Prediction of the Loading Characteristics by Neural Networks Using Structural Analysis of Composite Cylindrical Shells

복합재료 원통쉘의 구조해석을 이용한 신경회로망의 하중특성 추론에 관한 연구

  • 명창문 (정회원·국방과학연구소 중앙전산실) ;
  • 이영신 (충남대학교 기계설비공학과) ;
  • 서인석 (국가보안기술연구소 기반기술연구부)
  • Published : 2002.03.01


The predictions of the loading characteristics was performed by the neural networks which use the results through structural analysis. The momentum backperpagtion which can be modified the teaming rate and momentum coefficient, was developed. Input patterns of the neural networks are the 9 strains which positioned at the side of the shell and output layers is the loading characteristics. Hidden layers were increased from 1 layers to 3 layers. Developed program which were trained by 9 strains predict the loading characteristics under 0.5%. Inverse engineering can be applicable to the composite laminated cylindrical shells with developed neural networks.


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