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 Prediction of wave transmission over an outer submerged reef of tandem breakwater using RBF-based support vector regression technique(Springer, 2019) Kuntoji, G.; Rao, S.; Rao, M.The development of a mathematical model to determine transmitted wave height over a submerged reef of the tandem breakwater is complex. Therefore, it is necessary for researchers to adopt the physical model study to determine the parameters that influence the performance of breakwaters quantitatively. Physical modelling is laborious, expensive and lengthy in the procedure which makes it inconvenient for immediate needs. From the history, the development of the soft computing model shows that the soft computing techniques can be applied successfully to the prediction of the wave characteristics by making use of experimental data available. Similarly, attempt is made to predict the wave transmission over a submerged reef of tandem breakwater based on the data of Subba Rao developed in 2004 on a tandem breakwater in a 2D wave flume available at NITK Surathkal India using Support Vector Regression (SVR) model with different kernel functions. The non-dimensional input parameters used for the development of the models are five in number. Those inputs are incident wave steepness (Hi/gT2), relative reef crest width (B/Lo), relative reef submergence (F/Hi), relative reef crest height (h/d), depth parameter (d/gT2) and the output as (Ht/Htmax). The 202 data points (70%) are used for training and the 86 data points (30%) for testing out of 288 total data points. The statistical parameters are computed using the predicted and observed data points after training and testing the SVR models. The RBF kernel gives good correlation to the prediction of transmitted wave heights during testing with RMSE as 0.09 and MAE as 0.07. Therefore, the SVR with RBF kernel function can be adopted as an alternative technique to predict the wave characteristics such as wave transmission over a submerged reef of the tandem breakwater. © Springer Nature Singapore Pte Ltd. 2019.Item PSO-SVM approach in the prediction of scour depth around different shapes of bridge pier in live bed scour condition(Springer Verlag service@springer.de, 2019) Marulasiddappa, B.M.; Kuntoji, G.; Rao, M.; Mandal, S.Scour is one of the major factors which affects directly on the durability and safety of the Bridge abutments. Based on the experimental data of Goswami in 2012, an effort is made to predict local scour by using a hybrid approach of Swarm Intelligence based algorithms which is today one of the powerful tools of optimization techniques. In this work, an intelligent model based on support vector machine in combination with the particle swarm optimization (PSO-SVM) technique is developed. The PSO-SVM models are developed with RBF, Polynomial and Linear kernel functions. The circular, rectangular, round-nosed, and sharp-nosed shapes of piers are considered in live bed scour condition. The scour depth around bridge piers is predicted by considering Sediment size, flow velocity, and time of flow as input parameters. Prediction accuracy of the models is evaluated using the model performance indicators such as Root Mean Square Error (RMSE, Correlation Coefficient (CC), Nash Succlift Error (NSE), etc. The results obtained from the model are compared with the measured scour depth to validate the reliability of the hybrid model. Based on the results, PSO based SVM model is found to be successful, reliable, and efficient in predicting the scour depth around the bridge pier. © Springer Nature Singapore Pte Ltd. 2019.Item Prediction of wave transmission over submerged reef of tandem breakwater using PSO-SVM and PSO-ANN techniques(Taylor and Francis Ltd. michael.wagreich@univie.ac.at, 2020) Kuntoji, G.; Rao, M.; Rao, S.Protection of the damaged breakwater from the high-intensity wave action has become inevitable. Submerged reef can act as a protective structure in reducing the wave action. Further, placed the reef structures on the sea side of a conventional rubble mound breakwater will reduce the effects of wave action. The conventional breakwater and reef structure combination is a tandem breakwater. Keeping in mind the end goal to decrease the complexities associated in model scaling, time constraints and cost in conducting the experiments, an attempt is made to apply soft computing techniques such as an Artificial Neural Network (ANN) and Support Vector Machine (SVM) to model various problems of real case scenario, where mathematical modelling is also difficult. In the present study, Particle Swarm Optimization (PSO) optimizes various parameters of ANN and SVM model in predicting the wave transmission over a submerged reef of the tandem breakwater. The performance of proposed hybrid models such as PSO-ANN and PSO-SVM is evaluated using statistical indices. The results show that PSO-SVM tool performs better in predicting the wave transmission compared to PSO-ANN. © 2018, © 2018 Indian Society for Hydraulics.Item Effect of vehicular vibrations on L-4 lumbar vertebrae – A finite element study(Reed Elsevier India Pvt. Ltd., 2025) Kishore, Y.S.; Marulasiddappa, B.M.; Manoj, A.; Raveesh, R.M.; Rakesh, B.; Bhaskar, S.; Kuntoji, G.; Chethan, B.A.Lower Back Pain (LBP) is a global health issue, with increasing prevalence, partly attributed to vehicular vibrations experienced by motorcyclists. The L4 lumbar vertebra is responsible for greater mobility and flexibility of the body, but also is the most crucial body element affected by vehicular vibrations. Anthropometric properties, types of speed humps, and vehicle types are the critical variables that impact bone health during riding, need to be studied. To understand the potential zones of injury, computational simulation can be performed under the influence of vehicle vibrations while crossing different types of speed humps at varying speeds. In the present study, finite element method (FEM) is used to evaluate stress and deformation in the bone. The L4 cortical bone is modelled by considering the CT-Scan data and assumed to be homogeneous and isotropic material. Vibration data is collected using two vehicle types (Type I and Type II) on four different humps (Trapezoidal, Bitumen Semi-circular, Rubber Semi-circular, and Rumble strip). The bone's dynamic behavior is studied using FEM simulation, which involved static structural, modal and transient dynamic analyses. The findings from static analysis indicate that the most concentrated stress is located in the lower pedicle region and is an expected commonplace for injuries because of vibrations. In transient dynamic analysis, Type I vehicle showed a 25 % higher stress than Type II. © 2024 Professor P K Surendran Memorial Education Foundation