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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 被引量:2
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作者 Srinivasan CHANDRASEKARAN Arunachalam AMARKARTHIK +2 位作者 Karuppan SIVAKUMAR Dhanasekaran SELVAMUTHUKUMARAN Shaji SIDNEY 《Frontiers in Energy》 SCIE CSCD 2013年第3期279-287,共9页
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... 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%. 展开更多
关键词 ocean wave energy point absorbers heaving body non-floating object heave response ratio artificial neural network (ANN)
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Laboratory experiment on using non-floating body to generate electrical energy from water waves 被引量:2
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作者 Arunachalam AMARKARTHIK Srinivasan CHANDRASEKARAN +1 位作者 Karuppan SIVAKUMAR HarenderSINHMAR 《Frontiers in Energy》 CSCD 2012年第4期361-365,共5页
This paper describes an innovative method of using a nonbuoyant body to harness ocean waves. All the point absorbers are buoyant in nature and move up due to buoyancy and come down because of gravity. The point absorb... This paper describes an innovative method of using a nonbuoyant body to harness ocean waves. All the point absorbers are buoyant in nature and move up due to buoyancy and come down because of gravity. The point absorbers are designed to move along the waves to make the device efficient. These devices face excessive stress during the rough weather on account of the extreme motion of waves and cause the total device failure. The present study shows that using a nonbuoyant body for conven tional point absorber principle is much efficient and safer than any other device proposed till today. A small scale wave energy converter with nonbuoyant body was designed, fabricated and tested in small scale wave maker. An electrical generator was coupled with the device to generate electrical energy from harnessed waves. The generator was electrically loaded and the generated power was measured. It was found from the experiments that the proposed device showed a significant improve ment in electricity generation and safety during extreme conditions. In addition to the electricity generation, the characteristics of the device were also studied by using various wave and device parameters. 展开更多
关键词 ocean wave energy point absorbers heavingbody non-floating object heave response ratio electricalenergy generation
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