In-Situ Observation and Acoustic Emission Monitoring of the Initiation-to-Propagation Transition of Stress Corrosion Cracking in SUS420J2 Stainless Steel

Kaige Wu1,+, Fabien Briffod1, Kaita Ito2, Ippei Shinozaki3, Pornthep Chivavibul1 and Manabu Enoki1

1Department of Materials Engineering, The University of Tokyo, Tokyo 113-8656, Japan2Research and Services Division of Materials Data and Integrated System, National Institute for Materials Science,Tsukuba 305-0044, Japan3Materials Department, Research Laboratory, IHI Corporation, Yokohama 235-8501, Japan

In this work, acoustic emission (AE) monitoring was correlated with in-situ optical microscopy observation and electron backscatterdiffraction (EBSD) measurements to investigate the evolution of a single stress corrosion crack in SUS420J2 stainless steel subjected to chloridedroplet corrosion. A single dominant crack evolution was observed to transition from a slow initiation of active path corrosion-dominantcracking to a rapid propagation of hydrogen-assisted cracking. The initiation-to-propagation was concomitant with a significant increase in thenumber of AE events. In addition, a cluster analysis of the AE features including traditional waveform parameters and fast Fourier transform(FFT)-derived frequency components was performed using k-means algorithms. Two AE clusters with different frequency levels were extracted.Correlated with the EBSD-derived kernel average misorientation (KAM) map of crack path, low-frequency AE cluster was found to correspondwith the location of plastic deformation in the propagation region. High-frequency AE cluster is supposed to be from the cracking process. Thecorrelation between AE feature and SCC progression is expected to provide an AE signals-based in-situ insight into the SCC monitoring.[doi:10.2320/matertrans.MT-MAW2019004]

(Received May 16, 2019; Accepted June 20, 2019; Published July 26, 2019)

Keywords: stainless steel, stress corrosion cracking (SCC), pitting, plastic deformation, acoustic emission (AE), electron backscatter diffraction(EBSD)

1. Introduction

Stress Corrosion Cracking (SCC), caused by the syner-gistic interaction of corrosive environment and mechanicalload, is an important threat to stainless steels. Considering thewidespread use of stainless steels, SCC has been a primarycause of many failures of metallic structures and componentsin a wide range of industries.1) Thus, the reliable assessmentof the service life of the exposed components and structuresrequires the accurate prediction of initiation and propagationof SCC.

It is clear that SCC requires contributions from bothchemical and mechanical factors. Parkins2) firstly put forwardthe concept of “stress corrosion spectrum” to support acontinuous spectrum of SCC mechanism. It is suggested thatSCC is predominantly controlled by a changing dominantfactor from electrochemical to mechanical depending on theSCC progression. Figure 1 shows a schematic elucidationof a three-stage model for SCC progression which wasrearranged based on the references.2­4) Despite its complexnature due to combined metallurgical, mechanical andenvironmental effects, SCC in most cases begins with theearly localized corrosion4) or mechanical defect sites likepitting, intergranular attack (IGA), scratches, or other pre-existing flaws, subsequently develops as a short crack withslow propagation, to finally reach the long crack regimeeventually leading to the ultimate failure of the component.The SCC development in the initiation regime is oftenperceived to be slow and long term and can largely determinethe overall life of an exposed component.5,6) Therefore, anin-situ monitoring of the initiation-to-propagation transitionis greatly significant in the lifetime estimation of SCC.

In general, the initiation and propagation of SCC arestrongly affected by the electrochemical conditions and thelocal stress/strain state at the crack tip, and cannot be directlyand integrally estimated via traditional electrochemicalmethods7) or mathematical based models8) given thedifficulties to obtain the experimental input parameters.Acoustic emission (AE) method, a nondestructive testing(NDT) method based on the recording of elastic waves, isknown to be highly sensitive to local phenomena such aschemical reactions and physical changes. AE method haslong been used to study the steel corrosion like pittingcorrosion and SCC.9­18) Some of the registered sources ofAE signals in literature include pitting,9­13) hydrogen bubbleevolution,9­14) dislocations motion during plastic deforma-tion,15) cracking of oxide/corrosion products,14,16) falling-offof surface grain,14,16) generation and propagation ofcracks.13,15­18) However, so far no attention was paid tocombining in-situ observation and AE monitoring for thetransition identification during SCC progression, which isthe primary concern of the present work.

However, the accelerating SCC tests, recommended byASTM G129,19) ASTM G36,20) or NACE TM0177,21)

basically require the immersion of specimens into a bulksolution at an elevated temperature which is challenging tofacilitate AE experiments and in-situ observations. In thepresent work, a chloride droplet SCC test was improved withthe smooth U-bent SUS420J2 stainless steel specimen inhumidity to trigger a single crack evolution, thus accom-modating the experimental aim. Moreover, electronbackscatter diffraction (EBSD) analysis of the crack pathwas correlated with in-situ observation and AE behavior intime evolution so as to track the features in relation to theinitiation and propagation of SCC.

+Corresponding author, E-mail: kaigewu@rme.mm.t.u-tokyo.ac.jp

Materials Transactions, Vol. 60, No. 10 (2019) pp. 2151 to 2159©2019 The Japan Institute of Metals and Materials

2. Experimental Procedure

2.1 Material and specimenA commercial SUS420J2 stainless steel (provided by

Kusayama Unique Special Steel, Japan, C: 0.32mass%, Si:0.45mass%, Mn: 0.54mass%, Cr: 13.39mass%, Ni: 0.09mass%, P: 0.031mass%, S: 0.005mass%, Fe: bal.) was usedin this study. To improve the corrosion susceptibility, the steelwas first treated at 600°C for 1 h and 800°C for 1 h toprecipitate the carbides. It was then annealed at 1010°C for2.75 h and quenched in Argon air cooling. The obtainedmechanical properties of the steel were characterized by a0.2% proof stress of 1201MPa, an ultimate tensile strength(UTS) of 1679MPa, an elongation of 0.9% and a Vickershardness of 611. The specimen was machined from the bulksteel after heat treatment with a dimension of 170.0mm(L) © 6.3mm (W) © 1.5mm (T) and finally polished up to0.05 µm Al2O3 slurry for a mirror finish. Figure 2 showsthe microstructure of the steel specimen after being etchedusing Viella’s reagent for 10 seconds, indicating themartensitic lath with visible prior-austenite grain boundaries.The average gain size was determined as 22.8 µm. Circularand elongated undissolved carbides were observed withinmartensitic grains, especially near prior-austenite grainboundaries. Further energy-dispersive X-ray spectroscopy(EDX) mapping confirmed the carbides with enrichment incarbon and chromium and depletion in iron, indicatingCr-rich carbides. The specimen was intended to have lowtoughness, high residual stress and active corrosion path(i.e., grain-boundaries with segregated Cr-rich carbides) tofacilitate the crack initiation.

2.2 SCC experiment and AE measurementsTo improve the reliability in extracting and interpreting the

AE signals, a localized SCC attack under a single chloridedroplet accommodated with a continuous in-situ monitoringby digital microscope was designed with AE measurements.Figure 3 shows the experimental setup. The specimen was

bent and fixed in an experimental jig with a curvature radiusof 125mm leading to a constant strain of 0.6% at the apexof the specimen surface. A 1µL droplet of 1.0mass% neutralNaCl solution was dropped in the center area of the specimensurface using a microliter syringe. The experimentalapparatus was placed in a thermostatic bath (298K, 99­100% humidity) with pure water. The bath was covered witha transparent glass cap to allow in-situ observation usinga digital microscope (VHX-5000, Keyence Corp., Japan).Simultaneously, continuous AE measurement was performedusing a custom AE acquisition system developed in ourgroup, CWM.22) Two high-sensitivity R-CAST sensorsystems with a resonant frequency of 200 kHz (M204A, FujiCeramics Corp., Japan, 55 dB gain) were positioned 10mmand 30mm away from the droplet site to record the AEsignals. A threshold of 27 dB and a 100 kHz high-pass filter(HPF) were used as thresholds to isolate AE events from thecontinuous waveform. Then the target signals were extracted

Fig. 1 Schematic diagram of a three-stage model for SCC progression. Rearranged based on Refs. 2­4).

Fig. 2 The microstructure of chemically etched specimen: (a) opticalmicrograph, (b) backscattered electrons (BSE) SEM image, and (c) EDXmaps.

K. Wu et al.2152

by filtering out the noise outside the corrosion region usingthe source location method.

2.3 Cluster analysis of AE dataA cluster analysis of the extracted AE data was performed

using K-means algorithm. To improve the classification ofAE signals, the traditional AE parameters (i.e., amplitude,rise time, duration, counts+) together with the FFTfrequency components from 102.5 kHz to 996.1 kHz with aresolution of 4.9 kHz were input as AE features into the k-means algorithm. All input data were first normalized with Z-score standardization method.23) Then principle componentanalysis (PCA) was conducted to reduce the dimension of theobtained data matrix before the K-means clustering algorithmwas applied. The optimum number k of clustering wasdetermined using average silhouette coefficient (SCave.).24)

The silhouette coefficient for the i-th point, s(i), is defined asbelow:

sðiÞ ¼ bðiÞ � aðiÞmax½aðiÞ; bðiÞ� ð1Þ

bðiÞ ¼ mink Bði; kÞ ð2Þ

SCave:ðkÞ ¼Xn

i¼1sðiÞ

nð3Þ

where a(i) is the average distance from the i-th point to theother points in the same cluster and b(i) is the minimumaverage distance from the i-th point to points in a differentcluster, minimized over the clusters. The value of k at themaximum average silhouette coefficient was used as the bestclustering solution.

2.4 Microstructural characterizationThe SCC test was interrupted immediately after the crack

growth shifted from a slow crack initiation to rapidpropagation to prevent complete failure of the specimen

and allow EBSD measurements along the crack path. Aftertesting, the specimen was cut to an approximate length of20mm to fit the SEM observation chamber and ultrasonicallycleaned with ethanol at room temperature to remove thecorrosion products. Next, a fine polishing of the crack areawas performed with a colloidal silica suspension of 0.05 µmfor 2 hours in order to enable EBSD measurement. EBSDdata were collected using a field-emission SEM (JSM7000F,JEOL Ltd., Japan) equipped with a Tex-SEM laboratorydetector. A 15 kV acceleration voltage was selected with astep size of 0.15 µm for EBSD scanning. EBSD data wereanalyzed using OIM (EDAX-TSL) v7 software. The KernelAverage Misorientation (KAM) analysis was used to assessthe local plastic deformation around the crack path.25)

3. Results

3.1 SCC evolution and AE resultsFigure 4 shows the corrosion evolution of the SUS420J2

stainless steel under the single NaCl droplet. In details, itfirstly started with pitting corrosion as captured in Fig. 4(a)­(b). When pit grew to a critical size, as shown in Fig. 4(c),tiny cracks initiated from both sides of the corrosion pit.Subsequently, a characteristic feature of corrosion “atoll” wasgradually visualized as the formation of an annular, ring-likesurface stains under the droplet. Meanwhile, as shown inFig. 4(d)­(f ), the tiny crack developed to form a singledominant crack, normal to the U-bend load direction, inthe central region of the corrosion atoll. Some corrosionmicrocracks were also observed to be concurrent with thegrowth of the main crack and were supposed to be IGA.Figure 4(g) shows the first capture of small gas bubblesaround the pit mouth that were believed to be hydrogenbubbles in comparison to the experimental conditions forother bubbles.26) This is an important point as shortly after,the dominant crack shifted toward a rapid propagation with

Fig. 3 Schematic of the modified SCC test system incorporated with an in-situ digital microscope and AE measurement systems.

In-Situ Observation and Acoustic Emission Monitoring of the Initiation-to-Propagation Transition of Stress Corrosion Cracking 2153

increasingly amount of hydrogen bubbling at the mouths ofpit, crack and IGA fissures.

Figure 5 shows the AE data extracted during the corrosionprocess with the surface profile of pit size plus dominantcrack length over time. Correlated with in-situ observations,three distinct regions were recognized, i.e., stage I of pittingcorrosion without AE events recorded, stage II of slow crackgrowth with moderate AE activity, and stage III of rapidcrack propagation with massive AE signals. Partial enlarged

details in relation to the transition of pit-to-crack and slow-to-rapid crack growth is shown in Fig. 6. In stage I, corrosionpit was first observed in-situ with a size of approximately4 µm and grew to a critical size of approximately 32 µm withno AE events detected. Stage II started with a pit-to-cracktransition. AE signals were not detected immediately afterthe crack initiation but after a short time delay whichcorresponded to an AE-based NDT limit of approximately60 µm relevant to the present material and environmentcombination. In stage I, average pit growth rate (PGR) wasapproximated to be 0.03 µm/s. In stage II, the crack grewslowly with an average crack growth rate (CGR) of 0.04µm/s and the number of AE events increased moderately.In the late stage II, the hydrogen bubble evolution wasobserved. After 31 seconds, crack growth shifted to a highCGR of 1.68 µm/s and intense AE activity began to berecorded massively, indicating the start of stage III.

Figure 7 shows the detailed morphology of the corrosionwith EBSD scanning including inverse pole figure (IPF) andKAM maps of the dominant crack path. First, differentregions corresponding to stage I, II, and III can bedistinguished. A large number of IGA-induced fissures alongthe prior-austenite grain boundaries were clearly observed inthe central region of corrosion atoll. The corrosion pit seemsto initiate from the prior-austenite grain boundaries and manyundissolved carbides are precipitated nearby. Second, the IPFmap shown in Fig. 7(b) clearly indicated the intergranularcharacteristics of the crack development. It is likely thatthe IGA fissures played in facilitating the crack growth.Moreover, from the KAM map shown in Fig. 7(c), somezones of high KAM intensity situated around the beginningarea of stage III can be recognized, indicating local plasticdeformation along the specific region of crack path.

Fig. 4 In-situ observation of the crack initiation and propagation of SUS420J2 under the droplet of 1 µL neutral 1% NaCl solution inhumidity: (a)­(b) pitting corrosion; (c)­(f ) Slow, single dominant crack initiation from a corrosion pit and IGA; (g)­(i) rapid crackpropagation.

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nts, N

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ize

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a

Ave. CGRII = 0.04 µm/s

Fig. 5 The AE activity of amplitude and cumulative events and the profileof pit size plus dominant crack length over the time evolution. Here,marked points “a­i” are consistent with the sequences indicated in Fig. 4.

K. Wu et al.2154

As shown in Figs. 4 and 7, the dominant crack evolvedsimultaneously with the development of IGA. In order tovalidate whether the IGA contributed to the detected AEsignals or not, a comparative experiment on an unstressed flat

specimen of the same preparation under the same exposurecondition, i.e., being exposed to the same droplet of 1 µLneutral 1% NaCl solution and the same humidity, was carriedout. The test was conducted for 15 hours but no AE eventwas detected at all. Figure 8 shows the post observation ofthe corrosion morphology. Localized corrosion of pittingand IGA were visualized at the central region of a similarcorrosion atoll. Undissolved carbides are clearly distributedin the neighboring regions especially at the pit mouth and thegrain boundaries. However, no dominant crack was initiatedin addition to the IGA fissures and pitting. Implicitly, thepitting and the IGA can be ruled out from the AE sources.The AE signals during SCC progression are supposed to befrom the evolution of the single dominant crack.

3.2 Cluster analysis of AE data and correlative analysisFigure 9 shows the result of the cluster analysis. From the

SCave. variation against the number of clusters k, 2 clusterswere selected as the best clustering solution. Figure 9(b)shows a frequency comparison near the center of cluster 1

(a)

(b)

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AE signals

Cum

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Start of rapid cracking and massive AEs, 4426s.1st capture of H2

bubble, 4395s

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AE-NDT limit of approx. 60 µm

Pit-to-crack transition

Critical pit size of approx. 32 µm

Fig. 6 Partial enlarged details of Fig. 5 to highlight the transitions of pit-to-crack (a) and slow-to-rapid crack growth (b).

Fig. 7 (a) The corrosion morphology including corrosion pit, IGA and the single dominant crack being segregated by different regionscorrelated with in-situ observations; (b) IPF map, (c) KAM map of the crack path.

Fig. 8 (a) The central region including pitting and IGA of the corrosionatoll from a comparative experiment of an unstressed specimen beingexposed to the same droplet and humidity until 15 hours with no AE eventrecorded; (b) Partial enlarged detail.

In-Situ Observation and Acoustic Emission Monitoring of the Initiation-to-Propagation Transition of Stress Corrosion Cracking 2155

and 2, indicating the distinct feature in frequency level, i.e.,high-frequency for cluster 1 and low-frequency for cluster 2.The AE waveforms of two clusters were also compared asshown in Fig. 10. Cluster 1 signal exhibits burst-typewaveform with high frequency component, while cluster 2has continuous-type feature with lower level in the dominantfrequency component.

Figure 11 shows the evolution of the two AE clusters instage III with the corresponding optical microscopy obser-vation. Owing to a correlative analysis with KAM map, thestart of low-frequency cluster 2 was interestingly correspond-ing to the area of high local strain recognized by high KAMintensity. Taking into consideration the continuous wave-form-type, low-frequency cluster 2 seems to be correlatedwith the plastic deformation along the crack path. Hence,cluster 1 is supposed to be with the cracking process.

4. Discussion

4.1 Initiation and propagation of SCCSCC is a complex process dictated by various dynamic

mechanisms depending on the combination of material andenvironmental variables. A unified model responsible for

SCC evolution is still far from being realized. So far, the mostaccepted mechanisms in literature27,28) for SCC can bedivided into two main categories. The first one is anodicdissolution model, like active path corrosion (APC) and filmrupture models, which attributes the crack growth to anodicdissolution at the crack tip. The effect of mechanical stress isprobably to expose the bare metal by rupturing the protectivepassive film or deposited corrosion products. The secondmodel considers SCC as a mechanical process accelerated bythe specific chemisorption like hydrogen that can eitherreduce the fracture surface energy or induce dislocationemission at the crack tip. In this work, a combination of AEmonitoring and in-situ observation is adopted to focus on onesingle stress corrosion crack evolution in terms of dropletcorrosion. The process of SCC is discussed in details belowbased on in-situ observations.

In the early stage, the undissolved Cr-rich carbides arebelieved to be the precursor sites of localized corrosion, asshown in Figs. 4, 7, and 8, in relation to the Cr-depletedzones.29) After localized corrosion formed, a corrosion atollunder the droplet, whether stressed or not, becomes visible asshown in Fig. 4 and 8. This is due to the formation of localcell action, i.e., the center of the atoll serves as the anodic

(a)

2 3 4 5 6 7

0.2

0.4

0.6

0.8

Ave

rage

siho

uett

e co

effic

ient

,SC a

ve.

Number of cluster, k

(b)

Fig. 9 The result of AE cluster analysis: (a) The SCave. upon k number; (b) Comparison of the centers of cluster 1 and 2 based on thescheme of k = 2.

0

5000

10000

15000

20000 (d) FFT spectrum of AE signal 2

Mag

nitu

de, a

.u.

Frequency, f / kHz0 200 400 600 800 10000 50 100 150 200

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Vol

tage

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mV

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Vol

tage

, V /

mV

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Mag

nitu

de, a

.u.

Fig. 10 The AE waveforms (a)­(b) and corresponding FFT spectrums (c)­(d) of cluster 1 and 2.

K. Wu et al.2156

area and the perimeter as the cathodic area.30,31) Anodicdissolution reactions at the centers are:

Fe ! Fe2þ þ 2e� ð4ÞCr ! Cr3þ þ 3e� ð5Þ

while the cathodic reaction at the surrounding cathodicsurface is:

O2 þ 2H2Oþ 4e� ! 4OH� ð6ÞBreakdown of passive film and dissolution of metals

(Fe, Cr) by reaction (4) and (5) probably contribute to thelocalized corrosion of pitting and IGA as observed inFig. 4(a)­(f ). The oxygen reduction by reaction (6) occurredwith the formation of annular corrosion products. On theother hand, once the corrosion atoll forms, an electric fieldwill be set up and the potential gradient would concentrateCl¹ to the central anodic region and migrate out Na+ to theoutside region, which was previously verified with elementalmapping using EDX analysis.32) This would render thecentral anodic region more prone to corrosion and thereforecould explain formation of a single corrosion atoll under thesingle NaCl droplet. This improved SCC test is expected toensure the reliability in extracting AE signals related to SCC.

The segregation of carbides in the prior-austenite grainboundaries (Fig. 2) provides the active path for IGAindependent of the applied stress (Fig. 8). In the stressedspecimen (Fig. 4), the dominant crack in stage II seems togrow from the IGA-induced fissures in the atoll center(Fig. 7) and the CGR is relatively low (0.04 µm/s). This isconsistent with the active path corrosion (APC)-predominantcracking mechanism that is dependent on the sensitized

microstructural features in much lower CGR than hydrogen-assisted cracking.28,33)

With the corrosion enhanced, some dissolved metal ionscan be hydrated by reactions (7) and (8).31) Hydrolysisreactions decrease the local pH, which not only promotefurther metal dissolution but also cause the cathodic hydrogenevolution by reactions (9) as the depletion in oxygen in thecrack tip. The atomic hydrogen adsorbed on to the steel sur-face, Had, can either recombine to form molecular hydrogenand release as gas bubble by reaction (10) or diffuse into thesteel, Hab, by eq. (11)27,28) and assist in cracking.

Fe2þ þ 2H2O ! FeðOHÞ2 þ 2Hþ ð7ÞCr3þ þ 3H2Oþ 3Cl� ! CrðOHÞ3 þ 3HCl ð8Þ2Hþ þ 2e� ! 2Had ð9Þ2Had ! H2" ð10ÞHad ! Hab ð11Þ

The diffusion of hydrogen into BCC steel is known to beextremely rapid even at room temperature.27,28,33) This canexplain that the crack growth shifted toward a rapidpropagation (CGR of 1.68 µm/s) of stage III in only 31seconds after the first capture of hydrogen bubbling (Figs. 4and 6). The predominant model responsible for SCC instage III is therefore supposed to be hydrogen-assistedcracking in relation to hydrogen embrittlement (HE) mechan-ism. From the high-local plastic strain along the crack path instage III (Fig. 7), the role of hydrogen on the present casemay play a role in promoting dislocation emission at thecrack tip in relation with the hydrogen-enhance localizedplasticity (HELP) mechanism.34,35)

• In-situ observation, 4590s

• KAM map

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Cluster 1

4570 4580 4590 4600 4610 4620 4630

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clu

ster

2, N

Cum

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clu

ster

1, N

Cluster 2

Fig. 11 The evolution of low-frequency cluster 2 correlated with the transition area of high local strain recognized by KAM map of thecrack path.

In-Situ Observation and Acoustic Emission Monitoring of the Initiation-to-Propagation Transition of Stress Corrosion Cracking 2157

In a summary, SCC on the present corrosion system startedwith a chemical-predominant precursor evolution of pittingcorrosion (stage I), subsequently developed with APC-predominant slow crack initiation from the pitting and IGA(stage II), thereafter transitioned to a hydrogen-assisted rapidcrack propagation predominantly controlled by HE mechan-ism (stage III).

4.2 AE analysis and AE-based SCC monitoringIn the present corrosion system, the AE signals are well

recorded with the crack initiation and propagation. However,no AE event is detected in the precursor evolution of pittingcorrosion (stage I). In the author’s previous work,10,11) steelpitting corrosion that was purely controlled by electrochem-ical method was indeed monitored with the concurrent AEsignals. Additionally, the AE behavior was correlated withthe morphology of corrosion pit.12) Nevertheless, it mustbe noted that the AE detectability largely depends onexperimental conditions, the pit growth rate, the morphologyand dimension of pitting. In the electrochemically controlledpitting in acidic chloride solution,10­12) pitting grows quicklyand results into large pit. Even though, there exists aphenomenon of “delay time” for AE detection whichcorresponds to a critical pit size required for the acousticallyactivation of pitting corrosion. Different from the pitting inbulk solution, the pitting under neutral chloride dropletdevelops with the Cl¹ diffusion and the reactions of local celland therefore grows more moderately in rate and size thanthe electrochemically controlled pitting corrosion. This mayaccount for the difficulty in early pitting detection in dropletcorrosion with AE signals.

After pit-to-crack transition (stage II), the AE signals arenot detected immediately until a certain length (Fig. 6),indicating an AE-based NDT limit to SCC monitoring in thepresent case. From a comparison between the singledominant crack growth in stage II of stressed specimen(Fig. 4) and IGA in unstressed specimen (Fig. 8), coales-cence between the IGA-induced fissures, which serves as themain AE source, seemingly leads to the formation of a singledominant crack normal to the loading direction. Theformation of such fissures is confirmed to be silent in thecomparative experiment of unstressed specimen (Fig. 8).Suggestively, the AE-based NDT limit is likely linked to thegrowth of IGA-fissure at the pit mouth (Fig. 4(c)) before theoccurrence of fissure coalescence (Fig. 4(d)).

In stage II, the AE activity is quite moderate in amplitudelevel and number compared to stage III. This is probably thedirect response to the distinction between the CGR of stageII and III (0.04 µm/s vs. 1.68 µm/s). This obvious transitionin AE evolution may not only play a part in the SCCmonitoring, but matters in the discrimination between theAPC and HE-predominant cracking mechanisms. Last butnot least, attention should be paid to the correspondencebetween the low-frequency AE cluster 2 and the transitionarea of plastic deformation. Despite the qualitativecorrelation, the result indicates that the AE monitoringexhibits great potential in elucidating the SCC mechanism.Moreover, more attention is being paid to improve thecluster analysis to distinguish the AE features betweenhydrogen bubble evolution, plastic deformation and crack-

ing. Further improvement is expected to be reported in nextpaper.

Historically, SCC is often divided into the initiation andpropagation phases2­6) (Fig. 1). In most application, thedivision is arbitrary to a large extent. In this work, based ondiscussion above, stage I is the chemical-predominant pittingcorrosion being reasonably termed as “precursor evolution”.Stage II is probably APC-predominant crack growth in termsof “low rate and moderate AE response” and could bedeemed to be “crack initiation”. Stage III is predominantlycontrolled by hydrogen-assisted cracking in terms of “highrate and intense AE response” and therefore termed as “crackpropagation”. Table 1 shows the correspondence between theSCC process and the corresponding AE feature. Although anexact statistical analysis of all experimental data was notincluded in the aim of this work, distinct AE behavior isrelated to the different SCC stages. From this point on, theAE monitoring could effectively reflect the initiation-to-propagation transition during SCC progression. It is thusexpected that with the featured characteristics of AE behaviorupon the selected corrosion system it could benefit theunderstanding and monitoring of the initiation and prop-agation of SCC process.

5. Conclusions

A simple, repeatable SCC system (material properties, heattreatment, chloride solution droplet, humidity, surface finish,U-bend, etc.) was improved to facilitate a single crackevolution in SUS420J2 stainless steel and simultaneously toaccommodate in-situ observation and AE monitoring experi-ments. The following conclusions were drawn.(1) The SCC process could be recognized as three stages.

After the gradual visualization of a corrosion “atoll”because of local corrosion cell action, a single dominantcrack started with a precursor evolution of pittingcorrosion (stage I), subsequently developed with a slowcrack initiation (stage II) from the coalescence ofIGA fissures and finally transitioned to a rapid crackpropagation after the hydrogen-bubble observation(stage III). Crack initiation and propagation arebelieved to be predominantly controlled with APCand HE mechanisms, respectively.

(2) Not detecting AE signals in early pitting stage indicatesan AE-based NDT limit to SCC. The crack, shortly afterpit-to-crack transition, could be detected with AEsignals. AE events were moderate in stage II whilemassive in stage III. The distinction in number of AEevents well reflected the initiation-to-propagationtransition during SCC process.

(3) Cluster analysis of AE signals extracted two differentclusters with different frequency levels. Correlated withKAM map of crack path, low-frequency AE cluster waswell corresponding with the area of high local strain inthe propagation region. Low-frequency cluster seemsto be correlated with the plastic deformation along thecrack path. High-frequency cluster is supposed to bewith the cracking process.

(4) Despite further analysis is being improved in statisticalanalysis and source discrimination, with the reliable

K. Wu et al.2158

correlations between AE features and SCC progressionit is expected to provide AE-based in-situ NDTinsights into the understanding and monitoring ofSCC process.

Acknowledgement

This work was partially supported by Council for Science,Technology and Innovation (CSTI), Cross-ministerial Strate-gic Innovation Promotion Program (SIP), “StructuralMaterials for Innovation” (Funding agency: JST).

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Table 1 In-situ observation and basic features of the detected AE signals during SCC progression.

In-Situ Observation and Acoustic Emission Monitoring of the Initiation-to-Propagation Transition of Stress Corrosion Cracking 2159