RECENT INNOVATIONS IN PIPELINE SEAM WELD INTEGRITY ASSESSMENT

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1 RECENT INNOVATIONS IN PIPELINE SEAM WELD INTEGRITY ASSESSMENT Ted L. Anderson Quest Integrity Group 2465 Central Avenue Boulder, CO USA ABSTRACT. The integrity of pipelines with longitudinal seam welds has received renewed interest by operators and regulators, due primarily to a number of high-profile incidents. The pipeline industry currently assesses planar flaws in seam welds with methodology that dates back nearly 40 years. The traditional crack assessment models can lead to gross errors in the prediction of burst pressure. This article points out the problems with these models, using both theoretical analysis and a comparison with burst test data. Improved flaw assessment methods are described, along with a new software application for automated pressure cycle fatigue analysis. BACKGROUND There have been a number of catastrophic failures in seam-welded pipelines in recent years, the most notable of which was the 2010 explosion of a Pacific Gas & Electric (PG&E) pipeline in San Bruno, California. There is increasing pressure on operators to demonstrate that they are taking steps to improve the integrity of their pipelines. Simply adhering to the status quo in the form of existing integrity plans is no longer an option. The pipeline industry currently relies on flaw assessment methods that are nearly 40 years old, but improved models are available. There have been significant advances in fracture mechanics, fitness-for-service assessment, and remaining life models in the past 40 years. The pipeline industry can benefit by adopting methodologies that have been successfully applied in other industries, including oil & gas production, refinery, chemical, petrochemical, and power generation. This paper presents a sample of innovative technology that can be applied to the integrity management of seam-welded pipe. The focus of this article is on cracks and other planar flaws, but innovative approaches for other anomaly types are also available. Traditional methods for assessing flaws in pipelines, particularly crack assessment models, have a number of series serious shortcomings. These models are re-evaluated against burst test data in light of our improved knowledge of fracture mechanics. Also, a new software application for automated pressure cycle fatigue analysis is described.

2 OVERVIEW OF FAILURE OF PIPELINES CONTAINING CRACKS The presence of cracks and other planar flaws can significantly lower burst pressure in a pipe. The magnitude of the reduction is a function of crack size and material toughness. Figure 1 illustrates the relationship between burst pressure and toughness for a given crack. The toughness in this example is characterized by the critical stress intensity factor, K c, which is a fracture mechanics parameter [1]. Figure 1 shows three distinct regimes. At low toughness values, the pipe exhibits linear elastic material behavior, and burst pressure is linearly related to toughness. At the opposite extreme, the burst pressure is independent of toughness, and is instead governed by tensile properties. In the ductile rupture regime, metal loss models such as the B31G equations can be used to predict burst pressure. In the elastic-plastic regime, burst is governed by a combination of toughness and tensile properties. Fracture mechanics [1] is a relatively new engineering discipline that provides mathematical relationships between flaw size, material toughness, and burst pressure. Linear elastic fracture mechanics (LEFM) is suitable when the toughness is low. Elasticplastic fracture mechanics (EPFM) is a more robust model that encompasses both the linear elastic and elastic-plastic regimes in Fig. 1. For the past 40 years, the pipeline industry has relied on a crack assessment method, the ln-sec model [2], which predates the development of modern elastic-plastic fracture mechanics. Moreover, LEFM was in its infancy when ln-sec model was developed. Consequently, the ln-sec model contains fundamental errors that often lead to highly inaccurate predictions of burst pressure. This issue is explored further below. FIGURE 1. Relationship between burst pressure and material toughness.

3 THE LN-SEC MODEL Theoretical Evaluation of the Model Kiefner, et al [2] developed the ln-sec model in the early 1970s. It is based on a simplified fracture mechanics approach, and was calibrated to a series of burst data. In 2008, Keifner [3] introduced a modified version of the ln-sec model, which was intended to address known problems in the original method. The original ln-sec model starts with the linear elastic fracture mechanics equation for failure in a pipe with a longitudinal crack of length 2c: K M c (1) c T F where F is the hoop stress at failure, and M T is known as the Folias factor, which is a function of the crack length relative to the pipe diameter and wall thickness. The Folias factor can be viewed as a magnification factor on hoop stress due to the presence of the flaw. For fully ductile rupture (Fig. 1), M T is inversely proportional to the remaining strength factor (RSF), which is the ratio of the hoop stress at failure in the flawed pipe to the flow stress of the material: F 1 RSF (2) M flow T where the flow stress is taken to be the hoop stress at failure in a pipe without a flaw. Now consider a part-through surface crack, as illustrated in Fig. 2. Keifner et al introduced a surface correction factor, M s, which is equal to the remaining strength factor for this configuration: M s A 1 A o RSF 1 A 1 MT Ao (3) Where A is the area of the flaw and A o is the rectangular area t 2c. Equation (3) forms the basis of the B31G remaining strength factor equations and similar standard methods for assessing metal loss. Keifner et al [1] observed that Eq. (3) over-predicted the burst pressure for pipes with axial cracks, except when the material toughness was very high (as one would expect from Fig. 1). They adjusted for toughness by incorporating Eq. (3) into a simplistic elasticplastic fracture mechanics model, which was the only such model available at the time:

4 FIGURE 2. Part through surface flaw. K CVN 12 E A 2 c c F lnsec 2 2 8c flow 8c flow 2M s flow (4) Where CVN is Charpy energy in ft-lbs, A c is the area of the Charpy specimen (in 2 ), and E is Young s modulus in psi. The above expression, which is the original ln-sec model, assumes the following relationship between K c and Charpy energy: K c 12CVN E (5) A c Although Eq. (4) predicts the correct shape of the burst pressure versus toughness curve (Fig. 1), the predicted slope in the linear range differs from LEFM. Part of the problem is the surface correction in Eq. (3), which appears to work well for fully ductile rupture, does not apply to the linear elastic range. Figure 3 is a plot of the error in the original ln-sec model in the linear elastic range, relative to a rigorous LEFM model. Note that the largest error occurs for long and shallow cracks. Keifner became aware of the problems with Eq. (4) for long & shallow cracks, based on outliers in the original set of burst test results, as well as through subsequent application the model to new burst test data and hydrostatic test failures. In 2008, Keifner introduced a modified version of the ln-sec model [3]. The modified model included a correction factor that attempted to address the problems with long, shallow cracks.

5 FIGURE 3. Error in the original ln-sec model in the linear elastic range. Equation (4) was compared with a rigorous LEFM model for the case where toughness 0. Figure 4 is a plot of predicted burst pressure versus toughness, which is represented as CVN in order to retain the linear relationship with pressure at low toughness. The original and modified ln-sec models are compared with the LEFM prediction. As stated earlier, the original ln-sec model predicts the correct shape (Fig. 1), but the slope in the linear elastic range is off by roughly a factor of 2 in this specific case. The modified model, however, does not even predict the correct overall shape. This model predicts that burst pressure is insensitive to toughness, and that a non-zero burst pressure would be achieved with zero toughness. In other words, the error in the modified ln-sec model is infinite as toughness approaches zero.

6 FIGURE 4. Predicted burst pressure versus toughness for LEFM, as well as the original and modified ln-sec models. The original model has the correct shape (Fig. 1) but the slope in the linear elastic range is off by a factor of 2 in this case. The modified model predicts that burst pressure is insensitive to toughness, which is fundamentally incorrect. Comparison with Burst Test Data The shortcomings in both the original and modified ln-sec models, which were identified above through theoretical analysis, can also be observed in burst test data. The original Keifner et al article [2] includes burst test data for both blunt and sharp notches, where the latter was intended to represent sharp cracks. A subset of 35 burst tests in this article, which consisted of pipes with sharp surface notches for with Charpy data were available, are suitable for comparing with both Eq. (4) and Keifner s recent modification. Table 1 summarizes the comparison between predicted and actual burst pressure in the 35 experiments. The original ln-sec model is conservative on average, while the average predictions of the modified model are close to reality. The standard deviation in the predictions is slightly higher for the modified model. Merely looking at average predictions is not sufficient to identify systematic errors in the two models. Figures 5 to 7 are plots of predicted/actual burst pressure versus flaw length, flaw depth, and Charpy energy, respectively. According to Figures 5 and 6, the original ln-sec model grossly under-predicts burst pressure for long and shallow cracks, respectively. This result is consistent with Fig. 3. The modified model appears to correct the under-predictions, which was Keifner s intent, but there are also outliers

7 where the burst pressure is grossly over-predicted. The reason for these unconservative outliers is evident in Fig. 7, where predictions are plotted against Charpy energy. Most of the unconservative predictions correspond to low-toughness materials. TABLE 1. Summary of the comparison of the original and ln-sec models with 35 burst test results from the original Keifner et al article [2]. Predicted/Actual Burst Pressure Original Ln-Sec Model Modified Ln-Sec model Average of 35 Tests: Standard Deviation: FIGURE 5. Ln-sec model predictions versus flaw length. The original ln-sec model significantly underpredicts burst pressure for long flaws.

8 FIGURE 6. Ln-sec model predictions versus crack depth/thickness (a/t). The original ln-sec model significantly under-predicts burst pressure for shallow flaws. FIGURE 7. Ln-sec model predictions versus Charpy energy. The modified ln-sec model significantly overpredicts burst pressure for materials with lower toughness.

9 STATE-OF-THE-ART FRACTURE MECHANICS ANALYSIS Significant advances in the field of fracture mechanics have occurred over the past 40 years, when the original ln-sec model was developed. For example, the API 579-1/ASME FFS-1 Fitness-for-Service Standard [4] includes a simplified fracture mechanics model that is vastly superior to the ln-sec model, both the original and modified versions. A more advanced fracture mechanics model is described below. The J-Integral and Finite Element Analysis The most rigorous (and accurate) method to predict the effect of cracks on burst pressure is 3D elastic-plastic finite element analysis. Figure 8 shows a typical finite element model of a longitudinal crack in a seam weld. The preferred fracture mechanics parameter for elastic-plastic analysis is called the J-integral. Fracture toughness in the elastic-plastic regime is characterized by a critical value of J. Refer to Reference [1] for the detailed background of the J-integral. FIGURE 8. Typical finite element model of a longitudinal crack in a seam weld. The model is ¼ symmetric, meaning that the above picture represents ¼ of the pipe, with sections taken longitudinally through the seam weld and circumferentially at the mid-point of the crack.

10 While 3D finite element analysis is the most accurate method to predict burst conditions in pipes that contain cracks, it is not practical for widespread use. Finite element analysis requires special software and expertise which may not be easily obtained by a pipeline operator for standardized assessment. Recently, PRCI undertook a research program that addressed this concern. Southwest Research Institute, who was the contractor for the PRCI project, performed a large number of 3D elastic-plastic finite element analyses of pipes with seam weld cracks. They curve fit these results and produced a series of equations and tables that are presented in the final report [5]. Using Charpy Data in a Crack Assessment Traditionally, the pipeline industry has relied on Charpy testing to characterize toughness. However, fracture mechanics testing that quantifies toughness as a critical stress intensity factor (K c ) or critical J-integral provides a more direct measurement. Figure 9 compares the Charpy test specimen geometry with a typical fracture mechanics specimen. Both were notched on the ERW bond line. With the fracture mechanics specimen, however, a fatigue crack is introduced on the bond line. As a result, the specimen shown in Fig. 9(b) is more representative of a seam weld crack. Stated another way, a J test provides a direct measure of fracture toughness, while the Charpy test is an indirect measurement, analogous to ultrasonic wall thickness (UT) versus magnetic flux leakage (MFL) inline inspection technologies. It is possible to use Charpy data in an advanced crack assessment that applies either finite element analysis or the PRCI method. The trade-off is that the correlation between Charpy energy and the critical J-integral exhibits scatter and uncertainty, as discussed below. Wallin [6] has correlated Charpy energy with critical J-integral data by evaluating over 1000 data sets that encompass a range of steels. While there is a reasonable correlation between the two tests, it is not perfect. Equations (6a) to (6c) give the Wallin relationship, in US customary units, for the mean correlation, as well as the 5% lower bound and 95% upper bound. The original Wallin correlation is based on full-size Charpy specimens, but the expressions below include an adjustment for subsize specimens. J 1 mm in CVN Mean Correlation Ac (6a) J 1 mm in CVN 5% Lower Bound Ac (6b) J 1 mm in CVN 95% Upper Bound Ac (6c)

11 ERW Seam (a). Charpy V-notch specimen. Fatigue Crack (b) Fracture mechanics specimen. FIGURE 9. Laboratory specimens for measuring toughness at an ERW seam.

12 Where J 1 mm is the critical J-integral at 1 mm (0.039-in) of crack growth (ductile tearing). Despite the large dataset Wallin had at his disposal when developing his correlation, it is unlikely that the data included tests on ERW pipe. One would expect the base material (typically an API 5L steel) to fit the correlation because the Wallin dataset undoubtedly included steels with similar chemistry and microstructures. The ERW bond line and heataffected zone are another matter, however. One concern is that the Charpy notch is wider than the bond line, and might not give a true reflection of the toughness. Recently, the present author conducted Charpy and J testing on two different samples of ERW pipe. Both Charpy and fracture mechanics specimens were notched in 3 locations: the fusion line, 1 mm from the fusion line, and in the base metal. The results are plotted in Fig. 10, along with the predictions from the Wallin correlation (Eq. (6)). Each data point corresponds to the average of 3 Charpy tests, as well as a single J test. Five of six points fall within the 90% confidence band, but there is one outlier for tests on the bond line. Further testing on additional ERW seams will be necessary to confirm whether or not the Wallin correlation applies to the bond line, but the results in Fig. 10 are encouraging. FIGURE 10. Correlation between Charpy data and critical J-integral values for two samples of ERW pipe. The curves correspond to predictions from the Wallin correlation (Eq. (6)).

13 Even if the Wallin correlation applies to ERW seams, using Charpy data to infer toughness comes at a price. Namely, the uncertainty band in critical J values translates to an uncertainty in predicted burst pressure. Figure 11 shows an example of burst pressure predictions from Charpy values. The Wallin correlation was used in conjunction with the PRCI crack model described earlier. In this particular case, the 90% confidence band in the Charpy-J correlation corresponds to approximately a 200 psi uncertainty band in failure pressure. Figure 12 is a repeat of Fig. 11, but predictions from the original and modified lnsec models are overlaid on the graph. The original ln-sec model is biased toward the conservative side, which is consistent with the burst test comparison in Figs. 5 to 7. The burst pressure prediction from the modified model is insensitive to toughness, so it is unconservative at low toughness values and falls within the predicted scatter band (based on the PRCI J-integral model) for moderate toughness levels. FIGURE 11. Effect of Charpy energy on burst pressure, as predicted from the PRCI J-integral model, combined with the Wallin Charpy correlation.

14 FIGURE 12. Same as Fig. 11, but with the ln-sec models overlaid for comparison. AUTOMATED PRESSURE CYCLE FATIGUE ASSESSMENT Seam welded pipelines that are in cyclic service can experience fatigue failure if not properly managed. Planar flaws that are introduced at manufacture can grow over time due to pressure cycling. Eventually, a growing crack will lead to a leak or rupture if it is not remediated. Pressure cycle fatigue analysis (PCFA) is a technique that has been used by the pipeline industry to manage the risk associated with seam weld flaws that may grow in service. Pressure data are typically collected at pumping stations (in liquid lines) and stored in a PI data historian or similar system. Periodically, pressure readings at discrete time intervals are exported to a csv file or spreadsheet. These data are processed through a rainflow cycle counting algorithm, which quantifies the number and magnitude of pressure cycles in the form of a histogram. The histogram is then input into a fracture mechanics model to predict the growth of actual or postulated flaws in the pipeline. The PCFA is used to make decisions on the retest interval or re-inspection interval in cases where the integrity management plan calls for hydrostatic testing or ILI, respectively. The PCFA process is fairly time consuming and labor intensive. In a typical case, a pipeline operator sends pressure data to a consultant, who then submits a report to the

15 operator 2 or 3 months later. A PCFA is usually performed annually because more frequent intervals are not practical. Quest Integrity is has developed a software system, PACIFICA TM, for automatically performing PCFA. Figure 13 illustrates the system architecture. At initial setup for a given pipeline, the user enters basic data, such as pumping station locations, pipe dimensions, elevations, and material properties. Once the system is online, it periodically imports pressure data from the PI data historian, and then processes it through the rain-flow and fracture mechanics algorithms. Both the pressure data input and the processed output are stored in a database. Reports are generated at regular intervals based on user settings. Because the system is automated, it is possible to obtain virtually real-time updates on pressure cycling. For example, an operator may choose to generate PCFA reports on a weekly or monthly basis. It is also possible to track the growth of thousands of flaws in multiple pipelines. FIGURE 13. Overall system architecture of PACIFICA TM.

16 CONCLUSIONS 1. The original ln-sec failure model, which was developed in the early 70s, contains fundamental errors when compared to modern fracture mechanics theory. As a result, significant errors in burst pressure predictions can result. Based on a comparison with burst test data, the model tends to be conservative, but is particularly conservative for long and shallow flaws. 2. The modified ln-sec model was published in 2008, and was intended to address the problems in the original equation. Although the modified model reduces the level conservatism for long and shallow flaws, this fix comes at a high price. Namely, the model is highly unconservative for low-toughness materials. The model predicts that burst pressure is insensitive to toughness, which is simply incorrect. 3. The most accurate predictions of failure of pipes with longitudinal cracks can be made with 3D finite element analysis, but this requires special software and expertise. A new PRCI model overcomes this difficulty by providing parametric equations that are a curve fit of finite element solutions. 4. The J-integral test provides the most direct measurement of fracture toughness. Inferring toughness from Charpy testing is acceptable, but will result in a greater uncertainty in the burst pressure prediction. 5. A new software system has been developed for pressure cycle fatigue analysis (PCFA). This system assists in the integrity management of seam welded pipelines in cyclic service. REFERENCES 1. Anderson, T.L. Fracture Mechanics: Fundamentals and Applications. Third Edition, Taylor & Francis, Boca Raton, Florida, USA, Kiefner, J. F., Maxey, W. A., Eiber, R. J., and Duffy, A. R., Failure Stress Levels of Flaws in Pressurized Cylinders. ASTM STP 536, American Society for Testing and Materials, Kiefner, J.F., Modified Equation Helps Integrity Management., Oil and Gas Journal, October 6, 2008, pp API 579-1/ASME FFS-1, Fitness-for-Service, jointly published by the American Petroleum Institute and the American Society for Mechanical Engineers, June Chell, G.G., Criteria for Evaluating Failure Susceptibility due to Axial Cracks in Pressurized Line Pipe. PRCI Project MAT-8 Final Report, December Wallin, K., Fracture Toughness of Engineering Materials: Estimation and Application. EMAS Publishing, Birchwood Park, Warrington, UK, 2011.