Surface wave and storm surge prediction during Hurricane Sandy

Hurricane Sandy was the largest storm on historical record in the Atlantic Ocean basin with extensive coastal damage caused by large waves and high storm surge. The primary objectives of this thesis are to compare and evaluate three different spatially-varying surface wind fields of Hurricane Sandy to investigate the impact of the differences between the complex wind fields on predictions of the sea surface evolution, and to evaluate the impact of the storm on the hydrodynamics in Great South Bay (GSB) and the discharge of ocean water into the back-barrier bay from overwash over Fire Island. Three different spatially-varying surface wind fields were evaluated and compared to wind observations, including the parametric Holland (1980) model (H80), the parametric Generalized Asymmetric Holland Model (GAHM), and results from the WeatherFlow Regional Atmospheric Modelling System (WRAMS). The winds were used to drive the coupled Delft3D-SWAN hydrodynamic and ocean wave models on a regional grid. The results indicate that the WRAMS wind field produces wave model predictions in the best agreement with significant wave height observations, followed by the GAHM and H80 wind fields and that a regional atmospheric wind model is best for hindcasting hurricane waves and water levels when detailed observations are available, while a parametric vortex model is best for forecasting hurricane sea surface conditions. Using a series of four connected Delft3D-SWAN grids to achieve finer resolution over Fire Island and GSB, a higher resolution WRAMS was used to predict waves and storm surge. The results indicate that strong local winds have the largest influence on water level fluctuations in GSB. Three numerical solutions were conducted with varying extents of barrier island overwash. The simulations allowing for minor and major overwash indicated good agreement with observations in the east end of GSB and suggest that island overwash provided a significant contribution of ocean water to GSB during the storm. Limiting the overwash in the numerical model directly impacts the total discharge into GSB from the ocean through existing inlets. The results of this study indicate that barrier island overwash had a significant impact on the water levels in eastern GSB.

Axis Mapping: The Estimation of Surface Orientations and its Applications in Vehicle Localization and Structural Geology

The map representation of an environment should be selected based on its intended application. For example, a geometrically accurate map describing the Euclidean space of an environment is not necessarily the best choice if only a small subset its features are required. One possible subset is the orientations of the flat surfaces in the environment, represented by a special parameterization of normal vectors called axes. Devoid of positional information, the entries of an axis map form a non-injective relationship with the flat surfaces in the environment, which results in physically distinct flat surfaces being represented by a single axis. This drastically reduces the complexity of the map, but retains important information about the environment that can be used in meaningful applications in both two and three dimensions. This thesis presents axis mapping, which is an algorithm that accurately and automatically estimates an axis map of an environment based on sensor measurements collected by a mobile platform. Furthermore, two major applications of axis maps are developed and implemented. First, the LiDAR compass is a heading estimation algorithm that compares measurements of axes with an axis map of the environment. Pairing the LiDAR compass with simple translation measurements forms the basis for an accurate two-dimensional localization algorithm. It is shown that this algorithm eliminates the growth of heading error in both indoor and outdoor environments, resulting in accurate localization over long distances. Second, in the context of geotechnical engineering, a three-dimensional axis map is called a stereonet, which is used as a tool to examine the strength and stability of a rock face. Axis mapping provides a novel approach to create accurate stereonets safely, rapidly, and inexpensively compared to established methods. The non-injective property of axis maps is leveraged to probabilistically describe the relationships between non-sequential measurements of the rock face. The automatic estimation of stereonets was tested in three separate outdoor environments. It is shown that axis mapping can accurately estimate stereonets while improving safety, requiring significantly less time and effort, and lowering costs compared to traditional and current state-of-the-art approaches.