CLASH test results: Overtopping performance of different armour units for rubble mound breakwaters

http://www.itv.is/ics2005/Data/B1.3/Pearson_pa.pdf

Please note that the coefficients given in this paper have been updated after further analysis. Modified coefficients, with even better performance of Xbloc, have been published in Coastal Engineering 56 (2009) by T.Bruce et al.

These modified coefficients are also given on the following page:

 Overtopping and wave reflection

Abstract

The overtopping database of the CLASH project (Steendam et al., 2004) contains more than 10000 test results on wave overtopping at coastal structures. The database was used as input for a neural network which resulted in a generic prediction method for overtopping at coastal structures (Pozueta et al., 2004; Van der Meer et al., 2005). Interim analysis of the overtopping database indicated that there are some “white spots” where further model tests would be advantageous. This paper describes a major programme of tests to better establish the influence of armour roughness and permeability on overtopping. Specifically, the tests determined the relative difference in overtopping behaviour for various types of armour units. Roughness factors γf for the database and for use in the neural network prediction of overtopping were determined for rock (two layers), cubes (single-layer and two-layers), Tetrapod, Antifer, Haro, Accropode, Core-Loc and Xbloc.

Introduction

The overtopping database of the CLASH project (Steendam et al., 2004) contains more than 10000 test results on wave overtopping at coastal structures and is therefore considerably larger than initially foreseen. The overtopping database is based on existing data which were partly at the possession of partners within CLASH, but also data from elsewhere in Europe and worldwide were gathered. In a first phase of the set-up of the database, a detailed inventory was made of what was available at universities and research institutes on data sets on overtopping. Part of these data is based on generic tests, which were freely available, many others however are based on site-specific and practical tests, which often are confidential. All these data have been gathered, together with corresponding reports, containing all relevant information about the tests. The database was used as input for a neural network which resulted in a generic prediction method for overtopping at coastal structures (Pozueta et al., 2004; Van der Meer et al., 2005). Interim analysis of the overtopping database indicated that there are some “white spots” where further model tests would be advantageous. Test programmes to fill these “white spots” were devised. This paper describes a major programme of tests to better establish the influence of roughness/permeability on overtopping. Specifically, the objective was to determine the relative difference in overtopping behaviour for various types of armour units. Finally, this should lead to roughness factors γf for the database and for use in the neural network prediction of overtopping.

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