Numerical Study on Mechanism Responses of Submarine Pipeline Impacted by Bar-Shaped Falling Object
Bibliographic record
Abstract
Impact caused by bar-shaped falling objects from third-party activities could damage submarine pipelines seriously. In this paper, numerical simulation models of submarine pipelines are established to investigate the damage mechanisms, mechanical behaviors, and energy absorptions of submarine pipelines impacted by bar-shaped objects based on multiple theories and approaches, including elastic-plastic mechanics, geomechanics, elastic foundation beam theory, and finite-element method. The effects of essential physical parameters on the impact behaviors of submarine pipelines are discussed. The results show that the seabed could absorb the highest proportion of impact energy at the final state, but a rock seabed could lead to severe damage to the pipeline. With the increase of the impact velocity, the stress concentration and plastic deformation become serious, as well as the pipeline depression rate and the maximum impact force. High-stress area, plastic deformation area, pipeline depression rate, and absorbed energy proportion increase with the increase of the radius-thickness ratio. The most severe impact damage occurs on the submarine pipelines when a falling object has a tri-prism impact end. The pipeline depression rate increases as the impact angle becomes bigger. An inclined impact could lead to more severe damage if the inclined angle is between 60° and 75°.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".