In recent times, communities and structures along the Gulf of Mexico have experienced the destructive and devastating impact of hurricane surges and waves. While the impacts of surges have been studied, there exists a need for (1) the understanding of open-coast and bay environment hurricane wave conditions and (2) expedient prediction, for rapid evaluation, of wave hazards as a function of hurricane parameters. This thesis presents the coupled ADCIRC-SWAN numerical model results of wave height sensitivity based on the investigation of several hurricane parameters. Also presented is the development of parameterized maximum significant wave height models. These are determined by incorporating three forms of an equivalent fetch into (1) dimensionless best-fit equations and (2) Shoreline Protection Manual (SPM) method. Computational results indicate that for a range of simulated hurricane parameters, a wide range of spatial and temporal characteristics, for the significant wave height, exists. The location of hurricane landfall results in a significant difference in the wave height at specified points. Additionally, the variation in central pressures, radius sizes and forward speeds leads to elevated surge levels that contribute to wave generation. Furthermore, the time evolution trend of the generation of the significant wave height is found to be unique to its geographic location. In the development of parameterized maximum significant wave height models, the dimensionless best-fit equation approach indicates how strongly the various forms of the equivalent fetch and the bathymetric depth ultimately determines the predicted maximum significant wave height. This approach yielded RMSE that range between 0.52m – 0.68m. Additionally, the accuracy for this approach varied greatly as the highest scatter index was 0.28 for the open-coast points and 0.37 for the bay points. The SPM approach gives an indication of how strongly the functional form of the equivalent fetch determines the predicted maximum significant wave height. When compared to the dimensionless approach, this method produced a lower RMSE of 0.37m and a greater accuracy for the scatter index of 0.23 for the open-coast points and 0.31 for the bay points.

This thesis presents the mechanical design and dimensioning of a pressure vessel, which is to be used as housing for a marine substation in a wave power park. A concept for generation of electricity from ocean waves is being developed at the Division of electricity at Uppsala University. The concept is based on the use of a permanent magnet linear generator, placed on the seabed, connected via a line to a buoy at the surface. The generated electricity from a group of generators is transmitted in sea cables to a marine substation where conversion and transformation takes place before the electricity is transmitted to shore. To reduce the risk of water leakage, the gas pressure inside the marine substation is larger than the surrounding water pressure. The substation can be pressurized before submersion, which requires the housing to be designed as a pressure vessel. The pressure vessel has been dimensioned with formula based methods according to EN 13445, the European standard for unfired pressure vessels. The construction has been based on modifying a standard pressure tank. The housing has been designed for installation and sealing of a large number of electrical connectors. The connectors have been placed in a way that allows for future cable coupling with remotely operated vehicles and simplifies maintenance of the substation. Another design consideration has been to facilitate submersion by reducing the buoyancy of the substation.

This investigates the velocity fields of a plunging breaking wave impinging on a structure through measurements in a two-dimensional wave tank. As the wave breaks and overtops the structure, so-called green water is generated. The flow becomes multi-phased and chaotic as a highly aerated region is formed in the flow in the vicinity of the structure while water runs up onto the structure. In this study, particle image velocimetry (PIV) was employed to measure the velocity field of the water dominant region. For measurements of an aerated region that cannot be measured by PIV, a new measurement method called bubble image velocimetry (BIV) was developed. The principle and setup of the BIV method were introduced and validated. Mean and turbulence properties were obtained through ensemble averaging repeated tests measured by both methods. The dominant and maximum velocity of the breaking wave and associated green water are discussed for the three distinct phases of the impingement-runup-overtopping sequence. The distribution of the green water velocity along the top of the structure has a nonlinear profile and the maximum velocity occurs near the front of the fast moving water. Using the measured data and applying dimensional analysis, a similarity profile for the green water flow on top of the structure was obtained, and a prediction equation was formulated. The dam breaking solution used for the green water prediction was examined with determining initial water depth based on the experiment conditions. Comparison between measurements, the prediction equation, and the dam breaking flow was made. The prediction equation and the dam break flow with appropriate initial water depth may be used to predict the green water velocity caused by extreme waves in a hurricane. To demonstrate the aeration of the breaking wave and overtopping water, void fraction was also investigated. There is strong aeration in the region of overtopping water front generated by a plunging breaker. Void fraction of overtopping water was measured using a fiber optic reflectometer (FOR). The measured velocity and void fraction were also used to estimate flow rate and water volume of overtopping water.

Abstract Tidal wave may be distorted when entering the river of large topography variations. The traditional tidal harmonic may not be applied well to data collected in such a shallow river. Godin (1998) indicated that the hydrodynamics of rivers is dominated by the damping and the distortion induced by quadratic bottom friction. This research try to analyze the distortion of tidal wave in the Tanshui River (northern Taiwan) based on field measurements. Sea levels data are collected at fours stations along the lower river: Pole (4km offshore), Tanshui harbor(on the coast), Kuan-Do Bridge (7km inland) and Yuan-Shan Bridge (18km inland). The total distance of the four stations is 22 km. The synchronizing sampling period is January 10 to February 28 of 2001 (50 days). The analysis is trying to identify the following issues. (1) The transformation of tidal wave from coastal into the river and upper stream. (2) The errors of tidal prediction based on harmonic analysis. Several different conditions are examined including spring-neap tides, influence of fresh water output and peaks of high-low water. The influence of bottom friction of the inner river stations is emphasized. The results show that distortion of tidal wave is more pronounce inside the river. The main reason is explained due to the strength of bottom friction, which is proportional to the flow velocity. (1) During spring tide, a stronger flow contributes a larger bottom friction. (2) A higher water level (h) may have a faster wave speed ( ) that high water occurred before the forecast. The deviation in high water also is more significant than that of low water. (3) River flow increases the water level and cause the deviation of wave propagation inside the river.

The good of this thesis is to apply a numerical model for studying waveform of an internal solitary wave (ISW) on variable seabed topography. The numerical model developed by Lynett and Liu (2002) is adopted for this work but with modification to improve its accuracy, both mathematically and in programming codes. Numerical experiments using the modified model are then performed and the results compared with laboratory experiments of Kuo (2005), in order to validate its accuracy. The mathematical model derived in the present study is based on the assumption that an internal wave is weakly nonlinear and weakly dispersive in an inviscid fluid. The governing equations based on the continuity equation and Euler equations are solved for ISW propagation over variable topography. The input conditions for the numerical experiments include physical parameters related to water depth and geometry of submarine obstacle, such as depth ratio between upper and lower layers (H1/H2), height (hs) and type (triangular ridge and trapezoidal shelf) of obstacles, in addition to the amplitude (ai) of an incident ISW. From the results of numerical experiments, wave amplitude, phase speed, and wave energy of a transmitted ISW are obtained and compared with that of laboratory experiments. (Kuo, 2005) ISW propagation over a single obstacle is affected by a dimensionless parameter called ¡§blockage parameter", £a= (a1+h1)/(h1+h2-hs). Three types of interaction may be classified (weak interaction, moderate interaction, and wave breaking) depending on the value of£a . For an ISW propagating over two consecutive obstacles, the interval between them is significant in reducing its amplitude and energy, as the interval reduces. Moreover, the effect of relative height between two obstacles may also be classified into two types: (i) within the range of weak interaction, energy dissipation is less for a high obstacle first than for it as the second; (ii) within the range of moderate interaction, the energy dissipation is higher for a high obstacle first than for it as the second. Further comparisons have shown that the modified numerical model is in better agreement with the results of laboratory experiments (Kuo, 2005) than the original model of Lynett and Liu (2002). The results obtained from the present numerical experiments for ISW evolution on variable topography is encouraging which could benefit other who may be interested in internal wave propagation for practical applications in oceanography.

A two-dimensional finite difference model is developed for the simulation of saltwater intrusion in wave-induced aquifer system with either a confined or phreatic aquifer. The model considers many important factors, such as the dynamic pressure induced by wave motion, the pressure wave equation, the density-dependent Darcy¡¦s Law, and the salt transport equation. This paper presents numerical study of the effect of wave motion, resulting salinity structure responses and phreatic surface fluctuation on the process of seawater intrusion ¡K etc.

This thesis applies a numerical model to study the propagation of internal solitary wave based on a two-dimensional model developed by Lynett and Liu (2002) and modified by Cheng et al. (2005).The numerical model derived assumes weak nonlinearity and weak dispersion in a two-layer inviscid fluid system. The governing continuity and momentum equations are solved and the real topography is included in the wave model. In order to improve the accuracy of simulation, mixed-layer thickness is allowed to change from place to place. Initial conditions are modified so that wave forms of non-hyperbolic -secant functions and wave fronts taken by satellite can be used. The diffraction near the island of Dongsha is simulated, and results of both fixed and variable mixed-layer thickness are compared. Simulated waveform in MODIS images after 24 hours are compared with other wave fronts of the same image. Laterally, internal waves can become very wide when it is far away from its origin. The extra energy can be explained by nonlinear wave-wave interaction because the energy of large amplitude internal wave increases after interacting with smaller internal waves.

We studied the local single-particle tunneling characteristics [as observed with scanning tunnel microscopy (STM)] for N D and S D tunneling, where N is a normal metal, S is a s-wave superconductor, and D is a d-wave superconductor with a {100} | {110} grain boundary. The tunneling Hamiltonian method was used. The self-consistent order parameter is first determined using the quasiclassical Green'sfunction method, and then the tunneling characteristics at various distances from the interface, reectivity of the interface, and temperature are studied. For N D tunneling, a zero-bias conductance peak (ZBCP) occurs near the interface with diminishing magnitude away from it. For S D tunneling, the ZBCP splits to exhibit the gap of the s-wave low-Tc superconducting tunneling tip and there is a range of negative conductance just outside the peaks when the tunneling point is near the grain boundary. The results are compared with those obtained by using a constant order parameter in each grain.

One of the important topics in sleep medicine is sleep structure. Normal sleep consists of rapid eye movement (REM) sleep and nonrapid eye movement (NRME) sleep states. NREM sleep can be further classified into stage 1, 2 and slow wave sleep (SWS) according to the current sleep scoring standard. Among them, SWS has been considered to be very important due to its r restorative value. The goal of this research is to detect SWS by using a single channel EEG signal. Its applications can be divided into two phases. In the first phase, a personalized SWS detector is designed for each individuals By combining these personalized SWS detectors, the second phase develops a general SWS detection method that can be applied to general population with any personalized training process. By applying the proposed method to 62 persons, the experimental results show that the proposed method, in average, achieves 90.69% classification accuracy 90.09% sensitivity and 93.97% specificity. Our experimental results also demonstrate, when applied to persons with higher AHI (apnoea-hypopnea index) values, the proposed method can still provided satisfactory results.

This study aims at sleep stage classification problem via EOG signals. The classification problem consists of four steps. The first step is to distinguish slow wave sleep from the rest of the sleep periods. Wake periods are identified in the second step. The third step finds REM sleep and the last step classifies stage 2 and stage1 sleep. By using different EOG signal features in different steps of the classification process, this work uses back-propagation trained neural networks to perform classification. With the exception of stage 1 sleep, the sensitivity and positive predictive value ranges from 70% to 80%. The overall classification accuracy is 74.80%.