Micromachining has seen application growth in a variety of industries requiring a miniaturization of the machining process. Machining at the micro level generates different cutter/workpiece interactions, generating more localized temperature spikes in the part/sample, as suggested by multiple studies. Temper-etch inspection is a non-destructive test used to identify `grind burns' or localized over-heating in steel components. This research investigated the application of temper-etch inspection to micromachined steel. The tests were performed on AISI 4340 steel samples. Finding, indications of localized over-heating was the primary focus of the experiment. In addition, change in condition between the original and post-machining hardness in the machined slot bottom was investigated. The results revealed that, under the conditions of the experiment, no indications of localized over-heating were present. However, there was a change in hardness at the bottom of the machined slot compared to the rest of the sample. Further research is needed to test the applicability of temper-etch inspection to micromilled steel and to identify the source of the change in hardness.

Passive flow control achieved by surface dimpling can be an effective strategy for reducing drag around bluff bodies - an example of substantial popular interest being the flow around a golf ball. While the general effect of dimples causing a delay of boundary layer separation is well known, the mechanisms contributing to this phenomena are subtle and not thoroughly understood. Numerical models offer a powerful approach for studying drag reduction, however simulation strategies are challenged by complex geometries, and in applications the introduction of ad hoc turbulence models which introduce additional uncertainty. These and other factors provide much of the motivation for the current study, which focused on the numerical simulations of the flow over a simplified configuration consisting of a dimpled flat plate. The principal goals of the work are to understand the performance of the numerical methodology, and gain insight into the underlying physics of the flow. Direct numerical simulation of the incompressible Navier-Stokes equations using a fractional step method was employed, with the dimpled flat plate represented using an immersed boundary method. The dimple geometry utilizes a fixed dimple aspect ratio, with dimples arranged in a single spanwise row. The grid sizes considered ranged from approximately 3 to 99 million grid points. Reynolds numbers of 3000 and 4000 based on the inlet laminar boundary layer thickness were simulated. A turbulent boundary layer was induced downstream of the dimples for Reynolds numbers which did not transition for the flow over an undimpled flat plate. First and second order statistics of the boundary layer that develops agree reasonably well with those for turbulent channel flow and flat plate boundary layers in the sublayer and buffer layers, but differ in the outer layer. Inspection of flow visualizations suggest that early transition is promoted by thinning of the boundary layer, initiation of shear layer instabilities over the dimples, flow separation and reattachment, and tripping of the boundary layer at the trailing edge of the dimples.

As miniature and high-heat-dissipation equipment became major manufacture and operation trends, heat-rejecting and heat-transport solutions faced increasing challenges. In the 1970s, researchers showed that particle suspensions can enhance the heat transfer efficiency of their base fluids. However, their work was hindered by the sedimentation and erosion issues caused by the relatively large particle sizes in their suspensions. More recently, nanofluids--suspensions of nanoparticles in liquids-were proposed to be applied as heat transfer fluids, because of the enhanced thermal conductivity that has generally been observed. However, in practical applications, a heat conduction mechanism may not be sufficient for cooling high-heat-dissipation devices such as microelectronics or powerful optical equipment. Thus, the thermal performance under convective, i.e., flowing heat transfer conditions becomes of primary interest. In addition, with the presence of nanoparticles, the viscosity of a nanofluid is greater than its base fluid and deviates from Einstein's classical prediction. Through the use of a test rig designed and assembled as part of this dissertation, the viscosity and heat transfer coefficient of nanofluids can be simultaneously determined by pressure drop and temperature difference measurements under laminar flow conditions. An extensive characterization of the nanofluid samples, including pH, electrical conductivity, particle sizing and zeta potential, is also documented. Results indicate that with constant wall heat flux, the relative viscosities of nanofluid decrease with increasing volume flow rate. The results also show, based on Brenner's model, that the nanofluid viscosity can be explained in part by the aspect ratio of the aggregates. The measured heat transfer coefficient values for nanofluids are generally higher than those for base fluids. In the developing region, this can be at least partially explained by Prandtl number effects. The Nusselt number ( Nu ) results for nanofluid show that Nu increases with increasing nanofluid volume fraction and volume flow rate. However, only DI-H2O (deionized water) and 5/95 PG/H2O (PG = propylene glycol) based nanofluids with 1 vol% nanoparticle loading have Nu greater than the theoretical prediction, 4.364. It is suggested that the nanofluid has potential to be applied within the thermally developing region when utilizing the nanofluid as a heat transfer liquid in a circular tube. The suggested Reynold's number is greater than 100.

Efficient performance of gas turbines depends, among several parameters, on the mainstream gas entry temperature. At the same time, transport of this high temperature gas into the rotor-stator cavities of turbine stages affects the durability of rotor disks. This transport is usually countered by installing seals on the rotor and stator disk rims and by pressurizing the cavities by injecting air (purge gas) bled from the compressor discharge. The configuration of the rim seals influences the magnitude of main gas ingestion as well as the interaction of the purge gas with the main gas. The latter has aerodynamic and hub endwall heat transfer implications in the main gas path. In the present work, experiments were performed on model single-stage and 1.5-stage axial-flow turbines. The turbines featured vanes, blades, and rim seals on both the rotor and stator disks. Three different rim seal geometries, viz., axially overlapping radial clearance rim seals for the single-stage turbine cavity and the 1.5-stage turbine aft cavity, and a rim seal with angular clearance for the single-stage turbine cavity were studied. In the single-stage turbine, an inner seal radially inboard in the cavity was also provided; this effectively divided the disk cavity into a rim cavity and an inner cavity. For the aft rotor-stator cavity of the 1.5-stage turbine, a labyrinth seal was provided radially inboard, again creating a rim cavity and an inner cavity. Measurement results of time-average main gas ingestion into the cavities using tracer gas (CO2), and ensemble-averaged trajectories of the purge gas flowing out through the rim seal gap into the main gas path using particle image velocimetry are presented. For both turbines, significant ingestion occurred only in the rim cavity. The inner cavity was almost completely sealed by the inner seal, at all purge gas flow rates for the single-stage turbine and at the higher purge gas flow rates for 1.5-stage turbine. Purge gas egress trajectory was found to depend on main gas and purge gas flow rates, the rim seal configuration, and the azimuthal location of the trajectory mapping plane with respect to the vanes.

Recent studies of the occurrence of post-flutter limit cycle oscillations (LCO) of the F-16 have provided good support to the long-standing hypothesis that this phenomenon involves a nonlinear structural damping. A potential mechanism for the appearance of nonlinearity in the damping are the nonlinear geometric effects that arise when the deformations become large enough to exceed the linear regime. In this light, the focus of this investigation is first on extending nonlinear reduced order modeling (ROM) methods to include viscoelasticity which is introduced here through a linear Kelvin-Voigt model in the undeformed configuration. Proceeding with a Galerkin approach, the ROM governing equations of motion are obtained and are found to be of a generalized van der Pol-Duffing form with parameters depending on the structure and the chosen basis functions. An identification approach of the nonlinear damping parameters is next proposed which is applicable to structures modeled within commercial finite element software.

The effects of this nonlinear damping mechanism on the post-flutter response is next analyzed on the Goland wing through time-marching of the aeroelastic equations comprising a rational fraction approximation of the linear aerodynamic forces. It is indeed found that the nonlinearity in the damping can stabilize the unstable aerodynamics and lead to finite amplitude limit cycle oscillations even when the stiffness related nonlinear geometric effects are neglected. The incorporation of these latter effects in the model is found to further decrease the amplitude of LCO even though the dominant bending motions do not seem to stiffen as the level of displacements is increased in static analyses.

Myoelectric control is lled with potential to signicantly change human-robot interaction.

Humans desire compliant robots to safely interact in dynamic environments

associated with daily activities. As surface electromyography non-invasively measures

limb motion intent and correlates with joint stiness during co-contractions,

it has been identied as a candidate for naturally controlling such robots. However,

state-of-the-art myoelectric interfaces have struggled to achieve both enhanced

functionality and long-term reliability. As demands in myoelectric interfaces trend

toward simultaneous and proportional control of compliant robots, robust processing

of multi-muscle coordinations, or synergies, plays a larger role in the success of the

control scheme. This dissertation presents a framework enhancing the utility of myoelectric

interfaces by exploiting motor skill learning and

exible muscle synergies for

reliable long-term simultaneous and proportional control of multifunctional compliant

robots. The interface is learned as a new motor skill specic to the controller,

providing long-term performance enhancements without requiring any retraining or

recalibration of the system. Moreover, the framework oers control of both motion

and stiness simultaneously for intuitive and compliant human-robot interaction. The

framework is validated through a series of experiments characterizing motor learning

properties and demonstrating control capabilities not seen previously in the literature.

The results validate the approach as a viable option to remove the trade-o

between functionality and reliability that have hindered state-of-the-art myoelectric

interfaces. Thus, this research contributes to the expansion and enhancement of myoelectric

controlled applications beyond commonly perceived anthropomorphic and

\intuitive control" constraints and into more advanced robotic systems designed for

everyday tasks.

Parkinson's disease (PD) is a neurodegenerative disorder that produces a characteristic set of neuromotor deficits that sometimes includes reduced amplitude and velocity of movement. Several studies have shown that people with PD improved their motor performance when presented with external cues. Other work has demonstrated that high velocity and large amplitude exercises can increase the amplitude and velocity of movement in simple carryover tasks in the upper and lower extremities. Although the cause for these effects is not known, improvements due to cueing suggest that part of the neuromotor deficit in PD is in the integration of sensory feedback to produce motor commands. Previous studies have documented some somatosensory deficits, but only limited information is available regarding the nature and magnitude of sensorimotor deficits in the shoulder of people with PD. The goals of this research were to characterize the sensorimotor impairment in the shoulder joint of people with PD and to investigate the use of visual feedback and large amplitude/high velocity exercises to target PD-related motor deficits. Two systems were designed and developed to use visual feedback to assess the ability of participants to accurately adjust limb placement or limb movement velocity and to encourage improvements in performance of these tasks. Each system was tested on participants with PD, age-matched control subjects and young control subjects to characterize and compare limb placement and velocity control capabilities. Results demonstrated that participants with PD were less accurate at placing their limbs than age-matched or young control subjects, but that their performance improved over the course of the test session such that by the end, the participants with PD performed as well as controls. For the limb velocity feedback task, participants with PD and age-matched control subjects were less accurate than young control subjects, but at the end of the session, participants with PD and age-matched control subjects were as accurate as the young control subjects. This study demonstrates that people with PD were able to improve their movement patterns based on visual feedback of performance and suggests that this feedback paradigm may be useful in exercise programs for people with PD.

Dissimilar metal joints such as aluminum-steel joints are extensively used in automobile, naval and aerospace applications and these are subjected to corrosive environmental and mechanical loading resulting in eventual failure of the structural joints. In the case of aluminum alloys under aggressive environment, the damage accumulation is predominantly due to corrosion and is accelerated in presence of other metals. During recent years several approaches have been employed to develop models to assess the metal removal rate in the case of galvanic corrosion. Some of these models are based on empirical methods such as regression analysis while others are based on quantification of the ongoing electrochemical processes. Here, a numerical model for solving the Nernst- Planck equation, which captures the electrochemical process, is implemented to predict the galvanic current distribution and, hence, the corrosion rate of a galvanic couple. An experimentally validated numerical model for an AE44 (Magnesium alloy) and mild steel galvanic couple, available in the literature, is extended to simulate the mechano- electrochemical process in order to study the effect of mechanical loading on the galvanic current density distribution and corrosion rate in AE44-mild steel galvanic couple through a multiphysics field coupling technique in COMSOL Multiphysics®. The model is capable of tracking moving boundariesy of the corroding constituent of the couple by employing Arbitrary Langrangian Eulerian (ALE) method.Results show that, when an anode is under a purely elastic deformation, there is no apparent effect of mechanical loading on the electrochemical galvanic process. However, when the applied tensile load is sufficient to cause a plastic deformation, the local galvanic corrosion activity at the vicinity of the interface is increased remarkably. The effect of other factors, such as electrode area ratios, electrical conductivity of the electrolyte and depth of the electrolyte, are studied. It is observed that the conductivity of the electrolyte significantly influences the surface profile of the anode, especially near the junction. Although variations in electrolyte depth for a given galvanic couple noticeably affect the overall corrosion, the change in the localized corrosion rate at the interface is minimal. Finally, we use the model to predict the current density distribution, rate of corrosion and depth profile of aluminum alloy 7075-stainless steel 316 galvanic joints, which are extensively used in maritime structures.

Detection of molecular interactions is critical for understanding many biological processes, for detecting disease biomarkers, and for screening drug candidates. Fluorescence-based approach can be problematic, especially when applied to the detection of small molecules. Various label-free techniques, such as surface plasmon resonance technique are sensitive to mass, making it extremely challenging to detect small molecules. In this thesis, novel detection methods for molecular interactions are described.

First, a simple detection paradigm based on reflectance interferometry is developed. This method is simple, low cost and can be easily applied for protein array detection.

Second, a label-free charge sensitive optical detection (CSOD) technique is developed for detecting of both large and small molecules. The technique is based on that most molecules relevant to biomedical research and applications are charged or partially charged. An optical fiber is dipped into the well of a microplate. It detects the surface charge of the fiber, which does not decrease with the size (mass) of the molecule, making it particularly attractive for studying small molecules.

Third, a method for mechanically amplification detection of molecular interactions (MADMI) is developed. It provides quantitative analysis of small molecules interaction with membrane proteins in intact cells. The interactions are monitored by detecting a mechanical deformation in the membrane induced by the molecular interactions. With this novel method small molecules and membrane proteins interaction in the intact cells can be detected. This new paradigm provides mechanical amplification of small interaction signals, allowing us to measure the binding kinetics of both large and small molecules with membrane proteins, and to analyze heterogeneous nature of the binding kinetics between different cells, and different regions of a single cell.

Last, by tracking the cell membrane edge deformation, binding caused downstream event – granule secretory has been measured. This method focuses on the plasma membrane change when granules fuse with the cell. The fusion of granules increases the plasma membrane area and thus the cell edge expands. The expansion is localized at the vesicle release location. Granule size was calculated based on measured edge expansion. The membrane deformation due to the granule release is real-time monitored by this method.

Breast cancer cell invasion is a highly orchestrated process driven by a myriad of complex microenvironmental stimuli. These complexities make it difficult to isolate and assess the effects of specific parameters including matrix stiffness and tumor architecture on disease progression. In this regard, morphologically accurate tumor models are becoming instrumental to perform fundamental studies on cancer cell invasion within well-controlled conditions. In this study, the use of photocrosslinkable hydrogels and a novel, two-step photolithography technique was explored to microengineer a 3D breast tumor model. The microfabrication process presented herein enabled precise localization of the cells and creation of high stiffness constructs adjacent to a low stiffness matrix. To validate the model, breast cancer cell lines (MDA-MB-231, MCF7) and normal mammary epithelial cells (MCF10A) were embedded separately within the tumor model and cellular proliferation, migration and cytoskeletal organization were assessed. Proliferation of metastatic MDA-MB-231 cells was significantly higher than tumorigenic MCF7 and normal mammary MCF10A cells. MDA-MB-231 exhibited highly migratory behavior and invaded the surrounding matrix, whereas MCF7 or MCF10A cells formed clusters that were confined within the micropatterned circular features. F-actin staining revealed unique 3D protrusions in MDA-MB-231 cells as they migrated throughout the surrounding matrix. Alternatively, there were abundance of 3D clusters formed by MCF7 and MCF10A cells. The results revealed that gelatin methacrylate (GelMA) hydrogel, integrated with the two-step photolithography technique, has great promise in creating 3D tumor models with well-defined features and tunable stiffness for detailed studies on cancer cell invasion and drug responsiveness.