naa a22 4500 510731503 CHVBK 20180411082954.0 cr unu---uuuuu 180411e20130901xx s 000 0 eng 10.1007/s11708-013-0268-4 doi (NATIONALLICENCE)springer-10.1007/s11708-013-0268-4 Experimental investigation and ANN modeling on improved performance of an innovative method of using heave response of a non-floating object for ocean wave energy conversion [Elektronische Daten] [Srinivasan Chandrasekaran, Arunachalam Amarkarthik, Karuppan Sivakumar, Dhanasekaran Selvamuthukumaran, Shaji Sidney] To convert wave energy into usable forms of energy by utilizing heaving body, heaving bodies (buoys) which are buoyant in nature and float on the water surface are usually used. The wave exerts excess buoyancy force on the buoy, lifting it during the approach of wave crest while the gravity pulls it down during the wave trough. A hydraulic, direct or mechanical power takeoff is used to convert this up and down motion of the buoy to produce usable forms of energy. Though using a floating buoy for harnessing wave energy is conventional, this device faces many challenges in improving the overall conversion efficiency and survivability in extreme conditions. Up to the present, no studies have been done to harness ocean waves using a non-floating object and to find out the merits and demerits of the system. In the present paper, an innovative heaving body type of wave energy converter with a non-floating object was proposed to harness waves. It was also shown that the conversion efficiency and safety of the proposed device were significantly higher than any other device proposed with floating buoy. To demonstrate the improvements, experiments were conducted with non-floating body for different dimensions and the heave response was noted. Power generation was not considered in the experiment to observe the worst case response of the heaving body. The device was modeled in artificial neural network (ANN), the heave response for various parameters were predicted, and compared with the experimental results. It was found that the ANN model could predict the heave response with an accuracy of 99%. Higher Education Press and Springer-Verlag Berlin Heidelberg, 2013 ocean wave energy nationallicence point absorbers nationallicence heaving body nationallicence non-floating object nationallicence heave response ratio nationallicence artificial neural network (ANN) nationallicence Chandrasekaran Srinivasan Department of Ocean Engineering, Indian Institute of Technology Madras, 600036, Chennai, India aut Amarkarthik Arunachalam Department of Mechanical Engineering, Bannari Amman Institute of Technology, 638401, TamilNadu, India aut Sivakumar Karuppan Department of Mechanical Engineering, Bannari Amman Institute of Technology, 638401, TamilNadu, India aut Selvamuthukumaran Dhanasekaran Department of Mechanical Engineering, Bannari Amman Institute of Technology, 638401, TamilNadu, India aut Sidney Shaji Department of Mechanical Engineering, Bannari Amman Institute of Technology, 638401, TamilNadu, India aut Frontiers in Energy Springer Berlin Heidelberg 7/3(2013-09-01), 279-287 2095-1701 7:3<279 2013 7 11708 https://doi.org/10.1007/s11708-013-0268-4 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11708-013-0268-4 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Chandrasekaran Srinivasan Department of Ocean Engineering, Indian Institute of Technology Madras, 600036, Chennai, India aut NATIONALLICENCE 700 1- Amarkarthik Arunachalam Department of Mechanical Engineering, Bannari Amman Institute of Technology, 638401, TamilNadu, India aut NATIONALLICENCE 700 1- Sivakumar Karuppan Department of Mechanical Engineering, Bannari Amman Institute of Technology, 638401, TamilNadu, India aut NATIONALLICENCE 700 1- Selvamuthukumaran Dhanasekaran Department of Mechanical Engineering, Bannari Amman Institute of Technology, 638401, TamilNadu, India aut NATIONALLICENCE 700 1- Sidney Shaji Department of Mechanical Engineering, Bannari Amman Institute of Technology, 638401, TamilNadu, India aut NATIONALLICENCE 773 0- Frontiers in Energy Springer Berlin Heidelberg 7/3(2013-09-01), 279-287 2095-1701 7:3<279 2013 7 11708 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer