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In order to extend the statistical energy analysis(SEA) method to predict the vibration and sound radiation of underwater structures,we mainly analyze the effect of water loading on the key parameters in SEA and propose the approximate expressions of modal density and mean square velocity of submerged plates.With the radiation efficiency of submerged plates previously proposed by us,the modified SEA solutions of the radiated sound power and mean square velocity of submerged stiffened rectangular plates are established.Numerical examples show that the modified SEA solutions are more close to the theoretical solutions than the present SEA solutions,and reflect the mean value or trend of the theoretical solution much better,especially at lower frequencies.An experiment of point-exciting submerged plates was done in a lake.The experiment values show that for both un-stiffened and stiffened plates,the modified SEA solutions have a good agreement while the present SEA solution has considerable error,which validates the established statistical model.
In order to extend the statistical energy analysis (SEA) method to predict the vibration and sound radiation of underwater structures, we mainly analyze the effect of water loading on the key parameters in SEA and propose the approximate expressions of modal density and mean square velocity of submerged plates. Based on the radiation efficiency of submerged plates previously proposed by us, the modified SEA solutions of the radiated sound power and mean square velocity of submerged stiffened rectangular plates are established. Numerical examples that that modified SEA solutions are more close to the theoretical solutions than the present SEA solutions, and reflect the mean value or trend of the theoretical solution much better, especially at lower frequencies. An experiment of point-exciting submerged plates was done in a lake. experiment values show that for both un-stiffened and stiffened plates, the modified SEA solutions have a good agreement while the present SEA solution has considerab le error, which validates the established statistical model.