Source: Journal of loss prevention in the process industries. Unidade: EP
Subjects: ÓLEO E GAS, ESTRUTURAS OFFSHORE, DUTOS, CORROSÃO
ABNT
CRUZ, João Pedro Bachega et al. Uniform corrosion assessment in oil and gas pipelines using commercial corrosion prediction models: Part 2: uncertainty and risk considerations based on statistical analyses of gravimetric laboratorial tests, offshore pipelines inspections, and manufacturing tolerances. Journal of loss prevention in the process industries, v. 100, p. 1-24, 2026Tradução . . Disponível em: https://doi.org/10.1016/j.jlp.2025.105836. Acesso em: 14 fev. 2026.APA
Cruz, J. P. B., Veruz, E. G., Aoki, I. V., Schleder, A. M., Souza, G. F. M. de, Vaz, G. L., et al. (2026). Uniform corrosion assessment in oil and gas pipelines using commercial corrosion prediction models: Part 2: uncertainty and risk considerations based on statistical analyses of gravimetric laboratorial tests, offshore pipelines inspections, and manufacturing tolerances. Journal of loss prevention in the process industries, 100, 1-24. doi:10.1016/j.jlp.2025.105836NLM
Cruz JPB, Veruz EG, Aoki IV, Schleder AM, Souza GFM de, Vaz GL, Barros LO de, Orlowski RTC, Martins MR. Uniform corrosion assessment in oil and gas pipelines using commercial corrosion prediction models: Part 2: uncertainty and risk considerations based on statistical analyses of gravimetric laboratorial tests, offshore pipelines inspections, and manufacturing tolerances [Internet]. Journal of loss prevention in the process industries. 2026 ; 100 1-24.[citado 2026 fev. 14 ] Available from: https://doi.org/10.1016/j.jlp.2025.105836Vancouver
Cruz JPB, Veruz EG, Aoki IV, Schleder AM, Souza GFM de, Vaz GL, Barros LO de, Orlowski RTC, Martins MR. Uniform corrosion assessment in oil and gas pipelines using commercial corrosion prediction models: Part 2: uncertainty and risk considerations based on statistical analyses of gravimetric laboratorial tests, offshore pipelines inspections, and manufacturing tolerances [Internet]. Journal of loss prevention in the process industries. 2026 ; 100 1-24.[citado 2026 fev. 14 ] Available from: https://doi.org/10.1016/j.jlp.2025.105836
