As technology increases in capability, its purposes can become multifaceted, meaning it must accomplish multiple requirements as opposed to just one. An example of said technology could be high speed airplane wings, which must be strong enough to withstand high loads, light enough to enable the aircraft to fly, and have enough thermal conductivity to withstand high temperatures. Two objectives in particular, topology and sensor deployment, are important for designing structures such as robots which need accurate sensor readings, known as observability. In an attempt to display how these two dissimilar objectives coincide with each other, a project was created around the idea of finding an optimum balance of both. This supposed state would allow the structure not only to remain strong and light but also to be monitored via sensors with a high degree of accuracy. The main focus of the project was to compare levels of observability of two known factors of input estimation error. The first system involves a structure that has been topologically optimized for compliance minimization, which increases input estimation error. The second system produces structures with random placements of sensors within the structure, which, as the average distance from load to sensor increases, induces input estimation error. These two changes in observability were compared to see which had a more direct effect. The main findings were that changes in topology had a much more direct effect over levels of observability than changes in sensor placement. Results also show that theoretical input estimation time is significantly reduced when compared to previous systems.

The stability of nanocrystalline microstructural features allows structural materials to be synthesized and tested in ways that have heretofore been pursued only on a limited basis, especially under dynamic loading combined with temperature effects. Thus, a recently developed, stable nanocrystalline alloy is analyzed here for quasi-static (<100 s-1) and dynamic loading (103 to 104 s-1) under uniaxial compression and tension at multiple temperatures ranging from 298-1073 K. After mechanical tests, microstructures are analyzed and possible deformation mechanisms are proposed. Following this, strain and strain rate history effects on mechanical behavior are analyzed using a combination of quasi-static and dynamic strain rate Bauschinger testing. The stable nanocrystalline material is found to exhibit limited flow stress increase with increasing strain rate as compared to that of both pure, coarse grained and nanocrystalline Cu. Further, the material microstructural features, which includes Ta nano-dispersions, is seen to pin dislocation at quasi-static strain rates, but the deformation becomes dominated by twin nucleation at high strain rates. These twins are pinned from further growth past nucleation by the Ta nano-dispersions. Testing of thermal and load history effects on the mechanical behavior reveals that when thermal energy is increased beyond 200 °C, an upturn in flow stress is present at strain rates below 104 s-1. However, in this study, this simple assumption, established 50-years ago, is shown to break-down when the average grain size and microstructural length-scale is decreased and stabilized below 100nm. This divergent strain-rate behavior is attributed to a unique microstructure that alters slip-processes and their interactions with phonons; thus enabling materials response with a constant flow-stress even at extreme conditions. Hence, the present study provides a pathway for designing and synthesizing a new-level of tough and high-energy absorbing materials.

Robotic joints can be either powered or passive. This work will discuss the creation of a passive and a powered joint system as well as the combination system being both powered and passive along with its benefits. A novel approach of analysis and control of the combination system is presented.

A passive and a powered ankle joint system is developed and fit to the field of prosthetics, specifically ankle joint replacement for able bodied gait. The general 1 DOF robotic joint designs are examined and the results from testing are discussed. Achievements in this area include the able bodied gait like behavior of passive systems for slow walking speeds. For higher walking speeds the powered ankle system is capable of adding the necessary energy to propel the user forward and remain similar to able bodied gait, effectively replacing the calf muscle. While running has not fully been achieved through past powered ankle devices the full power necessary is reached in this work for running and sprinting while achieving 4x’s power amplification through the powered ankle mechanism.

A theoretical approach to robotic joints is then analyzed in order to combine the advantages of both passive and powered systems. Energy methods are shown to provide a correct behavioral analysis of any robotic joint system. Manipulation of the energy curves and mechanism coupler curves allows real time joint behavioral adjustment. Such a powered joint can be adjusted to passively achieve desired behavior for different speeds and environmental needs. The effects on joint moment and stiffness from adjusting one type of mechanism is presented.

There are many computer aided engineering tools and software used by aerospace engineers to design and predict specific parameters of an airplane. These tools help a design engineer predict and calculate such parameters such as lift, drag, pitching moment, takeoff range, maximum takeoff weight, maximum flight range and much more. However, there are very limited ways to predict and calculate the minimum control speeds of an airplane in engine inoperative flight. There are simple solutions, as well as complicated solutions, yet there is neither standard technique nor consistency throughout the aerospace industry. To further complicate this subject, airplane designers have the option of using an Automatic Thrust Control System (ATCS), which directly alters the minimum control speeds of an airplane.

This work addresses this issue with a tool used to predict and calculate the Minimum Control Speed on the Ground (VMCG) as well as the Minimum Control Airspeed (VMCA) of any existing or design-stage airplane. With simple line art of an airplane, a program called VORLAX is used to generate an aerodynamic database used to calculate the stability derivatives of an airplane. Using another program called Numerical Propulsion System Simulation (NPSS), a propulsion database is generated to use with the aerodynamic database to calculate both VMCG and VMCA.

This tool was tested using two airplanes, the Airbus A320 and the Lockheed Martin C130J-30 Super Hercules. The A320 does not use an Automatic Thrust Control System (ATCS), whereas the C130J-30 does use an ATCS. The tool was able to properly calculate and match known values of VMCG and VMCA for both of the airplanes. The fact that this tool was able to calculate the known values of VMCG and VMCA for both airplanes means that this tool would be able to predict the VMCG and VMCA of an airplane in the preliminary stages of design. This would allow design engineers the ability to use an Automatic Thrust Control System (ATCS) as part of the design of an airplane and still have the ability to predict the VMCG and VMCA of the airplane.

Origami and kirigami, the technique of generating three-dimensional (3D) structures from two-dimensional (2D) flat sheets, are now more and more involved in scientific and engineering fields. Therefore, the development of tools for their theoretical analysis becomes more and more important. Since much effort was paid on calculations based on pure mathematical consideration and only limited effort has been paid to include mechanical properties, the goal of my research is developing a method to analyze the mechanical behavior of origami and kirigami based structures. Mechanical characteristics, including nonlocal effect and fracture of the structures, as well as elasticity and plasticity of materials are studied. For calculation of relative simple structures and building of structures’ constitutive relations, analytical approaches were used. For more complex structures, finite element analysis (FEA), which is commonly applied as a numerical method for the analysis of solid structures, was utilized. The general study approach is not necessarily related to characteristic size of model. I believe the scale-independent method described here will pave a new way to understand the mechanical response of a variety of origami and kirigami based structures under given mechanical loading.

In-situ fatigue damage diagnosis and prognosis is a challenging problem for both metallic and composite materials and structures. There are various uncertainties arising from material properties, component geometries, measurement noise, feature extraction techniques, and modeling errors. It is essential to manage and incorporate these uncertainties in order to achieve accurate damage detection and remaining useful life (RUL) prediction.

The aim of this study is to develop an integrated fatigue damage diagnosis and prognosis framework for both metallic and composite materials. First, Lamb waves are used as the in-situ damage detection technique to interrogate the damaged structures. Both experimental and numerical analysis for the Lamb wave propagation within aluminum are conducted. The RUL of lap joints under variable and constant fatigue loading is predicted using the Bayesian updating by incorporating damage detection information and various sources of uncertainties. Following this, the effect of matrix cracking and delamination in composite laminates on the Lamb wave propagation is investigated and a generalized probabilistic delamination size and location detection framework using Bayesian imaging method (BIM) is proposed and validated using the composite fatigue testing data. The RUL of the open-hole specimen is predicted using the overall stiffness degradation under fatigue loading. Next, the adjoint method-based damage detection framework is proposed considering the physics of heat conduction or elastic wave propagation. Different from the classical wave propagation-based method, the received signal under pristine condition is not necessary for estimating the damage information. This method can be successfully used for arbitrary damage location and shape profiling for any materials with higher accuracy and resolution. Finally, some conclusions and future work are generated based on the current investigation.

All structures suffer wear and tear because of impact, excessive load, fatigue, corrosion, etc. in addition to inherent defects during their manufacturing processes and their exposure to various environmental effects. These structural degradations are often imperceptible, but they can severely affect the structural performance of a component, thereby severely decreasing its service life. Although previous studies of Structural Health Monitoring (SHM) have revealed extensive prior knowledge on the parts of SHM processes, such as the operational evaluation, data processing, and feature extraction, few studies have been conducted from a systematical perspective, the statistical model development.

The first part of this dissertation, the characteristics of inverse scattering problems, such as ill-posedness and nonlinearity, reviews ultrasonic guided wave-based structural health monitoring problems. The distinctive features and the selection of the domain analysis are investigated by analytically searching the conditions of the uniqueness solutions for ill-posedness and are validated experimentally.

Based on the distinctive features, a novel wave packet tracing (WPT) method for damage localization and size quantification is presented. This method involves creating time-space representations of the guided Lamb waves (GLWs), collected at a series of locations, with a spatially dense distribution along paths at pre-selected angles with respect to the direction, normal to the direction of wave propagation. The fringe patterns due to wave dispersion, which depends on the phase velocity, are selected as the primary features that carry information, regarding the wave propagation and scattering.

The following part of this dissertation presents a novel damage-localization framework, using a fully automated process. In order to construct the statistical model for autonomous damage localization deep-learning techniques, such as restricted Boltzmann machine and deep belief network, are trained and utilized to interpret nonlinear far-field wave patterns.

Next, a novel bridge scour estimation approach that comprises advantages of both empirical and data-driven models is developed. Two field datasets from the literature are used, and a Support Vector Machine (SVM), a machine-learning algorithm, is used to fuse the field data samples and classify the data with physical phenomena. The Fast Non-dominated Sorting Genetic Algorithm (NSGA-II) is evaluated on the model performance objective functions to search for Pareto optimal fronts.

Hydrogen embrittlement (HE) is a phenomenon that affects both the physical and chemical properties of several intrinsically ductile metals. Consequently, understanding the mechanisms behind HE has been of particular interest in both experimental and modeling research. Discrepancies between experimental observations and modeling results have led to various proposals for HE mechanisms. Therefore, to gain insights into HE mechanisms in iron, this dissertation aims to investigate several key issues involving HE such as: a) the incipient crack tip events; b) the cohesive strength of grain boundaries (GBs); c) the dislocation-GB interactions and d) the dislocation mobility.

The crack tip, which presents a preferential trap site for hydrogen segregation, was examined using atomistic methods and the continuum based Rice-Thompson criterion as sufficient concentration of hydrogen can alter the crack tip deformation mechanism. Results suggest that there is a plausible co-existence of the adsorption induced dislocation emission and hydrogen enhanced decohesion mechanisms. In the case of GB-hydrogen interaction, we observed that the segregation of hydrogen along the interface leads to a reduction in cohesive strength resulting in intergranular failure. A methodology was further developed to quantify the role of the GB structure on this behavior.

GBs play a fundamental role in determining the strengthening mechanisms acting as an impediment to the dislocation motion; however, the presence of an unsurmountable barrier for a dislocation can generate slip localization that could further lead to intergranular crack initiation. It was found that the presence of hydrogen increases the strain energy stored within the GB which could lead to a transition in failure mode. Finally, in the case of body centered cubic metals, understanding the complex screw dislocation motion is critical to the development of an accurate continuum description of the plastic behavior. Further, the presence of hydrogen has been shown to drastically alter the plastic deformation, but the precise role of hydrogen is still unclear. Thus, the role of hydrogen on the dislocation mobility was examined using density functional theory and atomistic simulations. Overall, this dissertation provides a novel atomic-scale understanding of the HE mechanism and development of multiscale tools for future endeavors.

Fracture phenomena have been extensively studied in the last several decades. Continuum mechanics-based approaches, such as finite element methods and extended finite element methods, are widely used for fracture simulation. One well-known issue of these approaches is the stress singularity resulted from the spatial discontinuity at the crack tip/front. The requirement of guiding criteria for various cracking behaviors, such as initiation, propagation, and branching, also poses some challenges. Comparing to the continuum based formulation, the discrete approaches, such as lattice spring method, discrete element method, and peridynamics, have certain advantages when modeling various fracture problems due to their intrinsic characteristics in modeling discontinuities.

A novel, alternative, and systematic framework based on a nonlocal lattice particle model is proposed in this study. The uniqueness of the proposed model is the inclusion of both pair-wise local and multi-body nonlocal potentials in the formulation. First, the basic ideas of the proposed framework for 2D isotropic solid are presented. Derivations for triangular and square lattice structure are discussed in detail. Both mechanical deformation and fracture process are simulated and model verification and validation are performed with existing analytical solutions and experimental observations. Following this, the extension to general 3D isotropic solids based on the proposed local and nonlocal potentials is given. Three cubic lattice structures are discussed in detail. Failure predictions using the 3D simulation are compared with experimental testing results and very good agreement is observed. Next, a lattice rotation scheme is proposed to account for the material orientation in modeling anisotropic solids. The consistency and difference compared to the classical material tangent stiffness transformation method are discussed in detail. The implicit and explicit solution methods for the proposed lattice particle model are also discussed. Finally, some conclusions and discussions based on the current study are drawn at the end.