static pressure of 4300 psi at the valve inlet. It is responsible for continuous fluid flow rate of up to 208 gpm when the valve becomes fully open. Computational Fluid Dynamics (CFD) approaches are widely being utilized for fluid research in design optimizations. A Standard Turbulence model was used to understand the fluid flow variables using velocity/pressure contours for several possible valve opening positions. A very low pressure developed below the poppet seat of the valve suggests the onset of cavitation zones which may lead to leakage. Leakage at such a descaling pressure further accounts for cavitation and may which ultimately affect valve's overall performance resulting in cartridge replacement. Using CFD, the poppet valve assembly was modeled and simulated using ANSYS Fluent, commercially available CFD software. Low pressure below the atmospheric gage pressure in the valve body is found to be responsible for the initial onset of cavitation.

Committee: Ganesh Kudav PhD (Advisor); Param Adhikari MS (Committee Member); Suresh Sharma PhD (Committee Member) Subjects: Engineering; Mechanical Engineering

MS, University of Cincinnati, 2012, Engineering and Applied Science: Mechanical Engineering

The growth dynamics of isolated gas bubbles (inception → growth → departure) emanating from a capillary-tube orifice submerged in isothermal pools of aqueous solutions of surfactants is computationally investigated. The Navier-Stokes equations are solved in the liquid and the gas phase. The evolution of the gas-liquid interface is tracked using a Volume-of-Fluid (VOF) method. Surfactant molecules in aqueous solutions have a tendency to diffuse towards the gas-liquid interface and are subsequently adsorbed onto it. This time dependent adsorption process gives rise to the dynamic surface tension behavior of the aqueous surfactant solutions. To computationally model this behavior, the species conservation equation for the surfactant is solved in the bulk fluid and is coupled with the dynamic adsorption-desorption of the surfactant on the interface. A new form of the surfactant transport equation is derived that was necessary to incorporate the interfacial transport in the volume-of-fluid method where the interface is spread over multiple grid cells. Computational results were obtained for bubble growth dynamics from a capillary orifice in a pool of pure water and in an aqueous solution of Sodium Dodecyl Sulphate (SDS). The evolving bubble shape and the flow field in the two phases in the pure liquid and in surfactant solution are compared for a variety of air flow rates (from 4 ml/min to 24 ml/min) in the constant bubble regime. To validate the computational model, the results for the transient shape and size of growing bubbles in pure water were compared with available experimental data and were found to be in excellent agreement. Results show that the dynamic surface tension relaxation gives rise to smaller bubble size at departure in aqueous surfactant solution compared to that in pure water. However, this effect is found to be a function of the air flow rate. At high air flow rates (24 ml/min), the short time for bubble growth allows relatively smaller drop in the (open full item for complete abstract)

Committee: Milind Jog PhD (Committee Chair); Yuen Koh Kao PhD (Committee Member); Raj Manglik PhD (Committee Member) Subjects: Mechanics

Doctor of Philosophy, The Ohio State University, 2010, Chemistry

Ab initio quantum calculations and ultrafast time-resolved laser flash photolysis techniques have been used to study singlet carbenes and the photochemistry of diazirines and diazo compounds. After a brief introduction of carbene chemistry in Chapter 1, the photophysics and photochemistry of aryldiazirines are investigated in Chapters 2 through 6. Detailed theoretical calculations begin with parent phenyldiazirine and its isomer phenyldiazomethane. The structures of the ground and electronic excited states (S1, S2, and S3) of both compounds are optimized with RI-CC2 and DFT methods. The denitrogenation of both phenyldiazirine and phenyldiazomethane to produce singlet phenylcarbene, and the isomerization between both compounds, are investigated mechanistically on their potential energy surfaces. These predictions support the spectroscopic assignment in ultrafast studies of arylalkyldiazirines in chapters 3 through 6 and the accuracy of these theoretical methods are calibrated by the excellent agreement with experimental data. In Chapter 3 we present the first direct observation of singlet phenylcarbene and measurement of its lifetime in solution using ultrafast time-resolved infrared spectroscopy. In Chapter 4 we provide the first direct observation of the S1 excited state of para-methoxy-3-phenyl-3-methyl diazirine (p-CH3OC6H4CN2CH3) with both IR and UV–vis detection techniques. The S1 state of the diazirine decays into the diazo compound directly. The S2 excited state is populated with 270 nm light and decays directly into singlet arylcarbene and diazo compound, as well as the S1 state, via internal conversion. A Hammett study of the S1 excited states is discussed in Chapter 5. An excellent linear correlation is obtained between the S1 lifetimes of arylchlorodiazirines and their para- substituent σp+ parameters. The effect of substitution of b-hydrogens on the S1 state lifetimes is examined in Chapter 6 and is consistent with the RIES mechanism. The wavelength depe (open full item for complete abstract)

Committee: Matthew S. Platz PhD (Advisor); Christopher M. Hadad PhD (Committee Member); T. V. RajanBabu PhD (Committee Member) Subjects: Chemistry

Doctor of Philosophy, Case Western Reserve University, 2009, Mathematics

Computational models provide a useful tool for experimentalists in understanding the processes occurring in a biological system that may otherwise be impossible toobserve directly. The pivotal role of the liver in metabolic regulation makes it a challenging organ to model and simulate. Computational models that can adequately describe hepatic metabolism further the understanding of the functions within the organ. This thesis designs, identifies and analyzes three computational models of hepatic metabolism which account for the complexity of liver biochemistry, hepatic heterogeneity and perfused organ states. These models are governed by systems of ordinary or partial differential equations that depend on a large number of parameters that need to be identified. The classical deterministic parameter estimation problem is recast in the form of Bayesian statistical inference, allowing the integration of a priori belief and data from several experiments. In this approach, the unknowns are modeled as random variables and their values are probability densities. Effcient Markov Chain Monte Carlo techniques are designed and adapted to draw samples effectively from the parameter densities. Setting deterministic models inside a statistical framework makes it possible to study the correlations of different pathways with the time courses of metabolites. This methodology is applied to quantify the sensitivity of various hepatic pathways related to glucose production to redox state under varying conditions, providing insight into the regulation of hepatic gluconeogenesis. The Bayesian framework that we utilize allows us to incorporate into our parameter estimation process information available prior to considering the data. We show that the choices made in the encoding of this a priori information may affect both the parameter estimation and the corresponding model predictions by introducing three priors for a particular model and scrutinizing their effects.

Committee: Dr. Daniela Calvetti PhD (Committee Chair); Dr. David Gurarie PhD (Committee Member); Dr. Richard Hanson MD (Committee Member); Dr. Erkki Somersalo PhD (Committee Member) Subjects: Biochemistry; Biomedical Research; Mathematics