This study is devoted to some of the most important issues for advancing inkjet printing for possible application in the coating industry with a focus on piezoelectric droplet on demand (DOD) inkjet technology. Current problems, as embodied in liquid filament breakup along with satellite droplet formation and reduction in droplet sizes, are discussed and then potential solutions identified. For satellite droplets, it is shown that liquid filament break-up behavior can be predicted by using a combination of two pi-numbers, including the Weber number, We and the Ohnesorge number, Oh, or the Reynolds number, Re, and the Weber number, We. All of these are dependent only on the ejected liquid properties and the velocity waveform at the print-head inlet. These new criteria are shown to have merit in comparison to currently used criteria for identifying filament physical features such as length and diameter that control the formation of subsequent droplets. In addition, this study performs scaling analyses for the design and operation of inkjet printing heads. Because droplet sizes from inkjet nozzles are typically on the order of nozzle dimensions, a numerical simulation is carried out to provide insight into how to reduce droplet sizes by employing a novel input waveform impressed on the print-head liquid inflow without changing the nozzle geometry. A regime map for characterizing the generation of small droplets based on We and a non-dimensional frequency, Ω is proposed and discussed. In an attempt to advance inkjet printing technology for coating purposes, a prototype was designed and then tested numerically. The numerical simulation successfully proved that the proposed prototype could be useful for coating purposes by repeatedly producing mono-dispersed droplets with controllable size and spacing. Finally, the influences of two independent piezoelectric characteristics - the maximum head displacement and corresponding frequency, was investigated to examine the quality of filament breakup quality and favorable piezoelectric displacements and frequencies were identified.

Humans learn to interact with many complex dynamic systems such as helicopters, bicycles, and automobiles. This dissertation develops a subsystem identification method to model the control strategies that human subjects use in experiments where they interact with dynamic systems. This work provides new results on the control strategies that humans learn. We present a novel subsystem identification algorithm, which can identify unknown linear time-invariant feedback and feedforward subsystems interconnected with a known linear time-invariant subsystem. These subsystem identification algorithms are analyzed in the cases of noiseless and noisy data. We present results from human-in-the-loop experiments, where human subjects in- teract with a dynamic system multiple times over several days. Each subject’s control behavior is assumed to have feedforward (or anticipatory) and feedback (or reactive) components, and is modeled using experimental data and the new subsystem identifi- cation algorithms. The best-fit models of the subjects’ behavior suggest that humans learn to control dynamic systems by approximating the inverse of the dynamic system in feedforward. This observation supports the internal model hypothesis in neuro- science. We also examine the impact of system zeros on a human’s ability to control a dynamic system, and on the control strategies that humans employ.

Transmissibility is the most common metric used for isolator characterization. However, engineers are becoming increasingly concerned about energy transmission through an isolator at high frequencies and how the compliance of the machine and foundation factor into the performance. In this study, the transfer matrix approach for isolator characterization is first reviewed. Two methods are detailed for determining the transfer matrix of an isolator using finite element simulation. This is accomplished by determining either the mobility or impedance matrix for the isolator and then converting to a transfer matrix. One of the more useful metrics to characterize the high frequency performance of an isolator is insertion loss. Insertion loss is defined as the difference in transmitted vibration in decibels between the unisolated and isolated cases. Insertion loss takes into account the compliance on the source and receiver sides. Accordingly, it has some advantages over transmissibility which is a function of the damping and mounted resonant frequency. A static analysis is to preload the isolator so that stress stiffening is accounted for. This is followed by modal and forced response analyses to identify the transfer matrix of the isolator. In this paper, the insertion loss of spring isolators is examined as a function of several geometric parameters including the spring diameter, wire diameter, number of active coils, and height. Results demonstrate how modifications to these parameters affect the insertion loss and the first surge frequency.

Statistical data suggests that increased use of evidence-based medical therapies has largely contributed to the decrease in American death rate caused by heart disease. And my studies are about two applications of magnetic resonance imaging (MRI) as a non-invasive approach in evidence-based health care research. In my first study, the achievement of a pulmonary valve replacement surgery was assessed on a patient with tetralogy of Fallot (TOF). In order to evaluate the remodeling of right ventricle, two biventricular finite element models were built up for pre-surgical images and post-surgical images. In my second study, 3D Lagrangian strains and torsion in the left ventricle of ten rats were investigated using Displacement ENcoding with Stimulated Echoes (DENSE) cardiac magnetic resonance (CMR) images. Tools written in MATLAB were developed for 2D contouring, 3D modeling, strain and torsion computations, and statistical comparison across subjects.

Gradients of proteins play a prominent role in many biological processes, from development of multicellular organisms to chemical signaling in the immune system. Deposition of surface gradients is a way to permanently modifying a surface’s properties, resulting in the creation of novel materials which have widespread applications in biologically relevant fields, such as directed cell growth, production of biocompatible implantable materials, and creation of functional biosensors. These types of surfaces can also be used as an ex vivo tool to help understand many biological processes by mimicking the environment in gradient-related phenomena in a controllable way. However, despite the large number of applications for chemically graded surfaces, creating them remains a challenge. In this work, a novel diffusion-based patterning mechanism is presented that relies on a 3D micropatterned poly(ethylene glycol) diacrylate (PEG-DA) ‘stamps’ for the controlled deposition of fluorescently-tagged protein ‘ink’ onto pre-treated glass slides. By controlling the contact time and mechanical deformation of the PEG hydrogel on the glass surfaces, it is possible to control local concentration of protein deposition.

It is shown that the relationship between an impedance change and the dynamic response of a linear system is in the form of the Moebius transformation. The Moebius transformation is a conformal complex transformation that maps straight lines and circles in one complex plane into straight lines and circles in another complex plane. The center and radius of the mapped circle can be predicted provided that all the complex coefficients are known. This feature enables rapid determination of the optimal impedance change to achieve desired performance. This dissertation is primarily focused on the application of the Moebius transformation to enhance vibro-acoustic performance of exhaust systems and expedite the assessment due to modifications. It is shown that an optimal acoustic impedance change can be made to improve both structural and acoustic performance, without increasing the overall dimension and mass of the exhaust system. Application examples include mufflers and enclosures. In addition, it is demonstrated that the approach can be used to assess vibration isolators. In many instances, the source properties (source strength and source impedance) will also greatly influence exhaust system performance through sound reflections and resonances. Thus it is of interest to acoustically characterize the sources and assess the sensitivity of performance towards source impedance. In this dissertation, the experimental characterization of source properties is demonstrated for a diesel engine. Moreover, the same approach can be utilized to characterize other sources like refrigeration systems. It is also shown that the range of variation of performance can be effectively determined given the range of source impedance using the Moebius transformation. This optimization approach is first applied on conventional single-inlet single-outlet exhaust systems and is later applied to multi-inlet multi-outlet (MIMO) systems as well, with proper adjustment. The analytic model for MIMO systems is explained in details and validated experimentally. The sensitivity of MIMO system performance due to source properties is also investigated using the Moebius transformation.

Wetting and spreading of liquid systems on solid substrates under transient conditions, driven by surface tension and viscous forces along with the interface interactions (e.g., a substrate dissolution or diffusion and/or chemical reaction) is a complex problem, still waiting to be fully understood. In this study we have performed an extensive experimental investigation of liquid aluminum alloy spreading over aluminum substrate along with corroboration with theoretical modeling, performed in separate but coordinate study. Wetting and spreading to be considered take place during a transient formation of the free liquid surface in both sessile drop and wedge-tee mating surfaces’ configurations. The AA3003 is used as a substrate and a novel self-fluxing material called TrilliumTM is considered as the filler metal. In addition, benchmark, non-reactive cases of spreading of water and silicon oil over quartz glass are considered. The study is performed experimentally by a high temperature optical dynamic contact angle measuring system and a standard and high speed visible light camera, as well as with infra read imaging. Benchmark tests of non-reactive systems are conducted under ambient environment’s conditions. Molten metal experiment series featured aluminum and silicone alloys under controlled atmosphere at elevated temperatures. The chamber atmosphere is maintained by the ultra-high purity nitrogen gas purge process with the temperature monitored in real time in situ. Different configurations of the wedge-tee joints are designed to explore different parameters impacting the kinetics of the triple line movement process. Different power law relationships are identified, supporting subsequent theoretical analysis and simulation. Under ambient temperature conditions, the non-reactive liquid wetting and spreading experiments (water and oil systems) were studied to verify the equilibrium triple line location relationships. The kinetics relationship between the dynamic contact angle and the triple line location is identified. Additional simulation and theoretical analysis of the triple line movement is conducted using the commercial computer software platform Comsol in a collaboration with a team from Washington State University within the NSF sponsored Grant #1235759 and # 1234581. The experimental work conducted here has been complemented by a verification of the Comsol phase-field modeling. Both segments of work (experimental and numerical) are parts of the collaborative NSF sponsored project involving the University of Kentucky and Washington State University. The phase field modeling used in this work was developed at the Washington State University and data are corroborated with experimental results obtained within the scope of this Thesis.

Al 7050-T7451 alloy with good combinations of strength, stress corrosion cracking resistance and toughness, is used broadly in the aerospace/aviation industry for fatigue-critical airframe structural components. However, it is also considered as a highly anisotropic alloy as the crack growth behavior along the short transverse direction is very different from the one in the long transverse direction, due to the inhomogeneous microstructure with the elongated grains distributed in the work material used in the sheet/plate applications. Further processes on these materials are needed to improve its mechanical and material properties and broaden its applications. The material with ultra-fine or nano grains exhibits improved wear and corrosion resistance, higher hardness and better fatigue life, compared to the one with coarse grains. In recent times, the development of novel processing technologies has gained great attention in the research community to enhance the properties of the materials employed in the aerospace, biomedical, precision instrument, automotive, nuclear/power industries. These novel processing technologies modify the microstructure of this alloy and improve the properties. The aim of this dissertation is to investigate the effects of cryogenic processes, including friction stir processing (FSP), machining and burnishing, on Al 7050-T7451 alloy to solve the inhomogeneity issue and improve its surface integrity. FSP is applied to modify the microstructure of Al 7050-T7451 alloy for achieving more homogeneous structure with near ultra-fine grains (UFG) which were less than 2 µm, particularly in cryogenic FSP with liquid nitrogen as the coolant. Approximately 10% increase could be observed from the hardness measurement from the samples processed by cryogenic FSP, in contrast to dry FSP. Also, the texture change from Al (200) to Al (111) could be achieved in all the samples processed by dry and cryogenic FSP. Cryogenic machining and burnishing processes were also applied to enhance the surface integrity of the manufactured components with near-UFG structure. The highest cutting temperature was reduced by up to 44.7% due to the rapid cooling effect of liquid nitrogen in cryogenic machining, compared with dry machining. Nano grains were produced in the refined layers induced by cryogenic burnishing. And, up to 35.4% hardness increase was obtained within the layer depth of 200 µm in the cryogenically-burnished surface. A numerical finite element method (FEM) model was developed for predicting the process performance in burnishing. Less than 10% difference between the experimental and predicted burnishing forces was achieved in the simulation of cryogenic burnishing, and reasonable predictions were also achieved for temperatures, severe plastic deformation (SPD) layers.

A low-order discrete dynamical system (DDS) for finite-rate chemistry of H2-air combustion is derived in 3D. Fourier series with a single wavevector are employed to represent dependent variables of subgrid-scale (SGS) behaviors for applications to large-eddy simulation (LES). A Galerkin approximation is applied to the governing equations for comprising the DDS. Regime maps are employed to aid qualitative determination of useful values for bifurcation parameters of the DDS. Both isotropic and anisotropic assumptions are employed when constructing regime maps and studying bifurcation parameters sequences. For H2-air reactions, two reduced chemical mechanisms are studied via the DDS. As input to the DDS, physical quantities from experimental turbulent flow are used. Numerical solutions consisting of time series of velocities, species mass fractions, temperature, and the sum of mass fractions are analyzed. Numerical solutions are compared with experimental data at selected spatial locations within the experimental flame to check whether this model is suitable for an entire flame field. The comparisons show the DDS can mimic turbulent combustion behaviors in a qualitative sense, and the time-averaged computed results of some species are quantitatively close to experimental data.

It is important for organizations to understand the factors responsible for establishing sustainable continuous improvement (CI) capabilities. This study uses learning curves as the basis to examine learning obtained by team members doing work with and without the application of fundamental aspects of the Toyota Production System. The results are used to develop an effective model to guide organizational activities towards achieving the ability to continuous improve in a sustainable fashion. This research examines the effect of standardization and waste elimination activities supported by systematic problem solving on team member learning at the work interface and system performance. The results indicate the application of Standard Work principles and elimination of formally defined waste using the systematic 8-step problem solving process positively impacts team member learning and performance, providing the foundation for continuous improvement Compared to their untreated counterparts, treated teams exhibited increased, more uniformly distributed, and more sustained learning rates as well as improved productivity as defined by decreased total throughput time and wait time. This was accompanied by reduced defect rates and a significant decrease in mental and physical team member burden. A major outcome of this research has been the creation of a predictive probability model to guide sustainable CI development using a simplified assessment tool aimed at identifying essential organizational states required to support sustainable CI development.