Paper Title:
Analysis in Atmospheric Corrosion Behavior of Bainite Steel Exposed in Offshore Platform Based on the Artificial Neural Network
  Abstract

Back propagation (BP) neural network model was established, using the corrosion data of five kinds of recently developed bainite weathering steel and the commercial weathering steel 09CuPCrNi exposed in the offshore platform in Wanning. The influences of elements P, Cu, C and Cr on the corrosion behavior of weathering steel were studied according to the model. The experimental results indicate that the corrosion depth of bainite weathering steel corroded for 1 year could decline owing to the increasing contents of P, Cu and Cr in steel while C has little effect on the variation of the corrosion depth.

  Info
Periodical
Advanced Materials Research (Volumes 291-294)
Chapter
Material Design of Computer Aided
Edited by
Yungang Li, Pengcheng Wang, Liqun Ai, Xiaoming Sang and Jinglong Bu
Pages
1212-1216
DOI
10.4028/www.scientific.net/AMR.291-294.1212
Citation
M. Zhang, J. F. Yu, S. W. Yang, X. L. He, "Analysis in Atmospheric Corrosion Behavior of Bainite Steel Exposed in Offshore Platform Based on the Artificial Neural Network", Advanced Materials Research, Vols. 291-294, pp. 1212-1216, 2011
Online since
July 2011
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Price
$32.00
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