Corrosion Science 47 (2005) 2589–2598 www.elsevier.com/locate/corsci
InXuence of the alloy element on corrosion morphology of the low alloy steels exposed to the atmospheric environments Akira Tahara ¤, Tadashi Shinohara Corrosion Group, Materials Information Technology Station, National Institute for Materials Science, 1-2-1 Sengen, Tsukuba, Ibaraki 305-0047, Japan Received 29 August 2004; accepted 21 October 2004 Available online 6 June 2005
Abstract Morphology of the corroded surface of low alloy steels beneath rust after long-term exposure test in the atmospheric environment was analyzed. The form of the corroded surface was measured with the laser displacement sensor scanning the surface. The resultant height map was divided by the mesh and the maximum corrosion depth was calculated in each cell. The maximum depth was arranged by the extreme value analysis. From this analysis two kinds of corrosion patterns were distinguished; i.e., uniform corrosion and local corrosion. Electrolytic iron shows the only uniform corrosion pattern. The addition of Cu, Ni and Cr changed the form of the corroded surface from the uniform corrosion to the combined pattern (uniform corrosion + local corrosion). The addition of Cr has a marked eVect in changing the corrosion pattern. 2005 Elsevier Ltd. All rights reserved. Keywords: Low alloy steels; Atmospheric corrosion; Corrosion form; Alloying eVect; Gumbel distribution function
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[email protected] (A. Tahara).
0010-938X/$ - see front matter 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.corsci.2004.10.019
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1. Introduction Many investigators have studied the atmospheric corrosion of the low alloy steels. Particularly, investigations of the weathering steels by Misawa et al. [1–3] are wellknown. We have reported also the corrosion loss and the analysis of the rusts on the surfaces of the low alloy steels exposed to atmospheric environments [4–6]. We have obtained only the averaged value from these analyses. A microscopic aspect was lacked in these analyses. Especially a few researchers are interested in the corrosion patterns of the corroded surface under the rust from a technological view point. Masuko et al. [7] executed the measurement of the atmospherically corroded surfaces of pure iron and Fe–1%Cu alloy by applying the Moire fringe patterns. They obtained the depth distribution proWle of those materials and clariWed the distribution of corrosion loss on an unevenly corroded surface. Yamamoto et al. [8] analyzed the characteristics of the atmospherically corroded surface by the two-dimensional fast Fourier transformation (FFT) method. They reported some cases that the periodicity appears on the auto-correlation coeYcients obtained by the two-dimensional FFT method for the test piece with a large corrosion loss. The main objective of the present work was to analyze the inXuence of the additional elements to the electrolytic iron from the morphology of the corroded surface using the depth proWling technique and the extreme-value statistics processing of the corrosion depth.
2. Experimental 2.1. Samples The electrolytic iron and some Fe-binary alloys (0.4%Cu, 1%Cr, 3%Cr, 5%Cr, 9%Cr, 1%Ni, 3%Ni, 5%Ni, and 9%Ni) were used as the test pieces. Table 1 shows the chemical compositions of these alloys. Test pieces were plates with 150 £ 100 £ 5 mm. After degreasing, these test pieces were exposed at Tsukuba, Choshi, and Miyakojima
Table 1 Chemical composition of the samples Material
C
Si
Mn
P
S
Cu
Cr
Ni
Al
Ti
V
Fe Fe–Cu Fe–1Ni Fe–3Ni Fe–5Ni Fe–9Ni Fe–1Cr Fe–3Cr Fe–5Cr Fe–9Cr
0.001 0.001 0.001 0.001 0.001 0.001 0.005 0.006 0.003 0.003
<0.003 <0.003 <0.003 <0.003 <0.003 <0.003 <0.003 <0.003 <0.003 <0.003
<0.001 <0.01 0.10 0.10 0.11 0.12 0.07 0.05 0.11 0.12
0.0008 0.0006 0.0003 0.0005 0.0006 0.0005 0.0010 0.0007 0.0003 0.0002
0.0011 0.0007 0.0001 0.0002 0.0003 0.0003 0.0002 0.0001 0.001 0.0003
<0.01 0.43 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01
<0.01 <0.01 <0.01 <0.01 <0.01 <0.01 1.01 3.05 5.03 9.03
<0.01 <0.01 0.98 3.02 5.01 9.06 <0.01 <0.01 <0.01 <0.01
<0.01 <0.01 <0.01 <0.01 <0.01 0.01 <0.01 <0.01 <0.01 <0.01
<0.01 <0.01 0.Q1 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01
<0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01
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Table 2 Information of environmental factors at each exposure site Exposure site
Tsukuba
Choshi
Miyakojima
Environment Latitude (North) Longitude (East) Air temperature (K) Relative humidity (%) Chloride deposition rate (mg NaCl/m2 day)
Rural 36°4⬘ 140°7⬘ 287.0 72.0 3.3
Rural/coastal 35°43⬘ 140°45⬘ 287.9 78.5 33.3
Subtropical coastal 24°44⬘ 125°19⬘ 296.9 79.3 43.9
These values are the average measures in 1999–2001.
Fig. 1. Outline of the apparatus for the corrosion form measurement.
for a prescribed exposure period. Table 2 shows the information on the environmental factors of each exposure site. The following two methods were used as the atmospheric exposure test condition. In the Wrst test condition, test pieces were directly exposed to the atmospheric environment (rain, wind, solar radiation and so on). The exposure test frames were inclined at the angle of 45° from the horizontal, facing the south. Hereafter this test is called “the open exposure test”. In the second test condition, test pieces were placed on the horizontal exposure frames covered with the metallic roof, shielded from rain and solar radiation. This test is called “the sheltered exposure test”. After the corrosion products on the exposed test pieces were removed, the morphology of the corroded surfaces was measured by the following system. 2.2. Measurement of the form of the atmospherically corroded surface Fig. 1 shows the outline of an apparatus for the measurement of the corrosion patterns. The apparatus was composed of the X–Y stage with high accuracy and the laser displacement sensor. Corrosion depth as a function of position was recorded using by this system. The area with 40 £ 40 mm in the center of the test piece was measured with 0.1 mm pitch. Therefore, the data of 401 £ 401 points (total 160,801 points) was measured per one test piece. These data were analyzed by the following methods.
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Fig. 2. Relationship between mean decrease of thickness and average height. Mean decrease of thickness was obtained from the weight loss. Average height was calculated from the data measured by the apparatus shown in Fig. 1.
2.3. Analysis of the corrosion morphology The data of the corrosion morphology, measured by the system in Fig. 1, are equal to the “height” above the base plane of the XY stage. The non-corroded surfaces, which can be used as the base level of the corrosion depth, were not found on the test piece surfaces because the corrosion progressed on the whole area of the test pieces. The mean decrease of the thickness of the test piece was obtained from the weight loss. The average of height was calculated from data of height. Fig. 2 shows the relationship between the mean decrease of the thickness and the average of height. We assumed that the position of the mean decrease is equal to the position of the average of height. Using this relationship, all height data, which measured by the apparatus shown in Fig. 1, were converted into the corrosion depth. Fig. 3 shows the measured example of the corroded surface. This test piece was exposed at Miyakojima for 63.1 £ 106 s. 2.3.1. Corrosion depth proWling The corrosion depth proWling was obtained by applying the analysis method proposed by Masuko et al. [6]. The 3D solid model of the corroded surface was reconstructed by using the depth data by the visualization program. At some corrosion depth, the 3D model was sliced and the sliced area was accumulated. Corrosion depth proWle was obtained by plotting the relationship between the corrosion depth and the ratio of sliced area to the whole area. 2.3.2. Extreme value analysis of the corrosion depth This method is often used for the analysis of the pitting depth of stainless steels. The measured surface with 40 £ 40 mm was divided by the mesh with the equal area (for instance, 4 £ 4, 8 £ 8, 16 £ 16 divisions and so on), and the maximum value of the corrosion depth was picked up in each cell. These maximum values of corrosion depth were assumed to be according to the Gumbel distribution function. These data were modiWed on the Gumbel plot.
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Fig. 3. Corroded surface of electrolytic iron exposed at Miyakojima for 63.1 £ 106 s (2 years).
3. Results and discussion 3.1. Corrosion depth proWle Figs. 4 and 5 show the corrosion depth proWle obtained by using the method explained in Section 2.3.1. The value of the vertical axis F(x) of these Wgures shows
Fig. 4. Corrosion depth proWle of Fe-binary alloys. Test pieces were exposed at Miyakojima for 63.1 £ 106 s.
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Fig. 5. Corrosion depth proWle of Fe-binary alloys. Test pieces were exposed at Tsukuba for 63.1 £ 106 s.
the ratio of the non-sliced area to whole area. The value of F(x) equals to “1” when the sliced area is zero and the value of F(x) equals to “0” when whole area is sliced. Fig. 4 shows the results of Fe–1%Cr and Fe–1%Ni alloys exposed at Miyakojima for 63.1 £ 106 s (2 years). Fig. 5 shows the results of four kinds of test pieces exposed at Tsukuba for 63.1 £ 106 s (2 years). The various alloying elements to the electrolytic iron have been plainly observed to have the eVects of shifting the proWles to the smaller direction of corrosion depth. The eVect of addition of nickel is more remarkable than the addition of copper and chromium. However, the diVerence of the corrosion morphology (the local corrosion or the uniform corrosion) was not so clear from the diVerence of the corrosion depth proWle.
Fig. 6. The Gumbel plot of the corrosion depth of Fe–3%Cr alloy exposed at Tsukuba for 63.1 £ 106 s: 16, 64 and 256 represent the numbers of the mesh.
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3.2. Extreme value analysis of corrosion depth Fig. 6 shows the result of the Gumbel plot of the corrosion depth of Fe–3%Cr alloy exposed at Tsukuba for 63.1 £ 106 s. In this Wgure, the three kinds of marks represent the results of dividing with 4 £ 4-, 8 £ 8- and 16 £ 16-mesh, respectively. It is possible to classify the maximum corrosion depth data into two groups. The Wrst group is smaller than the second group. The number of the data which belong to the second group hardly changes with increasing the number of the mesh. On the other hand, the number of the data composing the Wrst group increases with the number of the mesh. In each group, there is a linear relationship between the y-value and the corrosion depth. The slope of the Wrst group is smaller than that of the second group. However, the slope of these lines does not change with increasing the number of the mesh.
Fig. 7. (a) Surface and (b) the depth proWle of the sample of Fig. 5: The marks represent the position of the local corrosion data (second group in Fig. 5) and the (b) shows the depth proWle around “triangle” and “square” in the (a).
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Judging from these facts, the second group is assumed to represent the depth of the local corrosion (pitting corrosion) and the Wrst group is assumed to represent the depth of the uniform corrosion (the general corrosion). Fig. 7(a) shows the corroded surface of the same sample shown in Fig. 5. In this Wgure, the marks show the positions of the local corrosion corresponding to the second group in Fig. 6. Fig. 7(b) shows the depth proWles around the marks of triangle and square in Fig. 7(a). Judging from the depth proWles, pitting corrosion occurs at both of triangle and square. Therefore, it is conWrmed that the second group in Fig. 6 corresponds to the pitting corrosion, and the Wrst group corresponds to the uniform corrosion. Fig. 8 shows the Gumbel plot of Fe and Fe–Cr alloys exposed at Tsukuba for 63.1 £ 106 s. The electrolytic iron shows only one linear relationship. It is clear that the only uniform corrosion occurs on the surface of the electrolytic iron. The addition of chromium decreases the corrosion depth and two linear relationships appear on the Gumbel plot. On the surface of Fe–Cr alloys, both types of corrosion (uniform corrosion and pitting corrosion) occur. Therefore, two linear relationships appear on the results of Fe–Cr alloys. The smaller corrosion depth of Fe–Cr alloys is attributable to the higher corrosion resistance of the alloys with chromium. Among two linear relationships, which were observed in the results of Fe–Cr alloys, the lower line corresponds to the uniform corrosion, and the higher line corresponds to the pitting corrosion. The slope of the Wrst line corresponding to the uniform corrosion increases with the contents of chromium. The slope of the second line corresponding to the pitting corrosion decreases with the contents of chromium. It means that the pitting corrosion becomes superior to the uniform corrosion with addition of chromium. Fig. 9 shows the Gumbel plot of some Fe binary alloy exposed at Tsukuba for 63.1 £ 106 s. Alloying with chromium, nickel or copper leads to a decrease in the cor-
Fig. 8. The Gumbel plot of the corrosion depth of Fe–Cr alloys exposed at Tsukuba for 63.1 £ 106 s.
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Fig. 9. The Gumbel plot of the corrosion depth of some Fe-binary alloys exposed at Tsukuba for 63.1 £ 106 s.
rosion loss and to a shift of the corrosion pattern to “the combined corrosion pattern” (uniform corrosion + pitting corrosion). The addition of nickel has the biggest eVect in decreasing corrosion loss, although the addition of nickel scarcely changes the corrosion pattern. The addition of chromium has the marked eVect in changing the corrosion pattern. It has been said that the corrosion of Fe–Cr alloy under the chloride environment progress in the form of localized corrosion [9,10]. This research is the one that the above corrosion pattern was proven with the numerical data.
4. Summary Corrosion behavior of the low alloy steels was analyzed from the morphology of the atmospherically corroded surface. The morphology of corrosion of electrolytic iron shows the only uniform corrosion pattern. The addition of Cu, Ni and Cr changed the morphology of the corroded surface from the uniform corrosion to the combined pattern of uniform corrosion with local corrosion. The addition of Cr aVected markedly in changing the corrosion pattern.
References [1] [2] [3] [4] [5] [6]
T. Misawa, Bulletin of the Iron and Steel Institute of Japan 6 (5) (2001) 6. T. Misawa, M. Yamashita, H. Nagano, Materia Japan 35 (1996) 783. T. Misawa, M. Yamashita, K. Matsuda, H. Miyuki, H. Nagano, Tetsu-to-Hagane 79 (1993) 69. A. Tahara, H. Baba, T. Kodama, NIMS Corrosion Data Sheet, No. 1A, 2002. A. Tahara, T. Kodama, Proceedings of the JSCE Materials and Environments 2001 (2001) 313. A. Tahara, T. Kodama, Proceedings of the 48th Japan Conference on Materials and Environments, 2001, p. 17.
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[7] N. Masuko, T. Irita, I. Suzuki, Boshoku-Gijyutu 22 (8) (1973) 327. [8] M. Yamamoto, H. Katayama, A. Tahara, T. Kodama, Proceedings of the 47th Japan Conference on Materials and Environments, 2000, p. 81. [9] H.P. Leckie, H.H. Uhlig, Journal of Electrochemical Society 113 (1966) 1262. [10] M. Pourbaix, L. Klimzack-Mathieiu, Ch. Mertens, J. Meunier, Cl. Vanleugen-Haghe, L. De Munck, J. Laureys, L. Neelemans, M. Warzee, Corrosion Science 3 (1963) 239.