Browsing by Author "Ramesh, N."

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    Evaluation of hydrodynamic performance of quarter circular breakwater using soft computing techniques
    (Springer, 2019) Ramesh, N.; Hegde, A.V.; Rao, S.
    Breakwaters are massive structures constructed to provide the required tranquility within the ports. They are also used for safeguarding the beaches from eroding due to the severe action of waves, especially during inclement weather. In recent years, innovative structures such as Semi-circular and Quarter-circular Breakwaters (QBW) are being evolved to fulfill the ever-increasing demand from the coastal sector. QBW is a caisson with quarter circular surface towards incident waves, with horizontal bottom and a vertical wall on its rear side placed on a rubble mound foundation. In this paper, the experimental data collected at National Institute of Technology, Surathkal is used. The data collected is analysed by plotting the non-dimensional graphs of reflection coefficient, reflected wave height and incident wave height for various values of wave steepness. The values are used for prediction of QBW adopting Multi-Layer Perceptron (MLP) and Radial Basis Function (RBF) networks. Goodness-of-Fit (GoF) test using Kolmogorov–Smirnov (KS) test statistic is applied for checking the adequacy of MLP and RBF networks to the experimental data. The performance of these networks is evaluated by using Model Performance Indicators (MPIs), viz. correlation coefficient, mean absolute error and model efficiency. The GoF test results and values of MPIs indicated the MLP is better suited amongst two networks adopted for evaluation of hydrodynamic performance of QBW. © Springer Nature Singapore Pte Ltd. 2019.
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    Prediction of reflection coefficient of a perforated Quarter Circle Breakwater using artificial neural network (ann)
    (2019) Ramesh, N.; Hegde, A.; Rao, S.
    A 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.
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    Prediction of reflection coefficient of a perforated Quarter Circle Breakwater using artificial neural network (ann)
    (Institute of Physics Publishing helen.craven@iop.org, 2019) Ramesh, N.; Hegde, A.; Rao, S.
    A 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.
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    Prediction of wave reflection for quarter circle breakwaters using soft computing techniques
    (National Institute of Science Communication and Policy Research, 2022) Ramesh, N.; Bhaskaran, S.; Rao, S.
    The modified form of the semi-circular breakwater is called Quarter-Circle Breakwater (QBW). It consists of a quarter-circular surface facing incident waves, a horizontal bottom, a rear wall, and is built on a rubble mound foundation. In general, QCB may be constructed as emerged, with and without perforations that may be on one side or either side based on the coastal designer. These perforations dissipate the energy due to the formation of eddies and turbulence created inside the hollow chamber. In the present study, experimental data obtained from Binumol, 2017 are fed as input to both the models. This data is used to predict the reflection coefficient of QBW by adopting the ANN system approach. The reliability of the Artificial Neural Network (ANN) approach is done with statistical parameters, namely Model Performance Analysis (MPA) viz., Correlation Coefficient (CC), Root Mean Square Error (RMSE), Nash-Sutcliffe Efficiency (NSE), and Scatter Index (SI). The results of the MPA indicate that the ANN is suited for predicting the reflection coefficient of QBW. © 2022 National Institute of Science Communication and Information Resources (NISCAIR). All rights reserved.