Explicit Wave-Overtopping Formula for Mound Breakwaters with Crown Walls Using CLASH Neural Network–Derived Data
Publication: Journal of Waterway, Port, Coastal, and Ocean Engineering
Volume 142, Issue 3
Abstract
Based on the Crest Level Assessment of Coastal Structures (CLASH) Neural Network Overtopping prediction method, a new 16-parameter overtopping estimator (Q6) was developed for conventional mound breakwaters with crown walls, both with and without toe berms. Q6 was built up using the overtopping estimations given by the CLASH Neural Network and checked using the CLASH database. Q6 was compared to other conventional overtopping formulas, and the Q6 obtained the lowest prediction errors. Q6 provides overtopping predictions similar to the CLASH Neural Network for conventional mound breakwaters but using only six explanatory dimensionless variables (, and a toe berm variable based on ) and two reduction factors ( and ). Q6 describes explicit relationships between input variables and overtopping discharge, and hence it facilitates use in engineering design to identify cost-effective solutions and to quantify the influence of variations in wave and structural parameters.
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Acknowledgments
The authors are grateful for financial support from the Spanish Ministerio de Economía y Competitividad (Grant BIA2012-33967). The first author was funded through the FPU program (Formación del Profesorado Universitario, Grant AP2010-4366) by the Spanish Ministerio de Educación, Cultura y Deporte. The authors also thank Debra Westall for revising the manuscript.
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Journal of Waterway, Port, Coastal, and Ocean Engineering
Volume 142 • Issue 3 • May 2016
Copyright
© 2015 American Society of Civil Engineers.
History
Received: Feb 5, 2015
Accepted: Jul 14, 2015
Published online: Dec 30, 2015
Published in print: May 1, 2016
Discussion open until: May 30, 2016
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