By Topic

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

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Yu Zhu ; Sch. of Mech. Eng., Nantong Univ., Nantong, China ; Yuxi Ge ; Feng Huang ; Hongjun Ni

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.

Published in:

Computational Intelligence and Design (ISCID), 2012 Fifth International Symposium on  (Volume:1 )

Date of Conference:

28-29 Oct. 2012