Wave overtopping at rubble mound breakwaters with a non-reshaping berm
datasetposted on 30.06.2013 by J.C. [Jan Kees] Krom
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
Wave overtopping was investigated by means of a physical model. The breakwater scale model was divided into 8 collection bins. Overtopped volumes were collected and pumped into floating tanks further down the flume. After the experiment the mass of the floating tanks was measured and the mean overtopping discharge could be determined for 8 horizontal positions on the breakwater. The measured total overtopping discharges cannot be predicted accurately by existing prediction methods. On the basis of experimental data a new prediction method was proposed that achieves an excellent fit for total overtopping. The crest freeboard definition was adjusted to account for the permeability of the crest. The reduction factor accounting for slope roughness was made dependent on the Iribarren number. For Iribarren numbers higher than 6, this method calculates no reduction of overtopping due to slope roughness. The effect of a permeable berm on total overtopping was found to be remarkably different from the effect of an impermeable berm. Permeable berms below Still Water Level (SWL) lead to less reduction of overtopping than impermeable berms below SWL. Berms above SWL lead to wave breaking on the slope in front of the berm. Contrarily to impermeable berms above SWL, a permeable berm above SWL leads to significant reduction of overtopping. The measured spatial distribution of overtopping is associated with a lot of seemingly random behaviour. Large differences were found with the experimental data of Lioutas (2010). It is suspected that the used experiment setup gives rise to significant model effects for the spatial distribution of overtopping. An experiment setup was recommended that is expected to more accurately model the behaviour of the prototype situation. Data on the spatial distribution of overtopping could not accurately be predicted by existing prediction methods. In some cases existing prediction methods provided an upper limit for overtopping (Juul Jensen, 1984) but none led to a good fit with the experimental data. A new reduction factor was found that reduces the amount of scatter and provides a conservative prediction of the experimental data.