Study on buckling load analysis model of buried steel pipeline

Guoan Zhao; Chengsong Luo; Hailiang Nie; Weifeng Ma; Yue Zhang; Dalin Xia; Lei Lu; Chi Wu; Ying Mao

doi:10.1117/12.2691832

23 August 2023 Study on buckling load analysis model of buried steel pipeline

Guoan Zhao, Chengsong Luo, Hailiang Nie, Weifeng Ma, Yue Zhang, Dalin Xia, Lei Lu, Chi Wu, Ying Mao

Proceedings Volume 12784, Second International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2023); 127842A (2023) https://doi.org/10.1117/12.2691832
Event: 2023 2nd International Conference on Applied Statistics, Computational Mathematics and Software Engineering (ASCMSE 2023), 2023, Kaifeng, China

Abstract

Long-haul oil and gas pipelines are laid buried long distances and pass through complex and diverse landforms. They will bear different boundary conditions and environmental loads along the way, and often form large deformation conditions in local areas, leading to buckling failure of pipelines, which seriously affects the transportation efficiency of oil and gas pipelines and threatens the safety of people and property along the way. At present, there are many studies on buckling cases of buried pipelines, but most of them are for a single case analysis, and few comprehensive studies on load modes. In this paper, the boundary conditions and load combinations of steel pipe buckling are summarized. The buckling modes of steel pipe under different load forms are studied by finite element simulation, and then the load forms leading to different buckling models are analysed and summarized, which provides a theoretical basis for the buckling failure analysis in practical engineering.

Citation Download Citation

Guoan Zhao, Chengsong Luo, Hailiang Nie, Weifeng Ma, Yue Zhang, Dalin Xia, Lei Lu, Chi Wu, and Ying Mao "Study on buckling load analysis model of buried steel pipeline", Proc. SPIE 12784, Second International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2023), 127842A (23 August 2023); https://doi.org/10.1117/12.2691832

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