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Primary Article

Pitting Corrosion: Comparison of Treatments With Extreme-Value–Distributed Responses

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Pages 262-272 | Published online: 01 Jan 2012

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Janet E. Heffernan, Alastair Walker & Ping Liu. (2019) Improved estimation of ultra-deep water pipe collapse pressures by using extreme value theory. Quality Engineering 31:3, pages 363-374.
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Shiyao Liu & William Q. Meeker. (2015) Statistical Methods for Estimating the Minimum Thickness Along a Pipeline. Technometrics 57:2, pages 164-179.
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John H. J. Einmahl, Jun Li & Regina Y. Liu. (2009) Thresholding Events of Extreme in Simultaneous Monitoring of Multiple Risks. Journal of the American Statistical Association 104:487, pages 982-992.
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Articles from other publishers (5)

Haonan Ma, Weidong Zhang, Yao Wang, Yibo Ai & Wenyue Zheng. (2023) Advances in corrosion growth modeling for oil and gas pipelines: A review. Process Safety and Environmental Protection 171, pages 71-86.
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Hang ZhouSivashangari GnanasambandamMaurizio ForestaDavid WestonFan LiJingzhe PanMichelle Le Blanc. (2017) Measurement and Modeling of Pitting Depth Distribution for Phosphor Bronze Tapes Used in Underground Power Transmission Cables. CORROSION 73:7, pages 844-852.
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Yaoye Zhang, Dongsheng Li & Zhi Zhou. (2017) Time Reversal Method for Guided Waves with Multimode and Multipath on Corrosion Defect Detection in Wire. Applied Sciences 7:4, pages 424.
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Jozef L. Teugels. 2014. Wiley StatsRef: Statistics Reference Online. Wiley StatsRef: Statistics Reference Online 1 13 .
A. Jarrah, M. Bigerelle, G. Guillemot, D. Najjar, A. Iost & J.-M. Nianga. (2011) A generic statistical methodology to predict the maximum pit depth of a localized corrosion process. Corrosion Science 53:8, pages 2453-2467.
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