A method for predicting ship impact environment based on PI theorem

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Journal of Vibration and Shock ›› 2023, Vol. 42 ›› Issue (19) : 137-143.

ZHAO Xiaojun1, GUO Jun1, YANG Junjie2, WANG Fufan1

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Abstract

Considered many non-linear transmission relationships of underwater non-contact explosion response of ships, a method of RBF network built by K-means clustering and binary K clustering algorithm was applied to train and forecast the velocity spectrum of the impact response. In this network, many variables involved in the simulation are available to represent the characteristic parameters, and the dimensional analysis and π-theorem theory analysis are used to convert the characteristic parameters into dimensionless ones and eliminate the unsuitable parameters. The experimental results show that the dimensionless processing of parameters can improve the accuracy of the network's prediction of velocity spectrum, and significantly increase the proportion of the prediction value deviating from the simulation result within the range of 10%. In addition, it is concluded that the binary K clustering RBF network model combining with the dimensionless parameters has the best prediction effect on the impact spectrum value.

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impact response / dimensionless / neural network / clustering analysis

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ZHAO Xiaojun1, GUO Jun1, YANG Junjie2, WANG Fufan1. A method for predicting ship impact environment based on PI theorem[J]. Journal of Vibration and Shock, 2023, 42(19): 137-143

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