プロペラによるサーフェスフォースに影響する諸因子について

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Regression analysis and neural network were applied to evaluate the contribution of major factors of propeller geometry, wake distribution and attack angle variation to propeller induced pressure fluctuations and surface force on the basis of a large volume of data stored through the cavitaion tunnel tests conducted at the Shipbuilding Research Centre of Japan during these two decades. The measured and designated quantities in each case of the test and propeller geometry were readjusted as explanatory variables with properly non-dimensional expression taking into account of theoretical considerations. Not only 1st blade rate components of pressure fluctuation but also 2nd and 3rd components were examined as the target including characteristics of distribution and phase variations. Both multiple linear regression analysis and method of reconstruction learning of the layered neural network were applied. Major results obtained are (1) both cavitation number and tip clearance given as test conditions have significant effect on pressure fluctuations, as expected, (2) effect of attack angle variation and wake distribution suggested by cavitation theory is also confirmed being significant, (3) effect of propeller geometry is relatively less than that of hydrodynamic factors mentioned above, and (4) regarding the characteristics of pressure fluctuation distribution, much influence of cavitation number is shown as a new finding together with marked effect of tip clearance as expected.
社団法人日本船舶海洋工学会の論文

プロペラによるサーフェスフォースに影響する諸因子について

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