The Optimization Of Failure Risk Estimation On The Uniform Corrosion Rate With A Non-Linear Function

Authors

Fernanda Hartoyo, Universitas IndonesiaFollow
Jaka Fajar Fatriansyah, Universitas IndonesiaFollow
Imam Abdillah Mas'ud, Universitas IndonesiaFollow
Farhan Rama Digita, Universitas IndonesiaFollow
Hanna Ovelia, Universitas IndonesiaFollow
Datu Rizal Asral, Universitas IndonesiaFollow

Abstract

Failures in the oil and gas pipeline system are conditions that must be avoided and anticipated because the losses due to the failures can occur at a very high level. Internal corrosion is one of the significant causes of the failures in pipeline systems. In addition, this type of corrosion is due to the high content of carbon dioxide and other corrosive substances in crude oil and natural gas. Therefore, an optimal inspection scheduling system is required to prevent the possibility of pipeline failures due to corrosion and to avoid any overspending on the budget due to excessive inspection scheduling. Risk-based testing (RBI) is one of the best methods to define a test planning system by using an optimal risk assessment. In this article, a Monte Carlo random number generator is applied by using a huge number of random iterations to approximate the actual risk value of a pipeline system with a limited sample at the scene. The nonlinear corrosion rate function is used for comparison with the commonly used linear corrosion rate function based on ASTM G-16 95. Once a risk value is estimated, the value is monitored based on an assessment of the risk matrix for each corrosion rate function by using the RBI method. The results show that the nonlinear corrosion rate function provides a more accurate approach to estimating the actual risk value and ultimately leads to an optimal inspection planning system.

References

Z. Ahmad and D. Macdonald, Principles of corrosion engineering and corrosion control. Elsevier Science & Technology Books, 2016.

American Petroleum Institute (API Publication 580), Washington (DC, USA): Risk-Based Inspection, API Publishing Service, 2002.

P. Hou, X. Yi and H. Dong, "A Spatial Statistic Based Risk Assessment Approach to Prioritize the Pipeline Inspection of the Pipeline Network", Energies, vol. 13, no. 3, p. 685, 2020. Available: 10.3390/en13030685.

N. Arunraj and J. Maiti, "Risk-based maintenance—Techniques and applications", Journal of Hazardous Materials, vol. 142, no. 3, pp. 653-661, 2007. Available: 10.1016/j.jhazmat.2006.06.069 [Accessed 18 April 2022].

J. Fatriansyah, Y. Sasaki and H. Orihara, "Nonequilibrium steady-state response of a nematic liquid crystal under simple shear flow and electric fields", Physical Review E, vol. 90, no. 3, p. 032504, 2014. Available: 10.1103/physreve.90.032504.

J. Fatriansyah and H. Orihara, "Electric-field-induced flow-aligning state in a nematic liquid crystal", Physical Review E, vol. 91, no. 4, p. 042508, 2015. Available: 10.1103/physreve.91.042508.

R. Allen, D. Frenkel and P. ten Wolde, "Simulating rare events in equilibrium or nonequilibrium stochastic systems", The Journal of Chemical Physics, vol. 124, no. 2, p. 024102, 2006. Available: 10.1063/1.2140273.

J. Fatriansyah, D. Dhaneswara, M. Abdurrahman, F. Kuskendrianto and M. Yusuf, "Molecular Dynamics Simulation of Hydrogen Adsorption on Silica", IOP Conference Series: Materials Science and Engineering, vol. 478, no. 2, p. 012034, 2019. Available: 10.1088/1757-899x/478/1/012034.

J. Fatriansyah, T. Matari and S. Harjanto, "The Preparation of Activated Carbon from Coconut Shell Charcoal by Novel Mechano-Chemical Activation", Materials Science Forum, vol. 929, pp. 50-55, 2018. Available: 10.4028/www.scientific.net/msf.929.50.

"What Makes RStudio Different?", Rstudio.com, 2022. [Online]. Available: https://www.rstudio.com/about/what-makes-rstudio-different/. [Accessed: 08- Apr- 2022].

H. Wang, Monte Carlo Simulation With Applications To Finance. [S.L.]: CRC Press, 2019.

American Petroleum Institute (API Publication 581), Risk Based Inspection Technology, Downstream Segment-Second Edition, Washington D.C: American Petroleum Institute, 2008.

Recommended Citation

Hartoyo, Fernanda; Fatriansyah, Jaka Fajar; Mas'ud, Imam Abdillah; Digita, Farhan Rama; Ovelia, Hanna; and Asral, Datu Rizal (2022) "The Optimization Of Failure Risk Estimation On The Uniform Corrosion Rate With A Non-Linear Function," Journal of Materials Exploration and Findings (JMEF): Vol. 1: Iss. 1, Article 3.
DOI: 10.7454/jmef.v1i1.1001
Available at: https://scholarhub.ui.ac.id/jmef/vol1/iss1/3