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

Abstract:

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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)

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 et al., "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:

$35.00

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