Long-Term Atmospheric Corrosion in Spain: Results after 13–16 Years of Exposure and Comparison with Worldwide Data

Long term atmospheric corrosion in Mauritius

Corrosion Engineering Science and Technology ◽

10.1179/1743278214y.0000000240 ◽

2014 ◽

Vol 50 (2) ◽

pp. 155-159 ◽

Cited By ~ 7

Author(s):

B. Y. R. Surnam ◽

C. W. Chiu ◽

H. P. Xiao ◽

H. Liang

Keyword(s):

Atmospheric Corrosion

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Raman imaging of ancient rust scales on archaeological iron artefacts for long-term atmospheric corrosion mechanisms study

Journal of Raman Spectroscopy ◽

10.1002/jrs.1581 ◽

2006 ◽

Vol 37 (10) ◽

pp. 1228-1237 ◽

Cited By ~ 131

Author(s):

Delphine Neff ◽

Ludovic Bellot-Gurlet ◽

Philippe Dillmann ◽

Solenn Reguer ◽

Ludovic Legrand

Keyword(s):

Atmospheric Corrosion ◽

Raman Imaging ◽

Archaeological Iron ◽

Corrosion Mechanisms

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The role of Sn on the long-term atmospheric corrosion of binary Cu-Sn bronze alloys in architecture

Corrosion Science ◽

10.1016/j.corsci.2019.01.002 ◽

2019 ◽

Vol 149 ◽

pp. 54-67 ◽

Cited By ~ 2

Author(s):

T. Chang ◽

G. Herting ◽

S. Goidanich ◽

J.M. Sánchez Amaya ◽

M.A. Arenas ◽

...

Keyword(s):

Atmospheric Corrosion

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Localisation of oxygen reduction sites in the case of iron long term atmospheric corrosion

Corrosion Science ◽

10.1016/j.corsci.2011.04.002 ◽

2011 ◽

Vol 53 (8) ◽

pp. 2468-2473 ◽

Cited By ~ 18

Author(s):

Judith Monnier ◽

Emilien Burger ◽

Pascal Berger ◽

Delphine Neff ◽

Ivan Guillot ◽

...

Keyword(s):

Oxygen Reduction ◽

Atmospheric Corrosion

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Long-term prediction on atmospheric corrosion data series of carbon steel in China based on NGBM(1,1) model and genetic algorithm

Anti-Corrosion Methods and Materials ◽

10.1108/acmm-11-2017-1858 ◽

2019 ◽

Vol 66 (4) ◽

pp. 403-411 ◽

Cited By ~ 1

Author(s):

Yuanjie Zhi ◽

Dongmei Fu ◽

Tao Yang ◽

Dawei Zhang ◽

Xiaogang Li ◽

...

Keyword(s):

Genetic Algorithm ◽

Carbon Steel ◽

Atmospheric Corrosion ◽

Data Series ◽

Data Sets ◽

Content Type ◽

Term Prediction ◽

Long Term Prediction ◽

Corrosion Data

PurposeThis study aims to achieve long-term prediction on a specific monotonic data series of atmospheric corrosion rate vs time.Design/methodology/approachThis paper presents a new method, used to the collected corrosion data of carbon steel provided by the China Gateway to Corrosion and Protection, that combines non-linear gray Bernoulli model (NGBM(1,1) with genetic algorithm to attain the purpose of this study.FindingsResults of the experiments showed that the present study’s method is more accurate than other algorithms. In particular, the mean absolute percentage error (MAPE) and the root mean square error (RMSE) of the proposed method in data sets are 9.15 per cent and 1.23 µm/a, respectively. Furthermore, this study illustrates that model parameter can be used to evaluate the similarity of curve tendency between two carbon steel data sets.Originality/valueCorrosion data are part of a typical small-sample data set, and these also belong to a gray system because corrosion has a clear outcome and an uncertainly occurrence mechanism. In this work, a new gray forecast model was proposed to achieve the goal of long-term prediction of carbon steel in China.

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Long-Term Atmospheric Corrosion Behavior of Epoxy Prime Coated Aluminum Alloy 7075-T6 in Coastal Environment

Materials ◽

10.3390/ma11060965 ◽

2018 ◽

Vol 11 (6) ◽

pp. 965 ◽

Cited By ~ 5

Author(s):

Sheng Zhang ◽

Yuting He ◽

Teng Zhang ◽

Guirong Wang ◽

Xu Du

Keyword(s):

Aluminum Alloy ◽

Corrosion Behavior ◽

Atmospheric Corrosion ◽

Coastal Environment ◽

Aluminum Alloy 7075

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Atmospheric Corrosion in Marine Environments

CORROSION ◽

10.5006/0010-9312-34.12.433 ◽

1978 ◽

Vol 34 (12) ◽

pp. 433-437 ◽

Cited By ~ 12

Author(s):

R. A. LEGAULT ◽

V. P. PEARSON

Keyword(s):

Corrosion Behavior ◽

Atmospheric Corrosion ◽

Low Alloy Steels ◽

Marine Environments ◽

Weight Losses ◽

Alloy Steels

Abstract It has been demonstrated that the natural atmospheric corrosion behavior of low alloy steels in marine environments can be accurately described by an equation of the form: ΔW = KtN. With this relationship, reliable predictions of long term weight losses can be made from as few as two sets of determinations obtained in relatively short exposures. The reliability of this relationship has also been established for galvanized and aluminized steels.

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