Neural network simulation on effect of burning rate of modified carbon/carbon composites

Qiang Chen, Hejun Li, Kezhi Li, Shouyang Zhang

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

An artificial neural network (ANN) model for research of the burning rate of modified carbon/carbon composites (C/C composites) is developed by using back-propagation (BP) algorithm. The relationship between the modified additives and burning rate is analyzed on the basis of the model. The results show that the relative error between the expected value and the outputs of the network is lower than 0.3%. By the aid of the ANN model, an optimized combination of these additives is obtained. The burning rate of this kind of samples decreases by 49.3%, which proves the method effective and feasible. The model could reveal the inner regularity between the additive contents and burning rate of C/C composites.

Original languageEnglish
Pages (from-to)249-251+330
JournalHsi-An Chiao Tung Ta Hsueh/Journal of Xi'an Jiaotong University
Volume37
Issue number3
StatePublished - Mar 2003

Keywords

  • Artificial neural network
  • Burning rate
  • Carbon/carbon composites
  • Matrix modification

Fingerprint

Dive into the research topics of 'Neural network simulation on effect of burning rate of modified carbon/carbon composites'. Together they form a unique fingerprint.

Cite this