| LI Zhi,HUANG Xiao-yan,XIONG Chun-bao,NIE Dong-qing.An Investigation into the Corrosion Behavior of Subsea Pipelines with the Mixture Distribution Model[J],51(5):186-197, 233 |
| An Investigation into the Corrosion Behavior of Subsea Pipelines with the Mixture Distribution Model |
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| DOI：10.16490/j.cnki.issn.1001-3660.2022.05.020 |
| KeyWord:submarine pipeline corrosion damage behavior mixture distribution model Anderson-Darling test parameter correction |
| Author | Institution |
| LI Zhi |
National Center for Dam Safety Engineering Technology Research, Wuhan , China;Changjiang River Scientific Research Institute, Wuhan , China |
| HUANG Xiao-yan |
National Center for Dam Safety Engineering Technology Research, Wuhan , China;Changjiang Institute of Survey, Planning, Design and Research Co., Ltd., Wuhan , China |
| XIONG Chun-bao |
School of Civil Engineering, Tianjin University, Tianjin , China |
| NIE Dong-qing |
Shanghai Municipal Engineering Design Institute Group Co., Ltd., Shanghai , China |
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| Abstract: |
| Aiming at the randomness and polymorphism of long-term corrosion damage of submarine pipeline, the distribution characteristics and evolution law of corrosion damage of submarine pipeline with different service years are studied. An analysis method of corrosion characteristics of submarine pipeline based on mixture distribution model is proposed. Based on the measured data of corrosion damage of aging submarine pipeline, through the statistical analysis of corrosion damage characteristics of submarine pipeline under different service years, the optimal distribution model of corrosion damage of submarine pipeline is determined, and the random process model of corrosion damage of submarine pipeline based on mixture distribution model is established. Further, Arima method is established to continuously modify the model parameters and predict the pipeline corrosion damage. The results show that the optimal distribution of corrosion damage is different under different service time. Weibull, Gumbel and Gamma distribution models have good goodness of fit, and each distribution model shows different change trends with the increase of service time, and the corresponding distribution model parameters show dynamic changes; Combined with ARIMA model correction method, making full use of the measured data can continuously reduce the uncertainty of the model. The corrosion damage of submarine pipeline has obvious characteristics of polymorphism and randomness. It is difficult to use a single distribution model to generally describe the pipeline corrosion damage data. The application of the existing corrosion damage model has certain uncertainty and limitations. The analysis method based on the mixture distribution model can more accurately reflect the actual distribution law of long-term corrosion damage of submarine pipeline. |
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