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Analysis of Pitting Corrosion of Pipelines in a Marine Corrosive Environment Using COMSOL Multiphysics

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Abstract

In this work, we have developed a pipeline model made of 316 stainless steel considering the pipeline is subjected to a marine corrosive environment (seawater) and investigated pitting corrosion behaviour inside the pipeline with the help of COMSOL Multiphysics software. The extent of pitting corrosion was investigated by examining the electrochemical parameters such as electrolyte potential and electrolyte current density and explored the effect of variation in number of pits on the corrosion behaviour. Electrolyte potential distribution reveals that electrolyte potential variation along the pit surface is small and the value found to be highest at the pit- electrolyte interface. Thus, confirming that the pit electrolyte interface is more susceptible to corrosion. Electrolyte current density distribution showed that electrolyte current density value is highest at the pit, which is 314 A/m2 in case of single 3-D pit suggesting that the pit surface corroded heavily. In the case of multi-pit electrolyte current density distribution, the electrolyte current density computed to be 171 A/m2 and 106 A/m2 in double and triple pits, respectively. The obtained current density values have been used to calculate corrosion rate with the help of Faraday’s law. The multi-pits models are showing the corrosion rate of 195.7 mm/year and 121.3 mm/year for double and triple pit, respectively, which are comparatively lower than that of single pit (corrosion rate of 359.3 mm/year) due to increase in the area of anode surface.

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References

  1. Shabarchin O, Tesfamariam S (2016) Internal corrosion hazard assessment of oil & gas pipelines using Bayesian belief network model. J Loss Prev Process Ind 40:479–495. https://doi.org/10.1016/j.jlp.2016.02.001

    Article  Google Scholar 

  2. Bhardwaj A (2020) Fundamentals of corrosion and corrosion control in oil and gas sectors. Corros Inhib Oil Gas Ind 10:41–76. https://doi.org/10.1002/9783527822140.ch2

    Article  CAS  Google Scholar 

  3. Fessler RR (2008) Pipeline corrosion. Report, US Dep. Transp. Pipeline Hazard. Mater. Saf. Adm. Bak. Evanston

  4. Orazem M (2014) Underground pipeline corrosion. Elsevier, Amsterdam

    Google Scholar 

  5. Belarbi Z, Vu TN, Farelas F, Young D, Singer M, Nešić S (2017) Thiols as volatile corrosion inhibitors for top-of-the-line corrosion. Corrosion 73:892–899

    Article  CAS  Google Scholar 

  6. Mansoori H, Mirzaee R, Esmaeilzadeh F, Vojood A, Dowrani AS (2017) Pitting corrosion failure analysis of a wet gas pipeline. Eng Fail Anal 82:16–25. https://doi.org/10.1016/j.engfailanal.2017.08.012

    Article  CAS  Google Scholar 

  7. Kermani MB, Harrop D (1996) The impact of corrosion on oil and gas industry. SPE Prod Facil 11:186–190

    Article  CAS  Google Scholar 

  8. Caines S, Khan F, Shirokoff J (2013) Analysis of pitting corrosion on steel under insulation in marine environments. J Loss Prev Process Ind 26:1466–1483. https://doi.org/10.1016/j.jlp.2013.09.010

    Article  CAS  Google Scholar 

  9. Ghahari SM, Davenport AJ, Rayment T, Suter T, Tinnes JP, Padovani C, Hammons JA, Stampanoni M, Marone F, Mokso R (2011) In situ synchrotron X-ray micro-tomography study of pitting corrosion in stainless steel. Corros Sci 53:2684–2687. https://doi.org/10.1016/j.corsci.2011.05.040

    Article  CAS  Google Scholar 

  10. Abood TH (2008) The influence of various parameters on pitting corrosion of 316L and 202 stainless steel. Dep Chem Eng Univ Technol Univ Technol

  11. Liu ZY, Li XG, Cheng YF (2012) Understand the occurrence of pitting corrosion of pipeline carbon steel under cathodic polarization. Electrochim Acta 60:259–263. https://doi.org/10.1016/j.electacta.2011.11.051

    Article  CAS  Google Scholar 

  12. Dastgerdi AA, Brenna A, Ormellese M, Pedeferri MP, Bolzoni F (2019) Experimental design to study the influence of temperature, pH, and chloride concentration on the pitting and crevice corrosion of UNS S30403 stainless steel. Corros Sci 159:108160. https://doi.org/10.1016/j.corsci.2019.108160

    Article  CAS  Google Scholar 

  13. Moretti G, Quartarone G, Tassan A, Zingales A (1993) Pitting corrosion behavior of superferritic stainless steel in waters containing chloride. Mater Corros 44:24–30. https://doi.org/10.1002/maco.19930440107

    Article  CAS  Google Scholar 

  14. Tsutsumi Y, Nishikata A, Tsuru T (2007) Pitting corrosion mechanism of Type 304 stainless steel under a droplet of chloride solutions. Corros Sci 49:1394–1407. https://doi.org/10.1016/j.corsci.2006.08.016

    Article  CAS  Google Scholar 

  15. Sedriks AJ (1986) Effects of alloy composition and microstructure on the passivity of stainless steels. Corrosion 42:376–389. https://doi.org/10.5006/1.3584918

    Article  CAS  Google Scholar 

  16. Lan C, Tuerhan M, Liu C, Li H, Spencer BF (2018) Monitoring of chloride-induced corrosion in steel rebars. Corros Eng Sci Technol 53:601–610. https://doi.org/10.1080/1478422X.2018.1516539

    Article  CAS  Google Scholar 

  17. DeGiorgi VG, Kota N, Lewis AC, Qidwai SM (2013) Numerical modeling of pit growth in microstructure. Proc ASME Des Eng Tech Conf 2A:1–7. https://doi.org/10.1115/DETC2013-12074

    Article  Google Scholar 

  18. Böhni H (2000) Influence of temperature on the localized corrosion of stainless steels. Russ J Electrochem 36:1122–1128

    Article  Google Scholar 

  19. Park JO, Matsch S, Böhni H (2001) Effects of temperature and chloride concentration on pit initiation and early pit growth of stainless steel. J Electrochem Soc 149:B34

    Article  Google Scholar 

  20. Sharland SM, Jackson CP, Diver AJ (1989) A finite-element model of the propagation of corrosion crevices and pits. Corros Sci 29:1149–1166. https://doi.org/10.1016/0010-938X(89)90051-6

    Article  CAS  Google Scholar 

  21. Duddu R, Kota N, Qidwai SM (2016) An extended finite element method based approach for modeling crevice and pitting corrosion. J Appl Mech Trans ASME 83:1–10. https://doi.org/10.1115/1.4033379

    Article  CAS  Google Scholar 

  22. Zhang D, Yang L, Tan Z, Xing S, Bai S, Wei E, Tang X, Jin Y (2021) Corrosion behavior of X65 steel at different depths of pitting defects under local flow conditions. Exp Therm Fluid Sci 124:110333. https://doi.org/10.1016/j.expthermflusci.2020.110333

    Article  CAS  Google Scholar 

  23. Sabat RK, Sahoo SK, Panda D, Mohanty UK, Suwas S (2017) Orientation dependent recrystallization mechanism during static annealing of pure magnesium. Mater Charact 132:388–396. https://doi.org/10.1016/j.matchar.2017.09.003

    Article  CAS  Google Scholar 

  24. Sabat RK, Panda D, Sahoo SK (2017) Growth mechanism of extension twin variants during annealing of pure magnesium: an ‘ex situ’ electron backscattered diffraction investigation. Mater Charact 126:10–16. https://doi.org/10.1016/j.matchar.2017.02.008

    Article  CAS  Google Scholar 

  25. Deshpande KB (2010) Validated numerical modelling of galvanic corrosion for couples: magnesium alloy (AE44)-mild steel and AE44-aluminium alloy (AA6063) in brine solution. Corros Sci 52:3514–3522. https://doi.org/10.1016/j.corsci.2010.06.031

    Article  CAS  Google Scholar 

  26. Vodka O (2015) Computation tool for assessing the probability characteristics of the stress state of the pipeline part defected by pitting corrosion. Adv Eng Softw 90:159–168. https://doi.org/10.1016/j.advengsoft.2015.08.012

    Article  Google Scholar 

  27. Wang H, Han EH (2016) Computational simulation of corrosion pit interactions under mechanochemical effects using a cellular automaton/finite element model. Corros Sci 103:305–311. https://doi.org/10.1016/j.corsci.2015.11.034

    Article  CAS  Google Scholar 

  28. Mouloudi M (2021) Study of corrosion pit propagation in aluminum by numerical simulation using the finite element method. Int J Electrochem Sci 16:21–119. https://doi.org/10.20964/2021.11.24

    Article  CAS  Google Scholar 

  29. Sabat RK, Surya Pavan MVSSDS, Aakash DS, Kumar M, Sahoo SK (2018) Mechanism of texture and microstructure evolution during warm rolling of Ti–6Al–4V alloy. Philos Mag 98:2562–2581. https://doi.org/10.1080/14786435.2018.1493237

    Article  CAS  Google Scholar 

  30. Zhou YT, Wang YJ, Zheng SJ, Zhang B, Ma XL (2015) Strain-induced preferential dissolution at the dislocation emergences in MnS: an atomic scale study. Philos Mag 95:2365–2375. https://doi.org/10.1080/14786435.2015.1052030

    Article  CAS  Google Scholar 

  31. Zhou Q, Wu W, Liu D, Li K, Qiao Q (2016) Estimation of corrosion failure likelihood of oil and gas pipeline based on fuzzy logic approach. Eng Fail Anal 70:48–55. https://doi.org/10.1016/j.engfailanal.2016.07.014

    Article  Google Scholar 

  32. Sabat RK, Samal PK, Ahamed SM (2018) Effect of strain path on the evolution of microstructure, texture and tensile properties of WE43 alloy. Mater Sci Eng A 715:348–358. https://doi.org/10.1016/j.msea.2018.01.018

    Article  CAS  Google Scholar 

  33. Mirmahdi E (2021) Defects in turbine impeller blades with non-destructive testing: modeling, ultrasonic waves, defect analysis. J Inst Eng Ser C 102:1395–1401. https://doi.org/10.1007/s40032-021-00769-6

    Article  Google Scholar 

  34. Chalgham W, Wu K-Y, Mosleh A (2019) External corrosion modeling for an underground natural gas pipeline using COMSOL multiphysics. Proc COMSOL Conf

  35. Loto RT (2017) Study of the corrosion resistance of type 304L and 316 austenitic stainless steels in acid chloride solution. Orient J Chem 33:1090–1096. https://doi.org/10.13005/ojc/330304

    Article  CAS  Google Scholar 

  36. Dickinson EJF, Ekström H, Fontes E (2014) COMSOL Multiphysics®: finite element software for electrochemical analysis. A mini-review. Electrochem Commun 40:71–74. https://doi.org/10.1016/j.elecom.2013.12.020

    Article  CAS  Google Scholar 

  37. Cutress IJ, Dickinson EJF, Compton RG (2010) Analysis of commercial general engineering finite element software in electrochemical simulations. J Electroanal Chem 638:76–83. https://doi.org/10.1016/j.jelechem.2009.10.017

    Article  CAS  Google Scholar 

  38. Jafarzadeh S, Chen Z, Bobaru F (2019) Computational modeling of pitting corrosion. Corros Rev 37:419–439. https://doi.org/10.1515/corrrev-2019-0049

    Article  CAS  Google Scholar 

  39. Iwamoto T (2019) Validation as construction design method of anti-corrosion process for marine steel structures using COMSOL Multiphysics ® through mock-up sheet piles

  40. Dickinson EJF, Ekström H, Fontes E (2014) Electrochemistry communications mini review COMSOL multiphysics ®: finite element software for electrochemical analysis: a mini-review. Electrochem Commun 40:71–74. https://doi.org/10.1016/j.elecom.2013.12.020

    Article  CAS  Google Scholar 

  41. Olanipekun AT, Faola AE, Oluwabunmi KE, Oladosu TL (2014) Galvanic corrosion of a mild steel bolt in a magnesium alloy (AZ91D) plate simulation using COMSOL multiphysics. Int J Sci Eng Res 5:1329–1332

    Google Scholar 

  42. Ewans JW (2003) Electrochemistry module. Mater Today 6:45. https://doi.org/10.1016/s1369-7021(03)00950-7

    Article  Google Scholar 

  43. Multiphysics C (2012) Introduction to the corrosion module. Comsol

  44. Loto RT, Loto CA (2017) Potentiodynamic polarization behavior and pitting corrosion analysis of 2101 duplex and 301 austenitic stainless steel in sulfuric acid concentrations. J Fail Anal Prev 17:672–679. https://doi.org/10.1007/s11668-017-0291-6

    Article  Google Scholar 

  45. Marshall RS, Kelly RG, Goff A, Sprinkle C (2019) Galvanic corrosion between coated Al alloy plate and stainless steel fasteners, part 1: FEM model development and validation. Corrosion 75:1461–1473

    Article  CAS  Google Scholar 

  46. Katiyar PK, Misra S, Mondal K (2019) Corrosion behavior of annealed steels with different carbon contents (0.002, 0.17, 0.43 and 0.7% C) in freely aerated 35% NaCl solution. J Mater Eng Perform 28:4041–4052. https://doi.org/10.1007/s11665-019-04137-5

    Article  CAS  Google Scholar 

  47. Pidaparti RM, Fang L, Palakal MJ (2008) Computational simulation of multi-pit corrosion process in materials. Comput Mater Sci 41:255–265. https://doi.org/10.1016/j.commatsci.2007.04.017

    Article  CAS  Google Scholar 

  48. Valor A, Caleyo F, Alfonso L, Rivas D, Hallen JM (2007) Stochastic modeling of pitting corrosion: a new model for initiation and growth of multiple corrosion pits. Corros Sci 49:559–579. https://doi.org/10.1016/j.corsci.2006.05.049

    Article  CAS  Google Scholar 

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Acknowledgements

MD thanks the Department of Science and Technology, New Delhi, India, for financial support under a DST-INSPIRE Faculty award (IFA-14/CH-156). VP, YK and DG are thankful to IIT Indore for fellowship. AK extends his appreciation to the Deanship of Scientific Research at King Khalid University for contribution through research groups program under grant number RGP1/152/42.

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This research work was supported by Department of Science and Technology, New Delhi, India, under a DST-INSPIRE Faculty award (IFA-14/CH-156).

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Correspondence to Mrigendra Dubey.

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Prajapati, V., Kumar, Y., Gupta, D. et al. Analysis of Pitting Corrosion of Pipelines in a Marine Corrosive Environment Using COMSOL Multiphysics. J Bio Tribo Corros 8, 21 (2022). https://doi.org/10.1007/s40735-021-00620-6

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