Please use this identifier to cite or link to this item: https://idr.nitk.ac.in/jspui/handle/123456789/8833
Full metadata record
DC FieldValueLanguage
dc.contributor.authorRamesh, N.
dc.contributor.authorHegde, A.
dc.contributor.authorRao, S.
dc.date.accessioned2020-03-30T10:22:50Z-
dc.date.available2020-03-30T10:22:50Z-
dc.date.issued2019
dc.identifier.citationJournal of Physics: Conference Series, 2019, Vol.1276, 1, pp.-en_US
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/8833-
dc.description.abstractA breakwater is structure which is generally adopted in not only protecting the shoreline, but also in creating tranquil zone on the lee side of the structure minimizing the various movements on the anchored ships / vessels due to the wave / tidal action in the region resulting in easy handling of goods. Over the years, breakwater was generally constructed using rubble mounds. Due to the increase in demand for the coastal development all over the world, many innovative Breakwater were evolved as against the rubble mound. In the recent times, in order to economize the innovative breakwater construction, Semi Circular caisson type Breakwater has been studied. Based on Semi circularBreakwater (SBW), Quarter circular Breakwater (QBW) has been evolved. The hydrodynamic performance of a coastal structure is important, because it involves many parameters to be considered while designing a safe and economical structure. The hydro-dynamic performance of a Quarter circular breakwater is studied in a monochromatic wave flume in the Department of Applied Mechanics and Hydraulics, National Institute of Technology, Surathkal Karnataka, India. In the present paper reflection coefficient (Kr) of a perforated Quarter circular Breakwater (QBW) with various S/D ( spacing to diameter ratio) values is predicted applying Artificial Neural Network (ANN) technique using MATLAB. Four networks were constructed by varying the number of hidden layers based on the input parameters, which affects the performance of the breakwater. The predicted values of reflection coefficient using ANN, are compared with the experimental results. � Published under licence by IOP Publishing Ltd.en_US
dc.titlePrediction of reflection coefficient of a perforated Quarter Circle Breakwater using artificial neural network (ann)en_US
dc.typeBook chapteren_US
Appears in Collections:2. Conference Papers

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.