Simulation on the Performance of Ceramic-Lined Steel Pipe Prepared by SHS Process Based on Artificial Neural Network

Author

Yu Zhu ; Yuxi Ge ; Feng Huang ; Hongjun Ni

Author_Institution

Sch. of Mech. Eng., Nantong Univ., Nantong, China

Volume

1

fYear

2012

fDate

28-29 Oct. 2012

Firstpage

41

Lastpage

44

Abstract

In order to study the relationship between reaction recipe and the performance of ceramic-lined steel pipe prepared by SHS process, 21 groups data obtained in the experiment were used. the different reaction recipes were taken as input data. Besides, the crushing strength and the density of ceramic layer were taken as output data. the BP neural network model was established to simulate the performance of ceramic lined composite steel pipe under different reaction recipes. Simulation results show that: the use of BP neural network simulation of ceramic lined composite tube crushing strength and the density of the steel pipe ceramic layer maximum error of 2.6742% and 4.8445%.It meets the needs in the engineering.

Keywords

backpropagation; ceramics; combustion synthesis; composite materials; compressive strength; high-temperature techniques; mechanical engineering computing; neural nets; pipes; steel; BP neural network model; artificial neural network-based SHS process; ceramic layer density; ceramic lined composite steel pipe; ceramic lined composite tube crushing strength; reaction recipe; self-propagating high temperature synthesis; Biological neural networks; Ceramics; Data models; Neurons; Steel; Training; composite pipe; performance simulating; self-propagating high-temperature synthesis; the BP neural network;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Design (ISCID), 2012 Fifth International Symposium on

Conference_Location

Hangzhou

Print_ISBN

978-1-4673-2646-9

Type

conf

DOI

10.1109/ISCID.2012.19

Filename

6406870