Effects of Surface Live Loads on the Behaviour of Decommissioned Pipelines: Numerical Modelling and Analysis
Bibliographic record
Abstract
Steel pipelines are used throughout the energy industry as the primary means of transporting natural gas, crude oil, and petroleum-related products and chemicals. When a pipeline permanently ceases operation, it is decommissioned and may be abandoned and left in place underground. Over time, the pipeline will degrade due to environmental and in-situ conditions. Corrosion is the principal mechanism for the degradation of decommissioned pipelines. Corrosion and degradation reduce the material strength and stiffness of the pipe section. Degraded pipes may no longer be capable of bearing the loads imposed by groundcover and surface vehicles. Potential collapse of decommissioned pipelines poses a risk to both the public and the environment. The static structural response of buried decommissioned pipelines subjected to surface live load was analyzed using the finite element analysis software ABAQUS. The buried pipeline was modelled within a uniform soil block, eliminating the effects of boundary conditions. Soil-pipe interaction was considered assuming a frictional slippage contact definition. The pipe was subjected to both overburden dead load and surface live load. Surface live load was taken as the maximum axle load of a CL-800 truck using an appropriate dynamic loading factor. The effects of various in-situ parameters including the burial depth, pipe diameter, and wall thickness were investigated. The investigation further expanded to analyze the effects of surface loading magnitude, geometry and direction of travel, along with performing an ultimate limit states analysis. The primary results indicate that for reasonable burial depths, soil stiffness, pipe diameter, and wall thickness, the maximum stresses lie below the elastic limit. However, for shallow burial depths, local deformations and stresses become significant and increase rapidly.
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 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".