Penetration Depth of Projectiles Into Concrete Using Artificial Neural Network

Li Jianguang1、Li Yongchi1、Wang Yulan2

Strategic Study of CAE ›› 2007, Vol. 9 ›› Issue (8) : 77-81.

PDF(572 KB)
PDF(572 KB)
Strategic Study of CAE ›› 2007, Vol. 9 ›› Issue (8) : 77-81.

Penetration Depth of Projectiles Into Concrete Using Artificial Neural Network

  • Li Jianguang1、Li Yongchi1、Wang Yulan2

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Abstract

In this article,  nonlinear mapping relation between input of 13 variables of lp and σyt/σyp etc. , and output of penetration depth is established by dimensional analysis and theory of artificial neural networks for problem of penetration depth of projectiles into concrete.  Moreover,  a satisfied output about penetration depth from RBF neural network is gotten by a group of input sets and corresponding output sets,  which comes from M.  J.  Forrestal 's document.

Keywords

neural networks / dimensional analysis / penetration depth of projectiles into concrete / nonlinear mapping relation / RBF neural networks

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Li Jianguang,Li Yongchi,Wang Yulan. Penetration Depth of Projectiles Into Concrete Using Artificial Neural Network. Strategic Study of CAE, 2007, 9(8): 77‒81
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