J.W. van der Meer
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16 records found
1
Practitioners often employ diverse, though not always thoroughly validated, numerical models to directly or indirectly estimate wave overtopping (q) at sloping structures. These models, broadly classified as either phase-resolving or phase-averaged, each have strengths and limitations owing to the physical schematization of processes within them. Models which resolve the vertical flow structure or the full wave spectrum (i.e. sea-swell (SS) and infragravity (IG) waves) are considered more accurate, but more computationally demanding than those with approximations. Here, we assess the speed-accuracy trade-off of six well-known models for estimating q, under shallow foreshore conditions. The results demonstrate that: i) q is underestimated by an order of magnitude when IG waves are neglected; ii) using more computationally-demanding models does not guarantee improved accuracy; and iii) with empirical corrections to incorporate IG waves, phase-averaged models like SWAN can perform on par, if not better than, phase-resolving models but with far less computational effort.
Despite the widely recognized role of infragravity (IG) waves in many often-hazardous nearshore processes, spectral wave models, which exclude IG-wave dynamics, are often used in the design and assessment of coastal dikes. Consequently, the safety of these structures in environments where IG waves dominate remains uncertain. Here, we combine physical and numerical modeling to: (1) assess the influence of various offshore, foreshore, and dike slope conditions on the dominance of IG waves over those at sea and swell (SS) frequencies; and (2) develop a predictive model for the relative magnitude of IG waves, defined as the ratio of the IG-to-SS-wave height at the dike toe. Findings show that higher, directionally narrow-banded incident waves; shallower water depths; milder foreshore slopes; reduced vegetated cover; and milder dike slopes promote IG-wave dominance. In addition, the empirical model derived, which captures the combined effect of the varied environmental parameters, allows practitioners to quickly estimate the significance of IG waves at the coast, and may also be combined with spectral wave models to extend their applicability to areas where IG waves contribute significantly.
The strength of the grass sod is an important factor for the stability of a dike in the Netherlands during wave overtopping conditions. Many tests have been performed the last few years with the Wave Overtopping Simulator, leading to the Cumulative Overload Method and a critical velocity. This velocity is a strength parameter of grass on a dike under loads induced by overtopping wave volumes. A new method has been developed to determine this critical velocity, by measuring the force while lifting the grass sod perpendicular to the slope out of the sod. This force is rewritten into the critical grass normal stress which is one of the input parameters for determining the critical velocity of a grass sod. When the critical velocity resulting from this method is compared with the determined critical velocities with the Wave Overtopping Simulator, there is good correspondence between the results for the tested locations. Therefore the sod pulling test could provide results that are reliable enough to determine the critical velocity of a dike section.
One of the main objectives within the EU-project CLASH (www.clash-eu.org) was to create a generic prediction method for wave overtopping at coastal structures by means of the Neural Network technique. An extensive and homogeneous database on wave overtopping was set up within CLASH, mainly with the aim to be used for the training process of the Neural Network (NN). A total number of 10,532 tests from 163 independent test series were screened and included in the database. The final database consists of far more information than needed for the training of the NN: 31 parameters are included to describe each overtopping test of which only 17 are used for the NN development. This explains the possible use of the overtopping database on its own. Plotting various parameters of the database together in graphs gives a clear view on the contents of the database. Also the ranges covered by the parameters can be detected in this way. The creation of the database, the analysis of the database, and the possible use of the database on its own are described in this paper.