Review of Regional Atmospheric Corrosion Mapping Technologys

doi:10.11902/1005.4537.2022.060

Journal of Chinese Society for Corrosion and protection

2023, Vol. 43

Issue (1): 29-37 DOI: 10.11902/1005.4537.2022.060

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Review of Regional Atmospheric Corrosion Mapping Technologys

FAN Zhibin(

), LI Xingeng, WANG Xiaoming, WANG Qian

State Grid Shandong Electric Power Research Institute, Jinan 250002, China

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Abstract

Atmospheric corrosion map is a graphical method for describing the corrosivity of the atmospheric environment of a designated area on a geographic map, which can provide data support for the anti-corrosion design, maintenance, and life prediction of the outdoor projects. It is of great significance to save anti-corrosion cost and ensure the safety of the project. Atmospheric corrosion maps have evolved from the initial grid and contour maps to more intuitive and easy-to-read colorful maps. The development of the dose response function solves the problem that it is difficult to obtain sufficient corrosion data from the exposure test, and the atmospheric corrosion data of the target area can be calculated quickly by using the environmental data. The inverse distance weighting and kriging interpolation models are mainly used in constructing atmospheric corrosion maps to predict the assignment of data blank areas, but the relevant applicability and error analysis of the models have not been reported yet. Based on the development of atmospheric corrosion mapping technologys, the development directions of atmospheric corrosion mapping technology may be proposed as follows: the establish Dose Response Functions that reflect the corrosion mechanism of materials, with greater applicability and less error, and to study spatial interpolation models that are more suitable for atmospheric corrosion data.

Key words: atmospheric corrosion corrosion map dose response function spatial interpolation

Received: 06 March 2022 32134.14.1005.4537.2022.060

ZTFLH:

TG174

Fund: Science and Technology Project of State Electric Power Company Grid Shandong(5200-202016471A-0-0-00)

Corresponding Authors: FAN Zhibin, E-mail: fan200403707@163.com

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Cite this article:

FAN Zhibin, LI Xingeng, WANG Xiaoming, WANG Qian. Review of Regional Atmospheric Corrosion Mapping Technologys. Journal of Chinese Society for Corrosion and protection, 2023, 43(1): 29-37.

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https://www.jcscp.org/EN/10.11902/1005.4537.2022.060 OR https://www.jcscp.org/EN/Y2023/V43/I1/29

Region	Organization	Time	Data sources	Number of sites / pieces	Regional area km²	Resolution km²	Graphical form	Interpolation model	References
British	CIRIA	1971	Exposed Samples	3182	244100	10×10	Grid	---	[8, 9]
Oslo	NILU Norwegian Institute for Air Research	1985	DRF	---	454	---	Isolines	---	[27]
Yucatán Peninsula	Centro de InvestigacioÂn y de Estudios Avanzados, Unidad MeÂrida	1999	Exposed Samples	14	197600	---	Points	---	[10]
Korea	Andong National University	2011	Environmental Factors, Exposed Samples	21	100210	---	Color blocks	---	[11, 12]
Australia	CSIRO	1999	Environmental Factors, Exposed Samples	475	42000	---	Points	---	[40]
Australia and Vietnam	CSIRO and IMS	2012	Environmental Factors, Exposed Samples	75(Vietnam), 8 (Vietnam)	7617930 (Australia), 329556 (Vietnam)	5×5	Color blocks	Environment Model and Inverse Distance Weighting	[42]
India	Central Electrochemical Research Institute	2004	Exposed Samples	40	2980000	---	Points	---	[7]
Spain	Centro Nacional de Investigaciones Metalúrgicas (CENIM)	2010	DRF	100	505925	0.5×0.5	Color blocks	Kriging	[36]
Abu Dhabi	CSIRO and ADWEA	2011	Environmental Factors	---	67340	---	Color blocks	Environment Model	[41]
Slovakia	University of Zilina	2015	DRF	---	49037	---	Color blocks	---	[28,29]
Greater Athens	National Observatory of Athens	2013	DRF	20	412	---	Color blocks	Kriging	[38]
Switzerland	EMPA	2004	DRF	＞60	41284	0.25×0.25	Color blocks	Inverse Distance Weighting and Kriging	[32]
European Part of Russia	Russian Academy of Sciences	2002	DRF	---	4268350	150×150	Grid	---	[34]
Istanbul	Fatih University	2013	DRF	50	5343	---	Color blocks	Kriging	[39]
Peninsular Malaysia	Universiti Tenaga Nasional	2013	DRF	17	130590	---	Color blocks	Inverse Distance Weighting	[43]
Czech	SVUOM Ltd.	2015	DRF	---	78866	2×2	Color blocks	Kriging	[30,31]
Russia	Russian Academy of Sciences	2019	DRF	6213	17098200	0.5 Latitude×1 Longitude	Color blocks	---	[35]
Canary Islands	Universidad de L as Palmas de Gran Canaria	2016	Exposed Samples	39	7273	---	---	---	[13]
Chile	Pontificia Universidad Católica de Valparaíso	2016	Exposed Samples	31	756626	---	Color blocks	---	[14]
Europe	Royal Institute of Technology, Sweden Corrosion and Metals Research Institute, Sweden	2006	DRF	---	---	50×50	Color blocks	Kriging	[33]
Madrid	Centro Nacional de Investigaciones Metalúrgicas (CENIM)	2013	DRF	32	607	0.5×0.5	Color blocks	Kriging	[37]
South Africa	University of the Witwatersrand	2019	Exposed Samples	100	1219090	---	Color blocks	---	[15]

Table 1 Typical atmospheric corrosion maps abroad

Table 2 Domestic typical atmospheric corrosion maps

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