van der meer breakwater design approach example

As such, costal defences are designed based on an allowable limit for overtopping discharge. Wave-structure interactions are important in determining the resilience of coastal defences and their effectiveness in mitigating wave overtopping. Wave overtopping is observed at the crest of the coastal defence structure when water exceeds the defence crest level and inundates the coastal lands on the leeside of the structure ( Fig 1). The primary objective of coastal defences is to protect hinterland infrastructures and people from extreme sea levels, which typically arise from a combination of waves, high astronomical tides, and storm surges. This study shows that ML approaches can be adopted as a reliable and computationally effective method for evaluating wave overtopping at vertical seawalls across a wide range of hydrodynamic and structural conditions. In addition to this, Decision Tree (DT) based methods such as GBDT and RF are shown to be more computationally efficient than SVR and ANN, with GBDT performing simulations more rapidly that other methods. Comprehensive statistical analysis shows superior performance of the RF method, followed in turn by the GBDT, SVR, and ANN models, respectively. Feature Transformation and advanced Feature Selection methods are adopted to reduce data redundancy and overfitting. Hyperparameter tuning is performed to curtail algorithms to the intrinsic features of the dataset. The ML models are developed using data from the EurOtop (2018) database. This study examines the predictive performance of four ML techniques, namely Random Forest (RF), Gradient Boosted Decision Trees (GBDT), Support Vector Machines-Regression (SVR), and Artificial Neural Network (ANN) for overtopping discharge at vertical seawalls. However, the methodological appropriateness and performance evaluation of ML techniques for predicting wave overtopping at vertical seawalls has not been extensively studied. In recent years, with advances in computational efficiency, data-driven techniques including advanced Machine Learning (ML) methods have become more readily applicable. Methods for predicting overtopping have typically relied on empirical relations based on physical modelling and numerical simulation data. In addressing the increased risks of rising sea levels and more frequent storm surges, robust assessment and prediction methods for overtopping prediction are increasingly important. Where A is the area of the erosion area.Accurate prediction of wave overtopping at sea defences remains central to the protection of lives, livelihoods, and infrastructural assets in coastal zones. This research, conducted by Jentsje van der Meer, resulted in the Van der Meer formula in 1988, as described in his dissertation. That is why the Dutch government agency Rijkswaterstaat commissioned Deltares to start research for a more complete formula. Around 1985 it was found that the Hudson formula in use at that time had considerable limitations (only valid for permeable breakwaters and steep (storm) waves). This is necessary for the design of breakwaters and shoreline protection. The Van der Meer formula is a formula for calculating the required stone weight for armourstone under the influence of (wind) waves. Formula to calculate the stability of armourstone under wave action

Van der meer breakwater design approach example