Hurricanes strike the coast along the Gulf of Mexico and eastern seaboard of the United States annually. With each hurricane that makes landfall there is potential for significant damage and destruction with the majority of coastal devastation occurring from storm surge. It is accepted that hurricane strength, classified byt the Saffir-Simpson scale, and storm surge height are directly proportional. However, this scale my prove to be a false representation of surge height, especially according to location of landfall. This study will discuss the correlation between category 2, and greater, hurricanes and corresponding storm surge heights between the Gulf Coast and Atlantic coast. Through this research it shows that there is a variation in storm surge height between regions, concluding that the Gulf Coast is prone to higher surge heights than the Atlantic for like-category storms.

Student Number : 0418388R - MSc(Eng) research report - School of Electrical and Information Engineering - Faculty of Engineering and the Built Environment / Due to the high soil resistivities and high frequency of lightning strikes in South Africa, the background theory about the effect of soil resistivity on the LV surge environment is important, but the present local and international standards do not give reasonable explanations for this effect. The previously published experimental results and research results related to this effect were investigated. From these investigations, it can be shown that the soil resistivity can affect surge generation, surge propagation and surge attenuation significantly. Also, soil resistivity plays a main role in the lightning surges caused by both direct strikes and indirect strikes, which can cause severe damage to the LV distribution system. Soil resistivity also has a significant impact on the resistance of an earth electrode.

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Taiwan is often threaten by typhoon during summer and autumn. The surges brought by theses typhoons not only cause human lives in danger, but also cause severe floods in coastal area. Storm surge prediction remains still a complex coastal engineering problem to solve since lots of parameters may affect the predictions. The purpose of this study is to predict storm surges using an Artificial Neural Network (ANN). A non-linear hidden-layer forward feeding neural network using back-propagation learning algorithms was developed. The study included a detailed analysis the factors may affect the predictions. The factors were obtained from the formulation of storm surge discrepancies after Horikawa (1987). Storm surge behaviors may vary from different geographical locations and weather conditions. A correlation analysis of the parameters was carried out first to pick up those factors shown high correlations as input parameters for establishing the typhoon surge predictions. The applications started with collecting tide and meteorological data (wind speed, wind direction and pressure) of Dapeng Bay and Kaohsiung harbor. A harmonic analysis was utilized to identify surge deviations. The surge deviation recorded at Dapeng Bay was found higher then Kaohsiung harbor for the same typhoon events. Correlation analysis has shown positive correlations between wind field, both wind speed and direction, and the associated storm surge deviations at Dapeng Bay. Correlation coefficients (CC) 0.6702 and 0.58 were found respectively. The variation of atmospheric pressure during typhoons is found with positive correlation too (i.e. CC=0.3626). Whereas the analysis has shown that the surges at Kaohsiung harbor were only sensitive to wind speed (CC=0.3723), while the correlation coefficients of the wind direction (CC=-0.1559) and atmospheric pressure (CC= -0.0337) are low. The wind direction, wind speed and atmospheric pressure variation were then used as input parameters for the training and predictions. An optimum network structure was defined using the Dapeng Bay data. The best results were obtained by using wind speed, wind direction and pressure variation as input parameters. The ANN model can predict the surge deviation better if the empirical mode decomposition (EMD) method was used for training.

In the past few years, there has been an increase in the number of hurricanes hitting the Gulf of Mexico coastline. These hurricanes have caused damage in the billions of dollars, and hundreds of people have been killed during these events. The damage from hurricanes is caused by four main factors: storm surges, waves, strong winds and rain. At the coast, the damage due to the storm surge and waves is dominant. Numerical simulation models like ADCIRC are available for estimating storm surge, but high computational time makes it impossible to use them for evacuation planning purposes. Public perception of storm surge hazard is based upon the Saffir Simpson scale. As demonstrated by Hurricanes Katrina and Ike, the Saffir Simpson scale does not work well for surge prediction. The accurate and timely prediction of storm surge is very important. For this purpose, dimensionless Surge Response Functions (SRFs) for the open coast of Texas has been developed (Irish et.al 2008a and Song, 2009). The surge inside bays tends to be different from that at the open coast due to local geometric factors like shape, center of gravity, and characteristic size of the bay. To predict accurately the surge levels inside the bay, scaling laws are developed based upon the above mentioned factors. These scaling laws are used along with SRFs for the open coast (Irish et. al. 2009) to develop dimensionless SRFs for bays. The SRFs for 3 bays, Matagorda, Galveston and Corpus Christi have been explored. Results have shown that the Surge Response method works reasonably well for Matagorda, Corpus Christi and Galveston Bay. For these bays the dimensionless surge lies within the 95% confidence interval of Surge Response Functions.

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In water conveyance systems, sudden changes in the flow velocity cause a phenomenon called waterhammer associated with high pressure head changes. Unless a control device is used as a precaution, waterhammer may result in costly damages and even in some cases, loss of human lives. In light of this concept, different control devices that can protect the systems against waterhammer are introduced so that the great pressure differences are absorbed and the system is maintained undamaged. In this thesis, the main functions, the requirements for its construction and the different types of the surge tanks are explained. The governing differential equations defining the flow conditions of the surge tanks and their solutions are provided. In addition, for the use of design engineers a procedure to determine proper dimensions of a surge tank is developed. For the sake of dimensioning the surge tank effectively, empirical equations, which calculate the height of three different types of surge tanks with dimensionless parameters, are obtained. With the help of regression analysis, the correlation between the parameters of the developed equations are determined, and found to be relatively high. Finally, the economical aspect of a surge tank is discussed and comparison parameters are introduced to the designer.

Hydropower plants contains a lot of vital electrical power technology such as generators and transformers. To prevent damage to this equipment due to overvoltage, they are often protected by surge arrester and in some cases also by surge capacitors. The design and dimension of these components vary between different sites and regions and are often done using a template without considering the actual conditions of the site. In this thesis Simulink and Simscape Power System are used to study the case when a hydropower station is exposed to overvoltage. One of Fortum’s hydropower stations is simulated when being exposed to lightning and switching overvoltage to see how the existing overvoltage protection handles this stress. The results show that the surge arresters mounted in front of the generator managed to keep it safe for all overvoltage scenarios it is exposed to. They also shows that the surge capacitors mounted in front of the generator reduces the gradient of the overvoltage surge. However, as the surge arresters already keeps the overvoltage at safe levels, there is no need of reducing the overvoltage gradient and the surge capacitors becomes excessive in this particular hydropower plant. / Vattenkraftverk innehåller många vitala komponenter så som generatorer och transformatorer. För att skydda dessa oftast väldigt dyra komponenter mot överspänningar, används ventilavledare och ibland också överspänningskondensatorer. Utformning och dimensionering av skydden varierar mellan olika anläggningar och regioner. Dimensioneringen av skydden görs ofta schablonmässigt, utan någon väsentlig anpassning till de faktiska förhållandena. I detta examensarbete används simuleringsverktyget Simulink tillsammans med tillägget Simscape Power Systems för att simulera vad som händer när ett vattenkraftverk utsätts för olika överspänningar. Ett av Fortums vattenkraftverk studeras när det utsätts för blixt- och kopplingsöverspänningar för att se vad ventilavledarna samt överspänningskondensatorerna i denna anläggning fyller för funktion. Resultaten visar att ventilavledarna monterade framför generatorn klarar av att hantera alla överspänningar de utsätt för under simuleringarna. Resultaten visade också att överspänningskondensatorerna monterade framför generatorn sänker spänningsgradienten, men eftersom ventilavledarna redan håller spänningen på en säker nivå blir överspänningskondensatorerna överflödiga i denna station.

Idealized bathymetries were subjected to idealized cyclones in order to measure the storm surge response to a range of bathymetry features, under various storm conditions. Ten bathymetries were considered, including eight shoals, one pit, and a featureless reference domain. Six storms (two different sizes/intensities and three different landfall directions) were used as meteorological forcing. The bathymetry features influenced local surge response during pre- and post-peak surge conditions. However, peak surge and surge at the coast were not meaningfully affected by the presence of the bathymetry features considered. The effect of three bathymetry feature parameters on surge response was analyzed (i.e. depth below mean sea level, cross-shore width, and distance from shore). Of these parameters, feature depth below mean sea level was the most influential on surge generation.