The Comparison of Empirical Formulae for the Prediction of Mean Wave Overtopping Rate at Armored Sloped Structures

Abstract

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

Prediction of mean wave overtopping at simple sloped breakwaters using kernel-based methods

“…However, poor predictions of mean overtopping rate at armoured structures using empirical formulae have been reported in the literature (e.g. Koosheh et al 2020). Figure 1 displays the performances of Jafari & Etemad-Shahidi (2011) (hereafter JE), and EurOtop (2018) (mean approach: Equation (6.5)) (hereafter ET), formulae for simple sloped breakwaters.…”

Distribution of individual wave overtopping volumes at rubble mound seawalls

“…The performance of the existing formulae for the estimation of N ow was discussed above and the expression proposed in EurOtop (2018) was found the best one. The estimation of q using predictive tools is commonly associated with large errors (Koosheh et al, 2020) which can greatly affect the estimation of V max . Recently, Koosheh et al (2022) conducted laboratory experiments and analysed the skill of the existing empirical formulae to estimate q.…”

Prediction of Wave Transmission Characteristics of Low Crested Structures Using Artificial Neural Network

“…The construction of LCS is performed under specific conditions to produce the desired wave transmission coefficient; thus, the calculation or prediction of the transmission coefficient of the structure should be carried out as an important factor in designing the structure. To determine the wave transmission coefficient of LCS, various studies have proposed formulas for calculating the wave transmission rate, but the wave transmission coefficients are estimated through a regression analysis of mathematical experimental data, showing a limited analysis of the natural phenomena (Koosheh et al, 2020;Formentin et al, 2017).Recently, a machine learning model has been used to estimate and predict statistical structures from input and output data. This machine learning model can readily explain the regression analysis of nonlinear relationships (Hashemi et al, 2010;Rigos et al, 2016).…”