Evolutionary game theory has recently emerged as a key paradigm in various behavioral science disciplines. In particular it provides powerful tools and a conceptual framework for the analysis of the time evolution of strategic interdependence among players and its consequences, especially when the players are spatially distributed and linked in a complex social network. We develop various evolutionary game models, analyze these models using appropriate techniques, and study their applications to complex phenomena. In the second chapter, we derive integro-differential equations as deterministic approximations of the microscopic updating stochastic processes. These generalize the known mean-field ordinary differential equations and provide powerful tools to investigate the spatial effects on the time evolutions of the agents' strategy choices. The deterministic equations allow us to identify many interesting features of the evolution of strategy profiles in a population, such as standing and traveling waves, and pattern formation, especially in replicator-type evolutions. We introduce several methods of decomposition of two player normal form games in the third chapter. Viewing the set of all games as a vector space, we exhibit explicit orthonormal bases for the subspaces of potential games, zero-sum games, and their orthogonal complements which we call anti-potential games and anti-zero-sum games, respectively. Perhaps surprisingly, every anti-potential game comes either from Rock-paper-scissors type games (in the case of symmetric games) or from Matching Pennies type games (in the case of asymmetric games). Using these decompositions, we prove old (and some new) cycle criteria for potential and zero-sum games (as orthogonality relations between subspaces). We illustrate the usefulness of our decompositions by (a) analyzing the generalized Rock-Paper-Scissors game, (b) completely characterizing the set of all null-stable games, (c) providing a large class of strict stable games, (d) relating the game decomposition to the Hodge decomposition of vector fields for the replicator equations, (e) constructing Lyapunov functions for some replicator dynamics, (f) constructing Zeeman games -games with an interior asymptotically stable Nash equilibrium and a pure strategy ESS. The hierarchical modeling of evolutionary games provides flexibility in addressing the complex nature of social interactions as well as systematic frameworks in which one can keep track of the interplay of within-group dynamics and between-group competitions. For example, it can model husbands and wives' interactions, playing an asymmetric game with each other, while engaging coordination problems with the likes in other families. In the fourth chapter, we provide hierarchical stochastic models of evolutionary games and approximations of these processes, and study their applications

The present work applies the hybrid Voronoi cell finite element method (VCFEM) within geomechanics. Coupled seepage and deformation analysis using the VCFEM incorporating body forces allows accurate analysis of earth dams. The development of a novel approach for simulating granular material behaviour using the combined finite-discrete element method (VCFEM-DEM) provides new insights into strain localization in granular materials. Chapter 1 provides background including summary literature reviews for all concepts in the title including seepage analysis, micromechanical and continuum mechanics theory, Voronoi diagrams, finite elements (FEM), discrete elements (DEM) and combined FEM-DEM. Chapter 1 concludes by detailing the contributions of the present work. Chapter 2 presents the VCFEM for seepage analysis. The numerical examples include an investigation of mesh sensitivity and a comparison of conforming shape functions. Polygonal elements with more than four nodes show a decrease in mesh sensitivity in free surface problems, compared with four-node quadrilateral elements. The choice of conforming shape function within the VCFEM analysis did not affect the results. Chapter 3 formulates and applies the VCFEM-DEM, showing that strain localization effects in granular materials are important at all scales. The VCFEM-DEM captures shear banding in biaxial compression tests, demonstrating that global shear strains and inhomogeneities in the shear stress field present after consolidation are early precursors to the failure mode. At the field scale, strain localization can lead to significant non-uniformity in subsurface stress distribution owing to self-weight. Chapter 4 presents the coupled VCFEM for seepage and deformation. A practical example of the design of an earth dam demonstrates the application of general body forces within a hybrid formulation, notably lacking in the literature. Chapter 5 concludes by summarizing the key observations of the present work, and providing direction for future research. The Appendix provides additional details related to numerical integration within the VCFEM. / Thesis / Doctor of Philosophy (PhD) / The focus of the present work is the simulation of geomechanical behaviour at multiple scales. This ranges from simulating the interaction of grains of sand in a laboratory compression test to the seepage of water through and deformation of a large dam constructed of granular material. The simulations use a numerical tool called the Voronoi cell finite element method (VCFEM), which the present work extends to allow accurate analysis of the flow of fluid through a porous medium, deformation of a granular material under load and coupled analysis of these phenomena. The development and testing of this numerical tool for use in geomechanical analysis is itself a contribution. The present work also contains new insights into how localized stresses and strains in a granular material that are present well before the peak strength can have an important influence on the mode of failure.

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Titanium-7%wt-Aluminum (Ti-7Al) has been of interest to the aerospace industry owing to its good structural and thermal properties. However, extensive research is still needed to study the structural behavior and determine the material properties of Ti-7Al. The homogenized macro-scale material properties are directly related to the crystallographic structure at the micro-scale. Furthermore, microstructural uncertainties arising from experiments and computational methods propagate on the material properties used for designing aircraft components. Therefore, multi-scale modeling is employed to characterize the microstructural features of Ti-7Al and computationally predict the macro-scale material properties such as Young's modulus and yield strength using machine learning techniques. Investigation of microstructural features across large domains through experiments requires rigorous and tedious sample preparation procedures that often lead to material waste. Therefore, computational microstructure reconstruction methods that predict the large-scale evolution of microstructural topology given the small-scale experimental information are developed to minimize experimental cost and time. However, it is important to verify the synthetic microstructures with respect to the experimental data by characterizing microstructural features such as grain size and grain shape. While the relationship between homogenized material properties and grain sizes of microstructures is well-studied through the Hall-Petch effect, the influences of grain shapes, especially in complex additively manufactured microstructure topologies, are yet to be explored. Therefore, this work addresses the gap in the mathematical quantification of microstructural topology by developing measures for the computational characterization of microstructures. Moreover, the synthesized microstructures are modeled through crystal plasticity simulations to determine the material properties. However, such crystal plasticity simulations require significant computing times. In addition, the inherent uncertainty of experimental data is propagated on the material properties through the synthetic microstructure representations. Therefore, the aforementioned problems are addressed in this work by explicitly quantifying the microstructural topology and predicting the material properties and their variations through the development of surrogate models. Next, this work extends the proposed multi-scale models of microstructure-property relationships to magnetic materials to investigate the ferromagnetic-paramagnetic phase transition. Here, the same Ising model-based multi-scale approach used for microstructure reconstruction is implemented for investigating the ferromagnetic-paramagnetic phase transition of magnetic materials. The previous research on the magnetic phase transition problem neglects the effects of the long-range interactions between magnetic spins and external magnetic fields. Therefore, this study aims to build a multi-scale modeling environment that can quantify the large-scale interactions between magnetic spins and external fields. / Doctor of Philosophy / Titanium-Aluminum (Ti-Al) alloys are lightweight and temperature-resistant materials with a wide range of applications in aerospace systems. However, there is still a lack of thorough understanding of the microstructural behavior and mechanical performance of Titanium-7wt%-Aluminum (Ti-7Al), a candidate material for jet engine components. This work investigates the multi-scale mechanical behavior of Ti-7Al by computationally characterizing the micro-scale material features, such as crystallographic texture and grain topology. The small-scale experimental data of Ti-7Al is used to predict the large-scale spatial evolution of the microstructures, while the texture and grain topology is modeled using shape moment invariants. Moreover, the effects of the uncertainties, which may arise from measurement errors and algorithmic randomness, on the microstructural features are quantified through statistical parameters developed based on the shape moment invariants. A data-driven surrogate model is built to predict the homogenized mechanical properties and the associated uncertainty as a function of the microstructural texture and topology. Furthermore, the presented multi-scale modeling technique is applied to explore the ferromagnetic-paramagnetic phase transition of magnetic materials, which causes permanent failure of magneto-mechanical components used in aerospace systems. Accordingly, a computational solution is developed based on an Ising model that considers the long-range spin interactions in the presence of external magnetic fields.

Island biogeography theory predicts that the patterns and distributions of spatially isolated populations are governed by large scale processes. The high elevations forests in the Southern Appalachians represent a series of naturally fragmented islands that harbor many isolated populations of species at the southern limits of their range. Understanding the governing forces of population dynamics in this region will enhance the probability of species persistence in the face of threats such as global warming and human development. We surveyed bird populations across multiple elevations in Virginia and combined this with a multi-scale habitat analysis to determine influences of species presence and species richness. We detected 101 species across the elevation gradient, including 12 species with special conservation status and ten species whose presence increased with increasing elevation. These ten elevation sensitive species responded to habitat variables at both the microhabitat and landscape scale, with species-specific patterns of habitat variable correlation emerging. Habitat type was least effective in predicting species presence for any elevation sensitive species. Species richness declined over the elevation gradient until the highest elevations, where this trend reversed and richness began to increase. This pattern was driven by an increase in short-distance migrants beginning at mid-elevations, which ultimately overpowered a corresponding decrease in long-distance migrants beginning at similar elevations. Habitat analysis linked these patterns to a preference of short-distance migrants for smaller, more isolated non-forested patches, and a historical lack of persistence for long-distance migrants. Conservation and management decisions for the region should focus on a multi-scale approach that preserves all habitat types for continued species presence and high species richness, although the persistence of particular elevation sensitive species is compounded by unique species-habitat relationships and the perception of islands as species-specific. Continued monitoring of these fragmented populations in light of both short- and long-term threats which span multiple scales of influence will maintain high species richness and ensure the persistence of crucial breeding habitat. / Master of Science