Faculty Publications
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Item Prediction of damage level of inner conventional rubble mound breakwater of tandem breakwater using swarm intelligence-based neural network (PSO-ANN) approach(Springer Verlag service@springer.de, 2019) Kuntoji, G.; Rao, S.; Rao, M.; Reddy, E.N.B.The conventional rubble mound breakwater is a coastal protective structure commonly used decades before which alone failed to withstand the deepwater wave and its energy, and suffered a catastrophic failure. Keeping in mind both the safe functioning of harbor and stability of the breakwater for the fast-growing economy of the country, different types of breakwaters are being developed to serve this purpose. Tandem breakwater is an innovative type of breakwater, which is a combination of main conventional rubble mound breakwater and submerged reef in front of it. One of the advantages of this breakwater is that most of the wave energy is dissipated and wave intensity is reduced by submerged reef and the smaller waves interact with main breakwater and ensure its stability. Experimental studies are laborious and time-consuming to conduct. Therefore, it is necessary to carry out the detailed study of tandem breakwater stability by making use of simple and alternate techniques using the experimental data. In the present study, an attempt is made to understand the suitability and applicability of PSO-ANN, a hybrid soft computing technique for predicting damage level of conventional rubble mound breakwater of tandem breakwater. Based on the experimental data available in Marine Structure Laboratory, NITK, Surathkal, India, soft computing models are developed. The performances of the models are evaluated using model performance indicators. Results obtained demonstrate that the proposed new approach can be used to predict the damage level of conventional rubble mound breakwater of tandem breakwater efficiently and accurately. © Springer Nature Singapore Pte Ltd. 2019Item Item Concrete cubes as armour unit—an experimental study for berm breakwater(2011) Shirlal, K.G.; Rao, S.; Madhu, M.Berm breakwater consists of a wide berm at or around the water level and has an armour layer, whose shape changes in response to wave action yielding a stable profile. In the present study the influence of wave height, wave period and berm width on the stability of the breakwater as well as on the wave runup and wave rundown are studied. Experiments were conducted on berm breakwater model of 1:30 scale using concrete cubes as armour units. For the given experimental conditions the stability number was found to vary from 2.21 to 3.63. Further the model in 0.37m water depth was more stable than the one in 0.40 and 0.43m. The runup values were within the range of 0.52 to 1.08. While, the rundown values had the variation from 0.45 to 0.88. © 2011 Taylor & Francis Group, LLC.Item Damage level prediction of non-reshaped berm breakwater using ANN, SVM and ANFIS models(Society of Naval Architects of Korea, 2012) Mandal, S.; Rao, S.; Narayana, N.; Lokesha, u.The damage analysis of coastal structure is very important as it involves many design parameters to be considered for the better and safe design of structure. In the present study experimental data for non-reshaped berm breakwater are collected from Marine Structures Laboratory, Department of Applied Mechanics and Hydraulics, NITK, Surathkal, India. Soft computing techniques like Artificial Neural Network (ANN), Support Vector Machine (SVM) and Adaptive Neuro Fuzzy Inference system (ANFIS) models are constructed using experimental data sets to predict the damage level of non-reshaped berm breakwater. The experimental data are used to train ANN, SVM and ANFIS models and results are determined in terms of statistical measures like mean square error, root mean square error, correla-tion coefficient and scatter index. The result shows that soft computing techniques i.e., ANN, SVM and ANFIS can be efficient tools in predicting damage levels of non reshaped berm breakwater. ©SNAK, 2012.Item Particle Swarm Optimization based support vector machine for damage level prediction of non-reshaped berm breakwater(Elsevier Ltd, 2015) Narayana, N.; Mandal, S.; Rao, S.; Patil, S.G.The damage analysis of coastal structure is very much essential for better and safe design of the structure. In the past, several researchers have carried out physical model studies on non-reshaped berm breakwaters, but failed to give a simple mathematical model to predict damage level for non-reshaped berm breakwaters by considering all the boundary conditions. This is due to the complexity and non-linearity associated with design parameters and damage level determination of non-reshaped berm breakwater. Soft computing tools like Artificial Neural Network, Fuzzy Logic, Support Vector Machine (SVM), etc, are successfully used to solve complex problems. In the present study, SVM and hybrid of Particle Swarm Optimization (PSO) with SVM (PSO-SVM) are developed to predict damage level of non-reshaped berm breakwaters. Optimal kernel parameters of PSO-SVM are determined by PSO algorithm. Both the models are trained on the data set obtained from experiments carried out in Marine Structures Laboratory, Department of Applied Mechanics and Hydraulics, National Institute of Technology Karnataka, Surathkal, India. Results of both models are compared in terms of statistical measures, such as correlation coefficient, root mean square error and scatter index. The PSO-SVM model with polynomial kernel function outperformed other SVM models. © 2014 Elsevier B.V.Item Effect of armour unit layers and placement mode in the determination of stability of geotextile sand container (GSC) breakwaters(Elsevier Ltd, 2022) Elias, T.; Geetha, T.; Shirlal, K.G.Geosynthetic Sand Containers (GSCs) are increasingly harnessed for their coastal protection capabilities. Recent studies point to its efficacy to be used even as armour units of breakwaters. The current investigation aims at understanding the effect of armour unit layers and placement modes in altering the stability of GSC breakwaters. Single-layered and double-layered GSC structures with slope parallel and perpendicular placement are tested for stability against wave conditions of the Mangaluru coast. A 1:30 scaled monochromatic wave flume model study is adopted to detail the damage levels and stability of various GSC breakwaters. It is observed that the stability of structure increased by up to 17% when supplemented with double layers. Structure tends to be stable with increasing armour units size and fill percentage. Larger bags stacked to double layers is found to be the most stable configuration. 80% filled, slope parallel placement exhibited the least stability. The paper dealt with all factors affecting structure stability and deduced stability nomograms helpful for coastal engineers to design GSC breakwaters. © 2022
