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Subject: Anisotropy

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    Characterization of Surface Microtopography and Determination of Hydrotopographic Properties
    (North Dakota State University, 2012) Chi, Yaping
    Spatial characterization of surface microtopography is important in understanding the overland flow generation and the spatial distribution of surface runoff. In this study, fractal parameters (i.e., fractal dimension D and crossover length l) and three hydrotopographic parameters, random roughness (RR) index, maximum depression storage (MDS), and the number of connected areas (NCA), have been applied to characterize the spatial complexity of microtopography. Clear and meaningful relationships have been established between these parameters. The RR was calculated as the standard deviation of the processed elevation, and the fractal parameters were calculated with the semivariogram method. The puddle delineation program was applied in this study to spatially delineate soil surface and to accurately determine MDS and NCA. It has been found that fractal parameters can better characterize surface microtopography. More importantly, fractal and anisotropic analyses can help to better understand the overland flow generation process.
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    An Anisotropic Damage Mechanics Model for Concrete with Applications for Fatigue Loading and Freeze-Thaw Effects
    (North Dakota State University, 2013) Reberg, Andrew Steven
    It is well known that the formation and propagation of microcracks within concrete is anisotropic in nature, and has a degrading effect on its mechanical performance. In this thesis an anisotropic damage mechanics model is formulated for concrete which can predict the behavior of the material subjected to monotonic loading, fatigue loading, and freeze-thaw cycles. The constitutive model is formulated using the general framework of the internal variable theory of thermodynamics. Kinetic relations are used to describe the directionality of damage accumulation and the associated softening of mechanical properties. The rate independent model is then extended to cover fatigue loading cycles and freeze-thaw cycles. Two simple softening functions are used to predict the mechanical properties of concrete as the number of cyclic loads as well as freeze-thaw cycles increases. The model is compared with experimental data for fatigue and freeze-thaw performance of plain concrete.