Characterization of early fatigue microstructure in AISI 321 steel using eddy current non-destructive methodology

Kunpeng Liu , Zihua Zhao , Zheng Zhang

Journal of Wuhan University of Technology Materials Science Edition ›› 2013, Vol. 28 ›› Issue (6) : 1201 -1206.

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Journal of Wuhan University of Technology Materials Science Edition ›› 2013, Vol. 28 ›› Issue (6) : 1201 -1206. DOI: 10.1007/s11595-013-0845-8
Metallic Materials

Characterization of early fatigue microstructure in AISI 321 steel using eddy current non-destructive methodology

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Abstract

Accumulative damage during early stage of fatigue in AISI 321 steel was investigated by eddy current test, atomic force microscopy, X-ray diffraction and transmission electron microscopy. Surface slip, dislocation, and strain-induced martensite were determined as the main damage types. Moreover, damage during the fatigue was found to be increased with the increasing fatigue cycles and load amplitude. The contribution of strain-induced martensite to the total eddy current amplitude (V max) was enhanced with the increase in its volume fraction. Finally, a linear relationship between V slip and the height of surface slip was established.

Keywords

eddy current / early stage of fatigue / surface slip / strain-induced martensite / dislocation

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Kunpeng Liu, Zihua Zhao, Zheng Zhang. Characterization of early fatigue microstructure in AISI 321 steel using eddy current non-destructive methodology. Journal of Wuhan University of Technology Materials Science Edition, 2013, 28(6): 1201-1206 DOI:10.1007/s11595-013-0845-8

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References

[1]

Lang M, Johnson J, Schreiber J, . Cyclic Deformation Behaviour of AISI 321 Austenitic Steel and Its Characterization by Means of HECSQUID [J]. Nucl. Eng. Des., 2000, 198: 185-191.

[2]

Ye DY, Matsuoka S, Nagashima N, . The Low-cycle Fatigue, Deformation and Final Fracture Behaviour of An Austenitic Stainless Steel [J]. Mater. Sci. Eng. A, 2006, 415: 104-117.

[3]

Rajkumar KV, Rao BPC, Sasi B, . Characterization of Aging Behaviour in M250 Grade Maraging Steel Using Eddy Current Nondestructive Methodology[J]. Mater. Sci. Eng. A, 2007, 464: 233-240.

[4]

Kato A, Hayashi M Fatigue Life Estimation of Steel Using Laser Speckle Sensor [J]. NDT & E Int., 1999, 32(3): 139-145.

[5]

Man J, Obrtlík K, Polák J Study of Surface Relief Evolution in Fatigued 316L Austenitic Stainless Steel by AFM[J]. Mater. Sci. Eng. A, 2003, 351: 123-132.

[6]

Man J, Petrenec M, Obrtlík K, . AFM and TEM Study of Cyclic Slip Localization in Fatigue Ferritic X10CrAl24 Stainless Steel [J]. Acta Mater., 2004, 52(19): 5551-5561.

[7]

De Backer F, Schoss V, Maussner G Investigations on the Evaluation of the Residual Fatigue Life-time in Austenitic Stainless Steels[J]. Nucl. Eng. Des., 2001, 206: 201-219.

[8]

Grosse M, Niffenegger M, Kalkhof D Monitoring of Low-cycle Fatigue Degradation in X6CrNiTi18-10 Austenitic Steel [J]. J. Nucl. Mater., 2001, 296: 305-311.

[9]

Smaga M, Walther F, Eifler D Deformation-induced Martensitic Transformation in Metastable Austenitic Steels [J]. Mater. Sci. Eng. A, 2008, 483-484: 394-397.

[10]

Blodgett MP, Ukpabi CV, Nagy PB Surface Roughness Infl uence on Eddy Current Electrical Conductivity Measurements[J]. Mater. Eval., 2003, 61: 765-772.

[11]

Mercier D, Lesage J, Decoopman X, . Eddy Currents and Hardness Testing for Evaluation of Steel Decarburizing [J]. NDT&E Int., 2006, 39(8): 652-660.

[12]

Zilberstein V, Walrath K, Grundy D, . MWM Eddy-current Arrays for Crack Initiation and Growth Monitoring [J]. Int. J. Fatigue, 2003, 25: 1 147-1 155.

[13]

Grobstein TL, Sivashankaran S, Welsch G, . Fatigue Damage Accumulation in Nickel Prior to Crack Initiation [J]. Mater. Sci. Eng. A, 1991, 138: 191-203.

[14]

Lee SJ, Park YM, Lee YK Reverse Transformation Mechanism of Martensite to Austenite in a Metastable Austenitic Alloy [J]. Mater. Sci. Eng. A, 2009, 515: 32-37.

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