We present new adaptive control algorithms that address the problem of rejecting sinusoids with known frequencies that act on an unknown asymptotically stable linear time-invariant system. To achieve asymptotic disturbance rejection, adaptive control algorithms of this dissertation rely on limited or no system model information. These algorithms are developed in discrete time, meaning that the control computations use sampled-data measurements. We demonstrate the effectiveness of algorithms via analysis, numerical simulations, and experimental testings. We also present extensions to these algorithms that address systems with decentralized control architecture and systems subject to disturbances with unknown frequencies.

The present thesis provides a description of historical and current modeling methods with recent discoveries within the ablation community. Several historical assumptions are challenged, namely the presence of water in Thermal Protection System (TPS) materials, presence of coking in TPS materials, non-uniform elemental production during pyrolysis reactions, and boundary layer gases, more specifically oxygen, interactions with the charred carbon interface. The first topic assess the potential effect that water has when present within the ablator by examining the temperature prole histories of the recent flight case Mars Science Laboratory. The next topic uses experimental data to consider the instantaneous gas species produced as the ablator pyrolyzes. In this study, key gas species are identified and assumed to be unstable within the gas phase; thus, equilibrating to the solid phase. This topic investigates the potential effects due to the these process. The finial topic uses a simplified configuration to study the role of carbon oxidation, from diatomic oxygen, on the ablation modes of a TPS, surface versus volumetric ablation. Although each of these topics differ in their own right, a common theme is found by understanding the role that common pyrolysis and boundary layer gases species have as they interacts with the porous TPS structure. The main objective of the present thesis is to investigate these questions.

Statistical data from clinical studies indicate that the death rate caused by heart disease has decreased due to an increased use of evidence-based medical therapies. This includes the use of magnetic resonance imaging (MRI), which is one of the most common non-invasive approaches in evidence-based health care research. In the current work, I present 3D Lagrangian strains and torsion in the left ventricle of healthy and isoproterenol-stimulated rats, which were investigated using Displacement ENcoding with Stimulated Echoes (DENSE) cardiac magnetic resonance (CMR) imaging. With the implementation of the 12-segment model, a detailed profile of regional cardiac mechanics was reconstructed for each subject. Statistical analysis revealed that isoproterenol induced a significant change in the strains and torsion in certain regions at the mid-ventricle level. In addition, I investigated right ventricular cardiac mechanics with the methodologies developed for the left ventricle. This included a comparison of different regions within the basal and mid-ventricular regions. Despite no regional variation found in the peak circumferential strain, the peak longitudinal strain exhibited regional variation at the anterior side of the RV due to the differences in biventricular torsion, mechanism of RV free wall contraction, and fiber architecture at RV insertions. Future applications of the experimental work presented here include the construction and validation of biventricular finite element models. Specifically, the strains predicted by the models will be statistically compared with experimental strains. In addition, the results of the present study provide an essential reference of RV baseline evaluated with DENSE MRI, a highly objective technique.

The U.N. projects the world population to reach nearly 10 billion people by 2050, which will cause demand for manufactured goods to reach unforeseen levels. In order for us to produce the goods to support an equitable future, the methods in which we manufacture those goods must radically change. The emerging Circular Economy (CE) concept for production systems has promised to drastically increase economic/business value by significantly reducing the world’s resource consumption and negative environmental impacts. However, CE is inherently limited because of its emphasis on recycling and reuse of materials. CE does not address the holistic changes needed across all of the fundamental elements of manufacturing: products, processes, and systems. Therefore, a paradigm shift is required for moving from sustainment to sustainability to “produce more with less” through smart, innovative and transformative convergent manufacturing approaches rooted in redesigning next generation manufacturing infrastructure. This PhD research proposes the Helical Economy (HE) concept as a novel extension to CE. The proposed HE concepts shift the CE’s status quo paradigm away from post-use recovery for recycling and reuse and towards redesigning manufacturing infrastructure at product, process, and system levels, while leveraging IoT-enabled data infrastructures and an upskilled workforce. This research starts with the conceptual overview and a framework for implementing HE in the discrete product manufacturing domain by establishing the future state vision of the Helical Economy Manufacturing Method (HEMM). The work then analyzes two components of the framework in detail: designing next-generation products and next-generation IoT-enabled data infrastructures. The major research problems that need to be solved in these subcomponents are identified in order to make near-term progress towards the HEMM. The work then proceeds with the development and discussion of initial methods for addressing these challenges. Each method is demonstrated using an illustrative industry example. Collectively, this initial work establishes the foundational body of knowledge for the HE and the HEMM, provides implementation methods at the product and IoT-enabled data infrastructure levels, and it shows a great potential for HE’s ability to create and maximize sustainable value, optimize resource consumption, and ensure continued technological progress with significant economic growth and innovation. This research work then presents an outlook on the future work needed, as well as calls for industry to support the continued refinement and development of the HEMM through relevant prototype development and subsequent applications.

Burnishing is a chipless finishing process used to improve surface integrity by severe plastic deformation (SPD) of surface asperities. As surface integrity in large measure defines the functional performance and fatigue life of aerospace alloys, burnishing is thus a means of increasing the fatigue life of critical components, such as turbine and compressor blades in gas turbine engines. Therefore, the primary objective of this dissertation is to characterize the burnishing-induced surface integrity of Ti-6Al-4V alloy in terms of the implemented processing parameters. As the impact of cooling mechanisms on surface integrity from SPD processing is largely unexplored, a particular emphasis was placed upon evaluating the influence of cryogenic cooling with liquid nitrogen in comparison to more conventional methodologies. Analysis of numerical and experimental results reveals that burnishing facilitates grain refinement via continuous dynamic recrystallization. Application of LN2 during SPD processing of Ti-6Al-4V alloy suppresses the growth of new grains, leading to the formation of near-surface nanostructures which exhibit increased microhardness and compressive residual stress fields. This is particularly true in cryogenic multipass burnishing, where successive tool passes utilizing lower working pressures generate thermally stable work hardened surface layers, uniform nano-level surface finishes, and significantly deeper layers of compressive residual stresses.

A weakly ionized hypersonic flow solver for the simulation of reentry flow is firstly developed at the University of Kentucky. This code is the fluid dynamics module of known as Kentucky Aerothermodynamics and Thermal Response System (KATS). The solver uses a second-order finite volume approach to solve the laminar Navier– Stokes equations, species mass conservation and energy balance equations for flow in chemical and thermal non-equilibrium state, and a fully implicit first-order backward Euler method for the time integration. The hypersonic flow solver is then extended to account for very low Mach number flow using the preconditioning and switch of the convective flux scheme to AUSM family. Additionally, a multi-species preconditioner is developed. The following part of this work involves the coupling of a free flow and a porous medium flow. A new set of equation system for both free flows and porous media flows is constructed, which includes a Darcy–Brinkmann equation for momentum, mass conservation, and energy balance equation. The volume-average technique is used to evaluate the physical properties in the governing equations. Instead of imposing interface boundary conditions, this work aims to couple the free/porous problem through flux balance, therefore, flow behaviors at the interface are satisfied implicitly.

Myocardial infarction (i.e., a heart attack) is the most common heart disease in the United States. Mitral valve regurgitation, or the backflow of blood into the atrium from the left ventricle, is one of the complications associated with myocardial infarction. In this dissertation, a validated model of a sheep heart that has suffered myocardial infarction has been employed to study mitral valve regurgitation. The model was rebuilt with the knowledge of geometrical changes captured with MRI technique and is assigned with anisotropic, inhomogeneous, nearly incompressible and highly non-linear material properties. Patch augmentation was performed on its anterior leaflet, using a simplified approach, and its posterior leaflet, using a more realistic approach. In this finite element simulation, we virtually installed an elliptical patch within the central portion of the posterior leaflet. To the best of the author’s knowledge, this type of simulation has not been performed previously. In another simulation, the effect of patch within the anterior leaflet was simulated. The results from the two different surgical simulations show that patch implantation helps the free edges of the leaflets come close to one another, which leads to improved coaptation. Additionally, the changes in chordal force distributions are also reported. Finally, this study answers a few questions regarding mitral valve patch augmentation surgeries and emphasizes the importance of further investigations on the influence of patch positioning and material properties on key outcomes. The ultimate goal is to use the proposed techniques to assess human models that are patient-specific.

During hypersonic atmospheric entry, spacecraft are exposed to enormous aerodynamic heat. To prevent the payload from overheating, charring ablative materials are favored to be applied as the heat shield at the exposing surface of the vehicle. Accurate modeling not only prevents mission failures, but also helps reduce cost. Existing models were mostly limited to one-dimensional and discrepancies were shown against measured experiments and flight-data. To help improve the models and analyze the charring ablation problems, a multidimensional material response module is developed, based on a finite volume method framework. The developed computer program is verified through a series of test-cases, and through code-to-code comparisons with a validated code. Several novel models are proposed, including a three-dimensional pyrolysis gas transport model and an orthotropic material model. The effects of these models are numerically studied and demonstrated to be significant.

The work presented herein explores the ability of Ultra High Frequency Radio Frequency (UHF RF) devices, specifically (Radio Frequency Identification) RFID passive tags and Bluetooth Low Energy (BLE) to be used as tools to locate items of interest inside a building. Localization Systems based on these technologies are commercially available, but have failed to be widely adopted due to significant drawbacks in the accuracy and reliability of state of the art systems. It is the goal of this work to address that issue by identifying and potentially improving upon localization algorithms. The work presented here breaks the process of localization into distance estimations and trilateration algorithms to use those estimations to determine a 2D location. Distance estimations are the largest error source in trilateration. Several methods are proposed to improve speed and accuracy of measurements using additional information from frequency variations and phase angle information. Adding information from the characteristic signature of multipath signals allowed for a significant reduction in distance estimation error for both BLE and RFID which was quantified using neural network optimization techniques. The resulting error reduction algorithm was generalizable to completely new environments with very different multipath behavior and was a significant contribution of this work. Another significant contribution of this work is the experimental comparison of trilateration algorithms, which tested new and existing methods of trilateration for accuracy in a controlled environment using the same data sets. Several new or improved methods of triangulation are presented as well as traditional methods from the literature in the analysis. The Antenna Pattern Method represents a new way of compensating for the antenna radiation pattern and its potential impact on signal strength, which is also an important contribution of this effort. The performance of each algorithm for multiple types of inputs are compared and the resulting error matrix allows a potential system designer to select the best option given the particular system constraints.

The implementation of the mandatory alternative payment model (APM) guarantees savings for Medicare regardless of participant hospitals ability for reducing spending that shifts the cost minimization burden from insurers onto the hospital administrators. Surgical interventions account for more than 30% and 40% of hospitals total cost and total revenue, respectively, with a cost structure consisting of nearly 56% direct cost, thus, large cost reduction is possible through efficient operation management. However, optimizing operating rooms (ORs) schedules is extraordinarily challenging due to the complexities involved in the process. We present new algorithms and managerial guidelines to address the problem of OR planning and scheduling with disturbances in demand and case times, and inconsistencies among the performance measures. We also present an extension of these algorithms that addresses production scheduling for sustainability. We demonstrate the effectiveness and efficiency of these algorithms via simulation and statistical analyses.