The accurate prediction of the mean wave overtopping rate at breakwaters is vital to have a safe design. Hence, providing a robust tool as a preliminary estimator can be useful for practitioners. Recently, soft computing tools such as artificial neural network (ANN) have been developed as alternatives to traditional overtopping formulae. The goal of this paper is to assess the capabilities of two kernel-based methods namely Gaussian process regression (GPR) and support vector regression for the prediction of mean wave overtopping rate at sloped breakwaters. An extensive dataset taken from EurOtop (2018) database, including rubble mound structures with permeable core, straight slopes, without berm, and crown wall, was employed to develop the models. Different combinations of the important dimensionless parameters representing structural features and wave conditions were tested based on the sensitivity analysis for developing the models. The obtained results were compared with those of the ANN model and the existing empirical formulae. The modified Taylor diagram was used to compare the models graphically. The results showed the superiority of kernel-based models, especially the GPR model over the ANN model and empirical formulae. In addition, the optimal input combination was introduced based on accuracy and the number of input parameters criteria. Finally, the physical consistencies of developed models were investigated the results, of which demonstrated the reliability of kernel-based models in terms of delivering physics of overtopping phenomenon.
Growing energy demand worldwide and onshore limitations have increased interest in offshore renewable energy exploitation. A combination of offshore renewable energy resources such as wind and wave energy can produce stable power output at a lower cost compared to a single energy source. Consequently, identifying the best locations for constructing combined offshore renewable energy farms is crucial. This paper investigates the technical, economic, social, and environmental aspects of Combined Offshore Wind and Wave Energy Farm (COWWEF) site selection. Past literature was evaluated using a systematic review method to synthesize, criticize, and categorize study regions, dataset characteristics, constraints, evaluation criteria, and methods used for the site selection procedure. The results showed that most studied regions belong to European countries, and numerical model outputs were mainly used in the literature as met-ocean data due to the limited coverage and low spatiotemporal resolution of buoy and satellite observations. Environmental and marine usage are the main constraints in the site selection process. Among all constraints, shipping lanes, marine protected areas, and military exercise areas were predominately considered to be excluded from the potential sites for COWWEF development. The technical viability and economic feasibility of project deployment are emphasized in the literature. Resource assessment and distance to infrastructures were mostly evaluated among techno-economic criteria. Wind and wave energy power are the most important criteria for evaluating feasibility, followed by water depth, indicators of variability and correlation of the energy resources, and distance to the nearest port. Multi-Criteria Decision-Making (MCDM) methods and resource-based analysis were the most-used evaluation frameworks. Resource-based studies mainly used met-ocean datasets to determine site technical and operational performance (i.e., resource availability, variability, and correlation), while MCDM methods were applied when a broader set of criteria were evaluated. Based on the conducted review, it was found that the literature lacks evaluation of seabed conditions (seabed type and slope) and consideration of uncertainty involved in the COWWEF site selection process. In addition, the market analysis and evaluation of environmental impacts of COWWEF development, as well as impacts of climate change on combined exploitation of offshore wind and wave energy, have rarely been investigated and need to be considered in future studies. Finally, by providing a comprehensive repository of synthesized and categorized information and research gaps, this study represents a road map for decision-makers to determine the most suitable locations for COWWEF developments.
Armored sloped structures are generally used to provide the safety of their lee side, i. e. harbours and coastal regions against wave attacks and storm surge. Recently, due to the potential impact of climate change, increasing emphasis has been placed on their hydraulic performance (e.g. Pillai et al. 2019). Thus, accurate estimation of wave overtopping rate, as the hydraulic response of coastal structures, has an important role in design. Wave overtopping is a complex phenomenon and depends on structural geometry and wave characteristics. Hence, empirical formulae are generally used for estimation of mean overtopping rate. These formulae have been derived from laboratory measurements in which the dimensionless measured overtopping rates are correlated with the dimensionless structural and hydraulic parameters through physical arguments. The most well-known formulae for wave overtopping prediction can be found in the Coastal Engineering Manual (2012) and European Overtopping Manual (EurOtop, 2018). The CLASH database as one of the most comprehensive datasets, was initially provided by De Rouck and Geeraerts (2005). This data base was recently updated by including more test results (EurOtop, 2018). However, a detailed comparison of formulae proposed for the estimation of overtopping rates at rubble mound sloped structures is not reported. The present paper aims to evaluate the performance of existing empirical formulae namely EurOtop 2018 (hereafter ET18), Owen (1982), van der Meer and Janssen (1995) (hereafter VMJ) and Jafari and Etemad-Shahidi (2012) (hereafter JES) against EurOtop database (updated CLASH database). The analysis includes structures with different armor types (rock, concrete cubes etc.) with both impermeable and permeable cores, to evaluate the capability of used formulae under different conditions.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/0TL5zFCf6GU
Wave overtopping is considered an important aspect when designing waterfront or sea-defense structures, making it a part of any design to predict the overtopping rate. Because overtopping is quite a complex phenomenon, most of the previous studies were focused on deriving empirical formulas using data collected from laboratory tests. This paper, in particular, deals with the estimation of overtopping at vertical structures and considers four of the existing methods to compare their performance using the European Overtopping Manual (i.e. EurOtop) database. Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/iGwh_TZuc6M
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