Conference Papers

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506

Browse

Author: search.filters.author.Rao, M.Has files: No

Search Results

Now showing 1 - 10 of 10
  • No Thumbnail Available
    Item
    Prediction of wave transmission characteristics at submerged reef breakwater
    (Elsevier Ltd, 2015) Sreeranga, S.; Shirlalb, K.G.; Rao, M.
    Submerged reef breakwater is an off shore breakwater, with its crest at or below the sea water level, used for protection of coastal structures and beaches from the erosion caused by wave action. Reef breakwaters are coast parallel structure built wi th an objective of reducing the wave action on the beach. It is constructed with uniformed size armour whose weight is sufficient to resist wave attack. Modeling of co-efficient of wave transmission (Kt) of such reef is a topic chosen for present study. Preliminary equation is derived from dimensional analysis as semi empirical equation which involves different parameters like wave characteristics, reef dimensions and nominal diameter of armour units. Simulation of results is undertaken with modeling in MATLAB. Results obtained are thus compared with experimental results and existing equations from the literature. Finally semi-empirical equation for Kt is established. © 2015 Published by Elsevier Ltd.
  • No Thumbnail Available
    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.
  • No Thumbnail Available
    Item
    Experimental investigations of structurally pre-stressed actuator based active vibration isolation system
    (American Institute of Physics Inc. subs@aip.org, 2020) Divijesh, P.; Rao, M.; Rao, R.; Dheeraj; Sushith
    Active Vibration Isolation is considered to be one of the most effective methods to reduce the undesirable vibrations generated in any mechanical system. Stacked piezoactuators are suitable actuators used for variety of applications such as micro and nano positioning applications because of their high stiffness and fast response. However in order to provide optimal preloading force to the stacked actuators for longer lifetime and better performance with dynamic applications these stack actuators are structurally pre-stressed. In the present work, an active vibration isolation system is designed and developed using two structurally pre-stressed actuators namely source actuator and isolator actuator where source actuator is used for generating vibrations and the isolator actuator to nullify the generated vibrations. Initially the transfer function of the MLA 10x10x20 stack actuator was identified using its known parameters and was modeled in MATLAB/ Simulink to estimate the simulated displacement for a particular voltage at different frequencies. The simulated displacements were then compared with experimental displacements for different frequencies and the results were plotted. The experimental displacements of both source actuator and isolator actuator were found at different frequencies and was compared with the simulated displacements for a particular voltage and the results were plotted. Finally active vibration isolation experiments were carried out using the proposed set up for a particular voltage at different frequencies and the percentage of vibration isolation achieved was also estimated. © 2020 Author(s).
  • No Thumbnail Available
    Item
    An experimental investigation on toe stability for vertical—caisson breakwaters
    (Springer Science and Business Media Deutschland GmbH, 2021) Kumaran, V.; Subba Rao; Rao, M.
    For the design and construction of a vertical-caisson breakwater which is more significant task in the field of ocean engineering, since the incidicent wave and reflected wave acting on the structure causes severe bottom scouring and final leads to failure of the structure. The influences of wave height, wave period, and toe armor unit stability are under investigation in this study. The experimental work conducted by Brebner and Donnelly [1], was put forward, that for a certain fixed relative foundation depth (d1/d) and wavelength (L), the significant wave height (Hs), will have an exponential relationship with the number of rocks displaced in the armor layer of the toe of the vertical-caisson structure. The investigation are conducted in the regular 2D wave flume at wave mechanics laboratory, NITK, Surathkal. The present paper provides the required information regarding the damage level of toe armor units in transition water depths and the effect of wave parameters are analyzed. © Springer Nature Singapore Pte Ltd 2021.
  • No Thumbnail Available
    Item
    Development of piezoactuator based rotary tool feeding system for micro-EDM
    (Elsevier Ltd, 2022) Venugopal, T.R.; Rao, M.; Rao, R.; Sushith, K.
    Micro Electrical Discharge Machining (micro-EDM) is widely employed for the fabrication of component parts used in Micro Electro Mechanical System (MEMS) devices and many other applications. Spark gap, being a critical process parameter in micro-EDM, must be maintained at optimum length for stable machining. To meet this critical requirement, the tool feeding system employed in micro-EDM must be capable of feeding the tool electrode adaptively to maintain the optimum spark gap. This paper proposes to develop a Flexurally Amplified Piezoactuator based rotary tool feeding system for micro-EDM. Hysteresis behavior of the piezoactuated tool feeding system is modeled using Maxwell's hysteresis model. Model based tool feed control experiments were conducted for different feed displacements ranging from 100 μm to 600 μm and spindle rotational speeds from 400 rpm to 1800 rpm. From the experimental results it is observed that the developed rotary tool feeding system performs with an error less than 1% for larger feed displacements at higher spindle speeds. Machining experiment with tool rotation enhanced blind hole depth by 29.21% compared to machining without tool rotation. [copyright information to be updated in production process]. © 2022 Elsevier Ltd. All rights reserved.
  • No Thumbnail Available
    Item
    A Machine Learning Approach for Daily Temperature Prediction Using Big Data
    (Springer Science and Business Media Deutschland GmbH, 2022) Divakarla, U.; Chandrasekaran, K.; Hemant Kumar Reddy, K.H.K.; Reddy, R.V.; Rao, M.
    Due to global warming, weather forecasting becomes complex problem which is affected by a lot of factors like temperature, wind speed, humidity, year, month, day, etc. weather prediction depends on historical data and computational power to analyze. Weather prediction helps us in many ways like in astronomy, agriculture, predicting tsunamis, drought, etc. this helps us to be prepared in advance for any kinds disasters. With rapid development in computational power of high end machines and availability of enormous data weather prediction becomes more and more popular. But handling such huge data becomes an issue for real time prediction. In this paper, we introduced the machine learning-based prediction approach in Hadoop clusters. The extensive use of map-reduce function helps us distribute the big data into different clusters as it is designed to scale up from single servers to thousands of machines, each offering local computation and storage. An ensemble distributed machine learning algorithms are employed to predict the daily temperature. The experimental results of proposed model outperform than the techniques available in literature. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
  • No Thumbnail Available
    Item
    Comprehensive Prediction Model for Player Selection in FIFA Manager Mode
    (Springer Science and Business Media Deutschland GmbH, 2023) Divakarla, U.; Chandrasekaran, K.; Hemant Kumar Reddy, K.; Rao, M.
    Game is one of the most entertaining shows for today’s all generation peoples, particularly Football in most part of countries of the world. Football as a sport is only growing more and more popular every day. It is currently the world’s most-watched sport and has the highest viewership audience. As a result, a whole industry has arisen around this sport with one important part of it being FIFA. The amount of budget allocated and the number of persons involved in a Football game directly or indirectly can affect the financial budget of a person to a federation's finance. In such cases, player selection for a finalist from the federation is the most crucial task. Every year different approaches were investigated for player selections, but none of them was regarded as the best approach for team selection. Thus, there is a need for a standard approach for finding out the perfect players for their teams with the exact qualities that they demand. In response, we have developed a machine learning model that predicts players who could replace a current existing player in a team. Along with that, we have also incorporated Data Analytics that helps us decide which factors would be more important than others. The proposed prediction model is implemented and the results of our machine learning (SAGA-ML) tool are applied to Electronics Arts’ FIFA Soccer game. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
  • No Thumbnail Available
    Item
    Implementation of structurally pre-stressed piezo actuator based active vibration isolation system for micro milling
    (Elsevier Ltd, 2023) Divijesh, P.P.; Rao, M.; Rao, R.; Jain, N.; Prabhu, P.
    This paper presents the implementation of a structurally pre-stressed piezo actuator based active vibration isolation system incorporated with tool based micromachining setup for analyzing and comparing the milled pocket depth surface before and after isolation. A carbide micro end mill tool with 1 mm diameter and 4 flutes has been used for carrying out pocket milling experiments with and without vibrations on copper work pieces having 3 mm thickness. The machining parameters selected were spindle speed of 16,000 rev/min with 64 mm/min feed rate and 50 lm depth of cut. Two sets of pocket milling experiments were carried out using the proposed vibration isolation setup one with vibration and the other without vibration. In the first set of experiment, the source actuator was actuated for generating vibrations during pocket milling whereas in the second set of experiment, both source and isolator actuators were actuated for nullifying the vibrations generated during pocket milling. The macroscopic lens output images of the pocket depth surfaces before and after isolation were then compared corresponding to various actuation voltages at different frequencies using the proposed vibration isolation setup. Based on the macroscopic lens output images it was observed that the milled pocket depth surface obtained by actuating only source actuator showed distinct rings wherein the ring count matched with frequency and feed rate that has been provided during machining. However, the milled pocket obtained by actuating both source and isolator actuators resulted in surface characteristics with less pronounced rings similar to that of regular machining. Also the rings that has been formed showed more defined edges with the increase in actuator voltage indicating that these distinct patterns were caused due to the vibrations generated by the source actuator alone and not other factors. © © 2023 Elsevier Ltd. All rights reserved.
  • No Thumbnail Available
    Item
    Effect of data normalisation in estimating wave overtopping discharge parameter of semicircular breakwater using ANN and Random Forest.
    (Institute of Physics, 2023) Shankara Krishna, A.; Mane, V.; Rao, S.; Rao, M.
    Breakwaters are the structures constructed in the coastal areas to maintain calm inside the port or prevent beach erosion. Semi-circular Breakwater (SCB) is an innovative type of Breakwater made of hollow caisson on a base slab with or without perforations. In this study, the wave overtopping discharge parameter of an SCB is estimated using Artificial Neural Network and Random Forest. The data is collected and used in the current research from an experimental investigation conducted in the Wave Mechanics Laboratory of the Department of Water Resources and Ocean Engineering (WROE), NITK Surathkal. Using this experimental data, the ANN and Random Forest models are developed for the prediction of the wave overtopping discharge parameter of an SCB. The performance of the models is evaluated using different statistical parameters. Data with and without normalisation are used separately to check the effect of normalisation in the prediction of wave overtopping discharge parameter using ANN and Random Forest. From the results, it is found that ANN gives better results when the data is normalised. The performance of Random Forest is independent of the data normalisation. © Published under licence by IOP Publishing Ltd.
  • No Thumbnail Available
    Item
    Physical Model Study on the Soft Option of Coastal Protection Works by Vegetation Meadow—A Review
    (Springer Science and Business Media Deutschland GmbH, 2023) Surakshitha; Rao, M.; Rao, S.
    As the frequency of occurrence of the coastal hazards increasing along with sea level rise the number of hard structures installed to mitigate the beach erosion, flooding needs to be increased or upgraded. Attention on strategically utilizing the ecosystem service provided by vegetation to tackle such hazard is increasing in the coastal engineering field as the negative impact on the environmental and ecological system is less in this approach compared to conventional approach. The resistance offered by the vegetation meadow on wave energy depends on the submergence ratio, density of the plant per area, the rigidity of vegetation, and also on hydrodynamic characteristics. Prediction of behavior and effect on the wave propagation is necessary to determine the degree of effectiveness of the vegetation field in coastal defense. The physical model study which involves laboratory testing of small-scale models is one of the tools to examine and verify the effectiveness of structure under the action of the wave. The present paper focuses on the review of physical model study, their key findings and highlighting the criteria based on which material is selected to model the various real plants. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.