Ocean wave is a rich source of renewable energy with much higher power density than winds. Various WEC technologies have been proposed or are under development. In this study, we developed a 2-dimensional (2D) model and analyzed the rotational motion of the lift-type rotor’s blade under steady flow and unsteady flow. The numerical model was validated by experiments under steady flow. Fast Fourier Transform (FFT) analysis was performed to identify the major contribution of frequency in terms of vortexes generated in the flow field. A comparative study was also performed by comparing all the cases in terms of energy conversion efficiency under different wave conditions. It turns out that the efficiency of energy conversion has a maximum value in the steady flow, while the efficiency for unsteady flow keeps decreasing, therefore this is highly due to the increased dissipation because of the oscillating. When the flow is oscillating, the rotational speed of the rotor under periodic condition is lower than the rotational velocity with steady flow, and a curve fitting was performed in this study to predict the periodic average rotational speed. We conclude that for oscillating flow a minimum of 1.6% energy conversion efficiency can be expected, but it may vary for the actual ocean waves. It is expected the current 2D simulation results can contribute to the wave energy community, especially when the rotor design and optimization is required.
Three hundred and six coal samples were taken from main coal mines of twenty-six provinces, autonomous regions, and municipalities in China, according to the resource distribution and coal-forming periods as well as the coal ranks and coal yields. Nitrogen was determined by using the Kjeldahl method at U.S. Geological Survey (USGS), which exhibit a normal frequency distribution. The nitrogen contents of over 90% Chinese coal vary from 0.52% to 1.41% and the average nitrogen content is recommended to be 0.98%. Nitrogen in coal exists primarily in organic form. There is a slight positive relationship between nitrogen content and coal ranking.
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