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Research Papers: Pipeline Systems

A Phenomenological Model for Fatigue Crack Growth Rate of X70 Pipeline Steel in H2S Corrosive Environment

[+] Author and Article Information
Jing Wang

Lecturer
College of Mechanical Engineering
& Applied Electronics Technology,
Beijing University of Technology,
Beijing 100124, China
e-mail: wjing@bjut.edu.cn

Xiao-yang Li

College of Mechanical Engineering
& Applied Electronics Technology,
Beijing University of Technology,
Beijing 100124, China
e-mail: lixy@bjut.edu.cn

Contributed by the Pressure Vessel and Piping Division of ASME for publication in the JOURNAL OF PRESSURE VESSEL TECHNOLOGY. Manuscript received December 19, 2012; final manuscript received February 8, 2014; published online April 28, 2014. Assoc. Editor: Roman Motriuk.

J. Pressure Vessel Technol 136(4), 041703 (Apr 28, 2014) (10 pages) Paper No: PVT-12-1196; doi: 10.1115/1.4026821 History: Received December 19, 2012; Revised February 08, 2014

Long distance pipeline transmission is considered to be the most economic and safest method to transport natural gas in recent days. The pipeline safety problem is a focus of concern in the academic and industrial circles. Wildly used material X70 pipeline steel is tested in this paper. Based on actual conditions of long distance pipeline, experiments were designed by using orthogonal method. Corrosion fatigue crack growth tests were carried out under different H2S concentrations (2000 ppm, 1000 ppm, 500 ppm), stress ratios (0.9, 0.8, 0.7), and load frequencies (0.0067 Hz, 0.01 Hz, 0.013 Hz). A phenomenological model was built based on test data and Paris formula, which corrects parameters C and n of the Paris formula at the same time. The boundary element method (BEM) was used to simulate the process of corrosion fatigue crack propagation. Fatigue crack growth rates (FCGRs) under different loading conditions were obtained and all the parameters of the phenomenological model were calculated from test data. Compared with traditional Paris formula, this new model shows coupling interactions of stress ratio, load frequency, and H2S concentration to both slope and intercept of FCGR curve in log-log space. The simulation results show that the largest difference between actual test data and BEM simulation is less than 10%. According to the analysis of coupling interactions of each factor, the slope of fatigue crack growth rate (FCGR) curve in log-log space is mainly influenced by frequency; the influence of H2S concentration is nonlinear, and FCGR increases significantly with the increase of stress ratio and decrease of frequency. The BEM is suitable to be used in the engineering field to predict the residual life of pipelines.

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References

Figures

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Fig. 1

Microstructure of X70 steel (acicular ferrite)

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Fig. 2

Modified WOL specimen (mm)

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Fig. 3

Schematic of corrosion fatigue test device

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Fig. 4

Corrosion fatigue test device

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Fig. 5

Test data of corrosion fatigue crack growth rate experiments in H2S solution. (a) FCGR test data in H2S solution (2000 ppm), (b) FCGR test data in H2S solution (1000 ppm), (c) FCGR test data in H2S solution (500 ppm)

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Fig. 6

da/dN-ΔK curves of all specimens in log-log space

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Fig. 7

Variation between correction factor B and each factor. (a) Variation between correction factor B and frequency, (b) variation between correction factor B and H2S concentration, (c) variation between correction factor B and stress ratio

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Fig. 8

Variation of correction factor A. (a) Variation of correction factor A with different H2S concentrations, (b) variation of correction factor A with different stress ratios, (c) variation of correction factor A with different frequencies

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Fig. 9

Variation of correction factor B. (a) Variation of correction factor B with different H2S concentrations, (b) variation of correction factor B with different stress ratios, (c) variation of correction factor B with different frequencies

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Fig. 10

Influence of H2S concentration on FCGRs, (a) FCGR surfaces with different H2S concentrations, (b) fracture surface of point A (2000 ppm, R = 0.9, f = 0.0067 Hz), (c) fracture surface of point B (500 ppm, R = 0.9, f = 0.01 Hz)

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Fig. 11

Influence of stress ratio on FCGRs. (a) FCGR surfaces with different stress ratios. (b) Fracture surface of point A (1000 ppm, R = 0.9, f = 0.013 Hz). (c) Fracture surface of point B (1000 ppm, R = 0.7, f = 0.01 Hz).

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Fig. 12

Influence of frequency on FCGRs. (a) FCGR surfaces with different frequencies. (b) Fracture surface of point A (f = 0.0067 Hz, R = 0.8, 1000 ppm). (c) Fracture surface of point B (f = 0.013 Hz, R = 0.9, 1000 ppm).

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Fig.13

Mash result of CT specimen

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Fig. 14

Comparison between a-N curves obtained from BEM and test data (air environment)

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Fig. 15

Comparison between a-N curves obtained from BEM and test data (2000 ppm, R = 0.8, f = 0.01 Hz)

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