مجله هیدرولیک
سال سیزدهم شماره 1 (بهار 1397)

Abnormal waves are extremely large and unusual which rarely occur, but cause serious damages. Various factors such as extreme storms, particular topography of the seabed, marine currents, wave-wave interaction with different wavelengths and frequencies may cause wave occurrence and transformation. The main objective of this study is to propose a new hybrid approach to predict the occurrence of abnormal waves using wavelet transform and support vector machines (SVM) classifier based on meteorological data. The data sets used in this paper are from two major hurricanes Dean 2007 and Irene 2011 at four locations namely, 41004 and41041 in the Gulf of Mexico. To predict the occurrence of abnormal waves, at the first extreme waves are detected using wavelet transform. The outputs of this method are considered as SVM classifier targets. Wavelet transform is applied on the significant wave height data samples. The abnormal waves are readily identified from the wavelet spectrum as an area of high energy. The inputs of SVM classifier models are historical metrological data, including: Wind direction (WDIR), Wind speed (WSPD), Sea level pressure (PRES), Air temperature (ATMP), and Sea surface temperature (WTMP). The experiment results show that the proposed method is able to predict the occurrence of extreme wave heights with height accuracy.

In the present research, the formation and development of the delta and the interaction of the flow pattern and sediment in the reservoir under steady and unsteady flow condition of water and sediment is experimentally investigated. Laboratory observations showed that in spite of the perfect symmetry of the geometry and hydraulic conditions of the model, the flow at the reservoir entrance is randomly diverted to one side and an asymmetric but stable flow is created at the reservoir entrance. The sediment entry and its deposition in the reservoir leads to an unstable flow and a change in flow direction. The instability in unsteady flow is more severe than under steady flow condition. The results showed that with the growth of the delta, the deviation of delta decreases and approaches the symmetry. Delta development takes place in longitudinal and transvers directions and the maximum elongation of delta is about 0.8 at the initial stages, and decreases with delta development. An equation is developed for time of change in direction of flow in terms of the specific parameter of the hydrograph. In order to study the sedimentation pattern, non-dimensional parameters such as the length of delta (Xt*), deviation ratio (ψ) and delta elongation (η) are introduced. An equation is developed to estimate the length of delta using non-dimensional parameters.

Gravity currents, also called density currents or buoyancy currents, are flows driven by the density difference between the flow and its ambient environments. When a gravity current reaches the level of neutral buoyancy in a stratified water body, it can separate from the bed as an intrusion. Laboratory experiments are performed to investigate dense flow behavior in stratified ambient in this study. Experiments were carried out on 2.5% bed slope by 4 discharges, 1, 1.5, 2 and 2.5 l/s, and 4 concentrations 5, 10, 15 and 20 mg/l, that created current with a density of 1003.2, 1006.3, 1009.4 and 1012.5 respectively. Stratification was made by mixture of water and salt with vertical gradient. For creating density flow, silica particles with 8 diameters in average and density of 2.673 g/cm3 was used. To investigate the concentration profile, density and concentration were measured in three sections along the flume with three centimeters interval in depth using siphon mechanism. Experimental observations showed that the currents would separate from the bed and then horizontally intrude into the ambience and the density of ambient fluids below the separation point decreases. The measurements in this study indicate that the maximum concentration depth and thickness of body current decreases with increasing concentration in interflow and body current thickness stabilize with increasing discharge.

Vegetation can be divided into two groups in terms of height and water depth as the submerged vegetation and the emergent vegetation. This paper investigates the emergent vegetation, using reedy rods. The presence of vegetation cover in rivers and open channels calls for better understanding the effect of this significant factor in application of the boundary-layer laws, including the logarithmic law and the Coles’ law. The results show that the logarithmic law can be applied in the presence of vegetation cover with different densities as well as the gravel-bed streams. However, this law deviates in the outer layer where the empirical Coles’ law is not valid in the presence of vegetation cover. The more vegetation density, the more deviation of data from the Coles’ law. The reason for invalidity of Coles’ law in the outer layer is due to irregular velocity distribution and turbulence intensity in the presence of vegetation, leading to augmentation of the deviation with vegetation density.

Estimation of scour depth in pipelines laid on the seabed is an important subject in pipeline design process. Due to the variability of scouring nature, a hybrid stochastic scouring decision tree model (M5ʹ-GLUE) was developed using GLUE approach and it was compared with other deterministic scouring decision tree model under live bed condition. The results obtained in both train and test steps showed that the mean value of determination coefficient of hybrid model in estimation of scouring was 0.72. Therefore, the M5ʹ-GLUE model has good accuracy in the estimation of pipeline scouring. Furthermore, having employed two other index Root Mean Square Error and Agreement Coefficient, it was revealed that the accuracy of scouring estimation was improved by 18 percent using hybrid model in comparison to deterministic tree model. Less improvement was occurred under live bed condition with small (e/D). Generally, it can be concluded that the developed hybrid model in comparison to the deterministic tree model has good accuracy for estimation of scour depth in pipes laid on the seabed.

Estimation of scour depth in pipelines laid on the seabed is an important subject in pipeline design process. Due to the variability of scouring nature, a hybrid stochastic scouring decision tree model (M5ʹ-GLUE) was developed using GLUE approach and it was compared with other deterministic scouring decision tree model under live bed condition. The results obtained in both train and test steps showed that the mean value of determination coefficient of hybrid model in estimation of scouring was 0.72. Therefore, the M5ʹ-GLUE model has good accuracy in the estimation of pipeline scouring. Furthermore, having employed two other index Root Mean Square Error and Agreement Coefficient, it was revealed that the accuracy of scouring estimation was improved by 18 percent using hybrid model in comparison to deterministic tree model. Less improvement was occurred under live bed condition with small (e/D). Generally, it can be concluded that the developed hybrid model in comparison to the deterministic tree model has good accuracy for estimation of scour depth in pipes laid on the seabed.