Application of Integrated Computational Materials Engineering (ICME) Tools for Improving Fracture Toughness on ERW Line Pipe
Source abstract
Abstract
This study addressed an integrated computational materials engineering (ICME) approach to understanding the relationships between in-line annealing conditions and low-temperature fracture toughness of electric resistance welded (ERW) line pipe. Work was based on a pipe mill located at Axis Pipe and Tube in Bryan, Texas. The major assumption leading into this work is that the root cause for low-temperature fracture toughness in ERW welds is the presence of a decarburized band along the bond line. This decarburized band is inherent to the ERW welding process, providing a region of highly constrained undermatched material. In the presence of a flaw, a highly constrained fracture along this band can result. For Charpy testing at the bond line, dramatic reductions in fracture energy can be observed. In-line annealing offers the potential for back diffusion of carbon into this bond line, alleviating the fracture toughness concern. To characterize relationships between weld geometry, annealing processing conditions, and the resulting recovery of carbon in the bond line, ICME tools were employed. The approach here has been to use a series of ICME tools to accomplish this effort. This has included creating analytical constructs for pairing the coil with the pipe as well as for subsequent heat transfer in the workpiece itself. Microstructural modeling to address temperature-dependent carbon diffusivity and final phase distributions was done by a combination of design of experiment (DOE) techniques and commercial software. Essentially, commercial software was used to generate microstructural data as a function of processing and steel compositions that could be mapped using the DOE tools. Finally, carbon back diffusion was modeled using a one-dimensional approach with linearized compositional gradients. Tools were integrated into a stand-alone computer application. This application estimated thermal profiles, final microstructures, and degrees of carbon recovery based on inputs of steel geometry, chemistry, and annealer processing conditions. Results were compared with experimental work conducting Charpy impact testing at − 20 °C, using a GLEEBLE thermo-mechanical simulator to replicate various annealing conditions. The results showed a direct correlation between the predicted degree of carbon recovery and the subsequent low-temperature Charpy impact energies.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Microstructure and Mechanical Properties of Steels · Hydrogen embrittlement and corrosion behaviors in metals · Welding Techniques and Residual Stresses
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (29)
Show source-provided references
1. AWS (2007) High frequency welding. In: Welding handbook 9th ed, Vol. 3, welding processes, Part 2. American Welding Society, Miami, FL, pp 159–182
2. Ravikiran K, Xu P, Li L (2024) A critical review on high-frequency electric-resistance welding of steel linepipe. J Manuf Proc 124:753–77710.1016/j.jmapro.2024.06.046 ↗
3. Sharma NK, Kannan R, Li L, Anderson N, Rashid M, Collins L, Poplawsky JD, Unocic R (2021) A mechanism for carbon depletion at bondline of high-frequency electric-resistance-welded X70 pipeline steel. Metall Mater Trans A 52:3788–379810.1007/s11661-021-06339-w ↗
4. Kannan R, Li L, Guo L, Anderson N (2020) Bond formation mechanism for resistance welding of X70 pipeline steel. Weld J Res Suppl 99(8):209s–223s
5. Zak BY, Rys P (1972) The origin of the “Light Area” in upset welds of rolled carbon steel. Weld Res 51(5):262–279
6. Riecansky V, Lucas W (1974) Formation and significance of weld line defects in flash welded mild steel tube and bar. Weld Res Int 4(4):1–27
7. Forostovets BA, Demyanchuk A (1967) Chemical heterogeneity in flash welds in heavy section steel. Automat Weld 20(6):30–34
8. Young BA, Nanney S, Leis B, Smith JM (2014) Overview of a comprehensive study to understand longitudinal ERW seam failures. Int Pipeline Conf 46117:V002T06A050
9. Xu S, Laver A, Gianetto J, Liang J, Tyson WR, Matsuno S (2017) Charpy toughness of ERW seam welds. J Pipeline Eng 16(3):25–35
10. Ravikiran K, Li L, Lehnhoff G, Sharma NK, Kannan R, Saini N, Choudhury SD, Lyu Z (2023) Microstructure and crystallographic texture of high frequency electric resistance welded X65 pipeline steel. Mater Chem Phys 302:12775810.1016/j.matchemphys.2023.127758 ↗
11. Gould JE, Stotler TV, Steeves M (1994) Flash weldability studies of Incoloy alloy® 908. ASME Cogen Turbo Power 94, IGTI 9:77–90. ASME, New York
12. Dong P, Gordon R (1992) The effect of weld metal mismatch on structural integrity assessments—a preliminary investigation. EWI Research Report MR9201. EWI, Columbus, OH
13. Chung PC, Ham Y, Kim S, Lim J, Lee C (2012) Effects of post-weld heat treatment cycles on microstructure and mechanical properties of electric resistance welded pipe welds. Mater Des 34:685–69010.1016/j.matdes.2011.05.027 ↗
14. Rosenthal D (1941) Mathematical theory of heat distribution during welding and cutting. Weld J 20(5):220s–234s
15. Charitat T, Graner F (2003) About the magnetic field of a finite wire. Euro J Phys 24(3):26710.1088/0143-0807/24/3/306 ↗
16. Coufal O (2017) Faraday’s law of electromagnetic induction in two parallel conductors. Int J Appl Electromagn Mech 54(2):263–28010.3233/JAE-160123 ↗
17. NIST (2025) NIST digital library of mathematical functions. https://dlmf.nist.gov/
18. Eagar TW, Tsai NS (1983) Temperature fields produced by traveling distributed heat sources. Weld J 62(12):346s–355s
19. Cole K, Beck J, Haji-Sheikh A, Litkouhi B (2010) Heat conduction using Greens functions. CRC Press, Cambridge10.1201/9781439895214 ↗
20. Mendez, PF (2020) Reduced order models for welding and solidification processes. In: IOP conference series: materials science and engineering, vol 861(1), p 012003. IOP Publishing10.1088/1757-899X/861/1/012003 ↗
21. Andersson JO, Helander T, Höglund L, Shi P, Sundman B (2002) Thermo-Calc & DICTRA, computational tools for materials science. Calphad 26(2):273–31210.1016/S0364-5916(02)00037-8 ↗
22. Thermo-Calc Software AB (2024) Thermo-Calc 2023b [Software]. Thermo-Calc Software AB, Stockholm, Sweden. Includes DICTRA, TCFE13, and MOBFE8 licenses. https://thermocalc.com. Accessed 28 September 2023
23. Diamond WJ (2001) Practical experiment designs: for engineers and scientists. Wiley, Hoboken
24. Zener C (1949) Theory of growth of spherical precipitates from solid solution. J Appl Phys 20(10):950–95310.1063/1.1698258 ↗
25. SciPy—fundamental algorithms for scientific computing in Python. https://scipy.org
26. Flask (2010) User’s guide. https://flask.palletsprojects.com/en/stable/
27. ASTM International (2007) Standard test methods for notched bar impact testing of metallic materials. ASTM Standard E-23. ASTM International, West Conshohocken, PA
28. Kumar AS, Kumar BR, Datta GL, Ranganath VR (2010) Effect of microstructure and grain size on the fracture toughness of a micro-alloyed steel. Mater Sci Eng A 527(4–5):954–96010.1016/j.msea.2009.09.027 ↗
29. Niu Y, Jia S, Liu Q, Tong S, Li B, Ren Y, Wang B (2019) Influence of effective grain size on low temperature toughness of high-strength pipeline steel. Materials 12(22):367210.3390/ma12223672 ↗