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Acoustic Emission Monitoring of HIC Growth in Carbon Steel: Laboratory Testing
H. Attara, A. Traidiaa and A. Enezia
aResearch & Development Center, Dhahran, Saudi Aramco, [email protected]
Key: Acoustic Emission, Hydrogen-Induced Cracking
Abstract In the present work, Acoustic Emission Technique (AET) has been successfully used to identify
corrosion and cracking mechanisms that take place in 3 different types of low-carbon steels, and thus
to detect the acoustic signature of HIC. A manual approach has been followed in which a number of
experiments have been conducted to identify different mechanisms that can be monitored and detected
by the AET. The identified clusters are almost identical to what previous work by Smanio proposed,
however, it has been found that Hydrogen Induced Cracking (HIC) - resistant materials would also lead
to the generation of a cluster that has been related only to Non-HIC resistant materials in Smanio’s
work. Therefore, the approach followed in this investigation is based on the number of vectors resulted
in each of the cluster rather than specifying unique signal cluster that is only related to the HIC
development as the HIC-resistant materials would be expected to develop hydrogen embrittlement
phenomena and negligible amount of nano cracks. Nevertheless, AET showed a very promising
outcomes for qualifying the HIC resistivity of the steel, and for monitoring the three-different stages
that developed in sweet service steel at laboratory scale.
Introduction
Legacy steels manufactured prior to 1980s are still being utilized worldwide in the oil and gas industry for the transportation and treatment of hydrocarbons, while progressively replaced with more attractive steels. Due to their poor microstructure which is relatively rich in elongated manganese sulfide inclusions, such legacy steels are quite susceptible to hydrogen induced cracking when used in wet sour environment. Although the mechanism of HIC is now relatively well understood and the use of HIC-resistant steels with controlled microstructure has become a standard in material selection for sour environment, the idea of replacing all legacy pipelines with the newly developed steels is cost ineffective. TM-0284 standard has been developed in 1984 by NACE organization to give guidelines in classifying the steel based on its resistant to HIC on the basis of the Crack Area Ratio (CAR) using Ultrasonic Testing (UT) or Optical Microscope (OM). These requirement might change based on the severity of the environment and on the agreement between the end user and the manufacturer. HIC is originated if the steel is corroded by the influence of H2S species, which has the capability to hinder the recombination reaction of hydrogen, giving rise to extensive number of atomic hydrogen, in which they would penetrate and diffuse into the steel due to size difference under the act of pressure in the environment. Certain microstructure and inclusions would trigger and trap the hydrogen atoms within them, and with time, the hydrogen atoms will combine and from hydrogen molecules that would initiate the cracks leading to the HIC phenomena.
In order to continue operating such legacy steels with sufficient level of safety until their retirement from service, a mitigation plans must be put in place. This includes internal coating, frequent UT inspection of most susceptible locations associated with fitness for service assessment to decide whether or not the level of damage can still be accepted. In
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parallel, this mitigation plan can be complemented by the use of a Structural Health Monitoring (SHM) technique to track in real time the growth of HIC damage – the purpose of this work.
The main employed technique to evaluate and assess in-services HIC growth is advanced UT. The common concern of this NDT technique is its incapacity to track in real time the historical development of the cracks from the initiation stage. In contrast, , Acoustic Emission Technique (AET) has the power to perform online analysis and is classified as a real-time monitoring technique that could be utilized properly to monitor the acoustic activity in in the area of cracks detection , and ultimately track crack growth if the signatures of the different phenomena could be appropriately identified. Over the last half century, AET has been employed in many cases to investigate the signatures obtained before the initiation, during the growth of the cracks and upon the failure of sample for multiple failure mechanisms. In particular, it has been widely used in the field of Stress Corrosion Cracking (SCC) [1-10]. Less attention has been paid to HIC mechanism. Most published studies are related to laboratory experiments (ref) and the authors have treated the data generated during the whole experiment in global manner assuming that there is no difference between the characteristics of signals produced by other sources away from cracks. [11-13]. The major breakthrough has been accomplished by Smanio et al. [14-15] in which the authors followed successful logical steps to manually discriminate between the sources of acoustic waves such as hydrogen evolution (as a consequence of corrosion process), the formation of iron sulfide layer and finally crack initiation and growth. In a subsequent work, the authors were able to correlate the cumulated energy relative to the signals attributed to HIC growth with the CAR as measured by UT at the end of the experiment. Other research has confirmed that different clusters would developed for different activities [16]. Although some efforts has been done to study the kinetics and size the cracks using the acoustic [14], this area still unclear and vague.
The present paper work aims at re-confirming the manual clustering approach proposed by Smanio et al. using different pipeline steel grades. In addition, the experimental system used in the present work enables the simultaneous exposure of different steel plates and microstructures to the same environment which gives an added value and confidence in the results as compared to previously published data.
Experimental Procedure
Two types of low-steels were used for the experimental work; two pipeline steel grades (API X65 and X42) obtained from the field. HIC qualification tests according to NACE-TM-0284 were conducted on all steel grades to evaluate their susceptibility to HIC. . It revealed that X65 is classified as HIC resistant materials, whereas the X42 is HIC susceptible material. The chemical composition of the steels were analyzed according to ASTM E415 by Optical Emission Spectroscopy (OES) and is shown in the below table.
Steel C% P% Mn% Si% Ni% Cr% B% Ti/Nb%
X42 0.10 0.009 1.100 0.23 0.02 0.12 0.001 <0.01
X65 0.04 0.013 1.580 0.33 0.15 0.17 0.006 0.01/0.04
Table 1: Chemical Composition (wt%) of the steel used in the tests
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The low-alloy steels were machined in circular shape coupons with a dimension of 73 mm in diameter and thickness ranging from 8-10 mm. SiC polishing papers were used down to 320 grit according to NACE qualification test to allow for a proper surface preparation for the tests. Two different types of coupons have been tested simultaneously using the cell design shown in Fig. 1. Interestingly, the test cell design not only allows the use of different specimens in a single experiment, but it also allows a single side exposure of the test specimen which results in continuous hydrogen flux from the exposed surface to the outer surface through the experiment. This important feature allows to mimic the actual sour corrosion of pipelines and pressure vessels in the field and differentiates the present work with previously published results. . Open clamps were used to install and connect the specimens to the cell and expose it to the environment which consists of pure H2S gas bubbling in 1.7 L of NACE solution A electrolyte to promote sour corrosion and hydrogen uptake in the specimens. . Nitrogen gas purging was used before the saturation of the test solution with H2S to ensure removal of any trace of oxygen gas inside the cell (to dominate the sulfide corrosion process). The duration of H2S exposure varied from 4 to 8 days, followed by a N2 purging prior to opening the cell and removing the samples.
Figure 1: Experimental Setup for Acoustic Emission exposure test
The acoustic emission sensors were attached to the outer surface of the specimens to record the acoustic activities throughout the experiment. The AE system consists of a four-channel acquisition card with piezoelectric AE sensors, preamplifiers supplied by Physical Acoustic Limited Corporation (AEWIN software was used for data collection). The advanced data analysis has been done using NOESIS software. The amplitude threshold was adjusted to 40 dB (suggest by Smanio [17] to filter out big percentage of the surrounding noise) with a 40 dB preamplifier gain selection. The sample rate was chosen to be 1 million sample per second (1 MHz).
Result & Discussion
HIC Susceptibility
As per NACE standards TM0284, X65 has shown a great resistance towards developing HIC, whereas X42 was extensively affected by the sour corrosion and developed sufficient
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crack ratio to be classified as a HIC-susceptible steel. The tested steels were have been studied before and after the HIC qualification experiment, and UT analysis and microscopic calculation data revealed a great resistance of these grades of steel.
The optical microscope micrographs revealed that X42 consists of ferrite grains embedded with ferrite-pearlite banding along the rolling direction. On the other hand, the other grade is lacking of this banding behaviour. Moreover, the NMI content in X42 specimens are much higher than the other steel which indicate a high trapping efficiency of hydrogen atoms.
AE results
The main objective of the study is to ensure the feasibility of AET to distinguish the HIC-related signal from others. Therefore, the experiments have been varies in order to study the different acoustic activities produced from each experiment individually.
Noise signals
The first batch of experiments was conducted to identify the range of signals under noisy environment containing deionized water purged with pure nitrogen so it did not cause any type of corrosion or cracking development. As a result, under these condition, only AE signal associated with the noise are active. It was checked that there is no formation of corrosion layer and thus, the dense part (98 %) of the results considered to be AE sources originated from noise environment i.e. bubbling of gases, flow of solution, suction off gases by the fume hood.
As part of the corrosion mechanism that take place at the steel surface, as reported in many literature, the following equation takes places between the species:
𝐹𝑒 + 𝐻2𝑆𝑦𝑖𝑒𝑙𝑑𝑠→ 𝐹𝑒𝑆 + 𝐻2
The detailed processes of the previous reaction composed of anodic and cathodic reaction that would mainly form hydrogen molecules at the surface of steel. With the existence of sulfide species, the poisonous effect of it inhibit the recombination reaction of the hydrogen ion/atom to form hydrogen molecules. Therefore, part of the hydrogen would diffuse into the steel under the pressure factor, while the other part will be recombined and evolve hydrogen within the environment. Therefore, this evolution has been treated as the bubbling of gaseous inside the environment which will have similar characteristics. Table 2 gives the range of the main parameters that have been related to the bubbling effect.
Figure 2: Microstructure of X65 (left) and microstructure of x42 (right). It can be seen
that the perlite banding is elongated in X42 specimen whereas the microstructure is more
homogenous for X65.
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Parameters Range
Absolute Energy 0 – 5000 aJ
Duration 0 – 1000 µs
Amplitude 0 – 50 dB Table 2: Main characteristics that are believed to be related to related to noise in addition to
the hydrogen bubbling effect.
Corrosion layer signals
In order to identify the AE that are related to the formation of the sulfide layer, two approaches has been followed:
1- HIC-resistant materials has been tested simultaneously with Non-HIC resistant material at the same condition.
2- HIC-resistant material has been tested solely.
From these two approaches, it has been found that the both materials reveal a class that has a higher absolute energy and a relatively higher average duration compared to the noise/bubbling signals. Nonetheless, this class might interfere with the noise class, knowing that, the noise class has been greatly enhanced in terms of the number of hits after the introduction of the corrosive solution. Though, the development of the higher energy signals are certainly attributed to the corrosion layer formation as described by Smanio [17]. These signals represent almost 6.5% of the total signals generated during the test which lasted for 4 days. From the set of tests conducted in this investigation, it can hypothetically suppose that the rate of corrosion reaction that is occurring at the HIC-susceptible steels are relatively higher than HIC-resistant steel. This has been reported by Merson [16].
HIC Signals
Although the approach of simultaneously exposing both grades of steel to the sour environment would be thought to clearly reveal the signals related to HIC, the HIC-resistant steel shows some orientation towards developing these cracks contradicting to the results that has been found by Smanio in different studies [17].
Therefore, this investigation of acoustic signals generated from HIC initiation and development was based on the magnitude of the signals (cumulative Hits) rather than attributing it to a completely new separate class. As per John [18], the AE would be able to detect nano level mechanism that take place in the steel. Therefore, while the hydrogen is diffusing through the steel, hydrogen embrittlement or Nano cracking phenomena might evolve in the HIC resistant steel causing signals to overlap with signals that were correlated with HIC as Samino proposed. Figure 3 and 4 show the difference in the shape between HIC resistant steel and non-HIC resistant steel, in addition to the number of Hits for each one of them that are correlated each class separately based on the manual description (figure 5).
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Figure 3: Reperesntation of the signals generatedfrom HIC resistant steel in Energy-Duration
graph (above) and the evolution of these signals with time (below) it can be seen from the below
diagram that the bubbling and corrosion signals are continuous whereas the HIC signals are
not.
Figure 4: Reperesntation of the signals generatedfrom Non HIC resistant steel in Energy-
Duration graph (above) and the evolution of these signals with time (below), in comparsion
with signals generated from HIC resistant steel, these signals are more continous are denser.
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Figure 5: Number of HITs that generated in each of the cluster for HIC resistant steel (ch1),
Non HIC resistant steel (ch2) where class 1 represents bubble and noise, class 0 represents
HIC signals.
It worth to note from figure 4, that the signals pertain to HIC can be further divided into two different categories; high duration-low absolute energy and high duration-high absolute energy signals (this class is less denser in HIC Resistant steel) which would be further investigated in future studies based on the statistical approaches and additional experiments. Moreover, it clearly indicated in figure 3 that the corrosion layer related signals are denser in HIC susceptible steel compared to HIC resistant steel samples (almost 12 times greater for both HIC and corrosion layer signals which would be investigated in future researches). The results are reproducible given that 3 set of tests have been conducted on the same types.
Closing
In this study, it has been shown that AET considered as a promising powerful tool to be utilized for crack detection along with the UT in pressure vessel and pipeline steel for oil & gas applications, and those signals and cluster are pretty much similar to what has been found in the previous studies. Further investigation and treatment of the signals would be necessary to a complete discrimination. That involves, correlation between hydrogen permeation rate, corrosion rate and acoustic signals attributed to both hydrogen evolution and FeS layer formation. Phased array UT, modifying the corrosive environment, eliminating the generated noise from bubbling the gas, usage of different materials that have different resistivity towards forming HIC and corrosion layer and in-situ measurement of crack development and acoustic signals are essential activities to demonstrate clear discrimination between the different activities. Furthermore, the utilization of supervised techniques for clustering would be very helpful for further understanding of these clusters and their evolution with time.
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