Probabilistic Approach for Predicting Pipeline End Loads in Short HPHT Deep-Water Flowlines

Abstract This paper presents a case study for a deep-water, HPHT, short flowline evaluated using a probabilistic lateral buckling design approach that aims to predict the pipeline end loads. The lateral buckling assessment of short flowlines, with fixed pipe ends and length of 1000m, may show an acceptable lateral buckling result, not requiring a controlled lateral buckling strategy, i.e., no engineered triggers, to ensure the pipe integrity. Although the integrity of the pipeline is ensured, it is recommended to introduce at least one engineered trigger in the pipeline to reduce the end loads stably by creating a lateral buckle to release the compressive axial force in the pipeline. The end loads, affected by uncertain parameters, are evaluated based on a probabilistic approach to have a robust and demonstrably efficient design. It is expected that short flowlines have small, lateral out-of-straightness features (which are inherent to the pipeline installation process). The uncertainty in the out-of-straightness features along the line can influence the critical buckling force and therefore the end loads due to cyclic thermal loads. The proposed approach is useful for predicting the pipeline end loads for the anchor structures design at early or detailed phase in the presence of uncertain parameters. This probabilistic approach requires more simulation time, compared with the deterministic approach, but it helps to predict a more robust range for the lateral buckling response and lower anchor load, which may result in project cost savings.

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Publication Details

Published
2025-06-22
DOI
https://doi.org/10.1115/omae2025-157399
Primary Topic
Geotechnical Engineering and Underground Structures
Type
article
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article

Probabilistic Approach for Predicting Pipeline End Loads in Short HPHT Deep-Water Flowlines

Rodrigo Borges Primieri, Qiang Bai, Endryws Moura, Carlos Valer
Geotechnical Engineering and Underground Structures
article

Probabilistic Approach for Predicting Pipeline End Loads in Short HPHT Deep-Water Flowlines

Rodrigo Borges Primieri, Qiang Bai, Endryws Moura, Carlos Valer
article en

Abstract

Abstract This paper presents a case study for a deep-water, HPHT, short flowline evaluated using a probabilistic lateral buckling design approach that aims to predict the pipeline end loads. The lateral buckling assessment of short flowlines, with fixed pipe ends and length of 1000m, may show an acceptable lateral buckling result, not requiring a controlled lateral buckling strategy, i.e., no engineered triggers, to ensure the pipe integrity. Although the integrity of the pipeline is ensured, it is recommended to introduce at least one engineered trigger in the pipeline to reduce the end loads stably by creating a lateral buckle to release the compressive axial force in the pipeline. The end loads, affected by uncertain parameters, are evaluated based on a probabilistic approach to have a robust and demonstrably efficient design. It is expected that short flowlines have small, lateral out-of-straightness features (which are inherent to the pipeline installation process). The uncertainty in the out-of-straightness features along the line can influence the critical buckling force and therefore the end loads due to cyclic thermal loads. The proposed approach is useful for predicting the pipeline end loads for the anchor structures design at early or detailed phase in the presence of uncertain parameters. This probabilistic approach requires more simulation time, compared with the deterministic approach, but it helps to predict a more robust range for the lateral buckling response and lower anchor load, which may result in project cost savings.

TechnipFMC (France) (FR), TechnipFMC (United States) (US), TechnipFMC (Germany) (DE)
Openalex Percentile: Top 77%
Geotechnical Engineering and Underground Structures
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Probabilistic Approach for Predicting Pipeline End Loads in Short HPHT Deep-Water Flowlines — Rodrigo Borges Primieri, Qiang Bai, et al. · (2025) | TGRS Research Map | TGRS