A methodology for the optimum design under uncertainty of sensor arrays for structural health monitoring systems is developed. Stochastic finite element analysis, damage detection algorithms, and nonlinear optimization are integrated for sensor placement optimization under uncertainty. The stochastic finite element analysis incorporates uncertainties and spatial variability in dynamic mechanical loads, material properties, and structural geometry through random process/field techniques. Damage detection algorithms consist of feature extraction, feature selection, and state classification and aid in the prediction of sensor layout performance via probabilistic performance measures. The basic probabilistic finite element models as well as the sensor layout performance prediction method are assessed for validation prior to their utilization in sensor placement optimization. Several validation metrics are investigated for comparison of predicted natural frequencies, mode shapes, and probabilistic performance measures to corresponding experimental observations. The structural health monitoring sensors are required to be placed optimally in order to detect with high probability and reliability any structural damage before it becomes critical. A global-local approach that combines quadratic local approximations of the objective function with a branch and fit technique is used to optimize several probabilistic performance measures and multi-objective performance functions. The proposed methodology is illustrated for application on a prototype component of a thermal protection system.

The overall objective of this study is to advance highway bridge inspection procedures from current subjective methods to a more quantitative, objective framework for assessment and inspection within a management program. Through the integration of quantitative models, data, and inspection techniques, these advancements help to improve both the understanding and predictive capability associated with long-term bridge performance. A methodology for selection of a sample of bridges for study is developed based on latent class cluster analysis and considers both physical and environmental parameters. Current assessment procedures are augmented to include quantitative data and major forms of deterioration are identified along with available practical physically-based models for their estimation. Finally, inspection planning maps are developed to provide guidance on the implementation and management of an in-depth inspection program.

Many natural and technological processes involve phenomena dominated by interfacial mechanics occurring within the overlapping region between several solid/fluid phases. Interfacial phenomena typically involve interplay of complex processes and the exact mechanics involving such processes is still not fully understood. As advanced materials and structures are being investigated to better optimize weight, cost and strength, it is imperative that material interfaces be better characterized in terms of their properties, thereby increasing reliability in usage. Reliability can be increased either by building better structures or by manufacturing better materials. In this light, a method has been investigated to remove stress singularity at bi-material corners and thereafter applied to explain the reduction in the tensile strength of bonded interfaces after the incorporation of graphitic carbon nanofibers in the epoxy matrix. This approach is expected to produce more reliable material strength data. Simultaneously, in the context of a different bi-material problem (thin film-substrate), the fracture mechanics approach was utilized to propose a novel method for measurement of interfacial fracture toughness. In the final part of the study, the influence of non-uniform stress distributions at material interfaces was investigated to understand interfacial failure in brittle materials.

The major findings of this thesis are that free surfaces have enabled nanowires to show many unusual behavior and mechanical properties at nanoscale, including shape memory and pseudoelastic behavior, surface elasticity in hollow nanowires, and coupled effect from cross sectional geometry and side surface orientation, all of which could not be observed at macroscopic scale. <p> This thesis has shown that surface stresses allow the reversibility between higher energy <100>/{100} and lower energy <110>/{111} configurations in metal nanowires and thus lead to the shape memory behavior in nanowires. It has also shown that because the elastic properties of surfaces are substantially different from those of the bulk at nanoscale, and because hollow nanowires have higher surface to volume ratio compared to solid wires, the hollowness can be used to improve the elastic properties of nanostructures. Finally, the thesis has demonstrated for the first time that cross sectional geometry and transverse surface orientation have a first-order effect on the mechanical properties of metal nanowires.

This dissertation proposes a methodology for optimizing inspection schedules of large heterogeneous populations, by combining clustering analysis, reliability analysis, and nonlinear optimization techniques. Due to limitation of resources, only a small proportion of the population can be inspected. The proposed methodology first identifies the critical samples with the highest likelihood of failing through clustering analysis; then those critical samples inspection schedules are optimized with the purpose of maintaining or exceeding the minimum target reliability level while minimizing inspection costs. The clustering analysis is able to handle both numeric and nominal features. A detailed illustrative example is presented to demonstrate the methods practical application to inspecting railroad wheels. A general methodology for rolling contact fatigue life prediction under a stochastic loading process is used to calculate the reliability of the critical samples. Then a reliability-based inspection schedule optimization technique is developed for the critical samples, based on various costs and scenarios. The return on investment is also calculated for the proposed methodology.

Moisture is a major source of degradation of hot mix asphalt (HMA) used in highway pavements. Moisture damage occurs when there is a loss of bond either at the asphalt-aggregate interface or within the asphalt mastic. The presence of moisture may strip asphalt binder from the aggregate (adhesive failure) and/or weaken the asphalt mastic (cohesive failure) resulting in pavement cracking and deformation. Bond strength is determined via a direct tensile test utilizing the Pneumatic Adhesion Tensile Testing Instrument (PATTI). The usefulness of the direct tensile test is determined for asphalt binders and mastics and the influence of moisture on tensile strength of asphalt binders and mastics and between asphalt and aggregate pairs is evaluated. The results of the experiments verify that moisture degrades the bond strength of asphalt binders, mastics, and between asphalt and aggregate. <p> Results from the direct tensile test experiments are then linked to moisture diffusion simulations and bond strength degradation as a function of the amount of moisture at the asphalt-aggregate interface is established. Based on this relationship, the amount of damage that occurs over time in regards to the amount of moisture at the interface is quantified. <p> Finally, limit-state based reliability analysis concepts are introduced to formulate a performance criterion for moisture-induced damage of asphalt-aggregate systems. The moisture-induced damage parameter is an integral part of a larger framework developed for predicting moisture-induced damage in asphalt mixtures.

Analytical and experimental approaches to determine mixed-mode fatigue crack growth threshold and growth rates are not well established and remain an active research topic. This dissertation compared the existing methods and developed some alternatives to address the problem with less assumptions and broader applicability. The derived models are based on a characteristic plane methodology and extend the stress/strain- based approach to fracture mechanics-based approach. Both shear-dominated failure and tension-dominated failure can be analyzed. The orientation of the characteristic plane changes according to the mode mixity, the ratio of shear fatigue limit over tensile fatigue limit, and the crack/notch tip radius for near threshold crack. It also depends on the grain orientation for microstructually small crack. The effect of microstructure on the propagation of small fatigue cracks under rolling contact fatigue loading is examined in this dissertation. The local stress history is calculated using a macro-level 3-D elasto-plastic finite element model. A sub-modelling technique is used to achieve both computational efficiency and accuracy. The macro-level finite element model can accurately represent the contact stress of complex mechanical components and can consider the effect of loading non-proportionality. Then the equivalent stress amplitude at the critical location, which is calculated using a previously developed multiaxial fatigue limit criterion, is applied to a micro-level 2-D finite element model with center or edge crack. The fatigue model can automatically adapt for tensile/shear failure mechanisms according to material properties and loading conditions. Elasticity anisotropy, and randomness in both grain size and grain orientation are considered in the micro-level model. The geometric patterns of the grains in the polycrystalline wheel steel are generated using a 2D voronoi tessellation. The effects of applied load, crack size, grain orientation and grain disorientation on the mixed mode equivalent stress intensity factor are investigated using the developed models.

An efficient response surface construction method for fatigue life prediction is investigated in this study, based on the Gaussian process (GP) modeling approach. The model is applied to fatigue crack growth analysis, in order to save the computational effort in calculating the stress intensity factor through finite element analysis. The advantage of GP modeling is shown through comparison with traditional methods such as polynomial approximation developed by previous researchers. Then the GP method is applied to railroad wheel crack growth analysis. The GP method is also applied to develop an analytical model of fatigue crack growth data. An adaptive sample selection procedure is implemented to improve the accuracy of the GP model. The use of the GP approach can significantly reduce the number of tests required to model the fatigue crack growth data. Two sets of experimental data are used to validate the method.

Fracture and failure mechanics of advanced materials and structures with interfaces was investigated both experimentally and numerically. Dynamic fracture mechanics was used to model the phenomena when a main crack was encountering an interface. Critical dynamic fracture mechanics parameters of an infinitesimal kinked crack were determined through a relation of crack speeds, kinked angles and the other parameters of the main incident crack. Strength-based criteria were proposed to predict the interfacial debonding ahead of a main crack. In these studies, interface strengths were found to be crucial parameters for predicting crack propagation along the interface. Hence, a new specimen design to measure intrinsic interface strengths of dissimilar materials was performed, and accurate interfacial strengths were obtained.

Composite materials play an important role in todays engineering structures. These types of materials are made of two or more individual material components with weak interfaces in-between different material types. Since composite interfaces are generally more prone to failure in shear, an integrated experimental and numerical analysis is carried out to study shear failure at the interface of bonded composites. Two types of specimens, namely Iosipescu shear specimen, and straight edge butt-joint shear specimen are subjected to experimental testing in shear. Further, fringe pattern experiments are carried and the fringes are reproduced numerically. The results indicate that there is no specific advantage in using an Iosipescu specimen over a butt-shear specimen. Finally, a Monte Carlo method is used to analyze the failure in the shear specimens. An initial flaw model is assumed to cause final failure with crack length and crack location as random parameters. Conclusions are drawn from the simulations and the experimental analysis, and the need for a specialized test like the Iosipescu shear is doubted.