Development of a Corrosion Model for Prediction of Atmospheric Corrosion of Mild Steel

Mahendra Adikari; Nanda Munasinghe

doi:doi:10.11648/j.ajasr.20160206.20

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Development of a Corrosion Model for Prediction of Atmospheric Corrosion of Mild Steel

Mahendra Adikari, Nanda Munasinghe

Published in American Journal of Applied Scientific Research (Volume 2, Issue 6)

Received: 30 September 2016 Accepted: 28 October 2016 Published: 28 December 2016

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Abstract

Corrosion is a naturally occurring phenomenon commonly defined as the deterioration or loss of functions of materials (usually metals) due to the effect of the environmental factors. According to the nature of environment, corrosion can be broadly categorized as corrosion in atmosphere, corrosion in water, corrosion in sea, corrosion in soil etc. Among these types, corrosion of steel in atmosphere is a problem of great interest. Since steel is the most extensively used structural material in industry, and it is well accepted fact that the cost of material deterioration in an atmospheric environment is enormous. Corrosion of metal in atmosphere is inevitable but is controllable with the aid of proper corrosion management systems. For the implementation of a proper corrosion management system it is necessary to study the corrosive nature (corroivity) of the operation environment of a material. Development of a relationship between corrosivity and environmental variables such as relative humidity, temperature, salinity etc. which is known as Corrosion modeling is widely used method use for the evaluation of corrosivity of atmosphere. This paper describes the work carried out to formulate a model for the prediction of corrosion of mild steel under Sri Lankan atmospheric conditions. For this purpose, a model was proposed which is based on published literature on corrosion modeling. The proposed model was calibrated by the data obtained from field exposure tests which were conducted in four different locations in Sri Lanka. The chi-square goodness of fit test has been used to find out the performance of model. The model showed good performance with goodness of fit at 95% significance level. Finally, the model was validated with different set of data and the prediction performance of this model shows a good capability on forecasting of the rate of corrosion of mild steel in different atmospheric conditions in Sri Lanka.

Published in	American Journal of Applied Scientific Research (Volume 2, Issue 6)
DOI	10.11648/j.ajasr.20160206.20
Page(s)	91-96
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2016. Published by Science Publishing Group

Keywords

Corrosion Model, Atmospheric Corrosion, Mild Steel Corrosion, Weight Loss

References

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[2]	K. R. Trethewey, J. Chamberlain, Corrosion for Students of Science and Engineering, New York, 1988.
[3]	Roberg., Pierre, R., Hand Book of Corrosion Engineering, New York, 2000.
[4]	D. E. Klinesmith, R. McCuen, P. Albrecht; Effect of Environmental Condition on Corrosion Rate, Journal of Materials in Civil Engineering, ASCE, Vol. 19, 2007, P. 121–129.
[5]	Salvador, Pintosa., Nestor, V., Queipoa, OladisTroconis., deRincoÂnb., Alvaro RincoÂnb., Manuel Morcilloc, Artificial Neural Network Modelling of Atmospheric Corrosion in the MICAT project. Corrosion Science 42 (2000) P. 35-52.
[6]	Guttman H., Sereda, P. J., Metal Corrosion in the Atmosphere, ASTM STP 435, American Society for Testing and Materials 1968, P. 326-359.
[7]	Haynie. F. H., Uphan, J. B.; Corelation Between Corrosion Behaviour of Steel and Atmospheric Pollution Data, ASTM STP 558, American Society for Testing and Materials 1974, PP. 33-51.
[8]	Hakkararaien, T.,Ylasari,S.;Atmospheric Corrosion, W. H. Ailor,Ed John wiley and Sons New York, 1982, pp. 787-795.
[9]	Knotkova, D., Barton, K.; Corrosion Aggressivity of Atmosphere, ASTM STP 767, Atmosphericcorrosion of metals, American Society for Testing and Materials, 1982,P.225-249.
[10]	Winston, R, R., Uhling’s Corrosion Handbook, New York, 2005, P. 580.
[11]	Antonio, R, Mendoza., Francisco, Corvo.; Outdoor and Indoor Atmospheric Corrosion of NonferrousMetals, Journal of Corrosion Science, Vol 42, 2000, P. 1123-1147.
[12]	Kucera, V., Mapping Effects on Materials in Manual Mapping Critical Load, ICP Materials Coordination Centre, Stockholm, Sweden, 2004, Available online: http://icpmapping.org.
[13]	/NN/,Corrosivity of AtmospheresMeasurement of Pollutions,International standard organization, ISO 9225.
[14]	NN. Corrosion of Metals and Alloys - Removal of Corrosion Products from Corrosion Test Specimens, International Standard Organization, ISO 8407.
[15]	Panchenko, Yu. M., Marshakov, A. I., Long-term prediction of metal corrosion losses in atmosphere using a power-linear function, Corrosion Science, 109 (2016), P. 217-229.
[16]	Alcántara,J.,Chico,B.,Díaz,I., de la Fuente, D., Morcillo, M., Airborne chloride deposit and its effecton marine atmospheric corrosion of mild steel, Corrosion Science 9, (2015), P. 74-88.
[17]	Vasconcelos, H. C., Fernández-Pérez, B, M., J. Morales, Souto, R, M., S, González., Cano, V., Santana, j., Development of Mathematical Models to predict the Atmospheric Corrosion Rate of Carbon Steel in Fragmented Subtropical Environments, International Journal of electrochemical Science, 09 (2014), p.6514-6528.

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APA Style

Mahendra Adikari, Nanda Munasinghe. (2016). Development of a Corrosion Model for Prediction of Atmospheric Corrosion of Mild Steel. American Journal of Applied Scientific Research, 2(6), 91-96. https://doi.org/10.11648/j.ajasr.20160206.20

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Mahendra Adikari; Nanda Munasinghe. Development of a Corrosion Model for Prediction of Atmospheric Corrosion of Mild Steel. Am. J. Appl. Sci. Res. 2016, 2(6), 91-96. doi: 10.11648/j.ajasr.20160206.20

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AMA Style

Mahendra Adikari, Nanda Munasinghe. Development of a Corrosion Model for Prediction of Atmospheric Corrosion of Mild Steel. Am J Appl Sci Res. 2016;2(6):91-96. doi: 10.11648/j.ajasr.20160206.20

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@article{10.11648/j.ajasr.20160206.20,
  author = {Mahendra Adikari and Nanda Munasinghe},
  title = {Development of a Corrosion Model for Prediction of Atmospheric Corrosion of Mild Steel},
  journal = {American Journal of Applied Scientific Research},
  volume = {2},
  number = {6},
  pages = {91-96},
  doi = {10.11648/j.ajasr.20160206.20},
  url = {https://doi.org/10.11648/j.ajasr.20160206.20},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajasr.20160206.20},
  abstract = {Corrosion is a naturally occurring phenomenon commonly defined as the deterioration or loss of functions of materials (usually metals) due to the effect of the environmental factors. According to the nature of environment, corrosion can be broadly categorized as corrosion in atmosphere, corrosion in water, corrosion in sea, corrosion in soil etc. Among these types, corrosion of steel in atmosphere is a problem of great interest. Since steel is the most extensively used structural material in industry, and it is well accepted fact that the cost of material deterioration in an atmospheric environment is enormous. Corrosion of metal in atmosphere is inevitable but is controllable with the aid of proper corrosion management systems. For the implementation of a proper corrosion management system it is necessary to study the corrosive nature (corroivity) of the operation environment of a material. Development of a relationship between corrosivity and environmental variables such as relative humidity, temperature, salinity etc. which is known as Corrosion modeling is widely used method use for the evaluation of corrosivity of atmosphere. This paper describes the work carried out to formulate a model for the prediction of corrosion of mild steel under Sri Lankan atmospheric conditions. For this purpose, a model was proposed which is based on published literature on corrosion modeling. The proposed model was calibrated by the data obtained from field exposure tests which were conducted in four different locations in Sri Lanka. The chi-square goodness of fit test has been used to find out the performance of model. The model showed good performance with goodness of fit at 95% significance level. Finally, the model was validated with different set of data and the prediction performance of this model shows a good capability on forecasting of the rate of corrosion of mild steel in different atmospheric conditions in Sri Lanka.},
 year = {2016}
}

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TY - JOUR
T1 - Development of a Corrosion Model for Prediction of Atmospheric Corrosion of Mild Steel
AU - Mahendra Adikari
AU - Nanda Munasinghe
Y1 - 2016/12/28
PY - 2016
N1 - https://doi.org/10.11648/j.ajasr.20160206.20
DO - 10.11648/j.ajasr.20160206.20
T2 - American Journal of Applied Scientific Research
JF - American Journal of Applied Scientific Research
JO - American Journal of Applied Scientific Research
SP - 91
EP - 96
PB - Science Publishing Group
SN - 2471-9730
UR - https://doi.org/10.11648/j.ajasr.20160206.20
AB - Corrosion is a naturally occurring phenomenon commonly defined as the deterioration or loss of functions of materials (usually metals) due to the effect of the environmental factors. According to the nature of environment, corrosion can be broadly categorized as corrosion in atmosphere, corrosion in water, corrosion in sea, corrosion in soil etc. Among these types, corrosion of steel in atmosphere is a problem of great interest. Since steel is the most extensively used structural material in industry, and it is well accepted fact that the cost of material deterioration in an atmospheric environment is enormous. Corrosion of metal in atmosphere is inevitable but is controllable with the aid of proper corrosion management systems. For the implementation of a proper corrosion management system it is necessary to study the corrosive nature (corroivity) of the operation environment of a material. Development of a relationship between corrosivity and environmental variables such as relative humidity, temperature, salinity etc. which is known as Corrosion modeling is widely used method use for the evaluation of corrosivity of atmosphere. This paper describes the work carried out to formulate a model for the prediction of corrosion of mild steel under Sri Lankan atmospheric conditions. For this purpose, a model was proposed which is based on published literature on corrosion modeling. The proposed model was calibrated by the data obtained from field exposure tests which were conducted in four different locations in Sri Lanka. The chi-square goodness of fit test has been used to find out the performance of model. The model showed good performance with goodness of fit at 95% significance level. Finally, the model was validated with different set of data and the prediction performance of this model shows a good capability on forecasting of the rate of corrosion of mild steel in different atmospheric conditions in Sri Lanka.
VL - 2
IS - 6
ER -

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Author Information

Mahendra Adikari

Materials Laboratory, Industrial Technology Institute, Colombo, Sri Lanka
Nanda Munasinghe

Departmentof Materials Science and Engineering, University of Moratuwa, Moratuwa, Sri Lanka

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APA Style

Mahendra Adikari, Nanda Munasinghe. (2016). Development of a Corrosion Model for Prediction of Atmospheric Corrosion of Mild Steel. American Journal of Applied Scientific Research, 2(6), 91-96. https://doi.org/10.11648/j.ajasr.20160206.20

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ACS Style

Mahendra Adikari; Nanda Munasinghe. Development of a Corrosion Model for Prediction of Atmospheric Corrosion of Mild Steel. Am. J. Appl. Sci. Res. 2016, 2(6), 91-96. doi: 10.11648/j.ajasr.20160206.20

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AMA Style

Mahendra Adikari, Nanda Munasinghe. Development of a Corrosion Model for Prediction of Atmospheric Corrosion of Mild Steel. Am J Appl Sci Res. 2016;2(6):91-96. doi: 10.11648/j.ajasr.20160206.20

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@article{10.11648/j.ajasr.20160206.20,
  author = {Mahendra Adikari and Nanda Munasinghe},
  title = {Development of a Corrosion Model for Prediction of Atmospheric Corrosion of Mild Steel},
  journal = {American Journal of Applied Scientific Research},
  volume = {2},
  number = {6},
  pages = {91-96},
  doi = {10.11648/j.ajasr.20160206.20},
  url = {https://doi.org/10.11648/j.ajasr.20160206.20},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajasr.20160206.20},
  abstract = {Corrosion is a naturally occurring phenomenon commonly defined as the deterioration or loss of functions of materials (usually metals) due to the effect of the environmental factors. According to the nature of environment, corrosion can be broadly categorized as corrosion in atmosphere, corrosion in water, corrosion in sea, corrosion in soil etc. Among these types, corrosion of steel in atmosphere is a problem of great interest. Since steel is the most extensively used structural material in industry, and it is well accepted fact that the cost of material deterioration in an atmospheric environment is enormous. Corrosion of metal in atmosphere is inevitable but is controllable with the aid of proper corrosion management systems. For the implementation of a proper corrosion management system it is necessary to study the corrosive nature (corroivity) of the operation environment of a material. Development of a relationship between corrosivity and environmental variables such as relative humidity, temperature, salinity etc. which is known as Corrosion modeling is widely used method use for the evaluation of corrosivity of atmosphere. This paper describes the work carried out to formulate a model for the prediction of corrosion of mild steel under Sri Lankan atmospheric conditions. For this purpose, a model was proposed which is based on published literature on corrosion modeling. The proposed model was calibrated by the data obtained from field exposure tests which were conducted in four different locations in Sri Lanka. The chi-square goodness of fit test has been used to find out the performance of model. The model showed good performance with goodness of fit at 95% significance level. Finally, the model was validated with different set of data and the prediction performance of this model shows a good capability on forecasting of the rate of corrosion of mild steel in different atmospheric conditions in Sri Lanka.},
 year = {2016}
}

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