New numerical and laboratory investigations on wave overtopping at dikes with crown walls were carried out. The main objective of the experiments, presented for the first time in this contribution, is to investigate the effects of the inclusion of bullnoses on the top of crown walls to reduce the average overtopping discharge q. The study extends the experience available on structures with bullnoses, which is so far limited to dikes with promenades under non-breaking wave conditions. The new data on q resulting from the campaign of experiments are compared with the existing predicting formulae for q of the EurOtop manual (2016), in order to verify and upgrade their range of validity. A formulation for a new correction coefficient γ** to be included in the formulae is proposed to account for the effects of the bullnose also in case of structures subjected to breaking waves. A simple solution to represent the geometry of the bullnoses in the EurOtop Artificial Neural Network (ANN) is investigated. The solution, which avoids the ANN re-training and does not require the inclusion of new input parameters, applied to new and existing data gives promising results.

Reduction of the wave overtopping discharge at dikes in presence of crown walls with bullnoses

Zanuttigh, Barbara;Formentin, Sara Mizar
2018

Abstract

New numerical and laboratory investigations on wave overtopping at dikes with crown walls were carried out. The main objective of the experiments, presented for the first time in this contribution, is to investigate the effects of the inclusion of bullnoses on the top of crown walls to reduce the average overtopping discharge q. The study extends the experience available on structures with bullnoses, which is so far limited to dikes with promenades under non-breaking wave conditions. The new data on q resulting from the campaign of experiments are compared with the existing predicting formulae for q of the EurOtop manual (2016), in order to verify and upgrade their range of validity. A formulation for a new correction coefficient γ** to be included in the formulae is proposed to account for the effects of the bullnose also in case of structures subjected to breaking waves. A simple solution to represent the geometry of the bullnoses in the EurOtop Artificial Neural Network (ANN) is investigated. The solution, which avoids the ANN re-training and does not require the inclusion of new input parameters, applied to new and existing data gives promising results.
2018
Proceedings of 36th International Conference on Coastal Engineering (ICCE)
1
14
Zanuttigh, Barbara; Formentin, Sara Mizar
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/777039
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