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This thesis aims to understand how a number of real contact problems respond to local contact loads during cyclic loading and which combination of loads will give rise to a state of partial slip. At the core of this thesis lies a family of partial slip solutions for half-plane contact problems subject to different forms of periodic loading. This collection of partial slip solutions allows engineers and researchers alike to assess rapidly the contact behaviour, namely the position and extent of the zones of relative cyclic motion along the interface. While knowing the slip stick pattern, by itself, does not answer the question of whether an assembly is prone to fretting fatigue or not, it enables the user to set up simple laboratory experiments in order to determine the fretting fatigue strength of the design under consideration. The thesis begins with a taxonomy of the different classes of contacts that can arise in mechanical assemblies. In many fretting fatigue problems, we encounter one particular contact class, the so-called incomplete contact, which is suited for being represented by half-planes. After exploring the properties and limitations of plane elasticity and half-plane theory, we look at half-plane partial slip contact problems under different types of loading. We will make use of three different solution approaches (a) an analytical description using a superposition of full sliding shear tractions, (b) an analytical description using glide dislocations starting from a fully adhered state, and (c) an asymptotic description of the contact edge behaviour. Where suitable, the research results are applied to example geometries in order to familiarise the reader with the methodologies presented. The thesis concludes with the proposal of a generalised approach to fretting fatigue strength utilising experimental results published in the literature. The test data is reinterpreted by applying the outlined asymptotic methods in order to provide generality and comparability across different geometries and loading scenarios.

The tangential contact stiffness for ground Ti-6Al-4V surfaces is measured to linearly decrease with the application of tangential load. At the beginning of the application of tangential load, for ground surfaces, the ratio of the tangential contact stiffness to the normal contact stiffness is seen to be approximately half the Mindlin ratio. This is consistent with many other published experimental studies. Measurements of normal contact stiffness for ground surfaces conform to a model that posits a linear relationship between normal contact stiffness and normal load. An equivalent surface roughness parameter is defined for two surfaces in contact; and the normal contact stiffness for ground surfaces is observed to be inversely proportional to this parameter. Single asperity models were constructed to simulate the effect of different frictional laws and plasticity on the tangential displacement of an asperity contact. Further, multi-asperity modelling showed the effect of different normal load distributions on the tangential behaviour of interfaces. In addition, normal contact stiffness was modelled for a grid of asperities taking into account asperity interactions. A receding contact problem for which the required form of the distributed dislocations is bounded-bounded was solved. Then, a fundamental 2D frictional receding contact problem involving a homogeneous linear elastic infinite layer pressed by a line load onto a half-plane of the same material was analysed. This was done by the insertion of preformed distributed dislocations (or eigenstrains), which take into account the correct form of the separation of the interface at points away from the area of loading, along with corrective bounded-bounded distributions. The general method of solution was further refined and adapted to solve three other receding contact problems. The solutions demonstrated the robustness and applicability of this new procedure.

In a post-9/11 world, hostile actors are using vehicles as weapons to inflict civilian casualties. Pedestrians, vulnerable road users, military personnel, and police may be targeted using a vehicle as a weapon. The United States Department of Defense (DoD) also utilizes Entry Control Facilities (ECFs) which are carefully designed transportation corridors to manage how threat vehicles are able to access military facilities. In 2004, DoD started to upgrade all ECFs using both passive and active barriers. Many anti-ram vehicle barriers were evaluated according to the criteria established in ASTM F2656, but to date few options are available which are (1) adaptable to different lengths; (2) non-proprietary; and (3) reduced overall cost compared to proprietary counterparts. The objective of this research study is to design, evaluate, simulate, and full-scale crash test a threat mitigation barrier which provides dual functionality: safely capture errant vehicles involved in unintentional collisions, and prevent threats from gaining unauthorized access to military bases. The work includes generating engineering designs, performing computer simulations, performing data analysis and reporting, and performing material characterization in the Midwest Roadside Safety Facility (MwRSF) Small Structures Laboratory. At the MwRSF Outdoor Test Site, the conducting of component and full-scale crash testing of roadside features and evaluation of device combinations according to MASH criteria occurred. The research was structured around four pivotal components: a literature review, dynamic post-soil interaction simulations, dynamic anchor pullout simulations, and dynamic component testing. An optimal configuration of component dimensions, strengths, and material properties for a novel non-proprietary anti-ram barrier system was developed and proposed. This system is required to effectively restrain a truck under ASTM M50 impact conditions, adhering to either P2 or P3 deflection limits. This study augmented the understanding of the dynamic interactions between reinforced concrete anchors and soil, particularly focusing on the resistive forces and energy absorption characteristics. This enhanced understanding was intended to facilitate the engineering of the mentioned barrier system to meet ASTM M50 P2/P3 specifications. Advisor: Cody S. Stolle

Natural protective materials offer unparalleled solutions for impact-resistant material designs that are simultaneously lightweight, strong, and tough. Particularly, the dactyl club of mantis shrimp features chitin nanofibrils organized in a Bouligand structure, which has been shown to effectively dissipate high-impact energy during powerful strikes. The mollusk shells also achieve excellent mechanical strength, toughness, and impact resistance with a staggered, layer-by-layer structure. Previous studies have shown that hybrid designs, by combining different bioinspired microstructures, can lead to enhanced mechanical strength and energy dissipation capabilities. Nevertheless, it remains unknown whether combining Bouligand and staggered structures in nanofibrillar cellulose (NFC) films, forming a discontinuous fibrous Bouligand (DFB) architecture, can achieve enhanced impact resistance under localized ballistic impact. Additionally, the failure mechanisms under such dynamic loading conditions have been minimally understood. In this thesis, I present a comprehensive study to investigate the dynamic failure mechanisms and quantify the impact resistance of NFC thin films with DFB architecture by leveraging previously developed coarse-grained models and explicit projectile impact molecular dynamics simulations. The results show that when nanofibrils achieve a critical length with the DFB architecture, the impact resistance of NFC films outperforms the counterpart films with continuous fibrils by comparing their specific ballistic limit velocities and penetration energies. I also look into the underlying mechanisms contributing to this improvement in impact resistance, which include iii enhanced fibril sliding initiated at the discontinuous sites, intralayer and interlayer crack bridging, and crack twisting mechanism in the thickness direction enabled by the DFB architecture. Overall, the results in this thesis show that by combining Bouligand and staggered structures in NFC films, their potential for protective applications can be further improved. The findings presented in this thesis can provide practical guidelines for the design of protective films made of nanofibrils.

In an era of intensified market competition, the demand for cost-effective, high-quality, high-performance, and reliable products continues to rise. Meeting this demand necessitates the mass production of premium products through the integration of cutting-edge technologies and advanced materials while ensuring their integrity and safety. In this context, Nondestructive Testing (NDT) techniques emerge as indispensable tools for guaranteeing the integrity, reliability, and safety of products across diverse industries. Various NDT techniques, including ultrasonic testing, computed tomography, thermography, and acoustic emissions, have long served as cornerstones for inspecting materials and structures. Among these, ultrasonic testing stands out as the most prevalent method, owing to its versatility, accuracy, portability, and cost-effectiveness. However, traditional ultrasonic testing presents inherent limitations, all of which are directly or indirectly related to the need for contact with the structure. Therefore, Laser Ultrasonic Testing (LUT) has been introduced as a noncontact NDT technique, harnessing lasers and optical devices for wave generation and detection. In LUT, the material acts as an emitting transducer, and the ultrasonic waves are generated through the photoacoustic effect. LUT's non-contact nature eliminates the need for coupling mediums, enhances inspection speed, and enables automation and application in hostile environments (e.g., radioactive, high-pressure, high-temperature). Yet, LUT encounters its own hurdles. Low signal-to-noise ratios (SNRs) due to the low amplitude of generated waves, and the intricacies of wave generation and propagation pose significant challenges. Meeting these challenges requires precise simulations to understand the mechanisms behind laser-induced wave generation, optimize laser parameters, and explore innovative solutions. Therefore, this dissertation delves into the accurate modeling and simulation of laser-induced elastic waves in both isotropic and composite materials. Additionally, it presents a novel approach to addressing the challenges faced by LUT. Initially, a new theory of thermoelasticity capable of capturing intricacies due to ultrafast heating of material using short and ultrashort laser pulses is presented. Next, the root cause of numerical solution issues in simulating laser-induced elastic waves is explored, and a new guideline for spatial discretization of the domain is proposed. Subsequently, simulations are verified by analytical results. Furthermore, a new model for light absorption in composite materials, considering distinct optical absorptivities for different constituents, is proposed. Lastly, the dissertation thoroughly examines the effects of laser beam shaping on wave convergence and unveils the dynamics of laser-induced elastic waves in composite materials.

The expansion of the design space due to additive manufacturing (AM) has been a large motivator for the success of this family of processes. Despite the complexity of the physics in metal laser powder bed fusion AM causing significant stresses and strains in finished parts, the design advantages and subsequent performance improvements continue to drive the expansion of AM. Because the trial-and-error approach to AM part development is cost prohibitive, simulation of prints has become crucial. However, full thermo-mechanical simulation is susceptible to the same pitfall of time and computational cost in order to attain part-scale results. The development of lightweight AM print simulations that balance computational cost while retaining an acceptable level of accuracy is critical to the continued implementation and improvement of the AM process. In order to develop faster simulations, simplifications to and assumptions of the system must be made. In the context of simulating the mechanical behavior of printed AM parts, the work presented in this dissertation found that the part response can be captured in a pair of vectors that discretize the core and shell of a part and the in-plane and build-direction environments. This is implemented in the inherent strain method, where an initial small thermo-mechanical print simulation is performed on a millimeter-scale representative volume. From this, the vectors of inelastic strain are extracted using a novel method and subsequently applied to a part-scale mechanical simulation to yield the part’s critical post-print strain distribution. The parts were simulated as Inconel 625 on a 304 stainless steel iii build plate and validated against experimental measurements provided by the National Institute of Standards and Technology. Compared to the traditional approach of using only a single inherent strain vector to capture the full thermo-mechanical behavior, the piecewise vector set developed in this work significantly improved the median error from 82% down to 17%, with individual measurement location errors as low as 1%. The inclusion of the separate experimentally shown compressive core and tensile shell due to uneven cooling during the AM process, as well as the recognition of the different mechanical contexts of the in-plane and out-of-plane directions more accurately captured print behavior. This dissertation defines the inherent strain extraction technique and application, while improving the part-scale AM simulation cost-accuracy tradeoff balance.

The understanding of Bender Element mechanism and utilization of Particle Flow Code (PFC) to simulate the seismic wave behavior is important to test the dynamic behavior of soil particles. Both discrete and finite element methods can be used to simulate wave behavior. However, Discrete Element Method (DEM) is mostly suitable, as the micro scaled soil particle cannot be fully considered as continuous specimen like a piece of rod or aluminum. Recently DEM has been widely used to study mechanical properties of soils at particle level considering the particles as balls. This study represents a comparative analysis of Voigt and Best Fit theorem with DEM simulation. Multiple disk shaped uniformly distributed particles are arranged in a square shaped box. This particles are vibrated with a BE that generates shear and compressive wave within boundary area. Wave velocity is then recorded based on the movement of the particles at specific locations. Both S and P wave velocity is monitored based on the contact stiffness for both triangular and square arrangement. The study summarizes that DEM can accurately simulate the wave behavior. Also it shows that first peak method is a promising way to measure wave velocity. However, deviation between theoretical and simulation result occurs due to assuming non uniform stress and discrete element media.

This master's thesis is dedicated to enhancing the reliability of silver sinter die attachments, a pivotal component within the dynamic realm of power electronics. The study is meticulously organized into four distinct chapters, each contributing to a comprehensive understanding of silver sinter die attachment reliability and its implications for contemporary electronic packaging. In Chapter 1, an introduction is provided to the significance of silver sinter die attachment in the context of power electronics, underlining the imperatives associated with miniaturization, weight reduction, and heightened efficiency. The compelling need to investigate die attachment properties, particularly in high-temperature and high-power-density environments, is emphasized. Chapter 2 delves into the intricate design and fabrication of an H-bridge module, offering a practical framework for examining the die attachment process. Chapter 3 undertakes a thorough analysis of the reliability of the silver sinter die attachment layer. Employing Finite Element Analysis (FEA) in Ansys, the behavior of the silver sinter die attachment layer under varying stress scenarios is modeled and comprehensively understood. This in-depth analysis includes a comparative exploration of temperature cycling and power cycling reliability tests, providing valuable insights into the die attachment's response under diverse operational conditions, encompassing the aspects of plasticity through the Anand viscoplasticity model and lifetime modeling. Lastly, in Chapter 4, pioneering research is introduced, aimed at enhancing the mechanical reliability of silver sinter die attachment. This novel approach explores the integration of copper nanowires into the substrate interface, offering a unique strategy to fortify the attachment's mechanical robustness and durability. This work addresses the burgeoning demand for a comprehensive investigation of die attachment reliability, especially in the face of rising power densities and temperatures in power electronics.

With the densification of power electronics in the pursuit of decreased size and weight and increased efficiency, the need to investigate the properties of solder in packages with higher working temperatures and power densities is becoming apparent. Many research groups have conducted accelerated testing using methods such as thermal aging, shear or tensile stress tests, or electromigration tests, but relatively little research exists that considers the impact of several stresses in a combined study. This work aims to produce a novel method for estimating the lifetime of SAC305 solder joints under a combined stress scenario, which more accurately depicts the stress profile in real-world applications. Samples are fabricated and placed in an oven where constant current and constant shear stress are applied to the sample via power supply and a fabricated shear stress applicator, respectively. The health of the solder joints is monitored via 4-wire Kelvin resistance measurement. After testing, changes in microstructure of the samples can be evaluated via cross-sectioning and optical/scanning electron microscope. By varying the levels of temperature, current, and shear stresses applied to the sample, a regression model will be created to model the lifetime of the solder when all three stresses are taken into consideration. Using ANSYS to extract stress information from FEA analysis, the model is utilized to make an informed estimation of the operating lifetime of a cutting-edge flip chip MOSFET.

Spectroscopy is the practice of determining the chemical composition of a gas through analyzing the light that is filtered by the gas. Spectroscopy is commonly used by astronomers to deduce the atmospheric composition of planets. This process is done by initially measuring the spectrum of light from the star that the planet orbits, and then measuring it again once the planet is in between the observer and the star. The spectrum light that is filtered out is dependent on the chemical composition of the gas, and so this information can be used to determine the chemical composition of the atmosphere in question. This thesis focuses on an alternate method for spectroscopy involving a satellite equipped with a bright light that is orbiting the target planet. A telescope on the surface of the planet follows the movement of the satellite and captures its light, analyzing it with a spectrometer. The goal of this research is to develop, build, and program a prototype spectroscopic telescope that is able to follow the movements of a satellite orbiting Earth and to spectroscopically analyze the light reflected off of it. Over the course of this project, a prototype tracking telescope was successfully built and programmed. Spectrographic data was taken with it, and information was gathered about the program and modifications that need to be made for future iterations.

While Carbon Fiber Reinforced Polymers (CFRPs) have exceptional mechanical properties concerning their overall weight, their failure profile in demanding high-stress environments raises reliability concerns in structural applications. Two crucial limiting factors in CFRP reliability are low-strain material degradation and low fracture toughness. Due to CFRP’s low strain degradation characteristics, a wide variety of interlaminar damage can be sustained without any appreciable change to the physical structure itself. This damage suffered by the energy transfer from high- stress levels appears in the form of microporosity, crazes, microcracks, and delamination in the matrix material before any severe laminate damage is observed. This research presents a novel Non- Destructive Evaluation (NDE) technique for assessing subsurface interlaminar interphacial health. A new self-sensing smart composite material is born by embedding microscopic magnetically activated sensors between CFRP ply. Magnetostrictive Carbon Fiber Reinforced Polymer (MagCFRP) is a self-sensing structural health composite material that is magnetically activated by an external magnetic field. This research merges the governing magnetoelasticity and general magnetization mechanics with analytical, experimental, and numerical results. For mode I and mode II fiber- matrix debonding, cracking, and shear delamination, there was an observed localized magnetic flux density gradient of more than 3 mT (2%) with a reversible flux of only 25% for low driving magnetic flux density (≈ 0.2 T) using the indirect magnetization stimulation method.

Underwater robots are important for the construction and maintenance of underwater infrastructure, underwater resource extraction, and defense. However, they currently fall far behind biological swimmers such as fish in agility, efficiency, and sensing capabilities. As a result, mimicking the capabilities of biological swimmers has become an area of significant research interest. In this work, we focus specifically on improving the control and sensing capabilities of fish-like robots. Our control work focuses on using the Chaplygin sleigh, a two-dimensional nonholonomic system which has been used to model fish-like swimming, as part of a curriculum to train a reinforcement learning agent to control a fish-like robot to track a prescribed path. The agent is first trained on the Chaplygin sleigh model, which is not an accurate model of the swimming robot but crucially has similar physics; having learned these physics, the agent is then trained on a simulated swimming robot, resulting in faster convergence compared to only training on the simulated swimming robot. Our sensing work separately considers using kinematic data (proprioceptive sensing) and using surface pressure sensors. The effect of a swimming body's internal dynamics on proprioceptive sensing is investigated by collecting time series of kinematic data of both a flexible and rigid body in a water tunnel behind a moving obstacle performing different motions, and using machine learning to classify the motion of the upstream obstacle. This revealed that the flexible body could more effectively classify the motion of the obstacle, even if only one if its internal states is used. We also consider the problem of using time series data from a `lateral line' of pressure sensors on a fish-like body to estimate the position of an upstream obstacle. Feature extraction from the pressure data is attempted with a state-of-the-art convolutional neural network (CNN), and this is compared with using the dominant modes of a Koopman operator constructed on the data as features. It is found that both sets of features achieve similar estimation performance using a dense neural network to perform the estimation. This highlights the potential of the Koopman modes as an interpretable alternative to CNNs for high-dimensional time series. This problem is also extended to inferring the time evolution of the flow field surrounding the body using the same surface measurements, which is performed by first estimating the dominant Koopman modes of the surrounding flow, and using those modes to perform a flow reconstruction. This strategy of mapping from surface to field modes is more interpretable than directly constructing a mapping of unsteady fluid states, and is found to be effective at reconstructing the flow. The sensing frameworks developed as a result of this work allow better awareness of obstacles and flow patterns, knowledge which can inform the generation of paths through the fluid that the developed controller can track, contributing to the autonomy of swimming robots in challenging environments.

Line defects in crystals, known as dislocations, govern the mechanisms of plastic deformation at the micro-meso scale. The study of dislocations has proliferated the field of materials science and engineering for since the 1950’s, and modern studies show increasing utilization of computational methods to model the evolution of line defects in material systems. In keeping with modern research practice, the studies herewith demonstrate the use of advanced computing to generate models which can be used to better understand the behaviors of dislocations within crystal matrices. An advanced high-throughput model for a physically informed machine learning graph neural network (PIML-GNN) is outlined, which draws upon the output provided from Molecular Dynamics (MD) simulations and the computational efficacy of Dislocation Dynamics (DD). The intention of the study is to improve the dynamical prediction of DD mobility laws using the evolution of dislocation structures extracted from MD and processed using Ovito DXA analysis [29]. Each configuration is provided to the DD framework such that the local stress state can be embedded into the information passed to the ML model for training. The extracted dislocation mobility is then validated analytically by comparing regimes of phonon drag and thermal activation. In a separate study, the energetics of thermal activation are analyzed via a stochastic dislocation dynamics (SDD) approach. To impose stochasticity, which simulates the effects of thermal energy in the system, a Langevin thermostat overlays a white noise profile to the dislocation stress field whose amplitude scales directly with the absolute temperature of the simulation. Specific dislocation configurations are designed such that local energy minima are easily recognizable, and the stress state of the simulation is varied such that energy barriers can be overcome in thermally activated processes. From these studies, the bypass of local obstacles can be analyzed by extracting activation volumes and energies necessary to facilitate thermally activated processes in dislocation motion.

Robotic milling offers new opportunities for discrete part manufacturing as an alternative to milling using large conventional machine tools. The advantage of industrial robots is their large work volume, configurability, and comparatively low cost. However, robots are significantly less stiff than conventional machine tools, which can lead to poor surface finish, low machining accuracy, and low material removal rates. The purpose of this research is to predict the geometric errors, or surface location errors, that occur in a robotic mulling tool path, validate these predictions with machining tests, and compensate these errors by tool path modification. Compared with conventional machine tools, robots possess low stiffness, low frequency vibration modes and the presence of these modes causes surface location errors that are nearly independent of spindle speed in the range typically used for machining. Additionally, the robot often exhibits errors relative to the commanded tool path. By developing an understanding of both the dynamics of the robot and its tool path accuracy, predictions were made of the surface location error for a machined part and a compensation algorithm was developed. The accuracy of the predictions and compensation algorithm were verified with a series of experiments. Through this research it was determined that robotic milling is prone to large surface location errors, but it is possible to reduce these through offline compensation.

347H austenitic stainless steel exhibits exceptional creep and corrosion resistance, rendering it an exemplary candidate for pipeline materials, particularly in mid- to high-temperature working conditions. However, due to constraints in component dimensions, welding has been chosen as the preferred method for joining pipeline systems extensively employed in nuclear power plants, fossil fuel plants, and petrochemical companies. The welding process entails the accumulation of residual stress during the cooling stage, along with the introduction of microstructure evolution. Moreover, the residual stress field and microstructure continuously evolve under service conditions, thereby intensifying the susceptibility of crack initiation and propagation. The initial residual stress attains its maximum value but subsequently undergoes relaxation, while the microstructure gradient and uneven distribution of residual stress give rise to stress concentration, ultimately promoting premature failure, known as stress relaxation cracking (SRC). Prior investigations pertaining to the SRC issue have typically separated simulation and experimentation, leading to unreliable predictions. Concurrently, the lack of appropriate methods to integrate material thermo-mechanical properties into simulation models exacerbates the inaccuracies in predicting failure as the service time increases. Additionally, SRC tests necessitate the application of external loads to accelerate the testing process, thereby introducing additional uncertainties into the experiments and widening the disparity between simulation predictions and the actual failure time. Therefore, this report introduces a methodology that combines both simulation and experimentation to forecast the lifespan of 347H weldments, whereby the simulation model and experimental measurements can mutually corroborate each other.

Ensuring quality control within manufacturing is a vital necessity to the industry as it reduces waste, minimize cost, and provides a trusted product to the customer. Quality control is performed through inspection techniques that not only support the production line but assist the research and development of future materials and products. The advanced composite manufacturing field is a growing industry with large-scale polymer composite additive manufacturing and advanced discontinuous reinforced composites. Each has their own material property inspection requirements such as detection of residual warpage for the additive print process, fiber orientation for discontinuous composites, and thermal expansion measurements for all composites. This research outlines novel approaches and newly developed inspection techniques utilizing digital image correlation (DIC) to measure material properties of composites. DIC is an optical metrology method which provides full-field position and strain measurements while also being non-invasive. Three novel alterations of DIC are used to characterize composite manufactured structures and components. The three applications are (1) in-situ monitoring of thermal residual warpage of composite large-scale additive manufacturing (LSAM), (2) measuring relative fiber orientation within reinforced composites, and (3) local coefficient of thermal expansion (CTE) measurements. This research found the natural rough surface of the LSAM composite material replicates a speckle pattern suitable for the DIC correlation algorithm with a minimal 3.57% error. This enables DIC to monitor the print process in-situ without painting a speckle pattern. Additionally, DIC combined with a local heating method accurately measured the fiber orientation, achieving 2.5° ± 1.5° accuracy for a continuous unidirectional reinforced composite. The inspection of a discontinuous reinforced composite resulted in an error range from 2.2% to 24.1% when compared to the standardize radiography method. Finally, DIC also measured the coefficient of thermal expansion (CTE) when paired with an infrared camera to monitor the change in temperature. The presence of boundary conditions during locally heating reduced CTE values by 44.9% to 297.0% compared to the standardized method. A correction factor was developed to relate the DIC results to the standardized method.

Shoulder disability is a prevalent health issue associated with various orthopedic and neurological conditions, like rotator cuff tear and peripheral nerve injury. Many individuals with shoulder disability experience mild to moderate impairment and struggle with elevating the shoulder or holding the arm against gravity. To address this clinical need, I have focused my research on developing wearable passive exoskeletons that provide continuous at-home movement assistance. Through a combination of experiments and computational tools, I aim to optimize the design of these exoskeletons. In pursuit of this goal, I have designed, fabricated, and preliminarily evaluated a wearable, passive, cam-driven shoulder exoskeleton prototype. Notably, the exoskeleton features a modular spring-cam-wheel module, allowing customizable assistive force to compensate for different proportions of the shoulder elevation moment due to gravity. The results of my research demonstrated that this exoskeleton, providing modest one-fourth gravity moment compensation at the shoulder, can effectively reduce muscle activity, including deltoid and rotator cuff muscles. One crucial aspect of passive shoulder exoskeleton design is determining the optimal anti-gravity assistance level. I have addressed this challenge using computational tools and found that an assistance level within the range of 20-30% of the maximum gravity torque at the shoulder joint yields superior performance for specific shoulder functional tasks. When facing a new task dynamic, such as wearing a passive shoulder exoskeleton, the human neuro-musculoskeletal system adapts and modulates limb impedance at the end-limb (i.e., hand) to enhance task stability. I have presented development and validation of a realistic neuromusculoskeletal model of the upper limb that can predict stiffness modulation and motor adaptation in response to newly introduced environments and force fields. Future studies will explore the model's applicability in predicting stiffness modulation for 3D movements in novel environments, such as passive assistive devices' force fields.

Heavy metals and alkali Liquid Metals are suitable coolants for Generation IV terrestrial nuclear reactors for operating at elevated temperatures for achieving plant thermal efficiency more than 40% and the thermochemical generation of hydrogen fuel. In addition, the low vapor pressure of these liquids eliminates the need for a pressure vessel and instead operates slightly below ambient pressure. A primary issue with the uses of these coolants is their compatibility with nuclear fuel, cladding and core structure materials at elevated temperatures more than 500oC. Therefore, in pile and out-of-pile test loops have been constructed or being considered for quantifying the effect of the operating temperature flow velocity on the compatibility of versus fuel and structural materials with heavy liquid metals of lead (Pb) and lead Bismuth Eutectic (LBE) and alkali liquid metals of sodium for fast spectrum nuclear reactors. Recently, two in-pile test loops are thought for supporting the developments of molten lead and liquid sodium-cooled advanced reactors in the US and investigating the compatibility of several structure and cladding materials with these liquid metals at different temperatures and flow rates in a prototypical irradiation environment. These test loops were to be placed at designated locations within the core of the sodium-cooled, fast neutron spectrum 300 MWth Versatile Test Reactor (VTR). In these in-pile loops. It is desirable to employ miniature submersible v electromagnetic pumps (EMPS) with no moving parts for reliable operation. which is the focus of the present research. These pumps need to fit within the 2.5-inch diameter standard tube for the test loop riser downstream of the test article of one or more nuclear fuel rodlets, and with compatible components with molten lead and liquid sodium initially at temperatures up to 500oC. At these temperatures, 316SS cladding and structure materials is suitable choice, but not at higher temperature for which nickel free materials are being investigated. The objective of this research is therefore to develop designs and conduct performance analyses of miniature, submersible EMP for operating at temperatures < 500oC in in-pile and out-of-pile test loops for supporting the current development of GenIV molten Pb and liquid Na fast neutron spectrum terrestrial nuclear reactors. The two miniature submersible designs investigated are of a Direct Current-ElectroMagnetic pump (DC-EMP) and an Alternating Linear Induction Pump (ALIP). In the DC-EMP), in which DC electric current from Cu electrodes flows through the working fluid flowing in a narrow rectangular duct in the perpendicular direction to those of the flow and the generating magnetic flux density using permanent magnet(s). The produced Lorentz force in the pump duct drives the fluid flow. The ALIP’s linearly traveling magnetic fields produced by 3Phase alternative currents in winding coils surrounding the annular flow duct generate electrical current in the perpendicular directions of the generated electric current and magnetic field. The generated Lorentz force drives the flow in a narrow annular flow duct. The two submersible EMPs have an outer diameter of 66.8 mm outer diameters, which fit in a 2.5-inch standard tube with an inner diameter of 68.8 mm, and 1.00 mm clearance to the wall’s inner surface. The developed DC-EMP employs Alnico-5 permanent magnets with Hiperco-50 pole pieces for focusing the magnetic field lines in the 316SS rectangular flow duct and operating at temperatures up to 500oC. The novel 66.8mm pump design has dual pumping stages for enhance performance, enabled using a pair of Alnico-5 permanent magnets mounted along the rectangular flow duct and with opposite magnetizing directions in the two pumping regions of the flow duct. The electrical currents through the flow duct in the two pumping regions are supplied in opposite directions perpendicular to those of the flow and the magnetic field flux density, so that the generated Lorentz forces in the two pumping vi stages act in the same flow direction. The developed ALIP design employs hightemperature, ceramic insulated Copper wires for winding coils, and Hiperco-50 center core and stators. The performance analyses for the two pump designs are conducted using the lumped, electrical Equivalent Circuit Model (ECM). For the present DC-EMP the ECM on MATLAB platform is linked to the FEMM software, for calculating the effective electrical currents and magnetic field distribution in the pump duct at zero flow. The fast-running ECM includes a few simplifying assumptions, nonetheless it has been shown by other investigators and in this work to overpredict the pump characteristics by 10- 25%. The implements ECM for the present ALIP design is improved compared to the widely used and originally proposed model by Baker and Tessier. The accuracy of the improved ECM for the present ALIP design is confirmed by comparing predictions to the reported experimental data by others for low-flow sodium, small ALIP. The ECM predictions of the pump characteristics are

Particle accelerators are important for basic research as well as in applications such as ion implantation and cancer therapy. One important accelerator is the Los Alamos Neutron Science Center (LANSCE) located at Los Alamos National Laboratory (LANL) that primarily produces neutrons for research. The beam chopper simulation described here is a study to provide better modeling of this subsystem of LANSCE. A chopper is a device in which particles are intermittently sliced and directed to a target and/or experiment. The simulations in this thesis are used to analyze the correct operating parameters of the chopper. A good chopper model can help increase the efficiency of the particle accelerator, optimize the targeting time, and give us a better understanding of the interactions on the target. Therefore, chopper simulations are an important tool for evaluating the performance of LANSCE as well as helping with future developments.

Polylactic acid (PLA) is a biopolymer made from renewable resources such as sugar and corn. PLA filament is a popular material used in Fused Deposition Modeling (FDM) 3D-printing. While this material has many advantages, all the failed parts, support structures, rafts, nozzle tests, and the many prototype iterations during the 3D-printing process contribute to the plastic pollution and release of greenhouse gases. Although PLA is biodegradable, it can take years to degrade in landfills. Instead of throwing away PLA waste and buying new filaments, PLA can be recycled. Amongst the different recycling technologies, mechanical recycling is the most environmentally friendly. In this project, PLA filaments were mechanically recycled. One of the goals in this study was to identify the barriers to recycling and to introduce a more detailed recycling process. To achieve this goal, three different recycling extruders were tested to find the most user-friendly, which was the Noztek Pro Desktop extruder. Moreover, a new and more detailed material preparation process was introduced. In this method, PLA was first shredded. Then liquid nitrogen was added to make the material more brittle and easier to crush, and finally, it was ground. Additionally, the most effective process parameters for extrusion were presented. These parameters included temperature of 200 ºC, a pulley speed of 1.5 m/min, and using fans to cool the extruded filament before winding. The next goal was to evaluate the process with the added details and find the impacts of successive mechanical recycling on the properties of PLA. Therefore, a comprehensive testing was done including thermal (TGA and DSC), chemical (FTIR), and mechanical tests (tensile). Filaments could be recycled for three generations however after the third recycling, the filament no longer printed reliably. The test results demonstrated degradation of PLA. The UTS decreased from 44.7 MPa to 40.5 MPa, strain at break decreased from 10.4% to 7.5%, and the modulus, E, decreased from 1.603 GPa to 1.055 GPa. The FTIR results suggested that all samples had the same chemical structure of PLA. However, decreased intensity peaks around 920/cm show a decrease in crystallinity. In addition, a decrease in the absorbance band in the carbonyl region around 1750/cm, an intensity change from 700/cm to 2000/cm regions, and an intensity decrease around the 1180/cm-1240/cm were also observed. The DSC analysis showed that the Tg values were between 61.97 ℃ and 62.95 ℃, the cold crystallization temperatures had a range from 117.87 ºC to 128.81 ºC, and the melting temperatures ranged from 158.48 ºC to 161.28 ºC. Moreover, The TGA results showed that the decomposition temperatures were between 311.33 and 337.5 ºC. The recycling process was initially successful, however, after the third generation the filament became unprintable. This was due to decrease in crystallinity and molecular weight which caused brittleness, lower strength, and nozzle clogging. This research provided important design data regarding performance and limitations of recycled PLA.

This dissertation makes new contributions to the modeling and implementation of Tendon Driven Continuum Robots (TDCRs). Specifically, motivated by 3D printing of concrete using a continuum hose robot in construction applications, we focus on TDCRs featuring compliance in the robot backbone and actuating tendons, e.g. surgical robots/endoscopes/catheters with tendon actuation. We expand previous mechanics-based models to show how and why such compliance significantly restricts performance when traditional kinematics-based planning and control techniques are applied. The main contribution of this work is a new Elasticity Compensation(EC) model that explains why the ad hoc approach of preloading/pretensioning the tendons compensates for compliance by providing an analytical expression for the minimum preload required for accurate spatial bending of compliant TDCRs. The EC model, which is used to control tendon lengths and does not require either tendon tension sensing or computationally expensive dynamics or statics (Cosserat rod) modeling, is demonstrated on a TDCR in concrete printing experiments, and is shown to be a significant improvement over the state of the art. Additionally, we augment the performance of the EC model using closed loop control with quaternion feedback from an IMU.

Asymmetric bistable carbon fibre reinforced plastic (CFRP) composites enable a broad range of applications as they can sustain multiple stable configurations and have small snap-through load requirements. These unique features, coupled with their light strength-to-weight and stiffness-to-weight ratios, have made them preferred options for multifunctional systems. This study investigates the fatigue and hygroscopic response of 2-ply, [0/90] bistable CFRP laminates and proposes predictive modeling approaches for improved performance. While previous studies widely researched and documented the fatigue of general composites in axial loading, fatigue analysis of asymmetric bistable composites in the out-of-plane snap-through direction is inadequate. This study performs fatigue tests in this direction to snap the laminate between the two stable states during the cyclic loading and capture the stiffness and damage evolution for different combinations of test parameters incorporating frequencies from 1 to 10 Hz, two boundary conditions, and temperatures from 22°C to 150°C. The fatigue tests reveal that stiffness degradation and damage progression occur in two stages, while the specimens never experience global failure for any test combination. This analysis proposes a damage definition in terms of load, adopts the damage index with two analytical models: (1) Shiri Model and (2) Wu Model, and presents a range of model parameter values to predict damage during the first two stages for the specified conditions. The curvature and snap-through load evaluation demonstrates that fatigue loading does not affect these parameters. This finding enables application protocols to maintain bistable performance for a broad range of loading and environmental conditions. This study extends the predictive analysis by proposing machine learning (ML) modeling approaches to predict the non-linear load response of bistable composites in fatigue loading and utilizing the load response to predict stiffness and damage with six selected ML models: decision tree (DT), random forest (RF), adaptive boosting (ADA), gradient boosting machine (gb), artificial neural network (ANN) and k-nearest neighbors (KNN). The ML models are trained on the fatigue data acquired during the first part of the analysis. This approach evaluates the model performances with five validation tests incorporating tests with frequency and temperatures inside and outside the domain of the training data. The model assessment reveals that the ML models can capture the non-linear load-displacement response and provides a reasonable prediction of load, stiffness, and damage while offering expandability of prediction outside the training feature domain. Another aspect of this study is investigating the hygroscopic response of bistable composites in a variable relative humidity environment. The moisture absorption of asymmetric 2-ply, 4-ply, and 6-ply laminates is inspected in the laboratory environment to determine their curvature and snap-through load at different moisture content levels. The analysis reports a combined thermal and moisture expansion coefficient to predict these parameters with an improved analytical model and a finite element model. The models predict a linear drop in both parameters with increasing moisture content due to the plasticization of the epoxy polymer network and the subsequent relaxation of residual thermal strain, and these predictions demonstrate good agreement with test results.

The modern world would not be what it is now without machine tools. Advances in materials and processes, such as carbon fiber and additive manufacturing (AM), enable the design space for machine tool components to expand. However, machine tool components require accurate geometry, which is not available from parts produced by metal Big Area Additive Manufacturing (mBAAM). This project outlines the process in which a traditionally manufactured machine tool component, a welded box structure on an existing machine tool, was redesigned to be made using mBAAM. The goal was to design a structure that was printable using the MedUSA system at Oak Ridge National Laboratory (ORNL) and measure the dynamic characteristics of the printed part using modal testing for comparison to finite element models. The MedUSA system consists of three robotic arms that each manipulate a gas metal arc welding (GMAW) torch. The three torches were used to simultaneously deposit the mBAAM replacement for the traditional welded box structure. The print continued for 245 layers before it was stopped due to significant distortion caused by thermal deformation and fixturing failure. However, modal testing was completed on the 77\% complete structure to compare with finite element models that simulated bending mode shapes and natural frequencies. It was confirmed that the printed structure dynamics agreed with the numerical model predictions, which demonstrated that it is feasible to model a large-scale mBAAM part and understand its behavior prior to printing. Another significant outcome of this study is that the incomplete print shows that there remains a knowledge gap for successful mBAAM. The outcome of this project adds to the understanding necessary to enable successful large metal prints in the future. AM has become a popular technology due to its expanded opportunities for unique geometries and wide design space, but challenges remain. This printed structure, although incomplete, demonstrates ongoing issues with thermal management and residual stress in large parts. Overall, this study demonstrates an example of designing and printing a large-scale metal structure that was validated through modal testing.

Additive manufacturing (AM) has rapidly transformed from a novelty prototyping technology into a growing sector of production across a wide range of industries. Much work has been documented in literature to demonstrate the behavior of AM products under static and quasi-static loading conditions. However, the behavior of AM materials under high strain rate loading is not as well understood. This research attempts to advance the fundamental knowledge of the relationship between the unique aspects of AM and the mechanical performance under high velocity impact loading conditions. This project examines the behavior of AM 316L stainless steel (SS) exposed to high velocity impact, the associated shock wave propagation, and the resistance to fracture as a function of orientation and internal engineered features (a design tool unique to AM). This research involves fabrication, characterization, plate impact spallation testing, experiment modeling, and post-mortem analysis of 316L SS samples fabricated using laser powder bed fusion (LPBF). Connections and correlations were established using a variety of data sets. A build-impact orientation study and two engineered porosity studies (one with random distribution across the bulk and the other with single voids strategically placed) were conducted to develop a better understanding of shock wave propagation and spall fracture related to the unique aspects and capabilities of LPBF fabrication. This research demonstrated that impact orientation with respect to build direction influences the extent and location of spall damage due to the relative microstructural anisotropy and collections of powder filled voids slow and weaken the progressing shock front by presenting disturbances in portions of the wave front. An engineering design study based on the findings of the earlier studies further utilized purposeful engineering design to control the propagation of the shock wave (and associated pressure front) through the material. The use of internal features, a capability unique to LPBF, was the primary goal of the study. This study successfully demonstrated that a large, powder-filled void space placed within a solid sample provides damping qualities that both slow the progression of the shock front and reduce the magnitude of the pressure stress realized at the rear free surface (opposite of impact). Overall, the results of this research demonstrate that the anisotropic properties and unique capabilities of LPBF can be leveraged to control shock wave propagation and resultant damage in stainless steel materials. Unique aspects of this research include (1) comparing the spall response of LPBF fabricated samples to shock loading conditions applied at varying orientation relative to the build direction, (2) examining the use of powder-filled engineered void spaces to reduce the magnitude and velocity of the progressing shock front, along with the resulting damage, and (3) in both cases coupling the results of plate impact experiments with as-built and post-mortem sample characterization.

Cellular electroporation has become an effective and widely adopted method for intracellular delivery, yet the mechano-electrical process of electroporation using porous substrate as an interface remains largely unexplored. Most studies characterize the process through fluorescent imaging of molecular markers or resistance measurements of the cell layer. Although convenient, current methods often provide limited characterization of the cell behavior after electroporation and fails to paint a full picture about the effectiveness of electroporation. This inability to fully quantify the effects of electroporation in real-time hinders the advancement of the technique, and often leads to questionable efficacy and consistency. To address this lack of understanding, we developed a platform capable of performing both electroporation and impedance measurements using a microfabricated device and integrated electronics. The function and capabilities of the device are explained and proven through direct comparison to separate commercial systems. The device reveals cell impedance evolution from various modes of electroporation via real-time quantitative impedance measurements for the first time. Lastly, we show that different cells respond in different ways to electroporation. This integrated platform and the impedance monitoring offers a facile process to quantitatively evaluate the electroporation process in porous substrate-based electroporation. Advisor: Ruiguo Yang

Due to their remarkable properties, transition metal dichalcogenides (TMDs) have received much scientific interest throughout the past decade. Two layers of chalcogen atoms (S, Se, Te) sandwich a layer of transition metal atoms (Mo, W, Ta) to form the three-atom thick unit cell in TMDs. The interaction between TMD "single layers" is mediated by neighboring chalcogen planes and bonded by Van der Waals forces. Due to this weak out-of-plane interaction, bulk samples can be thinned down to a single layer by exfoliation. Among the TMDs, Molybdenum Disulfide (MoS2) shows promise in the field of electronics, optics, and sensing applications. Despite numerous experimental and computational studies, it is poorly understood how out-of-plane thermal properties behave, as they have a higher degree of freedom in the lattice. Recently, hybrid structures have been found to form at interface boundaries in small devices, but the mechanism behind them remains unclear. Additionally, the thermal and mechanical properties of MoS2 under the phase transition are poorly understood and reported. Here, we benchmarked the empirical potential and reported the layer-dependent out-of-plane thermal properties. From our approach to calculating the thermal properties, we have demonstrated that the out-of-plane thermal conductivity in MoS2 increases monotonically with the number of layers. We have filled the gap in understanding the contribution of stress on the quadrilateral phase (I4/mmm) transition from the stable 2H phase of MoS2 at room temperature and the contribution of local strain in the mechanism for single- and bilayer systems. This mechanism of the phase change in MoS2 will be helpful where a change in the device's mechanical properties can occur, e.g., during the removal of layers from the substrate due to the presence of external force or unwanted impurities (i.e., S line vacancies). The presence of intrinsic (edge, chirality) and extrinsic (system sizes) conditions in phase transitions is also presented in this work. We have also reported how the presence of sulfur line vacancies in single- and bilayer systems can affect phase transition while undergoing uniaxial tension. In this work, we have found that the metastable T" phase (formed from 2H in the transition process by sulfur plane gliding before transitioning into I4/mmm) is triggered by local tensile stress, while the local out-of-plane force triggers the I4/mmm phase. Additionally, we have also revealed that MoS2 has tunable elastocaloric properties, which can be utilized to cool nanodevices during the loading-unloading condition.

This thesis presents a predictive analysis of the stability of square bistable carbon fiber reinforced composite laminates under various loading conditions. The stability of these laminates is essential to their performance and longevity and is influenced by factors such as thickness and length. Analytical and numerical techniques are used to model the behavior of these laminates, and experimental tests are conducted to validate the models. The findings of this research have implications for the design and optimization of square bistable carbon fiber reinforced composites. The study investigates the relationships between the side length and thickness of square laminates for bistability. The following equations can be used for a relationship between curvature κ and thickness, t for bistable laminations of CFRP DA 409U/G35 150: κ=0.023t^(-1.059) and t=0.788κ^0.943. These findings provide valuable insights for designing and fabricating bistable laminates in engineering applications. These findings have significant practical implications for the design and manufacturing of laminates, as they enable engineers to select an appropriate thickness of laminate to achieve a desired curvature. Moreover, the knowledge gained from this study could be utilized to optimize the strength and durability of laminates for various applications, making it a valuable contribution to the field of engineering. Future studied would require generalizing this equation to other CFRP with varying material properties. The prediction of snap-through force for bistable laminates reveals that the force required for actuation is dependent on both the thickness and side length of the laminate. The non-dimensional study conducted in this research demonstrates that the force is a function of both parameters, and by introducing non-dimensional parameters, the graph of force versus side length collapses into a single curve for different numbers of plies. The experimental validation of the approach used to predict snap-through force was inconclusive. The difference in the values obtained from finite element analysis and experimentation could be due to inaccurate material properties and fabrication defects during the hand lay-up process. The present findings provide a useful foundation for further research and offer practical implications for the design and development of bistable laminates for various applications.

Bistable composites are a class of advanced materials that can actuate between two stable shapes, making them attractive for a wide range of engineering applications. However, designing these composites to achieve optimal performance remains a challenging task. To address the challenge, this research develops an integrated framework that combines a genetic algorithm optimization technique, finite element analysis in Abaqus, and experimental testing to explore the design comparative space for square bistable composites composed of DA 409 carbon fibers. This leads to the study of generating an optimization algorithm to account for the relationship between the chances of a successful maximum deflection between states of a two-ply system by varying the edge lengths to a 2 by 2-inch, 3 by 3-inch, 4 by 4-inch, and 5 by 5-inch composite structure. The optimized ply systems are evaluated using finite element analysis in Abaqus to assess their maximum/total deformation post curing and are compared to the optimized laminate. Finally, physical samples are experimentally tested to validate the performance of the optimized designs and finite element analysis model. The results of this research underscored the effectiveness of the proposed integrated framework for exploring the design space of bistable composites. The validated design space provides a small difference in its total deformation, values less than 1mm which contributes on to the success rate of an operated control space. This method can be leveraged to optimize the performance of bistable composites for a variety of engineering applications, including morphing aerospace structures, deployable structures, and soft robotics. In doing so, this framework will substantially enhance the efficiency, accuracy, and practicality of bistable composites, setting a new standard for high-performance materials in the field.

Compared with conventional materials, architected metamaterials have shown unprecedented mechanical properties and functionalities applications. Featured with controlled introduction of porosity and different composition, architected metamaterials have demonstrated unprecedent properties not found in natural materials. Such design strategies enable researchers to tailor materials and structures with multifunctionalies and satisfy conflicting design requirements, such as high stiffness and toughness; high strength with vibration mitigation properties, etc. Furthermore, with the booming advancement of 3D printing technologies, architected materials with precisely defined complex topologies can be fabricated effortlessly, which in turn promotes the research significantly. The research objectives of this dissertation are to achieve the enhanced mechanical properties and multifunctionalities of architected metamaterials by integrative design, computational modeling, 3D printing, and mechanical testing. Phononic crystal materials are capable of prohibiting the propagation of mechanical waves in certain frequency ranges. This certain frequency ranges are represented by phononic band gaps. Formally, band gaps are formed through two main mechanisms, Bragg scattering and local resonance. Band gaps induced by Bragg scattering are dependent on periodicity and the symmetry of the lattice. However, phononic crystals with Bragg-type band gaps are limited in their application because they do not attenuate vibration at lower frequencies without requiring large geometries. It is not practical to build huge models to achieve low frequency vibration mitigation. Alternatively, band gaps formed by local resonance are due to the excitation of resonant frequencies, and these band gaps are independent of periodicity. Therefore, lower frequency band gaps have been explored mostly through the production of phononic metamaterials that exploit locally resonant masses to absorb vibrational energy. However, despite research advances, the application of phononic metamaterials is sill largely hindered by their limited operation frequency ranges. Designing lightweight phononic metamaterials with low-frequency vibration mitigation capability is still a challenging topic. On the other hand, conventional phononic crystals usually exhibit very poor mechanical properties, such as low stiffness, strength, and energy absorption. This could largely limit their practical applications. Ideally, multifunctional materials and structures with both vibration mitigation property and high mechanical performance are demanded. In this work, we propose architected polymer foam material to overcome the challenges. Beside altering the topological architecture of metamaterials, tailoring the composition of materials is another approach to enhance the mechanical properties and realize multifunctionalities. Natural materials have adopted this strategy for long period of time. Biological structural materials such as nacre, glass sea sponges feature unusual mechanical properties due to the synergistic interplay between hard and soft material phases. These exceptional mechanical performance are highly demanded in engineering applications. As such, intensive efforts have been devoted to developing lightweight structural composites to meet the requirements. Despite the significant advances in research, the design and fabrication of low-cost structural materials with lightweight and superior mechanical performance still represent a challenge. Taking inspiration from cork material, we propose a new type of multilayered cellular composite (MCC) structure composed of hard brittle and soft flexible phases to tackle this challenge. On the other hand, piezoelectric materials with high sensitivity but low energy absorption have largely limited their applications, especially during harsh environment where external load could significantly damage the materials. Enlightened by the multiphase composite concept, we apply this design motif to develop a new interpenetrating-phased piezoelectric materials by combining PZT material as skeleton and PDMS material as matrix. By using a facial camphene-templated freeze-casting method, the co-continuous composites are fabricated with good quality. Through experiment and simulation studies, the proposed composite demonstrates multifunction with exceptional energy absorption and high sensitivity. Based on the above experimental studies, we further propose to use topology optimization framework to obtain the composites with the best performance of multifunctionalities. Specifically, we will use the solid isotropic material with penalization (SIMP) approach to optimize the piezoelectric materials with multi-objectives of 1) energy absorption and 2) electric-mechanical conversion property. The materials for the optimization design will be elastic PZT as skeleton and elatic material PDMS as matrix. To enable the gradient search of objective function efficiently, we will use adjoint method to derive the shape sensitivity analysis.

Radiative transfer theory describes the interaction of radiation with scattering and absorbing media. It has applications in neutron transport, atmospheric physics, heat transfer, molecular imaging, and others. In steady state, the radiative transfer equation is an integro-differential equation of five independent variables, which are 3 dimensions in space and 2 dimensions in the angular direction. This high dimensionality and the presence of the integral term present serious challenges when solving the equation numerically. Over the past 50 years, several techniques for solving the radiative transfer equation (RTE) have been introduced. These include, but are certainly not limited to, Monte Carlo methods, discrete-ordinate methods, spherical harmonics methods, spectral methods, finite difference methods, and finite element methods. Methods involving discrete ordinates and spherical harmonics have received particular attention in the literature. This work introduces a parallel space-angle discontinuous Galerkin (saDG) method to solve the steady-state RTEs. The objective-oriented design of the software allowed us to apply the saDG approach to a variety of RTEs with considerable ease, including 1x1s, 1x2s, and 2x2s. The direct solver can achieve high-order accuracy solutions for low-dimensional problems. However, for high-dimensional problems, the direct solver is time-consuming and requires significant memory usage that may exceed the computer's RAM capacity. To address this issue, we employed the Angular Decomposition (AD) method in the iterative solver, which improves runtime efficiency and reduces memory usage. To handle large-scale problems, we developed a parallel solver based on AD and Domain Decomposition (DD) methods. Finally, we applied Reflective Boundary Conditions to 2-D Cartesian radiative transfer problems.

The demand for robust materials in energy-based applications such as solid electrolytes for batteries, piezoelectric composites for mechanical energy harvesting, or new polymer materials for polymer binders in composite electrodes is on the rise. Mechanical degradation is the most common way for devices to fail in operation, thus a thorough understanding of a material’s mechanical properties is essential for application purposes. In this dissertation, the mechanical characterization of novel boron cluster solid electrolytes is presented. Therein, we determine the elastic modulus and hardness of these compounds using instrumented indentation. A comparison is made against other solid electrolytes. It is found that the boron cluster family of electrolytes are significantly more compliant than other common electrolytes, such as garnet. A study on the structure-property relationship of 0D hybrid chlorometallates is also presented. In this work, we find that the elastic modulus depends significantly on the density of the compound as well as the number of hydrogen bonding sites located on the organic cation. These results are rationalized by comparing them with organic crystals, where it was found that the energy framework of hydrogen bonds within the crystal play a substantial role in determining the stiffness of this family of crystals. A critical assessment of a novel energy-based method of determining the fracture toughness of materials using indentation is also presented. In this work, we find that the energy-based techniques found in literature give inaccurate values of fracture toughness when compared against more traditional methods. An improved method is proposed by introducing a calibration step into this process. Our results indicate that, once calibrated, this method provides significantly more accurate fracture toughness values. Lastly, an in situ AFM study on anodized aluminum coated aluminum anodes is presented. It is determined that defects in the insulating layer can lead to unwanted inhomogeneous lithiation. The process of this lithiation is imaged directly in real time with the AFM and is presented. The collection of this work demonstrates the importance of characterizing the mechanical properties of energy-based materials.

Literature has shown that 3D printed composites may have highly anisotropic mechanical properties due to variation in microstructure as a result of filament deposition process. Laminate composite theory, which is already used for composite products, has been proposed as an effective method for quantifying these mechanical characteristics. Starting with the analysis of comparing the printing orientation of premanufactured carbon fiber reinforced filament, the mechanical properties of 3D printed objects were examined. The mechanical properties changed not only as a result of machine choice, but how the sample is oriented along the printing bed. The analysis continued with looking at the dynamic properties of 3D printed composites. Results showed that the direction of the extruded strands altered the modal frequencies even for a sample with the same geometry. With the direction of the extruded strands affecting the mechanical properties, the composition of these strands is also shown to affect the mechanical properties of 3D printed composites. For commercially available fiber reinforced filaments, it was found through microscopic analysis that the fiber content stated by the manufacturer is inaccurate. In order to apply Classical Laminate Composite Theory (CLCT) the fiber volume fraction and aspect ratio need to be known. This lead to the creation of custom filament with the desired fiber content and geometry. The Halpin-Tsai model was used to predict the mechanical behavior of short fiber reinforced composites. Finally, the mechanical properties of continuous fiber composites were examined. The continuous fiber samples showed that fiber orientation had an vast effect on mechanical properties. A well oriented composite notably outperformed other fiber orientations with a drastic drop in Young's modulus even with slight misalignment in fiber direction, but also resulted in brittle responses which may not be preferable. CLCT is applied using the simulation software ansys workbench. The results showed considerable correlation for each orientation and can be an accurate predictor of mechanical characteristics for 3D printed continuous fiber composites.

Finding alternative power sources has been an important topic of study worldwide. It is vital to find substitutes for finite fossil fuels. Such substitutes may be termed renewable energy sources and infinite supplies. Such limitless sources are derived from ambient energy like wind energy, solar energy, sea waves energy; on the other hand, smart cities megaprojects have been receiving enormous amounts of funding to transition our lives into smart lives. Smart cities heavily rely on smart devices and electronics, which utilize small amounts of energy to run. Using batteries as the power source for such smart devices imposes environmental and labor cost issues. Moreover, in many cases, smart devices are in hard-to-access places, making accessibility for disposal and replacement difficult. Finally, battery waste harms the environment. To overcome these issues, vibration-based energy harvesters have been proposed and implemented. Vibration-based energy harvesters convert the dynamic or kinetic energy which is generated due to the motion of an object into electric energy. Energy transduction mechanisms can be delivered based on piezoelectric, electromagnetic, or electrostatic methods; the piezoelectric method is generally preferred to the other methods, particularly if the frequency fluctuations are considerable. In response, piezoelectric vibration-based energy harvesters (PVEHs), have been modeled and analyzed widely. However, there are two challenges with PVEH: the maximum amount of extractable voltage and the effective (operational) frequency bandwidth are often insufficient. In this dissertation, a new type of integrated multiple system comprised of a cantilever and spring-oscillator is proposed to improve and develop the performance of the energy harvester in terms of extractable voltage and effective frequency bandwidth. The new energy harvester model is proposed to supply sufficient energy to power low-power electronic devices like RFID components. Due to the temperature fluctuations, the thermal effect over the performance of the harvester is initially studied. To alter the resonance frequency of the harvester structure, a rotating element system is considered and analyzed. In the analytical-numerical analysis, Hamilton’s principle along with Galerkin’s decomposition approach are adopted to derive the governing equations of the harvester motion and corresponding electric circuit. It is observed that integration of the spring-oscillator subsystem alters the boundary condition of the cantilever and subsequently reforms the resulting characteristic equation into a more complicated nonlinear transcendental equation. To find the resonance frequencies, this equation is solved numerically in MATLAB. It is observed that the inertial effects of the oscillator rendered to the cantilever via the restoring force effects of the spring significantly alter vibrational features of the harvester. Finally, the voltage frequency response function is analytically and numerically derived in a closed-from expression. Variations in parameter values enable the designer to mutate resonance frequencies and mode shape functions as desired. This is particularly important, since the generated energy from a PVEH is significant only if the excitation frequency coming from an external source matches the resonance (natural) frequency of the harvester structure. In subsequent sections of this work, the oscillator mass and spring stiffness are considered as the design parameters to maximize the harvestable voltage and effective frequency bandwidth, respectively. For the optimization, a genetic algorithm is adopted to find the optimal values. Since the voltage frequency response function cannot be implemented in a computer algorithm script, a suitable function approximator (regressor) is designed using fuzzy logic and neural networks. The voltage function requires manual assistance to find the resonance frequency and cannot be done automatically using computer algorithms. Specifically, to apply the numerical root-solver, one needs to manually provide the solver with an initial guess. Such an estimation is accomplished using a plot of the characteristic equation along with human visual inference. Thus, the entire process cannot be automated. Moreover, the voltage function encompasses several coefficients making the process computationally expensive. Thus, training a supervised machine learning regressor is essential. The trained regressor using adaptive-neuro-fuzzy-inference-system (ANFIS) is utilized in the genetic optimization procedure. The optimization problem is implemented, first to find the maximum voltage and second to find the maximum widened effective frequency bandwidth, which yields the optimal oscillator mass value along with the optimal spring stiffness value. As there is often no control over the external excitation frequency, it is helpful to design an adaptive energy harvester. This means that, considering a specific given value of the excitation frequency, energy harvester system parameters (oscillator mass and spring stiffness) need to be adjusted so that the resulting natural (resonance) frequency of the system aligns with the given excitation frequency. To do so, the given excitation frequency value is considered as the input and the system parameters are assumed as outputs which are estimated via the neural network fuzzy logic regressor. Finally, an experimental setup is implemented for a simple pure cantilever energy harvester triggered by impact excitations. Unlike the theoretical section, the experimental excitation is considered to be an impact excitation, which is a random process. The rationale for this is that, in the real world, the external source is a random trigger. Harmonic base excitations used in the theoretical chapters are to assess the performance of the energy harvester per standard criteria. To evaluate the performance of a proposed energy harvester model, the input excitation type consists of harmonic base triggers. In summary, this dissertation discusses several case studies and addresses key issues in the design of optimized piezoelectric vibration-based energy harvesters (PVEHs). First, an advanced model of the integrated systems is presented with equation derivations. Second, the proposed model is decomposed and analyzed in terms of mechanical and electrical frequency response functions. To do so, analytic-numeric methods are adopted. Later, influential parameters of the integrated system are detected. Then the proposed model is optimized with respect to the two vital criteria of maximum amount of extractable voltage and widened effective (operational) frequency bandwidth. Corresponding design (influential) parameters are found using neural network fuzzy logic along with genetic optimization algorithms, i.e., a soft computing method. The accuracy of the trained integrated algorithms is verified using the analytical-numerical closed-form expression of the voltage function. Then, an adaptive piezoelectric vibration-based energy harvester (PVEH) is designed. This final design pertains to the cases where the excitation (driving) frequency is given and constant, so the desired goal is to match the natural frequency of the system with the given driving frequency. In this response, a regressor using neural network fuzzy logic is designed to find the proper design parameters. Finally, the experimental setup is implemented and tested to report the maximum voltage harvested in each test execution.

As natural gas production infrastructure is already in place in most of the world and will continue expanding for the foreseeable future, natural gas is an alternative to traditional liquid petroleum fuels in heavy-duty engines. Dedicated natural gas or dual-fuel diesel-natural gas heavy-duty engines are alternatives to diesel-only power generation equipment. One challenge is the large variation in the natural gas composition available for such applications, which is known to significantly affect engine’s combustion characteristics and the emissions composition. As the literature on dual-fuel combustion under low load engine operating conditions that use more realistic natural gas mixtures (i.e., mixtures that, in addition of methane (C1;the most abundant natural gas component), also contain ethane (C2), propane (C3), and butane (C4)) is limited, this study evaluated the combustion characteristics of a variety of C1-C4 mixtures using three different experimental platforms: a 4.5-L 4-cylinder heavy-duty production diesel engine modified for dual-fuel diesel-natural gas engine operation, a prototype 1.125-L single-cylinder engine with extended optical access that was based on the same production diesel engine, and a laminar flame burner. Experiments in the heavy-duty production engine under low load dual-fuel diesel-natural gas operating conditions (6 bar break mean effective pressure at 1000 RPM, 1000 bar diesel injection pressure, and 40% diesel substitution ratio) showed that gas composition affected the diesel fuel ignition delay and combustion phasing, which are known to affect both engine performance and emissions. As in-cylinder pressure correlated with the autoignition temperature of the gaseous mixture, mixtures with higher C2-C4 content produced the best engine performance and emissions compared to using 100% C1, suggesting that the addition of C2-C4 content benefits low load dual-fuel combustion. For example, brake specific carbon dioxide and nitrogen oxides emissions reduced up to 6.6% and 20%, respectively. In addition, gas mixtures containing C3 and C4 reduced the brake specific carbon dioxide equivalent by up to 50 g/kWh compared to the C1-only case. Experiments in the prototype single cylinder optical engine employed imaging diagnostics to better understand the C1-C4 effects observed in the production engine experiments. High boost and high intake temperature were used to create in-cylinder conditions similar to those in the production engine at the start of combustion. To enhance the visual differences between the natural gas components, only one component was used at a time instead of a multicomponent mixture as in the production engine experiments, and difficulties in accurately controlling the C4 flow resulted in using only C1-C3. Experiments were performed at similar low load dual fuel operating conditions (~ 6.6 bar indicated mean effective pressure at 1000 RPM, 500 bar diesel injection pressure, and ~ 63% diesel substitution ratio), using both traditional and advanced diesel injection timing (i.e., conventional mixing-controlled compression ignition or MCCI compared to reactivity-controlled compression ignition or RCCI). Natural luminosity data showed that C3 RCCI had a more advanced combustion phasing despite an increased ignition delay and higher spatially-integrated natural luminosity compared to C1 RCCI and C2 RCCI. An earlier premixed combustion and a smaller phasing difference between the apparent heat release and spatially-integrated natural luminosity was seen for MCCI compared to RCCI. The results suggested that the C1-C3 content indeed affected the diesel gas mixing and stratification of the low load dual-fuel operation, hence the differences in engine performance and emissions observed in the production engine experiments. As a result, the findings in this study can be used for modeling the dual-fuel combustion of C1-C4 blends and can help industry in utilizing more efficiently natural gas with higher C2-C4 content.

This thesis presents a path optimization solution for a robot in two different constrained 3-dimensional (3D) environments. The robot is required to travel from its current position to a goal position following minimum cost paths (optimal paths). The first environment has 3D obstacles that interfere with the robot’s path. The path cost for this environment accounts for the minimum distance traveled by the robot from the start to the goal position while avoiding obstacles. The second environment is the atmosphere of Venus, specifically a flyable region of this atmosphere with characteristics similar to Earth’s. This environment has strong westward winds that require a more complex cost function. The path cost also accounts for energy expenditure, such as thrust or drag, and energy accumulation, such as charging using the robot’s solar panels and gains of potential energy (e.g., due to upward directional winds). In this case, we can add to the path cost function the localization cost of the robot. Localization is simulated in the environment by the use of cameras pointing to the surface of the planet, with yields lower localization error when the vehicle is close to the surface. The approach proposed in this paper uses genetic algorithms, a heuristic search that, based on a population of initially feasible paths and a set of biologically inspired operations, finds a low-cost path. Path feasibility is assured by computing local reachability regions based on different factors such as wind velocity, obstacles, and the maximum speed of the robot. The method is illustrated through a series of simulations that show our results as a function of the number of iterations and path population sizes. Finally, a comparison with different planners is made in order to show that the genetic algorithms allow for more efficient and easier implementations.

The motivation for this thesis was to develop a cable-driven parallel robot (CDPR) as part of a two-part robotic device for concrete 3D printing. This research addresses specific research questions in this domain, chiefly, to present advantages offered by the addition of kinematic redundancies to CDPRs. Due to the natural actuation redundancy present in a fully constrained CDPR, the addition of internal mobility offers complex challenges in modeling and control that are not often encountered in literature. This work presents a systematic analysis of modeling such kinematic redundancies through the application of reciprocal screw theory (RST) and Lie algebra while further introducing specific challenges and drawbacks presented by cable driven actuators. It further re-contextualizes well-known performance indices such as manipulability, wrench closure quality, and the available wrench set for application with reconfigurable CDPRs. The existence of both internal redundancy and static redundancy in the joint space offers a large subspace of valid solutions that can be condensed through the selection of appropriate objective priorities, constraints or cost functions. Traditional approaches to such redundancy resolution necessitate computationally expensive numerical optimization. The control of both kinematic and actuation redundancies requires cascaded control frameworks that cannot easily be applied towards real-time control. The selected cost functions for numerical optimization of rCDPRs can be globally (and sometimes locally) non-convex. In this work we present two applied examples of redundancy resolution control that are unique to rCDPRs. In the first example, we maximize the directional wrench ability at the end-effector while minimizing the joint torque requirement by utilizing the fitness of the available wrench set as a constraint over wrench feasibility. The second example focuses on directional stiffness maximization at the end-effector through a variable stiffness module (VSM) that partially decouples the tension and stiffness. The VSM introduces an additional degrees of freedom to the system in order to manipulate both reconfigurability and cable stiffness independently. The controllers in the above examples were designed with kinematic models, but most CDPRs are highly dynamic systems which can require challenging feedback control frameworks. An approach to real-time dynamic control was implemented in this thesis by incorporating a learning-based frameworks through deep reinforcement learning. Three approaches to rCDPR training were attempted utilizing model-free TD3 networks. Robustness and safety are critical features for robot development. One of the main causes of robot failure in CDPRs is due to cable breakage. This not only causes dangerous dynamic oscillations in the workspace, but also leads to total robot failure if the controllability (due to lack of cables) is lost. Fortunately, rCDPRs can be utilized towards failure tolerant control for task recovery. The kinematically redundant joints can be utilized to help recover the lost degrees of freedom due to cable failure. This work applies a Multi-Model Adaptive Estimation (MMAE) framework to enable online and automatic objective reprioritization and actuator retasking. The likelihood of cable failure(s) from the estimator informs the mixing of the control inputs from a bank of feedforward controllers. In traditional rigid body robots, safety procedures generally involve a standard emergency stop procedure such as actuator locking. Due to the flexibility of cable links, the dynamic oscillations of the end-effector due to cable failure must be actively dampened. This work incorporates a Linear Quadratic Regulator (LQR) based feedback stabilizer into the failure tolerant control framework that works to stabilize the non-linear system and dampen out these oscillations. This research contributes to a growing, but hitherto niche body of work in reconfigurable cable driven parallel manipulators. Some outcomes of the multiple engineering design, control and estimation challenges addressed in this research warrant further exploration and study that are beyond the scope of this thesis. This thesis concludes with a thorough discussion of the advantages and limitations of the presented work and avenues for further research that may be of interest to continuing scholars in the community.

A discrete approach introduces a novel deep learning approach for generating fine resolution structures that preserve all the information from the topology optimization (TO). The proposed approach utilizes neural networks (NNs) that map the desired engineering properties to seed for determining optimized structure. This framework relies on utilizing parameters such as density and nodal deflections to predict optimized topologies. A three-stage NN framework is employed for the discrete approach to reduce computational runtime while maintaining physics constraints. A continuous representation that uses complementary energy (CE) methods to solve a representative element's homogenized properties consists of an embedded structure that is parametrically defined. Defining the meso-scale structure as a swept cross-section makes it possible to solve for force/displacement interactions by leveraging Castigliano's second theorem. Homogenization is used to find the equivalent material properties of a representative element; the properties are used to solve a compliant mechanism TO (CMTO). A direct stiffness method is used to provide a better alternative to homogenization by directly finding the force/displacement relationships. An RBF surrogate model is used in a multi-variate TO (MVTO) framework to find the relationship between the design parameter vector and the stiffness values, the sensitivities for the design parameter vector can be found by taking the derivate of the RBFs. The MVTO framework is compared against the homogenized approach to demonstrate the algorithm's efficacy. A visualization framework is presented that can display high-resolution textures on low-triangulation meshes to show regions of high stress or deformation.

Optimization can assist in obtaining the best possible solution to a design problem by varying related variables under given constraints. It can be applied in many practical applications, including engineering, during the design process. The design time can be further reduced by the application of automated optimization methods. Since the required resource and desired benefit can be translated to a function of variables, optimization can be viewed as the process of finding the variable values to reach the function maxima or minima. A Multiple Objective Optimization (MOO) problem is when there is more than one desired function that needs to be minimized concurrently. In MOO, Pareto Solutions are defined as the set of solutions that are not worse than any single solution of all objective functions simultaneously. In other words, MOO is a process of applying algorithms to find Pareto solutions to a certain problem. Using Tradespace analysis, we can further identify the optimal Pareto Solution with the highest utility at a fixed cost. The combination of MOO and tradespace analysis can evaluate hundreds of designs simultaneously to select the optimal one. Mechanical system design is the process of devising a procedure to accomplish the given task, for which a design engineer's role is to optimize resource consumption. With recent advancements in multi-functional systems, the complexity of machines has been increasing. This presents a great challenge for design engineers, who must contend with optimizing systems with several functions in tandem. It is thus essential to develop methods that can simplify the design process. Tower clocks, as a classical type of machine, were extensively used for public time display during the period when watches and home clocks iii were rare. These mechanical movements once played essential roles in society and industry. They could be found at churches, courthouses, and universities/schools to visually and auditorily record the passage of time for residents and students. They were also used to regulate railroad schedules and workforce hours for the emerging industrial sector. Although mainly used for decorative purposes today, the components of such movement, including the assembled gears, escapement, and pendulum with weight drive, provide insight into optimization and tradespace analysis problems. In this research, computational methods plus experimental observations were used to investigate the optimal designs of the E. Howard Clock Model 00 - a movement was manufactured by E. Howard Clock Company. First, A computer-aided-design (CAD) model of this movement was created using the SolidWorks® software package to illustrate the working principle of the pendulum clock and facilitate engineering optimization studies. Next, the mathematical model of this clock was developed and simulated to explore the operation behaviors and conversion of potential-to-kinetic energy. The experimental process to validate this model was also described in detail. After that, A Single Objective Optimization (SOO) algorithm (i.e., simulated annealing) was applied to the model to optimize the pendulum subsystem for accuracy, quality factor, and mass. Numerical results show the desired quality factor can be achieved by varying the pendulum length and bob radius/thickness. Compared to the original, the optimized design added 15% to the mass of the pendulum while maintaining the clock's accuracy. Tradeoffs between quality factor, pendulum properties, and period were investigated and discussed with representative experimental and computational results. Lastly, two Multiple Objective Optimization iv (MOO) approaches (i.e., Multi-objective Genetic Algorithm (MOGA-II) and Multiobjective Simulated Annealing (MOSA) were applied to the developed mathematic model. The optimal movement designs in terms of pendulum mass and time accuracy were further explored for a range of clock periods. Numerical results demonstrated a 0.7% increase in the quality factor and a 0.56% reduction in the mass while maintaining the designed period by modifying the above-mentioned pendulum's parameters. More importantly, these changes can provide material cost savings in a mass production scenario. Overall, this study highlighted the optimization design engineers have considered for decades which can now be visualized using computer tools for greater insight. This methodology has the potential to be applied in the designing of other complex systems as well.

Surface texturing is an effective way to reduce the adhesion and friction between two contacting surfaces by reducing the real area of contact between them, providing a potential solution for adhesion and friction-induced failures, for example, failures in micro-/nano-electromechanical systems (MEMS/NEMS). Surface texturing is also essential to the realization of functional surfaces such as superhydrophobic/philic and icephobic surfaces. However, textures are prone to deformation due to being subjected to higher contact pressures. The advancement of 3D nanoprinting by two-photon lithography (TPL), combined with the ability to make an in-situ observation of the interplay between the forces and the sliding surfaces at a single micro/nano structure level, provides opportunities for gaining a better understanding of textured surfaces, enabling better engineering of novel 3D micro-/nano-textures. Using TPL, textures were fabricated with precise shape, dimension, and position control for a systematic investigation of the effects of texture three-dimensionality by comparing 3D textures (truncated cones) to 2.5D textures (cylinders and rods). Moreover, macro- and micro-scale tribological testing and in-situ monitoring of the experiments using a digital microscope at the macro-scale and a scanning electron microscope (SEM) at the micro-scale provided unique insights into the multi-scale tribological properties of the textured surfaces by real-time monitoring of the interplay between the forces and the sliding surfaces down to a single micro-scale structure level. Macro-scale tests showed that cones not only had a lower coefficient of friction due to their reduced area of contact but also slide more smoothly and are more durable. Micro-scale tests shed new light on the relationship between friction and microstructure deformation by in-situ SEM monitoring of texture-counterface interactions. Micro/nano-hierarchical textures play essential roles in realizing the functionalities of surfaces. Their friction and deformation behavior at the nanoscale are relatively unknown. Targeted friction testing of individual micro/nano-hierarchical structures (micropillars covered with nanohairs) inside an SEM, helped show the coupling between micropillar deformation and nanohair height. It was also found that the bending of long nanohairs can provide assistive sliding forces and that buckling of the long nanohairs resulted in the development of lateral forces under only normal loading and before sliding started. Varying the tapering angle of the micropillars and the length of the nanohairs enabled control over the effective stiffness of the micro/nano-hierarchical structures. It was revealed that changes in the structure stiffness by varying the tapering angle affected the onset of sliding motion, friction force, and coupling between the deformation of the nanohair and the micropillar. Additionally, it was shown the nanohair buckling was delayed as a result of increasing the stiffness of the micropillar underneath the nanohair. Finally, atomic layer deposition (ALD) of ZnO on micro/nano-hierarchical structures was done and in-situ SEM mechanical and tribological tests were carried out to shed light on the effect of different ZnO thicknesses and polydopamine (PDA) underlayer. PDA showed improvements in the performance of structures at the lowest ZnO thickness (10 nm), while as the thickness increased to 30 nm, whether or not PDA underlayers existed, coatings exhibited increased failure and cracking.

When a solid substrate is withdrawn from a liquid bath a thin coating is deposited whose thickness is given by the Landau-Levich-Derjaguin (LLD) law. We perform an experimental study of dip coating of particle suspensions showing that particles of a given size can become entrained in the meniscus by the competition between viscous and surface tension forces. This is called capillary filtration and can be used as a tunable dynamic filter. For single particle suspensions, filtration can be in terms of either clumps or single particles, with the relevant entrainment points depending upon the rheology of the working fluid, either Newtonian silicone oil or non-Newtonian shear-thinning xanthan gum solution. For bi-disperse suspensions, we show there is a range of capillary number where the smaller particle is entrained in the film and the larger particle remains in the fluid bath, thus filtering the particles by size.

Abstract The understanding of microstructural damage mechanisms is the foundation of better understanding existing materials and future material development. There are significant challenges to measuring these damage mechanisms in-situ as continuous observation of the state of the microstructure is difficult or impossible for many experimental setups. This thesis presents a method for measuring grain boundary sliding (GBS) and local strain concentrations in-situ via a Heaviside function based algorithm. GBS is the shearing of two grains along their shared grain boundary and is a common damage mechanism in creep which presents as a discontinuity that can be measured with a Heaviside function. Multi-principal element alloys (MPEAs) have potential to be the future of alloy design as there are limitless compositions possible which could exceed the capabilities of conventional alloys. MPEAs are a new class of alloys with a loose definition that they are made of multiple principal elements, generally with ≥5 at% of each principal element. Ti80(AlCrNb)20 is the alloy used in this thesis due to its potential as a lightweight MPEA (LMPEA) and its solid solution β titanium phase composition which is well suited for strong creep resistance. High resolution digital image correlation (HRDIC) enabled creep tests are performed to measure the GBS and other localized slip of Ti80(AlCrNb)20. The GBS analysis code developed in this thesis utilizes the HRDIC creep data captured via optical microscope to measure GBS. Microstructural maps from electron backscatter diffraction (EBSD) are aligned with HRDIC creep imaging using fiducial markers to identify grain boundary locations, and the discontinuity across the grain boundary due to GBS was measured via a Heaviside function based algorithm. Measurement of GBS in-situ using an optical microscope is an advancement over existing methods by providing continuous data. This method also requires significantly less scanning electron microscope (SEM) time and access as the only SEM usage is an initial EBSD scan to identify the microstructure. Current methods utilize multiple or continuous SEM scans that can require the creep test to be stopped temporarily. As creep testing is typically at elevated temperatures, this induces thermic cycling in the sample which prevents a pure creep test. Being able to run a pure creep test without thermic cycling or interruptions while taking continuous measurements will improve the data analysis capabilities and informativity of future testing on microstructure damage.

The field of additive manufacturing (AM) has rapidly developed and expanded over the past decade. The geometric freedom provided by the process is unparalleled by any conventional means of manufacturing, opening the door to truly abstract design. Currently, the further adoption of AM practices is limited by a key issue: tensile residual stress. Tensile residual stresses are detrimental to part performance as they significantly reduce a material’s strength, fatigue life, corrosion resistance, and reliability, and are unfortunately an intrinsic quality of AM parts. AM parts are built by rapidly melting and re-solidifying hundreds of thin layers to gradually create the final product. This layer-by-layer approach exposes AM parts to extreme thermal gradients during their production, forcing the bulk into a state of tension. To mitigate this, a solution of hybrid AM has been proposed. Hybrid AM utilizes intermittent secondary processes to modify the residual stress state of parts. This research focused on the viability of using laser shock peening (LSP) treatments as the secondary process in hybrid AM as LSP can create high magnitude compressive residual stresses (CRSs) that extend deeply into the bulk. There exist significant barriers to the coupling of these two processes. Water plays an important role in LSP but is devastating to the AM process. The lack in understanding of the effects that thermal loads associated with the deposition of additional layers have on the modified residual stress states of hybrid AM parts is problematic as well. There were two objectives of this work: (1) assess the feasibility of nonconventional LSP treatments for hybrid AM applications and (2) quantify the losses in magnitude and depth of CRSs due to additional layer deposition (thermal cancellation). Results indicated that water is too critical to exclude from LSP processes for hybrid AM. Two distinct regions of thermal effects were identified for hybrid AM parts. In total, residual stress redistribution reached 550 µm beyond the LSP treated layer, however the number of additionally deposited layers affected only the first 160 µm. This work provides the first quantification of the response that hybrid AM parts have to thermal loads. Advisor: Michael P. Sealy

Bistable carbon fiber composites, whose bistability arises from having asymmetric fiber layouts in different layers, have shown immense potential for use in shape morphing and adaptive structure applications. While many studies in this field focus on these composite laminates’ external shapes at the two stable states, their snap-through behavior of shifting from one stable shape to the other remains a critical aspect to be investigated in complete detail. Moreover, symmetric loading conditions have been extensively studied based on the classical lamination theory, but the asymmetric loading conditions received far less attention. Therefore, this study examines an asymmetric, localized point load on a [0°/90°] bistable laminate and its complex transient deformation during the snap-through. Finite element simulation and experiment results reveal three uniquely different snap-through behaviors — two-step snap, one-step snap, and no snap — depending on the point load location. The localized initiation and propagation of a “curvature inversion zone,” calculated from finite element and digital image correlation results, are directly related to these snap-through characteristics. This study also explored the feasibility of using an extended analytical model of classical lamination theory. The study first establishes the working of an analytical model in MATLAB for two-ply laminates with user-defined geometrical and material properties. This established model is later used to qualitatively reproduce the findings for the asymmetric loading case by introducing a novel way of constraining the equations. The model compares three polynomial functions of different orders to approximate the out-of-plane laminate displacement field. This study’s results can offer valuable insights into the fundamental mechanics of snap-through behaviors and the actuation designs for the bistable composites for different loading scenarios.

The air exchange between two floors of a building has an impact on thermal comfort. The present research attempts to quantify this impact and identify the contributing factors disrupting the thermal comfort on and around stairs. Various heating and cooling scenarios were analyzed, using CFD modeling, in a simple two-story building separated by a single staircase. The research examines a single building layout with a fixed inlet and outlet configuration. In addition, the study investigated the short-term impact on thermal comfort. As a result, the duration of the simulations varies from two and half minutes to ten minutes, consistent with the typical cycling of unitary air-conditioning equipment. The main parameters of interest were the air temperature, air velocity, and the thermal comfort parameter Predicted Mean Vote (PMV). In both cooling and heating scenarios, the influence of the upper room and staircase had a negative impact on both the thermal comfort and energy usage in the building. The largest impact was seen during the heating scenario simulations. During the ten-minute heating simulations, the main area of the building saw a 2.12-2.79 °C drop in air temperature, along with PMV values of below -1.7.

Continuum Robots are bio-inspired structures that mimic the motion of snakes, elephant trunks, octopus tentacles, etc. With good design, these robots can be naturally compliant and miniaturizable, which makes Continuum Robots ideal for traversing narrow complex environments. Their flexible design, however, prevents us from using traditional methods for controlling and estimating loading on rigid link robots. In the first thrust of this research, we provided a novel stiffness control law that alters the behavior of an end effector during contact. This controller is applicable to any continuum robot where a method for sensing or estimating tip forces and pose exists. Using an integral approach, the control law is be capable of dictating different stiffness in multiple directions, both increase and decrease the stiffness of the end effector, as well as handle contacts with both rigid and compliant environments. An example of implementation is provided for a parallel continuum robot. In the second thrust of this research, we introduce a general 3D load estimation approach that can be applied to any continuum robot with an existing kinetostatic model that maps actuation and externally applied loads into a robot pose. This method uses numerical minimization to predict a load distribution that will fit a robot model predicted shape to a directly sensed shape. Validation was preformed on a passive steel rod, a single degree of freedom tendon robot, and a two degree of freedom tendon robot.

Peridynamic material correspondence model is able to incorporate material constitutive models directly from classical continuum mechanics theory. However, conventional correspondence model faces two major technical issues for its application to practical problems. The first is the material instability, which results severe oscillations in the predicted displacement fields. The second issue is the length scale effects of materials mechanical behavior at low length scales. This research journey mainly consists of three stages. The first two stages of this research journey focus on the development of the bond-associated peridynamic material correspondence model to inherently remove the material instability. The last stage focuses the development of the higher-order peridynamic material correspondence model to capture length scale effect at low length scale. In this paper, a reformulation of the bond-associated correspondence model was proposed. Detailed studies on the wave dispersion relations, static deformation problems support that the reformulation significantly improves the material stability of the original bond-associated correspondence model. In addition, A numerical study of the higher-order peridynamic material correspondence model is conducted to verify the material stability and show the capability of the higher-order formulation in capturing the length scale effect in materials accurately.

A study was conducted to investigate the low temperature combustion (LTC) regions of aerospace F24 and ULSD in the static setting of a CVCC and the dynamic setting of a CRDI research engine. This research is conducted to reduce in-cylinder emissions by understanding and implementing a technique to achieve an extended LTC. Emissions data for this study were collected during the operation of the CRDI research engine with a MKS 2030 FTIR and an AVL Microsoot 483. The parameters researched within the static setting of the CVCC included the determinations of the cool flames and NTC regions within the LTHR region. Investigations using the CRDI research engine included eight trials. These trials consisted of a baseline for each directly injected fuel, a trial with 0.24 bar of boosted intake air, a trial with 20% of recirculated exhaust gas, and finally a trial with PFI injections of a low reactivity bio-alcohol, n-butanol, during the intake stroke to cool the combustion chamber. PFI parameters also include additions of 0.24 bar of boost, 10% recirculated exhaust gas, and a pilot direct injection 60° BTDC. The low reactivity PFI fuel is utilized to facilitate an extended LTC. The CVCC results concluded with F24 and ULSD obtaining equal values for peak pressure and peak temperature, with the values of 42.3 bar and 1837.5 K, respectively. F24 maintained a longer period of cool flame formations and overall LTHR with values of 1.6ms and 1.96ms, respectively. The mass fraction burned results of ULSD within both the CVCC and dynamic setting of the CRDI research engine yielded better efficiency than F24 in nearly all trials. The trials implementing a LTC method within the CRDI research engine, was found to extend the low temperature combustion region of both F24 and ULSD. PFI trials reduced ignition delay by approx. 3 CAD and massively reduced soot emissions of ULSD and F24 by 9.9 and 2.5 times, respectively, compared to ULSD at baseline parameters. This reduction of soot was the greatest in-cylinder emissions reduction in the entire study. ULSD performed better overall in gaseous emissions outputs.

Wind loads cannot be avoided during a natural disaster such as a hurricane and could affect the strength and stability of vertical pressure vessels during exposure. Vertical pressure vessels cater to large wind loads; therefore, it is imperative to study the effect of additional loading on the structures. In this study, three pressure vessels with volumes of 50 CuFt, 200 CuFt, and 1100 CuFt, supported by three equidistant load cells under their legs are individually analyzed to determine von mises stress to estimate yield failure criteria. Two load rating criteria, maximum load capacity and water-filled condition (critical condition) are utilized for static analysis to determine the strength of load cells and to calculate safety factors. Solidworks and Ansys workbench 19.1 software were utilized to generate and compare the results of each analysis. The analysis shows that the load cells are sustainable for both criteria with the factor of safety of 1.95, 1.22, and 1.30 for the critical condition for the 50 CuFt, 200 CuFt, and 1100 CuFt pressure vessels respectively. Under normal conditions, the weight of the pressure vessel is unevenly distributed as it has been observed that there are greater loads (and deformations) in the two load cells approximately under the manway apparatus. This is extra important in the 50 CuFt vessel because the centerline of the manway does not lie on the angle bisector of the two nearest load cells. Once a constant, steady wind load is introduced, the vessel will not topple as the attached load cell assembly underneath is anchored to concrete. The only movement possible is vertical deflection in the load cell resulting in greater uneven load distribution on the load cells, this scenario leads to inaccurate measurement when the load exerted on the load cell exceeds the maximum load capacity. Varying steady wind speed conditions with a maximum wind velocity of 120 mph are calculated to determine the stability of the system. The empty pressure vessel condition under wind loading resulted in the stress at one load cell to be zero at approximately 71 mph, 83mph, and 88mph for 50 CuFt, 200 CuFt, and 1100 CuFt respectively. Further, stability and the stiffness of the pressure vessels with load cells were analyzed using dynamic analysis to determine the fundamental natural frequencies of the vessels and compared to the vortex shedding frequencies calculated at various wind velocities to investigate the potential of resonance when the vessel is subjected to steady wind conditions. Results indicate that the 50 CuFt model can be subjected to resonance conditions at an approximately constant velocity as low as 25 mph.

The ever-growing pressure of reducing the adverse impact of transportation systems on environment has pushed industries towards fuel-efficient and sustainable solutions. While several approaches have been used to improve fuel efficiency, the light-weighting of structural components has proven broadly effective. In this regard, reinforced thermoplastic composites (RTPC), owing to their high recyclability, higher impact strength and fast cycle times, have become competitive candidates at an industrial scale. However, to implement RTPC toward large scale structural applications several challenges pertaining to material design and manufacturing effects need to be addressed. To this end, a computational study is carried out to address three key challenges that limit the design and development of RTPC structures: (a) enhancing filler/matrix bonding strength at the microscale level, (b) understanding the effect of interfacial microstructure on the macroscale material behavior and (c) understanding the effect of manufacturing process on the mechanical performance at the structural level. First, the interface bonding strength between the non-polar/non-reactive polymer matrix and filler surface is generally poor and hence, may fail locally at these interfaces upon external loading. Many interfacial strengthening studies in the past lack precision and control in obtaining higher interfacial strength. The concept of controlled mechanical interlocking between fiber and matrix interface is explored computationally on an E-glass/polypropylene (PP) composite material system. To understand the micromechanics under dynamic and impact loads, the interfacial behavior at various strain rates is studied. A finite element parametric model is setup where different surface morphologies of E-glass/PP are investigated. The strength calculations consider both material failure and detachment of the matrix material from the anchoring sites. Second, to incorporate the effect of interfacial microstructure into macroscale material behavior, a continuum constitutive model is developed. The bulk material response at macroscale is evaluated by using a unit cell homogenization method. The mechanical behavior of the composite material at macroscale is modeled using a rheological three network viscoplastic (TNV) model. Numerical biaxial and shear tests are conducted for several geometric configurations of the fiber/matrix interface. The numerical data generated is used further to develop the TNV material model. The developed material model is validated for a laminated beam structure. The study elucidates the impact of various interface design variables on the material model parameters by establishing analytical relationships. Third, to investigate the effect of manufacturing process on the mechanical performance a manufacturing to response (MTR) pathway is established. This pathway was developed collabora-tively and consists of both computational methods to simulate and integrate all relevant manufac-turing process steps as well as experimental methods to validate each step from coupon to structural level. The composite material system selected for this study is AS4/Nylon-6 (PA6) with woven layup. The thermoforming process simulations are carried out using anistropic hyperelastic material model and the thickness variation, fiber orientations and residual stresses are captured from the analysis. Residual stresses developed in the formed structure during quench cooling from the elevated temperature are predicted by implementation of classical laminate theory (CLT). The static and dynamic performance for the thermoformed structure is evaluated and the effects of thermo-forming process are compared numerically, for the cases with and without inclusion of process effects. Lastly, the MTR pathway is implemented to perform a design optimization study of an ultra-lightweight fiber RTPC door of a vehicle. The objective of the optimization was to reduce the weight of an existing door of an OEM’s mid-size SUV by 42.5% while also satisfying various static and dynamic structural load requirements. Several static and dynamic studies are carried out at structural length scale. The door stiffness optimization is first carried out for various linear static load cases. This is followed by evaluation of crashworthiness performance under three non-linear load cases: (a) quasi-static pole test (FMVSS 214S) (b) full pole test (FMVSS 214) and (c) moving deformable barrier test (IIHS SI MDB).

The reliability of electronic devices is dependent upon the conditions to which they are subject. Temperature variations coupled with differences in thermal expansion between bonded materials results in thermomechanical stresses to build up, which can instigate failure in the interconnects or other critical regions. With the move towards electrification in the automotive industry, there is the increasingly important consideration of powertrain electronics reliability, the pertinent conditions being governed by the drive cycle or mission profile of the vehicle. The mission profile determines the power dissipated by the electronic devices, which determines the peak and mean temperature, temperature swing and the resultant stress range, as well the effective thermal cycling frequency. This thesis, submitted in partial completion of the requirements for the Master of Science in Mechanical Engineering, herein investigates the relationship between predicted lifetime of electronic components in the drivetrain of an electric or hybrid electric vehicle and the mission profile it is operated at. The primary datasets are taken from the Environment Protection Agency (EPA) fuel economy test cycles, which lists various standard mission profiles for different driving conditions. The thermal profiles resulting from each mission profile are used to extract damage parameters and used to estimate time to failure. As the lifetimes are dependent on the thermal transients, ways are explored to minimize the temperature swings. One such way is to use phase change materials as thermal reservoirs that can be very effective thermal management option under the right conditions. Phase change materials absorb thermal energy as latent heat, which allows them to absorb a very large amount of heat per unit volume, but they are limited by low thermal conduction and long regeneration times. An affordable and widely available phase change material, paraffin, is used as a case study. A model is developed to mimic a widely available commercial power module, and detailed parametric studies are done to understand the effectiveness and best practices in using paraffin as a phase change material in cooling. The results show that PCMs hold great potential in automotive electronics cooling, but there is a delicate trade-off between the latent heat, thermal conductivity, and dissipated power that can be handled. As coefficient of heat transfer of secondary cooling mechanism gets larger, using PCMs become less advantageous.